a human-computer interface based on single ...a human-computer interface based on single channel emg...

A HUMAN-COMPUTER INTERFACEBASED ON SINGLE CHANNEL EMGSIGNAL TO CONTROL A ROBOTIC

WHEELCHAIR

Siva Balan.N1, Surya.J2

Shriranjani.D3, Ramkumar.A.S4

1,2,3Dept. of Electronics and InstrumentationEngineering.

4Dept. of Electronics and CommunicationEngineering

1,2,3St.Josephs College of engineering,Chennai.

4Dhanalakshmi College of engineering,Chennai.

August 4, 2018

Abstract

The constantly improving technology revamp its appli-cations and the way we communicate with the rest of theworld. These advancements have led to ease the function-ality of the differently abled. Restoration gadgets are cu-mulatively being utilized to augment the nature of the lifeof differently capable individuals. Human Computer In-terface (HCI) have been ruminate over broadly to controlelectromechanical support system deploying bio-signals, forexample, EEG, EOG and ERG.EMG indicators have beenexamined in profundity because of the event of a positiveindicator design. Persons experiencing amazingly repressed

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International Journal of Pure and Applied MathematicsVolume 120 No. 6 2018, 11053-11066ISSN: 1314-3395 (on-line version)url: http://www.acadpubl.eu/hub/Special Issue http://www.acadpubl.eu/hub/

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portability like paraplegia generally can facilitate hand de-velopments. The current venture concentrates on the ad-vancement of a model wheelchair controlled by EMG in-dicators. In this piece of work, acquisition of EMG signalframework was produced. The obtained EMG indicator wasthen prepared to create different control signs. These con-trol signs were then used for the development of the mech-anized wheelchair model.Keywords:EMG, HMI, Surface electrode, Biopotential am-plifier.

1 Introduction

The loss of the ability to move some or all of the body is knownas paralysis. Paralysis affected people have normal lifespans, evenwhen the condition is the result of intensifying disease. Peoplewho are confined to wheelchairs can still ski, drive or even swim.Paralysis hit patients require considerable adjustments to daily liv-ing, because the muscles a person usually relies on to do certainthings no longer work or example, for people with acute paraly-sis, customary body functions like bowel movements and urinatingmay be grueling tasks .A Rehabilitation gadget is one that helps adifferently abled individuals to control their surroundings and con-vey all the more adequately. These assistive gadgets help in allowindividuals to perform errands with the assistance of technology.A perfect recovery relies in gathering data from the surroundings,examining the data, passing it on to the client and lastly gettingsummons from the client. The utilization of these recovery helpaids the differently abled individual to do his/her everyday exer-cises autonomously.

2 REQUIREMENT OF REHABILITA-

TION

A considerable area of our general public experiences one or theother sort of incapabilities because of mischances, neurological prob-lem, mind trauma and so forth. These shortcomings compel thepatients to rely on upon their relatives or peers for everyday exer-

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cises. Recovery gadgets unchain persons with incapability to live,play, study and work freely. In the long run they build the per-sonal satisfaction headed by the differentially abled individuals andincrement their respect toward oneself. A Rehabilitation gadgetis one that helps a differentially abled individual to control theirsurroundings and convey all the more satisfyingly. These assis-tive gadgets help in self determination by allowing individuals toperform errands with the assistance of improved technology [1]. Aperfect recovery help helps in gathering data from the surroundings,examine the data, pass on it to the client lastly get summons fromthe client. With developments in signal preparation, we can gadgetframeworks that can interpret the data naturally. The utilizationof these recovery helps aids the differentially abled individuals todo their everyday exercises individually.

