virtual environments for motor rehabilitation:...

Virtual Environments for Motor Rehabilitation: Review

MAUREEN K. HOLDEN, Ph.D.

ABSTRACT

In this paper, the current “state of the art” for virtual reality (VR) applications in the field ofmotor rehabilitation is reviewed. The paper begins with a brief overview of available equip-ment options. Next, a discussion of the scientific rationale for use of VR in motor rehabilita-tion is provided. Finally, the major portion of the paper describes the various VR systems thathave been developed for use with patients, and the results of clinical studies reported to datein the literature. Areas covered include stroke rehabilitation (upper and lower extremitytraining, spatial and perceptual-motor training), acquired brain injury, Parkinson’s disease,orthopedic rehabilitation, balance training, wheelchair mobility and functional activities ofdaily living training, and the newly developing field of telerehabilitation. Four major find-ings emerge from these studies: (1) people with disabilities appear capable of motor learningwithin virtual environments; (2) movements learned by people with disabilities in VR trans-fer to real world equivalent motor tasks in most cases, and in some cases even generalize toother untrained tasks; (3) in the few studies (n = 5) that have compared motor learning in realversus virtual environments, some advantage for VR training has been found in all cases; and(4) no occurrences of cybersickness in impaired populations have been reported to date in ex-periments where VR has been used to train motor abilities.

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INTRODUCTION

IN RECENT YEARS, the field of virtual reality (VR)has grown immensely. Practical applications for

the use of this technology encompass many fields,from aviation training and military applications, toindustrial training in machine operation, to medi-cine, where surgeons can be trained in surgicaltechniques using VR systems.

One of the newest fields to benefit from the ad-vances in VR technology is that of medical rehabili-tation. In the space of just a few years, the literaturehas advanced from articles which primarily de-scribed the potential benefits of using such technol-ogy, to articles that describe the development ofactual working systems, testing of prototypes, andearly clinical results with patients who have usedsome of these systems.

In this article, a brief overview of the equipmenttypically used in VR training systems is provided.There follows a review of the scientific rationale andthe potential advantages of using VR systems in thefield of rehabilitation. Finally, the “state of the art”for VR applications in motor rehabilitation is re-viewed. The application topics have been organizedby diagnostic or task specific categories for ease ofreference by the reader. The focus in this paper hasbeen restricted to the field of motor rehabilitation.

EQUIPMENT FOR VR SYSTEMS INMOTOR REHABILITATION

A virtual environment (or virtual reality) is a sim-ulation of a real world environment that is gener-ated through computer software and is experienced

Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cam-bridge, Massachusetts.

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by the user through a human–machine interface. Awide variety of hardware and software devices canbe utilized to create VR simulations of varying de-grees of complexity. Whereas in the real world wegain knowledge about our environment directlythrough our senses—vision, hearing, touch, propri-oception, smell—in the virtual world, we utilizethese same senses to obtain information about thevirtual world through a human–machine interface (e.g., head-mounted visual display). Thehuman– machine interface can provide informationspecific to one or more senses, depending on thetype of devices that have been selected for use. Theinformation gathered about the virtual environmentthrough the interface is then used to guide interac-tions of the participant within the virtual world.Input from the virtual environment can also becombined with natural sensory inputs from the realenvironment, to create a hybrid input to the centralnervous system (CNS).

A variety of equipment can be utilized to createdifferent kinds of virtual environments with differ-ent capabilities and purposes. Several availablebooks provide complete and detailed descriptionsof available VR equipment1–3; therefore, only cur-sory descriptions will be provided here. The basiccomponents for VR systems are a computer, usu-ally with a special graphics card that will allow fastcomputation and drawing of three-dimensional(3-D) images, display devices through which theuser views the virtual environment, hardware de-vices that can be used to monitor movement kine-matics, or provide simulations of haptic and forcefeedback to participants, and, of course, speciallywritten software that enables all these componentsto work in synchrony. More immersive virtual en-vironments provide the user with the perceptionthat the environment is real and 3-D, a quality re-ferred to as presence. Less immersive virtual envi-ronments provide less of a sense of presence andare more akin to looking through a window at ascene. While it might seem intuitive that moreimmersive virtual environments would be bestfor motor training, this may not actually be thecase, in part because of a practical difficulty. Suchimmersive virtual environments can generate cyber-sickness (a constellation of motion-sickness likesymptoms) in many participants.4,5 Common symp-toms of cybersickness include nausea, vomiting,headache, somnolence, loss of balance, and alteredeye–hand coordination. These are obviously unde-sirable events, particularly in participants with im-paired function in the CNS. Most of the studies oncybersickness to date have been on normal partici-pants but it is reasonable to assume that patients

with neurological impairments would be suscepti-ble to cybersickness with similar (if not higher) fre-quencies than normal participants. It is important tonote, however, that none of the studies reviewed inthis paper that have used VR to train impaired par-ticipants have reported any incidence of cybersick-ness. All these studies have used less immersivedesktop or wall screen displays. Although newerequipment, in theory, should greatly decrease theincidence of cybersickness,6 the effects of differentimmersive systems on patient populations is an areastill in need of investigation. Lewis and Griffen7

have provided a comprehensive description of keyissues to be considered in such investigations.

Display devices

The simplest visual display device is a desktopcomputer monitor, using an enhanced 2-D graphicsdisplay. Although such displays will not be as realis-tic as a true-stereo 3-D display, the sense of depth canbe enhanced through the use of depth cues such asperspective, relative motion, occlusion, and aerialperspective.1 Use of a liquid crystal display (LCD)projector and large wall screen as the monitor willalso enhance the sense of depth perception (and thussense of presence) in the user. Such set-ups are conve-nient, easy to use, require no glasses or headset withwires, and allow both the therapist and patient toview the same scene with ease. These displays havebeen preferred in clinical studies to date, as they arerelatively cheap and easy to use, and there have beenno reported occurrences of cybersickness in studiesusing such systems with clinical populations.

To move toward a more immersive virtual envi-ronment, one needs a display that can provide true3-D stereo. This can be done inexpensively withflicker glasses which display alternating right/leftviews of the picture synchronized to the frame rate;or more expensively with a head-mounted visualdisplay (HMD), which allows stereo viewing viasmall monitors mounted in front of each eye andlinkage of the VR viewpoint with head movements;or large screen stereo projection systems, which pro-vide compelling stereo with lightweight polarizingglasses. At the very high end, the CAVE™ system,developed at the University of Illinois at Chicago,8,9

provides a multi-person, room-sized, high-resolu-tion, 3-D video and audio virtual environment.

Interface devices

In addition to the standard mouse and joystickinterfaces that are routinely used to navigate large3-D worlds, a variety of devices will allow simula-

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tion of movement kinematics and sensory feedbacksuch as touch, pressure, or force. In theory, anytype of motion tracking device could be used tomonitor movement or simulate movements in avirtual world. In practice, electromagnetic trackingdevices are frequently utilized to monitor head,trunk, arm, and leg movements. They are lower incost and impervious to optical occlusion problems.However, they can be susceptible to signal distor-tion from large metal objects or from electromag-netic fields generated by electronic devices.10

For capture of the more detailed kinematics ofhand movements, an instrumented glove may beused. Inexpensive haptic feedback can be providedwith newly developed contact feedback devices,for example, small vibration devices attached tothe fingertips that become active when the partici-pant has “touched” a virtual object and turn offwhen the object is released. For higher fidelityhaptic feedback, a robotic arm, which generates 3or 6 degrees of freedom forces (e.g., PHANToM™),can be used. To utilize this kind of feedback in VRtraining, a hand-held stylus is usually attached tothe robotic arm, and the forces are translated to theparticipant through the stylus. This type of set-uphas been used to train surgical techniques,11,12 buthas not been used to date in rehabilitation. To feelmore realistic force feedback on different fingersand thumb, or throughout the arm, an exoskeletontype device is required. One such device, whichapplies forces to resist finger flexion, has been de-veloped by Burdea and colleagues.13 Commercialdevices which can apply force feedback to the fin-gers and thumb (“CyberGrasp”) or the entire arm(“CyberForce”) are also now available but expen-sive <www.immersion.com/3d/products/cyber_grasp.php>.

Auditory input can also be utilized in VR to en-hance spatial orientation and localization. For ex-ample, the CAVE system uses multiple speakersmounted in the room to create direction and dis-tance effects in the virtual world.8,9

SCIENTIFIC RATIONALE ANDADVANTAGES OF VR USE FOR

REHABILITATION

The discussion of the scientific rationale and ad-vantages for VR use in rehabilitation will focus on afew key concepts relevant to motor learning. Moreextensive discussion of these issues may be foundelsewhere.14–17 The key concepts to be discussed arerepetition, feedback, and motivation. We know thatrepetition is important both for motor learning and

the cortical changes that instantiate it. But it is notjust repetition alone that produces motor learning.The repeated practice must be linked to incremen-tal success at some task or goal. In the normal ner-vous system, this is achieved by trial and errorpractice, with feedback about performance successprovided by the senses (e.g., vision, propriocep-tion). But to practice movements over and over,participants must be motivated. Most people canrecall the extensive practice that was necessarywhen learning to ride a bicycle. In this case, the mo-tivation to tolerate the extensive practice periodwas provided by the anticipation of later fun to beexperienced while riding the bike.

VR provides a powerful tool with which to pro-vide participants with all of these elements—repet-itive practice, feedback about performance, andmotivation to endure practice. In particular, in avirtual environment, the feedback about perfor-mance can be augmented—that is, enhanced rela-tive to feedback that would occur in real worldpractice. A wide variety of methods have been usedto exploit aspects of VR technology to enhancemotor learning in people with disabilities throughreal time feedback (i.e., concurrent with task per-formance) and/or “knowledge of results” feedback.Knowledge of results feedback occurs immediatelyfollowing a trial or block of trials. Feedback hasbeen extensively investigated and there is generalagreement that it improves learning rate.18

Since feedback is central to motor learning in avirtual environment, it is important to examine theneurophysiological processes that are evoked byfeedback and discuss their relevance to the re-learning of motor skills. There is extensive evi-dence that the proprioceptive and exteroceptivefeedback associated with the execution of skilledtasks (in addition to internal feedback) inducesprofound cortical and subcortical changes at thecellular and synaptic level. For example, evidencederived from recording the activity of single cellsfrom the primary motor cortex of intact primateshas indicated that protracted use of the digits leadsto an enlargement of the cortical representation.Nudo et al.19 showed that cortical area M1 was al-terable by use throughout the life of an animal.Use-dependent alterations of cortical organizationhave also been found in auditory, visual, and so-mato-sensory areas.20–24

Direct evidence for the development of new pat-terns of activity in the cells of the motor areas of thefrontal lobe during the acquisition of a new motorskill has also been reported in a series of experi-ments in primates.25–27 The most striking result inthese experiments was the gradual recruitment of

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previously silent cortical neurons in area M1 dur-ing learning; these neurons displayed activity re-lated to the production of forces that compensatedfor externally imposed disturbances. Similar re-sults have been reported by Wise et al.28 using thesame technique of single-cell recordings with a dif-ferent behavioral paradigm. Co-occurrence of func-tional and structural plasticity within the samecortical regions has also been described for rats.29

Studies by Greenough et al.30 and Kleim et al.31

have revealed some of the mechanisms underlyingthe functional reorganization in the motor cortexfollowing motor learning. Rats trained on a com-plex motor task had larger dendritic fields and anincreased number of synapses in cortical motorcells in the hemisphere opposite to the trainedlimb. There is also experimental evidence thatsynaptic efficacy in the motor cortex may be modi-fied by the induction of long-term potentiation.32,33

It has also been shown in the rat29 and the primate34

that functional reorganization of the motor cortex(“remapping”) occurs only in response to the de-velopment of skilled forelimb movements, and notsimply to increased forelimb use.29,35 These studiesprovide neurophysiological evidence that motorrepetition alone is not enough to induce corticalcorrelates of motor learning.

