a smartphone prototype for touch interaction on the whole...
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A Smartphone Prototype for TouchInteraction on the Whole DeviceSurface
Huy Viet LeUniversity of StuttgartStuttgart, [email protected]
Patrick BaderUniversity of StuttgartStuttgart, [email protected]
Sven MayerUniversity of StuttgartStuttgart, [email protected]
Niels HenzeUniversity of StuttgartStuttgart, [email protected]
Permission to make digital or hard copies of part or all of this work for personal orclassroom use is granted without fee provided that copies are not made or distributedfor profit or commercial advantage and that copies bear this notice and the full citationon the first page. Copyrights for third-party components of this work must be honored.For all other uses, contact the Owner/Author.MobileHCI ’17 , September 04–07, 2017, Vienna, Austria.© 2017 Copyright is held by the owner/author(s).ACM ISBN 978-1-4503-5075-4/17/09.https://doi.org/10.1145/3098279.3122143
AbstractPrevious research proposed a wide range of interactionmethods and use cases based on the previously unusedback side and edge of a smartphone. Common approachesto implementing Back-of-Device (BoD) interaction includeattaching two smartphones back to back and building a pro-totype completely from scratch. Changes in the device’sform factor can influence hand grip and input performanceas shown in previous work. Further, the lack of an esta-blished operating system and SDK requires more effort toimplement novel interaction methods. In this work, we pre-sent a smartphone prototype that runs Android and has aform factor nearly identical to an off-the-shelf smartphone.It further provides capacitive images of the hand holdingthe device for use cases such as grip-pattern recognition.We describe technical details and share source files so thatothers can re-build our prototype. We evaluated the pro-totype with 8 participants to demonstrate the data that canbe retrieved for an exemplary grip classification.
Author KeywordsFull-touch phone; mobile; capacitive; prototype.
ACM Classification KeywordsH.5.2 [User Interfaces]: Prototyping
IntroductionThrough a combination of input and output in a single in-terface, touchscreens became the main interaction mecha-nism for smartphones. With Back-of-Device (BoD) inte-raction, researchers formed a field in which the previouslyunused back of the device is used to perform a wide rangeof use cases. Amongst others, BoD interaction can be usedto perform touch input on small devices without occludingrelevant content [2], perform unlock gestures on the backof the device to complicate shoulder surfing [5], or use aBoD touch panel to move the screen content to facilitateone-handed interaction [10]. Similarly, sensors on the de-vice edges enable use cases such as switching applicati-ons or navigating on a map [9] and using taps to trigger anapplication launcher [14]. In previous HCI research, sand-wich prototypes and building touch devices from scratch arecommon approaches to building BoD smartphone prototy-pes [2, 4, 5]. The disadvantage of these approaches areeither a thicker and heavier form factor when attaching de-vices back to back, or the lack of an established operatingsystem (OS) to integrate novel interaction methods or usecases in well-known applications and user interfaces.
In this work, we present a smartphone prototype that re-gisters capacitive touch input on the whole device surfacewith a form factor nearly identical to a standard smartphone(i.e. Google Nexus 5). Based on components of a Nexus5, an established OS is available to e.g. integrate novel in-teraction techniques into well-known applications. ThroughAndroid kernel modifications, the prototype also providescapacitive images that show how the hand touches andholds the device. We describe technical details and providesource files (e.g. PCB schemes, 3D models, and kernelsource files) for the reader to re-create our prototype fortheir future work. We show an evaluation to demonstratethe data that can be retrieved by the prototype.
Use cases that require touch input and capacitive imageson the whole device surface include e.g. grip classificationto predict actions, authentication, gestures on the BoD andedge, or performing touch input from the back. Further, thisprototype can be used for future research to record handgrips in situations where setups such as motion capturesystems are not possible (e.g. while walking outside).
Background and Related WorkOne approach to implement BoD interaction is to attach anadditional smartphone (e.g. [4, 5, 22, 28, 29]) or an externaltouch pad (e.g. [8, 13, 24]) back to back to the smartphonerepresenting the front screen. While this is a common ap-proach in HCI research [4], the resulting device thicknessand weight are noticeably higher compared to commercialdevices. These changes to the device’s form factor can in-fluence how users hold the device and interact with it. Thisis detrimental especially for use cases that observe howusers hold the device (e.g. context-awareness or prediction)or require users to use front and back of the device simulta-neously as shown in previous work [10]. Using two smartp-hone prototypes with different thickness, Le et al. [10] sho-wed that a difference of 3mm can already affect the gripstability noticeably in a negative way. An unstable grip ham-pers the finger’s freedom of movement as stretching fingerscauses the device to drop. Moreover, Sung et al. [25] foundthat the grip span (i.e. the distance between thumb and in-dex finger when grasping an object [23]) has a significanteffect on user’s touch performance. As the grip span incre-ases with thicker devices, the touch performance decreaseswhich leads to significantly less touch pressure and accu-racy during one-handed interaction.