3 OVERVIEW OF CURRENT REHA-

BILITATION TECHNIQUES

With a constant change in engineering, there is a huge improvementin the field of recovery strategies. Investigates are happening to cre-ate dependable, slightest effort and simple to utilize gadgets. Outof all the recovery procedures, HCI (Human Computer Interface)and HMI (Human Machine Interface) are the most recent and bestsystems. The main goal of the HMI framework is transformationof indicators created by people through different motions to controlsome electromechanical gadgets. While in HCI framework somekey strokes or cursor developments on the screen are controlled byutilizing these indicators. In HCI and HMI both non biosignals andbiosignals are utilized as a medium of control. The boss biosignalsutilized within the Interface are Electromyography (EMG), Elec-troencephalography (EEG) and Electrooculography (EOG). HMI isnormally utilized by engine hindered patients to control wheelchair.Restoration device are mainly grouped into two types; the first classmakes use of each one of those gadgets which are biosignal andthe second classification incorporates non biosignal based gadgets.Non biosignal recovery supports give 100% exactness and obligeless preparing for patients however the utilization of these gadgetsis restricted to patients with halfway or complete adaptability in

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their body parts. Biosignal based recovery gadgets mostly in largebiosignals like EEG, EOG or EMG as control signs [2]. The pointof interest of utilizing biosignal methodology is that when patientsget to be totally deadened, the main asset accessible to them thenis biosignals. The familiarization in light of the fact that biosig-nals generated by every individual are unique because of contrastin physiological properties and skin conductance makes biosignalapproach friendly to the user.A. Non biosignal approachPreponderantly non biosignal controlled restoration device uses strate-gies which make utilization of taste-n-puff reaction, tongue control,eye following, head development following and jaw control. Thesip-n-puff is an old method which is utilized to control mechanizedwheel seat by quadriplegic patients In this method, control sig-nals are given to a device utilizing gaseous tension by ”tasting”(breathing in) or ”puffing” (breathing out) on a pneumatic tube.SNP innovation for the most part makes utilization of four con-trol indicators which are prepared by hard taste, hard puff, deli-cate taste and delicate puff. Average arrangement of Sip-and-Puffdevice is the control of mechanized wheelchair. Control normallycomprises of four separate inputs from the client. A starting hardpuff will empower the wheelchair to advance, while a hard tastewill stop the wheelchair. Then again, an introductory hard tastewill allow the wheelchair to move abaft, while a hard puff will stopthe wheelchair. A constant delicate taste or delicate puff will em-power the wheelchair to move left or right separately relying uponthe span of tasting or puffing. The mouth-controlled informationgives clients a basic and successful approach to control mouse de-velopment. Nevertheless, the essential disadvantage of the tasteand puff method is that muscles of many paraplegics and otherincapacitated patients are not equipped for taste and puff activ-ity. An alternate normal system is the Head Movement Trackingmethod[3]. In this, head developments are converted into cursordevelopments on the screen. Cursor developments are relative tohead developments. Head developments are established by noveltechniques like accelerometer set in a patient’s top or by catchingfeature of head developments[9,10]. Be that as it may the issuewith this procedure is that differentially abled individuals of spe-cific classifications, for example, cerebral paralysis patients can’t

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even move their head agreeably. An alternate disadvantage of thisprocedure is that temple dependably needs to face the Polaroid.In the chin control method, the button sits in a glass formed joy-stick handle and is typically controlled by chin developments. Thisframework is material just for patients with great head control. Itgives more adaptability than head control. Tongue controlled re-covery is attained by numerous routines. In one system, a perpetualmagnet is joined to the tongue and development of tongue to anair-center incitement loop changes the inductance of curl comply-ing with Faraday’s laws. In an alternate strategy, a weight delicateisometric joystick is worked by the patient’s tongue. This joystickand the two switches give cursor control and left/right catch.B. Biosignal approachAs mentioned before, thes biosignal based recovery gadgets mostlyuses biosignals like EOG, ECG or EMG as control signs[11]. Thepoint of interest of utilizing this methodology is that when patientsget to be totally disabled, the main assets accessible to them arebiosignals.