Substantial functional reorganization also takesplace in the motor cortex of adult primates after afocal ischemic infarct.36 The retraining of skilledhand-use in these animals results in reorganizationin the adjacent intact cortex. Thus, the undamagedmotor cortex may play an important role in motorrecovery.37,38 Interestingly, Nudo et al. found that,in the absence of post-infarct training, the move-ments formerly represented in the infarcted area donot automatically reappear in adjacent cortical re-gions, but do so only in response to specific motorre-training activities.36,37

Real versus virtual practice

As will be seen in the latter part of this paper,augmented feedback about motor performance canreadily be provided in a virtual environment. And,as outlined above, scientific evidence suggests thataugmented feedback about performance will en-hance the cortical changes associated with motorlearning. But one might argue, most of the citedstudies have been conducted on animals, and theanimals were not trained using VR. What sort ofevidence exists about motor learning for humanparticipants trained in virtual environments? And,have any studies compared training in a real vs.virtual world environment?

On the first point, there exists a fair amount ofevidence that humans can learn motor skills in avirtual environment39–42 and that they can thentransfer that motor learning to a real world envi-ronment.43–45 Evidence that people with disabilitiescan learn motor skills in VR and transfer this learn-ing to real world performance will be presented inthe various sections to follow. In general, it can besaid here that people with disabilities do seem ableto both learn motor skills in VR and transfer theseabilities to the real world. But how does learning ina virtual environment compare to that which oc-curs in a real environment? On this second point,few studies exist. And this issue is an importantone for those in the rehabilitation field, who inevi-tably ask when discussing the use of VR in rehabili-tation: “Why bother with all that equipment; whynot just practice the real task? Wouldn’t that workbetter anyway, and cost less?” Of course, propo-nents of VR believe that outcomes will be enhancedfollowing practice in VR because of the ability tomake tasks easier, less dangerous, more cus-tomized, more fun, and of course easier to learn be-cause of the salient feedback that can be providedduring practice. To date, however, only five studieshave examined this issue in a controlled fashion.All five studies provide some experimental evi-dence that motor learning in a virtual environmentmay be superior.

In the first of these studies, Todorov et al.46 foundthat healthy participants who practiced a table-tennis stroke in a virtual environment, with aug-mented feedback from a virtual teacher, performedbetter following training than did participants whohad practiced the table tennis stroke with feedbackfrom an expert coach, or just practiced on theirown. (Participants were tested on a real world per-formance test.)

A second study of motor learning in VR trainednormal participants to move a hand held metal ringover a curved wire (“steadiness tester”) in either areal or a virtual environment.47 Participants receivedvirtual training, real training or no training on thesteadiness task. Prior to and following training, allparticipants were tested on the real task. The re-sults were that both virtual and real traininggroups improved significantly (p < 0.001) post-training, but the no training group did not. Theperformance, as measured by number of errors,was equivalent (p = 0.22) between those who re-ceived virtual or real training. These results sup-port the transfer of motor training in VR to realworld performance, in concert with the findings ofothers reported earlier. Next, these same partici-pants performed a second post-test on the steadi-

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ness tester, but were required to simultaneouslycarry out either a motor interference or a cognitiveinterference task. The motor Interference groupwas asked to tap on a Morse code key in time witha pre-recorded tempo. The cognitive interferencegroup was asked to listen for the names of fruits in-terspersed within a string of pre-recorded wordsand say “yes” when they occurred. These concur-rent tasks lasted for the duration of the steadinesstest. The results were that the motor interferencetask had a significantly greater effect on the steadi-ness test than did the cognitive interference task(p < 0.01). However, the very interesting result wasthat participants who had trained on the virtualtask were significantly less impaired (p < 0.05) bythe interference task than those who had trained onthe real task. This finding is in concert with the re-sults of Todorov et al.46 and implies an advantageor improved efficiency for the virtual training.

In the third study which compared real and vir-tual practice, Brooks et al.48 found that an amnesicpatient was able to learn two routes around a realworld hospital rehabilitation unit following train-ing in a VR simulation of these routes for 15 minper day for 3 weeks. An errorless learning49 methodwas used. Seven untrained routes were also tested;performance on these routes showed no improve-ment. Later, the patient was trained on two addi-tional routes in the same rehabilitation unit—one inVR and one in the real world. After 2 weeks oftraining, she had learned the route trained in VR,but not the route trained in the real world. Thus, inthis case, training in the virtual environment provedto be superior to training in the real world. It is alsointeresting to note that the patient easily trans-ferred the learned performance from VR to the realworld, despite the fact that the motor activity in VRconsisted only of manipulating a joystick, whereasin the real world, actual walking was of course re-quired. Obviously, the motor patterns of the twotasks varied considerably, implying that the learn-ing was at a more abstract or conceptual level.

In a fourth study, Webster et al.50 evaluated theeffectiveness of using a VR-based wheelchair train-ing program in improving real world wheelchairuse in a group of patients with stroke and unilat-eral neglect syndrome. A second group of patientswho had participated in a prior study of unilateralneglect served as a control group (i.e., non-random-ized). Both groups received standard rehabilitationwheelchair training, but only the experimental groupreceived the VR training. The results showed thatthe patients who had received the VR training madefewer errors and hit significantly fewer (p < 0.000)obstacles with their wheelchair during the real

world obstacle avoidance test than did participantsin the control group, who had not received thistraining. In addition, the number of falls duringtheir inpatient hospital stay was fewer for the VR-trained participants (p < 0.02) compared to controlparticipants.

A fifth study compared training to avoid obsta-cles during walking using VR-based vs. real worldtraining in a randomized controlled study of pa-tients with chronic stroke.51 Investigators reportedthat, although both groups improved on most ofthe outcome measures, participants in the VRgroup showed greater improvement (p < 0.001) in afast paced velocity test post-training.

Taken together, the results of these five studiescomparing different types of motor learning in a vir-tual versus real environment support the idea thatmotor learning following training in a virtual envi-ronment may be superior to that following realworld practice. Obviously, further work is needed toconfirm these findings, in particular with motor-im-paired patient populations, where only one random-ized controlled study has been published to date.51

Other factors that may enhance motor learning in VR

In addition to the important factors discussedabove (augmented feedback, facilitation of corticalplasticity through guided practice), a few otherideas that may enhance motor learning in VRshould be mentioned. For instance, there is psy-chophysical evidence that humans derive the speci-fications of a movement by tracking the trajectoryof the end-point of the limb.52,53 The precise defini-tion of “end-point” depends on the task itself andcan vary from the tip of a held object, to a finger, orto the entire hand. By explicitly showing this end-point trajectory to the participant via an animatedVR display, learning may be enhanced, especiallyin the initial phase.14,15,54

VR also allows us to program into the display avirtual teacher, who performs the task repeatedly.The powerful visual input of the teacher perform-ing the movement over and over may provide en-hancement of “learning by imitation” through directinput to M1 via mirror neuron inputs.55 Mirror neu-rons are cells which have been discovered in themonkey premotor cortex that fire when a move-ment is observed and when it is performed.56 Theymay provide a neurophysiological underpinning to“learning by imitation” in VR. This feature of learn-ing by imitation is not only an important way toprovide enhanced visual feedback, but also a wayto develop, through repetition, the formation of thecorrect pattern of cellular activity in the CNS.25,26


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VR offers the unique capability for real time feed-back to the participant during practice in a very in-tuitive and interpretable form. Patients can see theirown movement attempts in the same spatial frameof reference as that of the “virtual teacher” (unlikepractice with a real coach or therapist). Also, thetask can be simplified in the early stages of learn-ing, allowing the learner to focus on key elements.In contrast, in the real world situation, many poten-tial distracters exist and may slow down learningas the participant attempts to distinguish, throughtrial and error, the key aspects of the task on whichto focus. (This factor of reduced distractibility mayhave enhanced learning for the amnesia patient inthe study by Brooks et al.48) Training environmentscan also be customized for different therapeuticpurposes and the system designed to help thelearner detect and correct errors more rapidly.

New methodology

Finally, even if it proves to be the case followingfurther study that VR offers no performance advan-tage over real world practice for patients with motorimpairments, there will still be a significant place forVR use in rehabilitation. It is a powerful new toolthat can be utilized to test different methods ofmotor training, types of feedback provided, and dif-ferent practice schedules for comparative effective-ness in improving motor function in patients. Thetechnology provides a convenient mechanism formanipulating these factors, setting up automatictraining schedules and for training, testing, and re-cording participants’ motor responses.

USE OF VR FOR STROKEREHABILITATION

Upper extremity

Several groups of researchers have been workingto develop VR systems for upper extremity (UE) re-habilitation in patients with stroke, using a varietyof approaches.

MIT group. Holden and colleagues, based atMassachusetts Institute of Technology (MIT), Cam-bridge, Massachusetts, were the first to report suc-cessful use of VR to retrain movement in patientswith stroke.57 The VR motor re-training system theyhave developed is centered around the concept of“learning by imitation” of a virtual teacher,55 andallows the user to retrain a wide variety of armmovements (including shoulder, elbow, wrist, and

hand) in any part of the UE workspace, within thecontext of functional or goal-directed tasks. A briefsystem description is provided below; further de-tails may be found in Holden and Todorov,15 andHolden and Dyar.14

System description. The system consists of anelectromagnetic motion tracking device (Polhemus,Inc.), desktop computer display, and VR software.The VR software contains a basic 3-D graphics edi-tor which allows the user (therapist) to create“scenes” designed to be therapeutically meaning-ful to the targeted patients. Usually, a scene showssome simple task (e.g., place an envelope in a slot,hit a nail with a hammer, move a ball through aring, or lift a cup to the mouth). To date, approxi-mately 20 scenes, each with multiple levels of dif-ficulty, have been developed and tested withpatients, making a total of approximately 50 train-ing scenes. Following the basic scene creation, themotion tracking device is used to pre-record nor-mal participants performing the desired activities,within the context of the VR scene. These prere-corded trajectories (6 degrees of freedom (DOF);translation and orientation) then serve as the “vir-tual teacher” for the patient to watch and copy dur-ing the VR therapy practice. The entire limb or onlythe endpoint of the limb (i.e., hand or held object)and its trajectory may be displayed. The teacherdisplay may also be hidden from view if desired.

