Haptic Personal Trainer

Ildar MuslukhovUniversity of British Columbia

Vancouver, Canadaildarm@ece.ubc.ca

Andreas SotirakopoulosUniversity of British Columbia

Vancouver, Canadaandreass@ece.ubc.ca

ABSTRACTCurrent training techniques, using human trainers or pre-recorded video and audio training routines have a numberof limitations, both practical (e.g., expensive personal train-ing, limited feedback with video) and psychological (e.g.,reluctance of trainees to perform in front of a group). In aneffort to address these limitations, we propose, in our currentwork, a new approach that utilizes haptics as an additionalform of feedback. We developed a prototype, using bendingsensors and actuators that we fixed on clothing and whichwere worn by the users. A computer program used to recordand control the prototype and an Arduino platform was re-sponsible for the communication between the computer andthe sensors/actuators. We evaluated the performance of 10participants in two types of exercises; static and dynamic.Our preliminary results as well as the reaction of partici-pants to the prototype are promising, indicating that thehaptic feedback was helpful in performing the exercises andcreated a pleasurable experience while using the prototype.This work provides the basis for further investigation of thisapproach which the authors believe that can address effec-tively many of the limitations of training in the absence ofhuman trainers.

Categories and Subject DescriptorsH.4 [Information Systems Applications]: Miscellaneous;D.2.8 [Software Engineering]: Metrics—complexity mea-sures, performance measures

KeywordsHaptics, Training

1. INTRODUCTIONIn activities like floor gymnastics or dancing the develop-ment of proper technique and posture on the part of theperformer is a core component of the successful executionof the various elements. In order for novice trainees to de-velop the necessary skills required by the elements they aim

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to perform, proper instructions and feedback are required.This is currently achieved by assigning trainers to traineeseither personal or within a group. The traditional trainingmethods are constituted of verbal instructions and visualexamples of how to perform the various elements by theinstructor prior and after the trainee’s attempt as well asfeedback in the form of adjusting posture by touching thetrainee and giving instructions verbally while performing hisattempt.

There are various documented limitations in the traditionalmethods that might render training an unpleasant or inac-cessible choice for a number of individuals. Although studieshave shown that personal training has a significant effect onmotivating the individuals to keep exercising [11], it comesat a considerable cost. Moreover, group training has beendocumented to cause anxiety and embarrassment to certainindividuals due to their perceived lack of skills or exposure ofbody [5], [8] to other members of their group. On the otherhand , when one employs the current methods (e.g., videotraining programs), home training can prove challenging inreceiving useful and accurate feedback without a trainer be-ing physically present and providing real time feedback. Inorder to address these issues, methods should be developedthat, without compromising the desired outcome of perform-ing the attempted exercises correctly, would provide a cost-effective and pleasurable experience to the trainee. Further-more, current training techniques can be augmented withnew ways of providing feedback which will enable traineesto achieve the desired elements faster and understand whatthey are required to do easier.

In an effort to investigate possible solutions to the issuesdiscussed above, we developed a novel interface that drawsupon lessons learned from the haptics research area. Hap-tics have a well-established ability to provide feedback thatis readily understood by the user and has been successfullyused in situations that require precision and fast interpreta-tion of the feedback. For these qualities, haptics have beenextensively used in situations where precision is of outmostimportance, like microsurgery and robotic assisted surgery[6]. They have been also utilized in various physical exer-cise training schemes by various researchers. Building uponthis knowledge we are proposing, in our current work, a newscheme that will utilize haptic feedback to assist trainees toperform various exercises. In most relevant research proto-types and implementations the main idea is to measure ac-celeration, position or spacial characteristics of the trainee

and his surroundings and provide meaningful feedback thatwill assist in the correct or safe execution of the exercise. Onthe other hand, in an effort to accommodate needs relevantto particular types of exercises (e.g., balancing and precisebody posture, widely used in Yoga exercises for example) wepropose measuring joint/limb positioning using bending sen-sors. The sensors identify whether the trainee has achievedthe appropriate position, required by the exercise and/orthe trainer and if not, feedback is provided. The feedbackis in the form of vibrations at the area where the joint hasnot positioned properly. The goal of the haptic feedback isto draw the trainee’s attention to the particular muscle areaand help him correct the mistake without disrupting his con-centration. The idea of coarse haptic feedback, after mea-suring joint positioning, used to augment verbal instructionhas not been proposed before and it is the our main contri-bution in this work. A second contribution of the currentinterface is that it is designed in such way that it can be de-ployed in various locations providing completely automaticfeedback without the need of a human trainer. We envi-sion our solution, as a combination of a wearable hapticsdevice/costume and an application running on a portabledevice (e.g. smartphone) that can be used complimentaryto traditional training techniques, by people who choose totrain at home or other locations/occasions where a humantrainer might not be accessible or desirable all the times.

In order to test our proposed solution we developed a pro-totype and evaluated it, with a user study having 10 par-ticipants. We used two types of exercises as defined by theFederation Internationale de Gymnastique [16]: static anddynamic. Each type of exercises aims at investigating differ-ent aspects and uses of our haptic trainer prototype. Timeneeded to achieve a certain position in a balancing (static)exercise was investigated as well as time was observed incompleting a series of body postures that compromised adynamic exercises design to mimic a simple sequence ofdancing/exercise moves. Our initial results have been en-couraging showing good performance, on the part of theparticipant, when haptic feedback is employed. The cor-rect posture has been achieved faster when haptic feedbackwas employed in the static exercise, indicating that partici-pants were able to interpret the feedback faster compared tosolely verbal instructions. Furthermore, haptic feedback wasstrongly appreciated by our participants who agreed that itspresence made the exercises easier to follow and complete.Especially when coupled with verbal instructions. In the dy-namic exercise, there was no statistical difference in the timeneeded to complete the exercise, however, our participantsindicated a strong preference for the combination of verbaland haptic feedback in this case too.