Another common approach is to develop a smartphone pro-totype from scratch (e.g. [1, 2, 3, 26]). While the resultingform factor depends on the included hardware, the lack of
an established framework (e.g. an OS such as Android oriOS) requires more effort to implement sophisticated usecases such as integrating a novel interaction technique intowell known mobile applications or user interfaces. For ex-ample, the Android SDK provides a wide range of compo-nents, interfaces, and documentation to enable users toeasily develop or extend mobile applications. Further ap-proaches to detect touch input on different surfaces includeusing inaudible sound signals [17, 21, 27], high-frequencyAC signals [34], electric field tomography [33], conductiveink printed touch sensors [6], the smartphone’s camera [30,31] and other built-in sensors such as IMUs and microp-hones [7, 20, 32] to sense touch input. While these techni-ques do not require any attachments that noticeably increa-ses the device’s thickness, their disadvantages make themnot suitable for use cases such as grip classification. Forexample, sound or AC signals are prone to interferencewhile using built-in sensors (e.g. accelerometer or camera)results in limited accuracy or limited area. Further, theseapproaches do not provide a replacement for capacitiveimages that are required for use cases mentioned above.
Figure 1: The full prototype withthe Touch Device and HardwareContainer .
Figure 2: The Touch Device with afront and back touchscreen, andcapacitive sensors on the sides.
To achieve a familiar form factor, Le et al. [10] 3D-printed aback cover for an LG Nexus 5X to attach a resistive touchpanel to the back of the device. This increases the device’sthickness by only 0.9mm. However, the touch panel beingresistive and covering only a quarter of the device makesit infeasible to reconstruct the user’s grip. Mohd Noor etal. [15, 16] used a custom flexible PCB featuring 24 capaci-tive sensors distributed around the device’s back and sidesto maintain a form factor similar to standard smartphones.While they showed that hand grips can be detected ade-quately, the resolution may still be too low for more preciseinteraction techniques, such as a 1:1 transfer of a back-touch to the front screen. On the commercial side, the Yo-
# Ref-Id Manufacturer Part No Data Sheets
2 B2B-F BM10NB(0.8)-40DS-0.4V(51) goo.gl/ObJNJk2 B2B-M BM10B(0.8)-40DP-0.4V(51) goo.gl/nWbiIj3 MPR121 MPR121QR2 goo.gl/iRc4Hq2 USB-B Adafruit-1833 goo.gl/SYSW8b2 BTN Adafruit-1119 goo.gl/ONkoEr4 FFC-F FH12-50S-0.5SH goo.gl/xtcA2r2 FFC-C DIY-08-00073 goo.gl/k3dNvi
Table 1: List of parts comprised in the full-touch smartphoneprototype. # indicates the amount required, Ref-Id is the identifierwe use refer to the respective component.
taPhone1 features an e-ink capacitive touchscreen on therear. However, using front and back touchscreens simulta-neously is not possible and edge sensors are not available.
In summary, previous work presented different types ofsmartphone prototypes to evaluate novel BoD and edgeinteraction techniques. While sandwich prototypes and buil-ding devices from scratch are common approaches in HCIresearch, they either change the device’s form factor notice-ably with negative effects on the hand grip or do not providethe integration into established frameworks.
Smartphone PrototypeTo develop a prototype with a form factor similar to an off-the-shelf smartphone (i.e. a Google Nexus 5) while offeringthe support of an OS (i.e. Android), we used two Nexus5 smartphones for the front and back side, and a capaci-tive touch controller to operate additional touch sensorson the sides. We used these components since the tou-chscreens and side sensors provide capacitive images ofthe sensed touches so that information such as the finger
1https://yotaphone.com/us-en/
placement can be retrieved. While we followed the appro-ach of stacking the smartphones, we avoid the increase inthickness by separating the touchscreens from the remai-ning components of the smartphones. Thus, our prototypecomprises two modules (see Figure 1) which we refer to asfollows: Touch Device represents the smartphone with afront and back touchscreen, and capacitive sensors on thesides as shown in Figure 2; Hardware Container is a sepa-rated case that comprises the remaining hardware compo-nents of both smartphones, including batteries and circuitboards as well as a microcontroller to operate the side sen-sors (see Figure 4). Each of the two modules includes aself-designed printed circuit board (PCB) which we will referto as PCBTD and PCBHC for the Touch Device and the Har-dware Container respectively. The PCBs act as extensionadapters that are connected to the hardware componentswithin the respective module to establish a connection be-tween the Touch Device and Hardware Container throughflexible flat cables (FFC) as shown in Figure 1. Table 1 listsall required hardware parts, such as connectors or cables.In the following, we describe both modules.