During training, the same motion tracking de-vice used to record the “virtual teacher” is attachedto the patient. The arm movements of the patientcan then be monitored and displayed in real time inthe context of the virtual scene, along with the pre-recorded movements of the virtual teacher. The de-gree of match with the teacher trajectory providesaugmented feedback in a visual context to the par-ticipant during practice. The amount of match mayalso be quantified to provide augmented knowl-edge of results feedback following each trial. Thisfeedback is presented to the participant as a“score,” or paired with verbal cues, such as “Verygood!” The scoring algorithm is flexible, allowingthe therapist to specify weights for different aspectsof performance as needed for particular patients.For example, displacement error, orientation error,angular or linear velocity, smoothness, and otherfactors may be weighted to emphasize one or moreof these factors during training. A more completedescription of the score algorithm may be found ina forthcoming paper.58

Although the desktop display allows only en-hanced two-dimensional (2-D) displays, 3-D dis-play is possible if stereo headsets, flicker glasses,

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or large screen polarizing projectors are used. Todate, however, the desktop has been the preferredchoice for these initial clinical studies, both becauseof lower cost and to minimize any risk of cyber-sickness in these impaired participants. Recently, atelerehabilitation version of the system has beendeveloped and deployed. Two disadvantages ofthe system developed by Holden and colleaguesare that it presently lacks a full hand model (fingersand thumb) and haptic feedback capability. How-ever, the group is presently working to add thesefeatures to their system.

Study results. In the first study reported byHolden et al.,57 the purpose was to assess whetherparticipants with stroke would even be able to use avirtual environment to practice motor tasks, and ifso, whether any movements that they learned in VRwould generalize to performance in the real worldon similar and untrained tasks. Two participantswith stroke (3.5 and 1.5 years post-stroke; one withright hemiparesis and aphasia; one with left hemi-paresis, parietal lobe symptoms, left side inattentionand hemianopsia; initial Fugl-Meyer [FM] MotorScores = 31.5 (max = 66) for both participants) weretrained on a complex reaching task on their involvedside, requiring shoulder flexion with external rota-tion, elbow extension, and forearm supination com-bined with grasp. During training, each participantheld a (real) Styrofoam envelope using a lateralgrasp. The envelope was fitted with a sensor, whichrecorded the endpoint trajectory of the patient’sreaching movements, which in turn was displayedto the patient in the context of a VR scene. In the VRscene, a “teacher” animation placed an envelope inthe slot of a virtual mailbox. Six levels of difficultyfor this scene were devised (near and far reach withdifferent hand orientations). Participants practicedfor 1-hr sessions at a frequency of once or twice aweek, for a total of 16 sessions. Before and aftertraining, participants were assessed on their reach-ing ability using a 3-D kinematic test performed inthe real world. The kinematic test was repeatedthree times at 1-week intervals, prior to and follow-ing training. In the test, participants held an enve-lope in their hand and attempted to place it in a real“mailbox” slot. The box and slot were placed in ninedifferent locations, only one of which had beentrained in VR. Participants were also tested usingtwo standard clinical tests: the FM Test of Motor Re-covery for Stroke,59 and the motor task section of theSAILS test of UE function.60

Results for the kinematics test indicated that, notonly could participants transfer what they learnedin VR practice to the real world, but also, that they

generalized the motor learning to untrained spatiallocations. Both participants showed significant im-provement for distance errors to the target acrossboth trained and untrained locations (64% reduc-tion in error for P1, 50% reduction for P2, whenaveraged across all target locations). Hand orienta-tion errors improved for P1 in the trained locationand for five of eight untrained locations; however,no improvements in hand orientation were seen forP2. As expected, the control of hand orientationwhile reaching and grasping proved more difficultto learn than control of reach with no constraint onhand orientation. The clinical tests also showedsome improvement, greater for P1: FM motor testimproved by 17% for P1; 5% for P2. Neither partici-pant improved on the SAILS test, probably due topoor fine motor control of hand for both partici-pants. However, P1 reported that he gained theability to perform three new functional tasks withthe right arm following the VR training.

In a second study, the issue of motor generaliza-tion was examined in greater depth. The study pro-vided further evidence that movements trained inVR in patients with stroke can be generalized tosimilar real world tasks and to certain types of un-trained tasks. Preliminary results from the firstseven participants have been reported and will bereviewed here.14,61,62 Final results of this study, in-cluding a more extensive analysis of kinematicdata, additional participants and statistical analy-ses will be presented in a forthcoming paper.

In this study, two movements were trained in avirtual environment using the same system as inthe first study, but with the addition of quantitativefeedback about trajectory match with the virtualteacher that could be presented in the form of ascore following each trial. Specific and non-specificmotor generalization was assessed. Specific gener-alization was defined as transfer of learning fromVR to the real world measured during real worldperformance of 14 tasks designed to assess the fol-lowing six types of generalization: (1) same taskgeneralization; ( 2) spatial generalization; (3) gravi-toinertial force (GIF) generalization; (4) combinedspatial plus GIF generalization; (5) generalizationto tasks requiring novel recombination of trainedmovement elements; and (6) control tasks with un-trained elements. Non-specific generalization wasdefined as transfer of learning from VR to the realworld as measured by change in clinical tests ofmotor recovery and function following the VRtraining.

Participants (n = 7) with cortical and/or subcorti-cal stroke were tested (mean duration post-strokewas 20.4 months, mean age 52.6 years; four had left


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hemiparesis, three had right; five were male, twofemale). Initial FM UE motor scores ranged from 18to 54; mean score was 32 (maximum = 66). All par-ticipants primarily used the uninvolved UE for ac-tivities of daily living (ADL) tasks and were nolonger receiving therapy for the arm.

Participants were trained on two tasks in a vir-tual environment using a series of scenes that simu-lated the tasks at increasing levels of difficulty. Thefirst scene was the mailbox scene, which elicitedforward reach with grasp; the second scene re-quired the participant to reach smoothly out to theside (abduction to 45 degrees) with open hand andelbow extension, by moving the hand from its startposition resting on a table in front of participant atmidline, through a series of rings arranged alongthe trajectory of the hand path, approximately in asemicircle, to the final position out to the side.(Such a movement would be useful to catch one’sbalance, use hand for postural support, or to reachfor objects located lateral to participant.) Eachscene displayed a virtual “teacher” performing thecorrect movement. Augmented feedback about error,based on degree of match with the teacher trajec-tory, was provided during movement practice, ini-tially at high frequency, then faded to a lowerfrequency as sessions progressed. Participants re-ceived 30 sessions in total, 1 hr each, at a frequencyof three sessions per week.

During the specific generalization tests, 3-D kine-matics of the arm and trunk were measured usingan electromagnetic tracking device. Spatial errors(distance from movement endpoint to target) andnumber of velocity peaks were calculated for eachtrajectory. Non-specific generalization was as-sessed using the FM test of motor recovery, theWolf Motor Test for UE function,63,64 and twostrength tests. The test battery was administeredprior to and after the VR training.

Five of the seven participants showed quantitativeevidence of generalization, defined as a >25% reduc-tion in spatial error (range = 25–98%) or >25% reduc-tion in the number of velocity peaks (range = 25–97%)for the test movements following training. Largergeneralization effects were found for same task, spa-tial, GIF, and combined spatial plus GIF tasks than fornovel recombination and untrained tasks.

Results for the clinical testing (non-specific gen-eralization) of these participants (plus one addi-tional participant [n = 8]14) showed that the meanvalues post-training were significantly higher onboth the FM Motor and FM Total scores, indicatingimprovement (p = 0.008 and p = 0.048) for FMMotor and Total scores, respectively. These resultsindicate that most of the improvement was in

motor function, but some participants also had de-creased pain, increased range of motion and im-proved sensory scores post-training. Individually,all participants showed some level of improvementon the Motor subtest; the range was 2.5%–42%; themean across participants was 15% ± 14.8%. Indi-vidually, three of the eight participants improvedby >20% on the FM Motor test.

Results for the Wolf Motor Test of UE Functionindicated improvement, with lower Total Timescores post-training (p = 0.021). Average improve-ment was 31% ± 25.7% (range, 1–83%). Individu-ally, six of the eight participants improved by>20%. Of note is that the participants who showedlittle change on the FM measure all had large im-provements on the Wolf Motor test of UE Function.Conversely, the two participants who showed littlechange on the Wolf Motor test showed largerchanges (>20%) on the FM test.

Two strength tests, for shoulder flexion and forgrip strength, also improved after VR training. Thedifferences for shoulder flexion strength (mean in-crease 118%) were statistically significant (p = 0.02),and the differences for grip strength (133%) wereclose to significance (p = 0.058). Considered individ-ually, six of the eight participants increased eithershoulder flexion or grip strength, or both, by >20%.

Taken together, these improvements in threestandard clinical tests of function were surprising,given that participants practiced only two move-ments during VR training and that most of thetasks tested were untrained. These results are alsoencouraging, as they imply that something moregeneral than one specific movement is beingtrained by these VR methods, and thus VR may bean efficient way to train a set of “basis functions,”which in turn allow the execution of a variety ofmore skilled movements.

A third study on patients with stroke conducted bythis group will be described in the last section enti-tled Telerehabilitation. In this study, a wider varietyof training scenes (8–10 per participant) were used,and the scenes were designed to address specificdeficits displayed by each participant.

Rutgers group. A second group, Burdea andcolleagues, based at Rutgers University and theUniversity of Medicine and Dentistry of New Jer-sey, has centered their development around thehand. (The Burdea group has done extensive en-gineering development for a variety of VR reha-bilitation applications.)

System description. Their UE system makes useof the commercially available Cyberglove™ to

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monitor hand position and to provide feedbackabout kinematics of hand movement during train-ing, and a laboratory-built glove, Rutgers Master II,to provide haptic monitoring and feedback com-bined with position sensing.13,65 Four types of handexercise routines have been developed: (1) range ofmotion (ROM); (2) speed; (3) fractionation; and (4)strength.