4 EMG SIGNAL ACQUISITION SYS-

TEM

A. MaterialsAD620 (Texas instruments), µA741 (General-Purpose OperationalAmplifier), Ag/AgCl throwaway electrodes (BPL, India) with link-ing probes, DAC and custom in-house made miniaturized wheelchairmodel were used in the study. The capacitors, resistors, motors andother parts were procured from local market. B. Method used forEMG based assistive techniqueThe development work involved three parts:• Signal acquisition part included development of EMG acquisitionsystem.• Signal classification part included classification of different fingermovement types.• Application part involved implementation of rehabilitation de-vices which can be controlled using EMG

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Figure 1: Basic block diagram

C. Electrodes and input cablesDisposable pre-gelled Ag/AgCl electrodes were used to acquire sur-face EMG signals from the body. Since the EMG signal amplituderange was in mill volts, they were very much adaptable to variousnoise sources. To subdue the effects of RF noise and electromag-netic interference, shielded wires were used to connect Ag/AgClelectrodes and signal acquisition circuits.D. Selection of surface electrodeThe selection of surface electrode is one of the important parts of theproject. It plays an important role to interface between biomedicalinstrumentation tool and electronic system at human body. Duringcontraction, the nerves will send a signal to initiate muscle and apotential will be developed across the muscle due to the flow ofions in and out of muscle cells. Then, this ionic current will beconverted into electronic current with surface electrodes placed onthe surface of the skin measure [4].For this project, the surface electrode type Ag-AgCl will be used.Ag-AgCl is the common most common composite for the metallicpart of surface electrode. To make sure the conductivity of the sur-face electrode, an electrolytic gel is used as an interface between theskin and the metallic part of the electrode. The AgCl layer permitscurrent from the muscle to pass freely across the junction betweenthe electrolyte and the electrode. Due to this, less electrical noisewill produce as compared with equivalent metallic electrodes andbecause of this, this type of surface electrode are used in over 80%of surface EMG applications. In the market, there are disposableand reusable electrodes. The disposable electrodes are the mostcommon size there are very light and it comes in a wide assortment

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of shapes and sizes. With proper application, the disposable elec-trodes can minimize the risk of electrode displacement even duringrapid movement [5,6]. However, since the electrodes area appliedon the skin, some limitations must take into action. The surfaceelectrode are must use on the muscle that close to the surface ofthe skin only and the position of the electrodes must be kept stablewith skin in order to avoid the distortion effect.E. EMG SignalThe result of using surface electrodes should also be noted by theclient. For example, an unfiltered and unprocessed signal detectingof MUAP is called a raw EMG signal

Figure 2: The raw EMG signal

EMG spikes shape is very random, which means that each record-ing burst will not produce the exact shape. Strong superpositionspike will produce when two or more motor unit fire at the sametime and the location between the motor unit and the electrodesis near. Raw EMG range is 0.1V to 20mV and from 2Hz to 2 kHzwhich may change between different kinds of people [7]. Since theamplitude of the raw signal is very small, it must be amplify andsometimes it requires more than one amplification stages. Besidesthat, the signal must also go through the filter in order to eliminatelow or high frequency noise [8].F. Amplifier circuitIn general EMG signal amplitude varies from 1-10 mill volts. Henceadditional care should be taken during the digitization of the sig-nal in order to minimize the error. Amplifier circuit consists of aninstrumentation amplifier (AD620) whose gain is adjusted to 1000.The instrumentation amplifier has taken because of its high inputimpedance and CMRR. The output of the instrumentation ampli-fier is obtained from PIN 6. An active ground was formed in orderto reduce the common mode signal from the output. The outputof the amplifier circuit is fed in to the low pass filter of frequency

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500 Hz. The output of the filter is fed in to the lab view whereclassification of signal is done.

5 METHODOLOGY

The signal conditioning circuit setup was prepared for acquiring theEMG signals from the subjects for four different motions of handcorresponding to directions namely, front, back, left and right ofthe wheelchair. The four different hand motions are,• No motion of hand• Thumb abduction• Finger extension• Wrist flexion.The preamplifier circuit consists of an instrumentation amplifier(AD620) whose gain is adjusted to 1000. Dot board design of biopo-tential amplifier and hardware design of signal acquisition systemis given in figure 3.

Figure 3: Reconstructed circuit in Dot board

Where, Rg (Rg = 49.9Ω ) was the resistor connected between the 1stand 8th pin of the AD620.When Rg 49.9Ω,Gain is approximatelyequal to 1000. The following figures show the different hand move-ments and their corresponding EMG signals.