Figure 3: The Touch Devicemodule without touchscreenswhich shows the PCB.
Figure 4: The Hardware Containercontaining the PCB that isconnected to the circuit board andbatteries of two Nexus 5, and anArduino to operate the capacitiveside sensors.
Touch DeviceThe Touch Device (see Figures 2 and 3) consists of a 3Dprinted frame, two Nexus 5 touchscreens, 37 copper platesas capacitive touch sensors on the edges, and a PCBTD .The 3D printed frame holds both touchscreens and en-closes PCBTD . The capacitive touch sensors are fixatedon the left, right and bottom side of the frame. Each touchsensor is a 6 × y × 0.5mm (with y = 6mm for left andright, and y = 12mm for the bottom side) copper platewhich is glued into engravings of the frame with a gap of1.0mm in between and sanded for a smoother feeling.The copper plates are connected to the PCBTD which inturn comprises three MPR121 capacitive touch control-lers operated by a Genuino MKR 1000 microcontroller in
the Hardware Container . Similarly, both touchscreens areconnected via a board-to-board connector (B2B-F) on thePCBTD and are operated by the remaining components ofthe Nexus 5 located in the Hardware Container . The twoFFCs are routed through the top side of the Touch Deviceas there is a low likelihood that it disturbs the user whenholding the phone in a usual grip [11]. The dimensions ofthe Touch Device are 137.6 × 68.7 × 8.9mm (115 g). Incomparison, the dimensions of an off-the-shelf Nexus 5 are137.8× 69.1× 8.6mm (130 g).
Hardware ContainerThe Hardware Container (see Figure 4) is a 3D printed boxthat contains two Nexus 5 circuit boards and batteries, aGenuino MKR 1000 microcontroller, a micro USB breakoutboard (USB-B), and two tactile buttons (BTN). When usingour prototype in mobile situations such as walking, the Har-dware Container can be attached to e.g. the user’s arm(see Figure 8), belt or placed in a backpack. Thus, we keptthe box as small as possible by disassembling the Nexus5 to remove all frames and unused components (e.g. backcamera). The circuit board of the Nexus 5 is connected toa compatible board-to-board connector (B2B-M) on PCBHC
which in turn is connected to the touchscreens. To provideaccess to the Nexus 5’s power button and USB port, we re-placed the power button and USB port with a replacementbutton (BTN) and a USB micro breakout board (USB-B)which are placed on the Hardware Container . The Gen-uino MKR 1000 is connected to the PCBHC so that thecapacitive side sensors connected to the PCBTD can beoperated. The dimensions of the Hardware Container are157.2× 115.5× 15.2mm with a weight of 221 g.
Retrieving and Processing TouchesFor both Nexus 5, single touch points are accessible throughthe Android SDK. To retrieve the finger placement for our
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Figure 5: Heat maps depicting the registered touches while holding the smartphone prototype in five different hand grips. The outer rows andcolumns represent the respective edges of the smartphone. The axes represent the position in mm when facing the front of the smartphone.Green spots represent touches on the front screen, black represents all other sides. These heatmaps are shown from the front perspective.
envisioned use cases, we modified the Android kernel togain access to the capacitive images reported by the tou-chscreen (Synaptics ClearPad 3350) controller’s debug-ging interface. These are 27 × 15 px images in which eachpixel corresponds to a 4.1 × 4.1mm square on the 4.95′′
touchscreen. The pixel values represent the differences inelectrical capacitance (in pF ) between the baseline measu-rement and the current measurement. Capacitive imagescaptured by the prototype are shown in Figure 5. We usedI2C calls to access the register for test reporting as descri-bed in the RMI4 specification (511-000405-01 Rev.D) andin the driver’s source code2. Capacitive images are writtento the procfs3 to provide access for Android applications.The MPR121 provides a measurement for each side sensorso that we already have a capacitive image for the sides.The capacitive images are obtained at 20 fps for the tou-chscreens, and at 130 fps for all side sensors.
(a) Grip 1
(b) Grip 2
(c) Grip 3
(d) Grip 4
(e) Grip 5
Figure 6: The five different gripsfrom Lee et al. [12] as shown toparticipants.
To merge the front, back and side capacitive images foranalysis (e.g. investigating finger placement), we used anearest-neighbor approach to match the unix timestamp.
2github.com/CyanogenMod/android_kernel_lge_hammerhead/blob/cm-14.1/drivers/input/touchscreen/touch_synaptics_ds5.c
3tldp.org/LDP/Linux-Filesystem-Hierarchy/html/proc.html
For interactive use cases, the back touchscreen device andthe Genuino both transfer their capacitive images to thefront touchscreen device which hosts a WiFi hotspot. Thetransfer latency measured by an average round trip timeover 1000 samples is 7.2ms (SD = 2.6ms).