In the ROM exercise, participants begin withtheir fingers in extension, and attempt to move ei-ther the thumb or the four fingers into flexion. Asthey do so, a picture is revealed on the screen, withthe amount revealed roughly equivalent to theamount of flexion ROM. For the speed exercise,participants again begin in extension, seeing theiropen “virtual” hand on the screen. Then a butterflybegins to flutter around the hand, and the partici-pant attempts to rapidly flex the fingers in order to“catch” the butterfly. The fractionation exercise isdesigned to help participants practice isolated fin-ger control. In this exercise, participants see a pianokeyboard on the screen, with the virtual hand onthe keys. The patient tries to depress a single keyusing a single finger (flexion), while maintainingthe other fingers in extension. If successful, the keyturns green; errors cause keys to turn red. For thestrength exercise, a different glove is used (RutgersMaster II),13 which has small pneumatic pistons inthe palm, with movable rods fixed to the fingertips.The participant practices with thumb and eachfinger separately, depressing the piston against aforce applied via the computer. On the screen, theparticipant sees a virtual hand, with virtual pistonsin the palm. The pistons are red at the start of eachtrial, but turn green if the target force level isachieved by the patient. For all of these exercises,participants receive immediate visual feedbackabout their ongoing performance by viewing thevirtual hand on the screen. In addition, followingeach trial, participants receive a numerical scorewhich provides quantitative information abouttheir performance.65,66

Study results. The Rutgers group has used theirhand rehabilitation system in two clinical studieswith chronic stroke patients. The first study usedthe system on three participants with right hemi-paresis.65,67 In this initial study, the VR treatment wascombined with another type of treatment for UE re-habilitation, constraint-induced (CI) therapy.68,69 Theparticipants ranged in age from 54 to 83 years, were3–6 years post-stroke, and had a fairly high degree ofmotor recovery, as they met the criteria used for in-clusion in CI studies (i.e., active wrist extension of20° and 10° of active MP extension).

Participants were treated for 5 hr per day for 9days, with one 2-day break. The majority of thetime (approximately 3.5 hr/day) was spent in CItherapy, while the remainder was spent in VR ther-apy (approximately 1.5 hr/day). Because two dif-ferent treatments were used in combination, it isnot possible to determine whether, or to what ex-tent, the VR therapy contributed to the changesfound in the participant’s post-training.

Participants’ progress following this combinedtherapy was measured using quantitative mea-sures of ROM, speed, fractionation, and work, de-rived from the VR training data (performance offirst 2 days vs. last 2 days). In addition, a clinicaltest of hand function (Jebsen)70 and dynamometermeasures of grip strength were performed. Resultsfor the measures derived from the VR training datashowed a variable pattern, with all three partici-pants showing improvement on at least some of themeasures. The ROM changes were small (approxi-mately 10° finger flexion; 20° thumb flexion). How-ever, changes for fractionation and speed, seen intwo of the three participants, were larger (25° forfractionation; speed increases of 16–69% for thumband 21–52% for fingers). Mechanical work capacityimproved by a small amount across participants(9–25%). For the clinical test, two participants im-proved (+11%, +29%), while the third participantgot worse (�7%). All three participants increasedtheir grip force (range, 13–59% increase). However,two participants showed similar rates of grip forceincrease on their non-involved side, so some of thechange seen following training may have been dueto the simple practice of the dynamometer griprather than to specific effects of either the CI or VRtraining.

In the second study reported by Burdea and col-leagues,66,71 eight participants with stroke weretreated using the VR system alone. Preliminary re-sults from the first four of these participants are pre-sented in the first report,66 while results for all eightparticipants are presented in a more recent report.71

Data from the second report is reviewed here. Par-ticipants ranged in age from 50 to 81 years, six weremale; two female; seven had a right hemiparesis,and one had a left hemiparesis. Although initialclinical scores are not reported, all had a fairly highdegree of motor recovery, as they met the minimumcriteria of active wrist extension of 20° and activeMP extension of 10°. Treatment sessions were 2 hr inlength, conducted 4–5 times per week for 3 weeks(total = 13 sessions, or approximately 26 hr). The VRexercises were the same as those in the prior study(i.e., ROM, speed, fractionation, and strength). Eachexercise was repeated 40–60 times, for a total of


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approximately 160–200 movement repetitions persession. As in the prior study, participants receivedfeedback about performance both during and afterevery trial. Results were measured by assessing thepercent improvement in performance in VR (first2 days vs. last 2 days of training). In addition, par-ticipants performed a clinical test (Jebson test ofhand function70) and a real world grasping taskusing the Cyberglove, to assess transfer to real worldperformance.

For the quantitative VR measures (ROM, speed,fractionation, and work), results are not averagedacross participants; rather, they are presented foreach participant individually, as “each participantshowed improvement on a unique combination ofmovement parameters.” The most impressive areasof change seem to be for thumb ROM (four of eightparticipants improved by >40%) and for fractiona-tion where six of eight participants improved by>40%). The changes for speed and work are smalland likely not clinically significant, though the au-thors report “statistical significance” based on re-sults of unpaired t-tests, performed individually foreach participant. For example, on the speed mea-sure, only three of 16 cases (16 = 8 finger + 8 thumbmeasures) had >20% improvement, and only threeof the eight participants had >20% change on thework measure. For the Jebson test of hand function,results were pooled across participants, and a 15%improvement was found. However, since thesedata were pooled across participants, it is not clearwhether the 15% change reflects a large improve-ment by a few participants, or a smaller change bymost participants.

For the grasping task, hand kinematic data wereanalyzed in terms of movement time, averagedacross participants. No change in movement timewas found for the transport phase, but an 18% de-crease in movement time was found for the grasp-ing phase, although three of the eight participantsdid not decrease their grasp movement time. Al-though the authors report that they performed adiscriminant analysis on the hand kinematic dataas a way to assess hand preshaping during theevolving movement, the results of this analysis arepresented for only one participant’s data in graphi-cal form. For this participant, classification errorsfrom the discriminant analysis are shown to de-crease as the movement evolves, indicating an im-provement in the timing of hand preshaping duringthe grasping task.

Groups in Sweden, United Kingdom, and Italy. Agroup in Sweden has described the use of anotherVR system, consisting of a Reachin Technologies

AB 3.0 system with haptic force feedback providedby a PHANToM device and stereoscopic visionprovided by CrystalEyes CE-2 glasses in a singlecase study of one stroke patient.72 The participantwas a 59-year-old man with left hemiparesis, 11weeks post-stroke, with normal spatial competenceand body awareness. He trained using a computergame developed by Reachin Technologies, in whichthe participant strikes a ball, which in turn knocksover bricks, and gives a score. He was treated threetimes per week for 4 weeks for a total of 12 sessionsand progressed through four levels of difficulty(based on faster ball velocities), using a perfor-mance criterion. It was unclear whether he was alsoreceiving additional therapy. The use of telemedi-cine was mentioned, but it was not clear whetherthe patient was using the VR system in the labora-tory, with the telemedicine system employed as anadjunct to communicate response to the treatmentfrom home, or whether the entire VR system wasinstalled in the patient’s home, and the treatmentwas conducted via a telemedicine set-up.

The patient was evaluated using three tests: (1)Purdue pegboard; (2) hand grip using a dyna-mometer; and (3) a laboratory-developed reachingtest, using the PHANToM to record data. Followingthe training, he increased the number of pegs fromsix to eight on the Purdue test, increased gripstrength from 68 to 264 N, and improved somewhaton selected kinematics measures derived from hisreach trajectory data. For example, path length ofthe trajectories decreased (by 0–11 cm, dependingon direction), movement time decreased (by ap-proximately 0.5 sec), and movement velocity in-creased (by ~10 cm/sec for one direction).

A group at the University of Nottingham73 ex-plored the use of VR in stroke rehabilitation via a“user centered design approach” that involvedconsultation with stroke survivors, therapists andstroke researchers. Based on input from thesegroups, the activity of making a hot drink was se-lected for development and study. This group useda different approach for their VR system. Theybegan by building a real (“tangible”) interface forthe task, consisting of a series of instrumented ob-jects. To conduct training in the task of making ahot drink, the real objects and VR are integrated ina unique fashion. For example, the computer firstinstructs the patient verbally to place the kettleunder the tap. Once the movement has been sensedfrom the instrumented real kettle, a signal is sent tothe computer and the VR plays a simulation of theactivity (e.g., participant hears water running andsees a kettle filling). Then the next subtask in the se-quence is suggested verbally by the computer. If

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the patient performs the incorrect task, the com-puter corrects the participant and the user cannotproceed until the correct task is performed usingthe correct real world hardware. This procedure isrepeated until the 16 subtasks for this activity havebeen completed.

Seven participants tried out this system in a pilottest. The participants were community dwellingstroke patients, all with right hemiparesis andaphasia. Six of the seven had “little to no use” ofthe involved arm. (Although not specifically men-tioned, this would imply that participants wereusing their non-involved extremity to complete thetask, making it more a cognitive training than amotor training tool for these particular partici-pants.) Observations were made as participantsused the system, and notes were taken on both par-ticipant and system performance. Through thisprocess, problems were identified and potentialsolutions were discussed. The two main points,which are planned for implementation in futuremodels of the system, were to let the user imitatethe virtual task, and to provide feedback about per-formance using the VR system in order to enhancelearning of the task. (Note that the system devel-oped by Holden and colleagues14,15,55 already doesthis.) While this device appears to be a good train-ing system, its effectiveness has yet to be tested. Italso seems labor intensive in terms of its develop-ment (especially if additional tasks were to betrained), and it is not clear whether training on thisone task would generalize to other real world tasks.

Others have described the usefulness of VR sys-tems in the assessment of arm motor deficits follow-ing stroke or brain injury.74 Piron et al. describe howa VR system was used to provide a more sensitive,precise and objective measure of progress in reha-bilitation settings. Twenty patients with chronicstroke (mean, 8.2 months post-stroke) were treatedwith “standard” rehabilitation therapy for 1 hr perday, 5 days per week (20 sessions total). Before andafter the therapy, patients were tested with the FMTest of Motor Recovery59 and two kinematic mea-sures (movement duration and average velocity),which were derived from 20 repetitions of a reach-ing movement, performed in a virtual environment.The changes in the kinematic measures followingtherapy were statistically significant (average move-ment duration was 4.4 sec prior to and 3.5 sec fol-lowing treatment; average velocity changed from19.6 cm/sec before therapy to 26.3 cm/sec aftertherapy). In addition, the kinematic measures werefound to correlate significantly with the FM test59

(Pearson correlation = �0.82 to �0.97 for duration,and 0.82 to 0.97 for velocities, all at p < 0.01). The VR

test was thought to be useful for evaluating the re-sults of rehabilitation treatments, as it was fasterand easier to perform than the FM test.

Several of the research groups whose work is de-scribed above are also developing telerehabilitationapplications of their VR systems.