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Figure 4: Thumb abduction

Figure 5: No motion of hand

Figure 6: Finger extension

Figure 7: Wrist flexion

A. EMG signal classificationThe analog output from the circuit was fed in to the LabVIEWwhere classifications of signals were done, using MCC DAQ and aprogram was framed in such a way that four different ranges are de-fined for different RMS value and if particular amplitude satisfiesany of the predefined ranges then the corresponding LED glows.The RMS values of signal as per the classification are shown in fol-lowing table along with their corresponding wheelchair direction.

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TABLE 1: Obtained values through LabVIEW

The schematic diagram of the block diagram of program, signalclassification and corresponding glowing of LED as per classificationare shown in the following figures.

Figure 8: RMS value during thumb extension

Figure 9: RMS value during relaxation

Figure 10: RMS value during full hand abduction

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Figure 11: RMS value during full hand flexion.

The complete working of the circuit along with the robotic wheelchairmodel is shown in the figure below.

Figure 12: Robotic Wheelchair model.

B. Performance evaluationExperimental results suggest that accuracy of the proposed methodis greater than 90%, 91%, 85% and 80% respectively for forward,backward, left and right direction of motion of the wheelchair model.

6 CONCLUSION AND FUTURE EN-

HANCEMENT

A. ConclusionIn the present work, a bio signal controlled wheel chair has beendesigned and implemented. The developed device will help in elimi-nating the drawbacks of the traditional electric powered-wheelchair.This system is used to generate the control signal with differenthand movement. These generated control signals are used to con-trol the wheelchair model corresponding to hand movement. In-stigation of EMG based control system for assistive gadget will bea good assistive technique for people suffering from extremely re-stricted peripheral mobility. From the application point of view

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generated control signal can also be used to control the other reha-bilitative devices.B. Future enhancementThe prospects of current project are huge in thee time to come. Infuture it can be used to control the other rehabilitation device likeprosthetic arm etc. The range of the device can also be expandedby replacing the RF module by GSM module. Quality of the sys-tem can be improved by using high precision components. Rangeof motion can also be proliferated by modification in the program.The same algorithm can also be used to control different rehabili-tation device by different bio potential signals.

References

[1] J. Katz, et al., ”Handbook of clinical audiology,” 1994.

[2] V. Stanford, ”Biosignals offer potential for direct interfacesand health monitoring,” Pervasive Computing, IEEE, vol. 3,pp. 99-103, 2004. .

[3] L. Wei, et al., ”Use of forehead bio-signals for controlling an in-telligent wheelchair,” in Robotics and Biomimetics, 2008. RO-BIO 2008. IEEE International Conference on, 2009, pp. 108-113.

[4] E. Criswell, Cram’s introduction to surface electromyography:Jones & Bartlett Publishers, 2010.

[5] D. Farina, et al., ”Biophysics of the generation of EMG sig-nals,” Electromyography: physiology, engineering, and nonin-vasive applications, pp. 81-105, 2004.

[6] D. Andreasen, et al., ”Exoskeleton with EMG based activeassistance for rehabilitation,” in Rehabilitation Robotics, 2005.ICORR 2005. 9th International Conference on, 2005, pp. 333-336.

[7] P. Kadam, ”Powered Wheelchair Controller Using Hybrid Bio-Signals,” 2010.

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[8] O. Fukuda, et al., ”EMG-based human-robot interface for re-habilitation aid,” in Robotics and Automation, 1998. Proceed-ings. 1998 IEEE International Conference on, 1998, pp. 3492-3497.

[9] X. Chen, et al., ”Hand gesture recognition research basedon surface EMG sensors and 2D-accelerometers,” in Wear-able Computers, 2007 11th IEEE International Symposium on,2007, pp.

[10] I. Moon, et al., ”Intelligent robotic wheelchair with EMG, ges-ture, and voice-based interfaces,” in Intelligent Robots andSystems, 2003.(IROS 2003). Proceedings. 2003 IEEE/RSJ In-ternational Conference on, 2003, pp. 3453-3458.

[11] L. Chong and H. Wang, The Design of Wheelchair Based onSEMG Control, 2008 2nd Int. Conf. Bioinforma. Biomed. Eng.,pp. 17211724, May 2008.

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a human-computer interface based on single ...a human-computer interface based on single channel emg...

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