Technical DemonstrationTo demonstrate the data that can be retrieved from the pro-totype, we conducted a user study to let participants holdthe device using five grips presented in previous work [12].
Participants and ProcedureWe recruited 8 participants with an average age of 26.3(SD = 2.1) from the campus of our university. We showedparticipants five different grips (see Figure 6) in a counter-balanced order using a Latin square. We instructed them toimitate the grip which was shown in a front and back viewand to press a button on the front touchscreen to start therecording when they were ready. The capacitive imageswere recorded for 30 seconds during which participants didnot move their fingers. The study took about five minutes.
ResultsAfter synchronizing all sides, we have 24,223 frames repre-senting the finger placements. The heatmaps in Figure 5
show the average capacitive measurements over all partici-pants for each grip. Using scikit-learn’s4 MLPClassifier withunchanged hyperparameters, the five grips can be clas-sified with an average accuracy of 82.5% (min = 62.6%,max = 100.0%, k -fold cross-validation over all participants).Figure 7 shows the confusion matrix for the evaluation.
Gr1 Gr2 Gr3 Gr4 Gr5
Gr5
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Gr1
7 474 151 1205 2769
482 0 94 3379 636
0 0 5282 147 42
117 3942 73 224 384
4603 2 1 56 153
Figure 7: Confusion matrixshowing the classification resultsfor the exemplary grip classifier.
Figure 8: The Hardware Containerattached to a participants arm todemonstrate how the prototype canbe used in mobile scenarios.
DiscussionWe presented a smartphone prototype that senses capa-citive touch input on all sides. In a user study, we recor-ded the finger placement in the form of capacitive imagesof common grips that were described in prior work [12] tocreate heat maps (see Figure 6). While it is possible to as-sign each heat map to a grip by eye, we also used basicmachine learning to demonstrate the feasibility of grip clas-sification using the capacitive images. The accuracy of theexemplary user-independent grip classification suggeststhe feasibility and is similar to the ones reported in previ-ous work [3]. To enable others to re-build our prototype, weshare the 3D models, PCB schemes, a list of used parts,and the kernel modifications with the community5.
In the current state, this prototype has two limitations asa tradeoff for a familiar form factor and the support of anestablished operating system. Compared to the Nexus 5,the back side is entirely flat instead of slightly curved. Thisis due to the design decision of minimizing the device sizeand could be solved by minimally increasing the device’swidth and thickness to add a curve to the left and right side.The second limitation is the flexible flat cables (FFCs) thatare routed through the top side of the smartphone. With aweight of only 4 g and an initial length of 500mm (readilyextendable), we observed that the FFCs neither restricthand movements (e.g. tilting or moving the device) nor
4scikit-learn.org5github.com/interactionlab/full-touch-smartphone
apply any noticeable force on the top edge of the device.Previous work showed that fingers are not touching the de-vice’s top edge when holding in portrait orientation [11].Thus, the FFCs are neglectable when using the device inportrait mode during one and two-handed interaction. Toevaluate interaction in landscape mode, the PCB schemes,as well as the 3D frame, can be readily modified to routethe FFCs to the right or left side. For studies in mobile sce-narios (e.g. while walking or being encumbered [18, 19]),the Hardware Container can be attached to the user’s up-per arm as shown in Figure 8. This prototyping approachis not limited to a Nexus 5 so that larger smartphones ortablets can be used for a larger prototype.
Conclusion and Future WorkIn this work, we developed a smartphone prototype that re-gisters touch input on the whole device surface based oncapacitive sensing. In contrast to prior work, our prototypehas a form factor nearly identical to an off-the-shelf Nexus5 so that users’ hand grip and input performance are notinfluenced by an increased thickness. To evaluate the pro-totype’s functionality, we conducted a user study to collecttouch data for five common grips presented in prior workand visualized the finger placement in heat maps.
In future work, we use the prototype for interaction techni-ques and use cases that require the finger placement andtouch input beyond the front touchscreen. Amongst others,this includes BoD and edge input, grip pattern and changerecognition, and an investigation of grips and finger place-ment in mobile situations where motion capture systems,tracking gloves or cameras are not applicable. While theback touchscreen was only used to capture the finger pla-cement in this work, future work could also look into usingthe second screen on the back to extend the display spaceor to present information to the opposite.
ACKNOWLEDGEMENTS This work is supported by theDFG within the SimTech Cluster of Excellence (EXC 310/2)and the MWK Baden-Württemberg within theJuniorprofessuren-Programm.
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