Lower extremity/gait

Burdea and colleagues have also developed a VRhaptic device for use in training ankle control, the“Rutgers Ankle.”75–77 The details of the engineeringdesign are well described in these articles, so only abrief description is provided here. The system con-sists of a Stewart platform-type haptic interfacethat provides 6 DOF resistive force to the patient’sfoot, in response to his or her performance in agame-like VR exercise. The patient is treated in thesitting position, with the foot attached via a foot-plate to the device. Two exercise games have beendeveloped. In the first, the patient pilots a virtualairplane, by using the foot, through a virtual sky.As the plane moves forward, a series of opensquare hoops are presented on the screen. The goalis for the participant to maneuver the planethrough the hoops without hitting the sides. This isdone by mapping the ankle kinematics to the flightpath (e.g., ankle dorsiflexion causes the nose of theplane to point upward, eversion causes the plane togo toward the left). Difficulty level can be adjustedby changing the number and placement of hoops,airplane speed, and the amount of resistance pro-vided by the haptic interface. A second game callsfor the participant to pilot a virtual speedboat overthe ocean while avoiding buoys, again by movingthe ankle up/down or in/out. A recent addition tothese games is the ability to apply task-related hap-tic effects such as a “jolt” when a buoy or hoop ishit, or to change the environmental conditions byadding turbulence to the air or water (implementedby generating a low-frequency side-to-side vibra-tion of the platform75).

To date, the system has been used in two pilotstudies with stroke patients, the first a single casereport77 and the second involving three patients.75,76

In the first study, a 70-year-old patient with lefthemiparesis, 11 months post-stroke, was treated.Concurrent with the experiment, the patient wasalso receiving outpatient physical therapy twice aweek. That therapy was focused on improving theuse of the affected hand, strength and coordinationof affected leg, and on balance and coordinationtraining in standing. Thus, it is difficult to knowwhich treatments may have contributed to thechanges noted after the VR treatment. The patient


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received six sessions of VR training, with testingand training in sessions 1 and 6. The amount of timespent working in the VR exercise ranged from 13 to26 min over the sessions. The patient practicedankle movements by interacting with the airplanescenario, guiding the plane through the hoops, atincreasing levels of difficulty, as described earlier.Following training, the participant had gained 10degrees of plantarflexion ROM, increased torqueproduction for ankle inversion and eversion (by3 Nm), and ankle power from 200 W in session 1 to550 W in session 6. The largest changes were seenfor accuracy, as measured by the number of hoopsentered (whether on not sides were hit); this in-creased from 32% in session 1 to 95% in session 6 forthe dorsiflexion/plantarflexion movement. Clini-cally, a large decrease was seen in time required toclimb four stairs, which was 90 sec in session 1 and20 sec in session 6.

In the second study,75,76 three patients with stroke,mean age 52 years, 1–8 years post-stroke, weretreated three times per week for 4 weeks, for 1-hsessions (total = 12 sessions, with total exercise timeranging from 20 to 50 min per session). It is notmentioned whether these patients were receivingany additional concomitant therapy. The patientsdemonstrated increased power, as measured by thesystem, as well as increased muscle strength, asmeasured by a hand-held dynamometer (range ofincrease across the four muscle groups, 0.5–13 N).Although increases in gait speed are reported, theonly value presented is for one participant, who in-creased his score on the 6 min walk test by 9%. Thechanges in strength seen for selected muscles forsome participants were large, especially consider-ing the relatively small amount of time spent intreatment. The Rutgers Ankle system has also beenpilot tested with orthopedic patients.

These authors are currently developing a sub-stantial enhancement to this system, which willallow training in standing and also virtual walk-ing.78,79 The new system will add a locomotor hap-tic interface to two linked Stewart platforms (onefor each foot). It will be able to withstand higherloads and apply 6 DOF force and torque to the feet,thus simulating different surface support condi-tions (such as ice, gravel, normal sidewalk). VRsimulations for use with the device are being devel-oped, one for crossing a street, and another forwalking on a park path.

Another group of researchers, located at the PaloAlto Veterans Administration, have recently de-scribed the use of VR technology to train obstacleavoidance during walking in chronic post-stroke

patients,51 and reported an advantage for the VRmethod. In this study, 20 participants with hemi-paresis (10 right, 10 left, mean age, 60.7 years; meantime post-stroke 3.8 years) were randomly assignedto receive training in obstacle avoidance duringwalking via either a real world scenario or a virtualworld scenario. Both groups received six sessionsof 1 hr in duration, given over a 2-week period (6 hrof total training). Each session consisted of 12 walk-ing trials. During each trial, a series of 10 objectshad to be “stepped over.” Participants in the realworld scenario practiced stepping over (real) foamobjects placed along their walking path at distancesapproximating their stride length. Participantsbegan with small (2” � 2”) objects and progressedto larger objects based on their performance. Partic-ipants in the virtual training scenario walked on atreadmill at a self-selected comfortable velocity andviewed virtual obstacles through a head-mounteddisplay (HMD). The virtual objects were superim-posed on a real time lateral video view of their footand leg as they attempted to clear the object. Thesoftware was programmed with collision detection,and if the foot “touched” the virtual object, a tonewas heard, and a vibrotactile signal was applied tothe participant’s toe or heel, to provide enhancedfeedback as to the location of the error. In addition,the participant could see their foot on the video. Al-though the view was rotated 90º from the normalwalking viewpoint, there were no reports of ill ef-fects or confusion on the part of participants (per-haps because it was an HMD, and no conflictingvisual input from a different perspective could beseen). There were also no complaints of cybersick-ness from any of the participants. Virtual trainingparticipants practiced with 10 steps over virtual ob-jects per trial, as in the real world condition. Partic-ipants were allowed to hold on to the side rails ofthe treadmill, and as an additional precaution,wore an overhead safety harness to protect againstpossible falls.

Although both groups improved on most of theoutcome measures used, participants in the VRtraining showed greater improvement (p < 0.001) infast paced velocity post-training. There also seemedto be an advantage for the VR group in improve-ments in obstacle clearance and step length of thenon-paretic side, but these differences were not sta-tistically significant. A 2-week follow-up test showedthat participants in both groups had retained theimprovements they had made, with some mea-sures showing continued improvement. Given therelative brevity of the training and low number ofrepetitions, and the duration post-stroke of the par-

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ticipants, these results are impressive, and lay thegroundwork for further work in this area.

Spatial and perceptual-motor training in stroke

Connor et al.80 have experimented with the useof an active force-feedback (AFF) joystick to traina perceptual motor skill in the uninvolved UE of12 stroke patients. These authors wished to testwhether errorless learning (EL), a method provento be effective in teaching new information to par-ticipants with memory problems,81,82 could proveuseful in re-training perceptual motor deficits. Er-rorful (EF) learning (movement practice, allowingerrors, and standard knowledge of results feed-back) was used as a control training method. Twelvecommunity dwelling stroke patients were re-cruited, all >1 year post stroke, age 38–83 years. Allhad some form of visuospatial processing deficit,ranging from minor to profound. A within-partici-pant, cross-over design, randomized to sequencewas used. Group 1 received EF first; Group 2 re-ceived EL first. Participants were treated once aweek for 4 weeks for each method, with a 3-weekwashout period in between. During training, par-ticipants sat at a computer and used an AFF joy-stick with their uninvolved hand. A series of lettersor numbers were randomly dispersed on the com-puter screen, together with a variable number ofdistracter objects. The participant’s task was to con-nect the sequential items by moving a cursor on thescreen using the joystick, then pressing the buttonon the joystick when they felt the cursor was in thecorrect location. In the EL condition, a “force fieldvalley” was defined which prevented movementsto incorrect targets on the screen, but allowed cor-rect movement. Thus, when participants moved, no“errors” were made. In the EF conditions, no forceswere applied, so participants could make errors,which they saw visually on the screen.

Participants were tested weekly, before, duringand after training. Five sets of different target com-binations were used. Data were analyzed for re-sponse time and for maximal deviation from astraight trajectory for each target link. The resultsshowed no difference for EL versus EF. Overall,five of 12 participants improved on response time;only one improved in the trajectory error measure.Group 1 (EF first) did better than Group 2 (EL first)in that four participants versus one participant in-creased response speed. However, these differencesmay also have been due to differences in partici-pant impairment levels. Although these results arenot dramatic, they do indicate the feasibility of the

treatment approach. The authors speculate thatbetter participant selection, more frequent andmore individualized treatment might improve theresults in the future with this method.

In another study, Rose et al. evaluated the effectsof a VR exposure on spatial memory and objectrecognition memory.83 Forty-eight patients withbrain injury of vascular etiology (stroke), withequal numbers of young and old, left and righthemisphere involvement, participated. Mean agewas 61 ± 17 years. Forty-eight unimpaired controlparticipants, mean age 36 ± 11 years. were also in-cluded. Patients and control participants were ran-domly assigned to an active or passive VR group. Avirtual bungalow, consisting of four interconnectedrooms, was created and displayed on a desktopcomputer. The virtual rooms could be navigatedusing a joystick. In addition, a total of 20 objectswere embedded in various locations throughoutthe four rooms. Participants in the active groupwere told to enter the house and use the joystick tofind a route through the rooms. At the same time,they were instructed to study the various objectsand to try to find a toy car. Participants in the pas-sive group watched a recording of the last activeparticipant’s path through the house (this was aclever control for exposure time), but received thesame instructions regarding the embedded objects.All participants received only one trial of the task.Following this single VR exposure, participantscompleted two tests: (1) a spatial recognition test,in which they guided reconstruction of the bunga-low by the experimenter, using real 2-D cardboardelements; and (2) an object recognition test, in whichparticipants were randomly presented with pho-tographs of the 20 test objects that had been in thebungalow, and 20 ruse objects, and had to reportwhether they recognized the objects as having beenin the virtual house. Since the idea was to test inci-dental memory, no instructions were given in ad-vance as to what would be tested following the VRexposure.

The results showed that for the spatial recon-struction test, active VR use improved the perfor-mance as compared to passive VR use, for bothpatients and controls. Considering that participantsreceived only a single exposure to the VR bunga-low, these results are quite impressive. They sug-gest that one way to enhance spatial learning/memory in patients with stroke may be to use mo-toric encoding to tap into spared procedural mem-ory. VR can provide a convenient way to do this.For the object recognition task, however, active/passive VR made no difference to patients’ scores,


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whereas for the control participants, performancewas better following the passive VR condition. Thisfinding was interpreted for control participants ashaving been due to having more time availableduring the passive exploration condition to viewobjects in the virtual house (e.g., less attention toactual control of the joystick). The fact that a similareffect did not occur in the stroke participants wasattributed to their memory deficit (relative to con-trols) and to having had no enforced proceduralcomponent in the active exploration VR condition(such as touching each object) that might have facil-itated procedural learning.

Children with severe motor disabilities oftenhave poorly developed spatial awareness.84 Onesignificant contributing factor to this deficit isthought to be the reduced ability to explore the en-vironment in an active way secondary to the mobil-ity impairment. VR technology has been proposedas a way to offer such children a chance for active,independent spatial exploration. Wilson et al.85 havetested whether such training in VR would result inimproved spatial knowledge in a comparable realworld setting. The authors used a desktop VR sys-tem to train large-scale spatial knowledge of a two-story building. Participants (n = 10) were childrenwith a variety of disabling conditions, includingspina bifida, cerebral palsy, and muscular dystro-phy. All relied on a wheelchair as their primemethod of mobility, though three participants couldwalk short distances with a walker. They ranged inage from 7 to 11 years. A control group of eighthealthy adults, mean age of 23 years, received noVR training, but underwent the same testing as thechildren. Children received one training session.They explored a virtual model of the actual build-ing in which the experiment was conducted, withthe goal of finding the fire extinguishers and thefire exit door. Immediately following VR training,they were tested on knowledge of the fire extin-guishers and fire door locations in the real buildingin two ways. First, while still in the training roomwith the computer, participants used a pointer toaim at the expected location. This was followed bya wheelchair tour of the real building, duringwhich participants were asked to guide the experi-menter to two specific locations. Results showedthat all the participants were able to point to andfind the desired locations in the real world, and todo so significantly better than control participantswho received no training.

Broeren et al. in Sweden have used a VR system tomeasure neglect in patients following stroke.86 Thesystem utilized a Reachin 3.0 system, stereo visionwith Crystal Eyes, and a PHANToM to provide hap-

tic feedback. In this paper, they describe the devel-opment of a VR test to measure neglect, and com-pare the results with those from standard clinicalmeasures of neglect. Four patients with stroke, meanage 51.5 years, 7–36 weeks post-stroke were evalu-ated. All were right handed, with left hemiparesis,and had shown evidence of neglect at 2–5 weekspost-stroke. A reference group of nine healthy par-ticipants, mean age 53 years, was also tested. Partici-pants completed two clinical tests of neglect, the StarCancellation test,87 and the Baking Tray Test,88 andthe VR test developed by the authors.

The authors found a reasonable correspondencebetween the tests, and they found that the new VRtest was at least as sensitive as the clinical tests indetecting neglect. In addition, the VR test was ableto measure additional variables that might enhanceits sensitivity relative to the clinical tests. For exam-ple, target detection time, and search strategy pat-terns showed abnormalities in Participant 1, whohad scored within the normal range on the stan-dard clinical tests.

Another group is working on improving wheelchairmobility in patients with stroke who have unilateralneglect.50 This study is discussed in the WheelchairMobility and Functional ADL Training section.

ACQUIRED BRAIN INJURY: MOTOR TRAINING

Most rehabilitation efforts using VR with thispopulation have involved cognitive rehabilitation,a topic reviewed elsewhere in this issue (Brooks etal., this issue). There have been few attempts towork with motor retraining in the acquired braininjury (ABI) population using virtual environ-ments. One group that has done so is Holden andcolleagues.89,90 In this study, eight patients with ABI(seven male, one female; mean age 27.3 ± 8.8 years,mean duration post-injury 9.5 ± 7.0 years) weretrained in the functional task of pouring from acup, within a virtual environment. The VR systemused was the same one described previously foruse with stroke patients, but the scenes used weredifferent. Participants had primarily a hemipareticdeficit (five right, three left) and received trainingon the involved arm. All participants received ablock of 16 one-hour treatment sessions, at a fre-quency of three times per week. Four of the eightparticipants received a second block of 16 VR ses-sions, making a total of 32 sessions. Prior to and fol-lowing each treatment block, participants receivedan evaluation battery of tests. The battery was ad-ministered twice, at a 2-week interval. Four mea-

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sures of UE motor performance were included: (1)the FM Test of Motor Recovery;59 (2) the Wolf MotorTest;63,64 (3) strength tests for shoulder flexion andgrip; and (4) a behavioral kinematic test of pouringskill. This last test consisted of measuring the 3Dkinematics of trunk and arm movements during apouring task performed in the real world. Duringtesting, participants held a cup filled with oatmeal,then at the start signal, lifted the cup and pouredthe contents into a second cup, located on a table infront of them. Six target locations were used; onlyone or two of these locations were trained duringthe VR sessions. The end-point trajectories (path ofthe cup) were analyzed to assess progress.

Following VR training, both the Wolf Motor Testand the FM Total UE scores improved (p = 0.010,p = 0.034, respectively), and the FM Motor subscoreshowed a trend toward improvement (p = 0.068).Strength did not change significantly. These resultsindicate a significant amount of generalization ofthe motor training received in VR to functionalADL tasks. The term “generalization” is used herebecause these clinical tests consist primarily oftasks that were not specifically trained in VR dur-ing the experiment. Analysis of the pour trajectorydata indicated that the time spent to accomplish thepouring task and the size of the spatial volume en-compassed by the cup path during pouring (an in-dication of stability of the hand during pouringand the precision of the pouring movement) de-creased for most participants following training.Quantitative measures derived from the pouringtrajectories, averaged across participants, suggestedsome reductions in length of hand path, trunkmovements, response times and number of velocitypeaks following training. However, for the mostpart, these changes did not reach statistical signifi-cance. When data for individual participants wereevaluated, it was found that some participants im-proved more on the transport phase of the move-ment, while others improved more on the precisionof the pouring movement. Thus, when data fromthese two types of participants were averaged to-gether, these positive effects cancelled each otherout, and mean improvements appeared low.

The study served to demonstrate that even par-ticipants with significant motor and cognitive im-pairment are capable of at least some learningwithin a virtual environment, and that it is feasibleto use VR to teach functional tasks, such as pouringfrom a cup, which would be inconvenient or messyin the real world.

A group from Sweden has reported early resultsfrom a project designed to evaluate the potentialusefulness of VR in brain injury rehabilitation.91 In

this paper, the authors describe the broad spectrumof tasks that need to be re-learned by patients fol-lowing brain injury. Such tasks require learning ona variety of levels, from physical to cognitive. Threebroad categories of tasks which present challengesfor participants with brain injury were identified:preparing food, managing finances, and findingone’s way from one place to another. Specific VRapplications were developed to train tasks from eachof these categories. The tasks selected were (1)kitchen-based training (making coffee, setting atable); (2) using vending machines, specifically anautomated teller machine (ATM); and (3) way-finding, specifically using two prototype virtualenvironments representing the local hospital anduniversity buildings. Although no clinical data ortraining data are reported, the article does presentuseful and relevant information about the develop-ment of such a system for this population.

Researchers from Texas have begun to evaluatethe use of VR as a diagnostic tool for ADL skills fol-lowing ABIs.92 They have developed a virtualkitchen environment and a test task, that of makingsoup and a sandwich, to serve as an evaluationtool. This meal preparation task was broken downinto 81 subtasks; each subtask received a ratingwith the sum of ratings as the total score. This testtool has been evaluated for reliability and validity.To assess these attributes of the test, 54 participantswith ABI were evaluated. Participants ranged inage from 18 to 69 years, with the majority of partic-ipants (63%) between 18 and 35 years old. Forty-sixhad been in a coma following injury, with a meanduration in coma of 11 days. All had total Func-tional Independence Measure (FIM) scores of >60and FIM cognitive domain sub-scores of >20. Eachparticipant performed the virtual kitchen test ontwo occasions within a 3-week period. They alsoperformed an actual kitchen test, similar to the vir-tual test, on two occasions. In addition, they re-ceived a single occupational therapy (OT) evaluationfor meal preparation and for cognitive skills, and upto 12 different neuropsychological tests.

An intraclass correlation coefficient (ICC) testwas used to evaluate test-retest reliability and re-vealed an r value of 0.76, indicating good reliability.A Pearson test was used to assess validity, revealingan r value of 0.63 for the virtual kitchen test withthe actual kitchen test (p < 0.01). Significant correla-tions were also found for the virtual kitchen perfor-mance with eight other tested variables (range ofr values 0.30–0.56, p < 0.05). A regression model wasconstructed, using the tested variables, to assesswhich tests were the strongest predictors of actualkitchen performance. Although the model was sta-


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tistically significant, the R2 was not overwhelming(R2 = 0.34). Two variables in the model had signifi-cant beta weights: the virtual kitchen performance(� = 0.35, p = 0.014) and OT meal preparation score(� = 0.45, p = 0.007).

VR USE IN PARKINSON’S DISEASE

One of the primary symptoms of Parkinson’s dis-ease (PD) is akinesia, or difficulty in the initiationand continuance of motions, in particular duringambulation. These symptoms tend to worsen as thedisease progresses. Although the symptoms can bemitigated by drugs such as L-dopa, over time thesedrugs can become less effective and may produceunwanted side effects, such as correaform andathetotic movements. Thus, an alternative methodto treat akinetic gait in PD could offer patients away to delay or reduce drug use while still main-taining or improving function

Such a method is being developed and tested bya group of researchers led by Weghorst and Riess.The method is based on an interesting phenome-non associated with patients with PD termed “ki-nesia paradoxa.” Patients with PD, who are unableto ambulate, or even initiate a step on open groundare, paradoxically, able to step over objects placedin their path with little difficulty. Weghorst and col-leagues have conducted a number of studies toascertain whether VR technology could provide away to take advantage of this phenomenon and fa-cilitate walking in PD patients by presenting vir-tual objects overlaid on the natural world.

In the first study, investigators attempted to de-termine which aspects of the stimuli accounted forthe “kinesia paradoxa” effect.93 For example, couldnon-tangible objects elicit it? If a virtual environ-ment was used to provide the cue, how would fac-tors such as eye dominance, field of view, locationwithin field of view, and image realism affect theresponse? Testing was done with both a simplelaser pointer and with a Virtual Vision Sport, a dis-play device with a visor and small lens mounted infront of one eye reflecting a liquid crystal display(LCD). The authors found that spatial stabilizationof the cue was a critical factor in its effectiveness.The cue had to appear stable in the external world(i.e., a virtual cue had to move relative to the partic-ipant). The realistic nature of the cue was found notto be important; robust effects were obtained withboth the laser pointer and small yellow squares inthe VR display. The vertical field of view was foundto be important, as both a cue near the body, andtwo or three cues, corresponding to 2–3 paces

ahead, were needed. The cue near the body was as-sociated with gait initiation, but the far cues wererequired to continue gait. The laser pointer provedto be inconvenient, as it had to be moved, andturned on and off, to facilitate the gait. As well, inoutside light, the laser pointer was not visible.

Two patients with PD were evaluated with theVR technique. The first participant had a dramaticincrease in stride length, from 3 to 26 in. This par-ticipant also learned, after 2 h of practice using thelaser pointer as a cue, to initiate and sustain gaitwithout a cue. This effect was maintained (thoughfragile) for 2–3 months. The second participant hada smaller increase in stride length (8%), and wasunable to learn to initiate and continue gait in theabsence of cues.

In later articles, the system features are describedin more detail.94–97 One report mentions that theprototype system was found to work with “morethan 20 patients in early testing,” but specific re-sults, such as standard gait measures, are not re-ported.96 The authors refer to the use of “augmentedVR” in the system, by which they mean technologythat combines the real world view with the virtualenvironment view. Initially, see-through head-upinformation displays that fuse the natural scenewith physically registered graphical overlays wereused in combination with a head position tracker toachieve a “space-stabilized” image. However, thesedisplays were not bright enough to compete withambient light. The solution was to partially occludethe visual field, using a field-multiplexed display,which projects an image near optical infinity super-imposed on the realworld image. A portion of onevisual field is occupied by an occlusive and colli-mated reflection of a small LCD panel mounted inthe brow piece. Continuous virtual objects (bars)scroll downward in the participant’s visual field,giving the illusion of objects that are stable relativeto the ground. This induces participants with PD to“step” over them. The lower part of the field ofview has been found to control the gait initiationresponse, while the upper part of the field of viewis linked with sustaining the gait. Another key fac-tor in success of the technique was found to be themovement speed of the virtual cues, which must belinked to the user’s gait speed, so that virtual cuesare spaced at apparent stride length.

With further testing, the investigators have alsofound that the greater the impairment of the par-ticipant, the more realistic the virtual cues need tobe. However, the realism required is not photoreal-ism, but “interactive” realism (i.e., the run-timemodifications of cue spacing to adjust to differentwalking speeds and stride lengths, as well as per-

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spective changes with head tilt). Further work isnow being done to investigate the relative impor-tance of a variety of factors on the effectiveness ofthe visual cues ability to elicit the “kinesia para-doxical” effect.95,97

Riess is currently working on the development ofa sunglasses-like commercial device to deliverthese visual stimuli to PD patients. He has also re-ported that similar visual cues can have a profoundcalming effect on the dyskinesia induced by longterm use of L-dopa.95

A group in Italy has reported on the potentialusefulness of VR as a way to evaluate deficits inADL in participants with PD.98 In this paper, theyreport preliminary findings on two participantswith PD who navigated in a virtual flat using a joy-stick and were then tested on three performancemeasures: (1) a speed test (“walking” from livingroom to bathroom; (2) a pointing task (object identi-fication); and (3) an incidental memory task (objectrecall). Ten normal participants were also tested.The participants with PD also received a battery ofsix standard neuropsychological tests, the results ofwhich were in the normal range. The results for theVR tests, however, suggested some differencesfrom those of the normal participants, especiallyfor the speed test and, to a lesser extent, the inci-dental memory test.

WHEELCHAIR MOBILITY ANDFUNCTIONAL ADL TRAINING

A computer-assisted training (CAT) program forthe treatment of unilateral neglect has been de-veloped by Webster et al.50 In a recent study, theyexamined whether use of the CAT system in combi-nation with a wheelchair simulator device wouldbe effective in improving real world performanceon a wheelchair obstacle course in a group of pa-tients with stroke and unilateral neglect syndrome.In addition, they examined whether this traininginfluenced the number of falls experienced by par-ticipants during their inpatient hospital stay.50 Fortypatients (38 men, two women) with right hemi-sphere stroke participated. All were right handedand showed evidence of unilateral neglect, definedas specific scores on two standard tests of neglect,the Random Letter Cancellation Test99 and the Rey-Osterrieth Complex Figure test.100

Twenty of the patients received the CAT treat-ment for neglect. The remaining 20 patients, whohad participated in a prior study of unilateral ne-glect, served as controls. Both groups received astandard inpatient rehabilitation program, includ-

ing real world wheelchair training to improve mo-bility and obstacle avoidance skills. Participants inthe VR experimental group also received 12–20 ses-sions of CAT. Sessions were 45 min in length, deliv-ered five times per week during the inpatientrehabilitation stay. The control participants did notreceive additional training of any kind beyond thestandard rehabilitation care (thus, as measured bytime, the amount of therapy was unequal betweenthe two groups). Extensive testing was performedon participants. All participants received the previ-ously mentioned neglect tests as part of screeningprocedure. Participants in the VR-CAT group weretested on two virtual tests, a video tracking test anda video obstacle course test, before and after theCAT training to assess their virtual world learning.The main outcome measures, assessed for bothgroups, were the number of falls during partici-pants’ inpatient stay (obtained from a review of in-cident reports), and scores on a wheelchair obstaclecourse test performed in the real world.

The training method employed by the investiga-tors is very well thought out, logically progressed,and highly relevant to the deficits one sees in suchpatients. Their method is fully described in their ar-ticle, but will be briefly summarized here. Patientsview a virtual wheelchair on a large, wall size LCDscreen. They navigate the chair using either a handcontroller or wheelchair simulator, through variousscenes that involve turns and obstacle avoidance.Five modules were developed that began with sim-ple task components, and then progressed to morecomplex task control based on participant’s perfor-mance. The five modules were (1) scanning the fullfrontal environment; (2) coordinating scanningwith right UE movements; (3) detection of stimuliin left hemi-space; (4) wheelchair simulation; and(5) additional training on obstacle avoidance. Ex-tensive software features of many types were usedto provide feedback about performance and guidecorrect movement.

The results showed that the patients who had re-ceived the VR-CAT training made fewer errors,and hit significantly fewer (p < 0.000) obstacleswith the left side of their wheelchair during thereal world wheelchair obstacle course test than didparticipants in the control group, who had not re-ceived this training (1.3 vs. 5.1 collisions, respec-tively). In addition, participants in the VR-trainedgroup sustained significantly fewer falls (p < 0.02)than those in the control group (two of 19 patientsin CAT group; eight of 19 in the control group). Re-sults for the virtual performance tests, conductedon participants in the CAT group, showed thatperformance had improved post-training for both


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the video tracking and VR wheelchair obstacletest, indicating that learning in the virtual worldhad occurred.

Although this study has some flaws (participantswere not randomized to the treatments; experimen-tal and control participants received differingamounts of total therapy time), the results are stillimpressive. It is one of the few studies in the VR lit-erature in the rehabilitation field with reasonablenumbers of participants and at least an attempt toprovide a control group. The findings are impor-tant, not only because they seem to indicate thatsymptoms of neglect can be remedied by virtualworld training, but also because they show signifi-cant generalization from virtual world practice toreal world performance, that is, fewer collisionsduring actual wheelchair use, and fewer falls dur-ing everyday activities.

Another group has been working on the develop-ment of different interface options for driving elec-tric wheelchairs and on VR applications that can beused to train patients in how to drive electric wheel-chairs.101 This work addresses an important prob-lem, as one study estimates that 40% of people whoneed electric wheelchairs cannot presently use thembecause they are unable to control them sufficientlyusing currently available controls.102 The authorsfirst developed an isometric joystick as an alterna-tive to the standard position sensing joystick. Then,both devices were interfaced with a VR wheelchairmobility training module. Ten participants with dis-abilities (predominantly spinal cord injury) weretested; all were experienced electric wheelchairusers (mean 10 years experience). Participants weretested in both VR based tasks and real world taskswhich involved wheelchair mobility control usingboth interface devices. The results indicated no dif-ferences for the type of joystick interface in eithertime or RMS error (i.e., error indicating deviationfrom a straight path), for all tasks combined, andfew differences when individual tasks were evalu-ated. A significant correlation was found for perfor-mance in VR versus real world tasks, as measuredby RMS error (r2 = 0.81 for position joystick, p =0.008; r2 = 0.72 for isometric joystick, p = 0.02). Thisfinding indicates VR could serve as a good trainingtool for electric wheelchair control, as performancein the two environments was fairly comparable.

A third group, from Singapore, has developed amore generic VR system that can be used to train avariety of ADL skills.103 The system contains anauthoring tool than can be utilized to construct avariety of training scenarios. A virtual hand is dis-played within the virtual scene and is able to inter-act with 3-D objects placed in the scene. In this

article, they describe two specific scenes that theyhave developed, a pick and place task, designed toimprove spatial skills, and a virtual kitchen, whichcan be utilized to practice tasks such as making acup of coffee, using a stove, or making a microwavemeal. However, no patient data have been collectedor analyzed as yet with this system.

Researchers in Canada have developed andtested a VR program designed to teach safe street-crossing ability to children.104,105 Although the sys-tem was tested on normal children, it is reportedhere as it would appear to be a useful tool for re-training adults with acquired brain injury or strokein similar skills. A virtual environment was firstdeveloped that consisted of a virtual city, movingvehicles, people, and different intersections. Then,modules were designed to teach various key skills,such as stopping at the curb, looking left-right-leftbefore crossing, and so on. Following development,95 children were randomly assigned to receive ei-ther the VR street crossing training (three trials), ora control treatment, which consisted of practice onan unrelated VR program. Children were evaluatedin the real world by observers who rated actualstreet crossing behavior of the children, 1 week be-fore and 1 week after the intervention.

Performance in the virtual environment was alsotested. While all children improved their perfor-mance in the virtual environment, only childrenfrom a suburban school showed improved perfor-mance in actual street crossing; urban school chil-dren did not make the transfer from virtual to realperformance. The authors speculate that, with fur-ther training, transfer may have been achieved.

BALANCE TRAINING

A group from Israel has been working on balancetraining and related skills in participants with a vari-ety of neurological disabilities, using a laboratory-adapted version of VividGroup’s Gesture Xtremeprojected VR scenarios.106 In this article, they de-scribe the development of the adaptations they em-ployed for training, and pilot results for patients whohave used the system thus far. The participants in-cluded patients with stroke (n = 3), spinal cord injury(n = 4), and cerebral palsy with mental retardation.Although specific treatment details (e.g., number ofsessions, length of treatment) and performance dataare not provided in this preliminary report, the au-thors do say that all patients responded positively tothe treatment, felt a sense of presence, made more ef-fort during the VR training than during standardtraining, and made gains in their mobility.

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Another preliminary report on the use of VR inbalance training has been provided by Whitney etal.107 The authors describe a VR system they havedeveloped for use in balance training of partici-pants with vestibular disorders, which they termthe “Balance Near Automatic Virtual Environ-ment” (BNAVE). Persons with peripheral vestibu-lar disorders frequently suffer from disequilibriumduring standing and walking, and visual blurringduring head movements. They are often treated investibular rehabilitation programs by exposure tosituations that stimulate their symptoms in order topromote habituation. Typically, patients are takenthrough a graded type exposure that progressivelyadds situations and positions that provoke and in-crease their symptoms (e.g., dizziness, motion sick-ness, loss of balance). Such training is an ideal typeof therapy to deliver via VR, as large immersive vi-sual fields can be created and changed easily to suitpatients needs, and stimuli applied to patients canbe carefully controlled and measured.

The BNAVE system developed by Whitney et al.is a spatially immersive, stereoscopic, projection-based VR system that encompasses a participant’sentire horizontal field of view, and most of the ver-tical field of view, when looking forward (viewangle, 200º horizontal, 95º vertical). The validityof the system’s immersion was tested in a pilotstudy using five participants. Two participants hadperipheral vestibular disorders (more than 1 yearpost-onset and well compensated), and three werehealthy normal participants. Each participant wasexposed to three conditions, while standing on aforce platform in the center of the virtual “room”:(1) normal room lighting, nothing on VR screens;(2) infinite tunnel with checkerboard pattern mov-ing at a sinusoidal velocity; and (3) infinite tunnelwith a constant velocity profile (pulsed). The ante-rior-posterior movement of the participant’s centerof foot pressure and head movement were mea-sured. Both normal and vestibular-impaired partici-pants responded to the visual stimuli provided bythe BNAVE system with substantial increases inhead movements (range, 100–300% increase) andbody sway movements (3.3 vs. 9.2 cm) in synchronywith the visual motion. The results confirmed therobust effect of the visual stimuli provided by thesystem on postural responses.

Keshner and Kenyon108 have used an immersivevirtual environment, produced by a CAVE™ sys-tem, a multi-person, room-sized, high-resolution,3-D video and audio environment 8,109 to study theorganization of dynamic postural responses in nor-mal participants. In this study, normal participantswere exposed to constant velocity motion or sinu-

soidal motion of the visual scene in either a 3-Dstereoscopic scene (Experiment 1, n = 3) or a ran-dom dot pattern (Experiment 2, n = 3) while at-tempting to maintain static posture or walk a shortdistance (Experiment 3, n = 4). Their results sup-port the idea that postural controllers in the ner-vous system may set limits of motion at each bodysegment rather than be governed solely by the per-ception of visual vertical. For example, with pitchplane stimulation, the upper body appeared to re-spond to visual-vestibular signals with changes atthe hip; in contrast, ankle movements appearedmore linked to segmental proprioceptive inputs andinputs from ground reaction forces. Although thiswork is more theoretical in nature, it is mentionedhere as presumably it may lead in the future to newtherapeutic intervention methods for participantswith postural instability.

ORTHOPEDIC REHABILITATION

The Rutgers Ankle system described earlier hasalso been pilot tested on patients with orthopedicdisorders.110–112 In the first of these papers,110 thesystem is described in detail, and results from aproof-of-concept trial are reported. Four patientswith ankle problems participated, two with hyper-mobility and two with hypomobility. Each partici-pant was seen once, experienced the system, andhad their ankle ROM and torque evaluated.

Patient reactions to the system were evaluatedthrough use of a questionnaire. Patient reactionswere positive and the device was able to discriminatea difference between the involved and uninvolvedankle torque and ROM in the two participants forwhom both ankles were tested. In the secondpaper,111 the system is described further, and six pa-tients with orthopedic disorders were tested in orderto evaluate the system’s capabilities and its potentialuse as an evaluation tool. However, data for only onepatient is presented; these data demonstrated a dif-ference in torque values between the involved anduninvolved sides.

In the third paper, a pilot study conducted onthree patients with ankle injuries is described. Case1 was a 14-year-old patient, 2 weeks after Grade 1ankle sprain. Case 2 was a 15-year-old patient, 5months after Grade 2 ankle sprain. Case 3 was a56-year-old patient, 2 months after bimalleolar frac-ture. Patients received five treatment sessions overa 2-week period, sessions were 30 min, deliveredtwo to three times per week. A sixth session was usedfor the post test. The treatment consisted of pilotinga virtual airplane through hoops, at progressive


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levels of difficulty, as described earlier for thestroke patients. Cases 1 and 3 were also receivingconcomitant physical therapy for their ankle prob-lem. Case 2 received only the VR therapy. Each caseis discussed separately, and different measures arepresented for each participant. The authors reportthat all three participants improved. However, onlyfor participant 2 could these changes be attributedto the VR treatment, as the other participants werereceiving additional therapy at the same time. Themost consistent improvement across the three par-ticipants was in task accuracy, defined as the num-ber of hoops entered versus missed. All were ableto reach 100% accuracy, from a start point of 40%,65%, and 25%, respectively, for cases 1, 2, and 3. Im-provements of varying amounts in ankle ROM andtorque production, one leg stance time, stair de-scent time, and speed of target hoop acquisitionwere also noted in one or more participants.

TELEREHABILITATION

Rosen,113 in his extensive review of the newly de-veloping field of telerehabilitation, identified accessto and quality of care as key factors in the rationalefor the developments in this field. The unfortunatereality is that many patients who have completedtheir acute in-patient rehabilitation following astroke or other injury may have limited access toout-patient rehabilitation upon their return home torural communities. Even many patients in urbansettings have poor access to transportation, or mayfind travel to a clinic too tiring because of the addedeffort imposed by their disability. Such patientscould benefit from telerehabilitation services, inparticular those aimed at the provision of directtherapeutic services over the internet.

Several groups have been working to developsuch telerehabilitation applications for VR tech-nologies in rehabilitation. Some have focused ontruly home-based systems58,114–117 while others areworking to develop clinic to clinic connections.118,119

Holden and colleagues have recently expanded thefunctionality of their original VR system14,15,54,55 toinclude telerehabilitation capability. Their telereha-bilitation system can provide real-time interactivetreatment sessions in the patient’s home with atherapist who is located remotely at a clinic.58,114,120,121

Both the patient and therapist see a simultaneousdisplay of the VR program on one monitor and cancommunicate via video-conferencing on a secondmonitor. The system can be used to train a widevariety of arm movements in any part of the UEworkspace.

Initial results from an ongoing study designed todevelop and test the clinical feasibility of the systemon patients with stroke, have demonstrated clini-cally meaningful improvements (range, 17–67% p =0.003–0.05) on a variety of outcome measures. Fol-lowing 30 1-hr VR sessions, delivered in the homevia the internet, patients with stroke showed statisti-cally significant improvements on the FM test ofMotor Recovery, Wolf Motor Test of UE Function,Strength tests for shoulder and hand grip,114,121 andkinematic measures of arm movement trajectoriesrecorded during real world functional movementtasks.58,121 Piron et al.,116 working in Italy, have alsoreported success with home-based telerehabilita-tion, finding a significant improvement in the meanvalues for clinical and VR trajectory measures of thefirst five participants tested, following four weeks ofdaily therapy via telerehabilitation. (The VR soft-ware used by this group was developed at MIT byHolden and colleagues.)

Burdea and colleagues have developed a VR-based telerehabilitation system that focuses onhand rehabilitation using force feedback, andtested the system on orthopedic patients.118,119

Reinkensmeyer and co-workers117 have developeda web-based telerehabilitation system that the pa-tient can access independently, and with which heor she can practice simple movements using anadapted computer joystick with force feedback.These systems appear to be designed mainly for in-dependent work by the patient, with the network-ing component being used to send data to thetherapist for later evaluation. Although a video-conferencing link was included in one of these sys-tems,119 it was too slow to support real timeinteractive therapy. Thus, as presently configured,only highly constrained movements in a very smallworkspace can be practiced using these systems.Both of these telerehabilitation systems haveproven feasible in pilot testing on a single patient.In contrast to results reported by Holden et al.114

and Piron et al.,116 neither of the patients tested byPopescu et al.119 or Reinkensmeyer et al.117 were re-ported to show significant improvement on stan-dard clinical tests of UE function followingtraining. However, some changes in force produc-tion,118,119 movement, and speed117 on selected testitems were seen.

CONCLUSION

This review details the wide variety of clinical ap-plications for which VR systems are now being de-veloped and tested. The published clinical studies,

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for the most part, still consist of small studies with-out control groups, geared toward feasibility orproof of concept testing. However, this type of de-sign is appropriate for testing a new technology inthe early stages of its application. As the reader ex-amines the wide variety of VR systems that havebeen or are being developed, it is important to keepin mind that VR is not really a treatment in itself—and thus cannot be found to be “effective” or not formotor rehabilitation. Rather, VR is only a new tech-nological tool that can be exploited to enhancemotor retraining. But how well the new VR systemswork in this regard will depend very much on howfamiliar the developers and users are with the scien-tific rationale behind motor learning as well as thespecific details of the motor impairments presentedby different clinical populations. This understand-ing will be key to designing appropriate system fea-tures and successful VR treatment interventions.Conversely, considerable engineering knowledge isrequired to understand the potential capabilities ofthe various technologies and which functions arenecessary for the various applications.

Thus, to be maximally successful, experiments inthis area require collaborative efforts among a teamof clinicians, engineers, and neuroscientists—not atrivial task. In terms of the types of clinical problemsthat have been investigated in studies of VR applica-tions to motor rehabilitation, patients with strokehave received most of the attention. The record ofsuccess in this area to date has been good (e.g., seeresults for UE training, gait training, and wheelchairmobility training), and the potential for further suc-cess in this area appears quite promising. The poten-tial to apply VR to training patients with vestibulardisorders is great, but the equipment set-up for thistype of application is quite expensive, and may limitits widespread use. In contrast, standard balancetraining could be widely applied to general rehabili-tation populations with comparatively less expen-sive equipment. The potential for applications in PDappears quite promising, but will require furthersystem development and testing. Motor rehabilita-tion has been undertaken in patients with acquiredbrain injury with some success, but the cognitivedeficits displayed by this population may remainthe best area of potential application for VR in thispopulation. Finally, the field of telerehabilitation isin its infancy, but has great potential, especially ifsystem cost can be reduced.

Much work remains to be done in such areas asidentifying which types of patients will benefitmost from VR treatment, which system features arecritical, and what types of training routines willwork best. However, a few findings appear to be

solidly emerging from the VR work to date, as theyhave appeared repeatedly in multiple studies bydifferent research groups. These findings are that:(1) patients with disabilities appear capable ofmotor learning within virtual environments; (2)movements learned in VR by patients with disabili-ties transfer to real world equivalent motor tasks inmost cases, and in some cases even generalize toother untrained tasks; (3) in the few studies (n = 5)that have compared motor learning in real versusvirtual environments, some advantage for VRtraining has been found in all cases; and (4) no oc-currences of cybersickness in impaired populationshave been reported to date in experiments whereVR has been used to train motor abilities.

ACKNOWLEDGMENTS

This work was supported by NIH grants nos.HD40959, HD40959–02S1, and M01-RR-01066.

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Address reprint requests to:Dr. Maureen K. Holden

Department of Brain and Cognitive SciencesMcGovern Institute for Brain ResearchMassachusetts Institute of Technology

Cambridge, MA 02139

E-mail: [email protected]


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