The remainder of this paper is structured as follows. Insection 2 we discuss related work followed by a discussionon our prototype and study design in section 3. In section4 we present our results which are discussed in section 5.Finally we provide conclusions and future work in section 6.

2. RELATED WORKResearch in the area of haptic interfaces is active in the lastseveral years and many interfaces have been developed aim-ing at assisting different human-computer interaction paradigmsand needs, from surgery to interpersonal communications.

[4, 1]. The human tactual sense is generally divided in totwo subsystems: tactile and kinesthetic senses. Tactile (orcutaneous) sense refers to the perceived stimulation to thebody surfaces while the kinesthetic sense refers to the per-ceived limp positions, movements and muscle tensions. Wecan already see successful products in our daily life such asvibration mode in cell phones, Wii game consoles (and nowPlay Station 3 also uses such controls) that take advantageof this human sensing modality. These new interfaces ordisplays gave us better user experience and improved theusability of the products which they have been applied to.We seek to investigate the incorporation of tactile feedbackin training building upon previous research in the field andproposing ways to utilize the modality of touch for interact-ing with the computer even further.

In previous work, efforts to create a pleasant training experi-ence have been made (e.g., in martial arts training) utilizingsensors and sound as forms of feedback [14]. As a mea-suring device the authors used acceleration sensors on thewrists of the trainee, thus they were able to assess how muchpower the trainee had put in the execution and also, thetime length of a particular move. Although they providedfeedback whenever the trainee made a mistake during an ex-ercise they did not provide indication for the exact locationwhere the mistake took place. For example, during TSUKImovement the trainee has to do 2 types of movements withtheir hands: kick and turn, if an error is detected in either ofthe components of the exercise sound feedback will providedwithout further indication.

Personal haptic assistants for active training or rehabilita-tion processes have been part of the research community’sinterest. Thus in [10] authors focused on haptic feedbackfor patients who are undergoing training for rehabilitationafter hip replacement surgery. Their main focus was on themovements which are restricted after this particular type ofsurgery. Although their solution did not require expensivemotion capture technologies (such as video cameras and spe-cial marker based suits) and could be used outside easily itis not suitable for training exercises because of the feedbacknature. They provide user with binary feedback ”no feed-back” or ”attention” which is not mapped to any particularmuscle or joint.

Motion recognition systems based on video cameras havealso been used widely. For example in [9] the authorsused one of Vicon’s motion capturing system, which is basedon set of strobes, IR cameras and reflectors, placed on thetrainee. Although this solution provided very detailed usermotion capturing functionality, it does need investing in ex-pensive equipment and also is not suitable for outdoor usage.It is worth to note that the authors achieved interesting re-sults in their work and showed that performance increasedby 27%.

In CHI 2010 there was a work in progress report [7] whereresearcher presented their on going research. Their main ob-jective was to investigate motor function development whilelearning the violin. They did not report any concrete resultsin their report, although they stated that they saw a clearimprovement.

In another relevant work [13], presented in CHI 2009, theauthors noted the importance of the place where actua-tors are put to convey tactual feedback. They showed thattrainees in a very noise environment can better perceive tac-tile feedback rather than aural. The authors also noted thatit is often not possible to get any feedback from you coachbecause of the activity nature, e.g. skiing, snow boarding,swimming etc. However, in this work the authors rely on anexpert giving feedback remotely in real time whereas, ourapproach seeks to evaluate how effective/feasible automaticgenerated feedback is.

Furthermore, haptic sensation and wearable haptics has beenutilized in research aiming to investigate attention-gettingpractices as in work by Baumann et al in [3]. In thatwork, wearable haptics have been utilized to emulate humanattention-getting practices with promising results. Attention-getting in a non disruptive way can be of great importance insports training as well, as these activities require the traineeto maintain focus at the exercise at hand.

From the literature we can see that tactile feedback is anactive contemporary research area, and a lot of effort is de-voted to understand this underdeveloped, in terms of com-puter interfaces, modality as well as turn research ideas intoconsumer products. We believe that cheep and individualpersonal assistants (trainers) will make a lot of difference inthe future, because they can also solve the problem of novicetrainees feeling embarrassed when they join a sports club.With such personal trainers, trainees will be able to polishtheir skills without having to put up with the limitation oftraditional training techniques at home or with a trainer.

3. METHODOLOGY AND STUDY DESIGN3.1 Research Questions and HypothesesOur research aims at answering the following research ques-tions:

• R1, Does haptic feedback allow trainees understand therequirements of their exercise, learn it faster and per-form it accurately with investing less effort and timecompared to solely verbal instructions?

• R2, Can haptic feedback, based on a recording of an ex-pert executing the element, provide adequate guidancefor novice users in performing the same exercise?

• R3, Are mechanisms utilizatin haptic feedback moti-vating for the users to maintain and learn a trainingroutine by making it a pleasurable, less stressful expe-rience?

We had the following hypotheses for our design:

• H1, The augmentation of verbal instructions with hap-tic feedback will lead in better or equally good perfor-mance in the exercise compared to solely verbal instruc-tions.

• H2, Haptic and Verbal feedback is going to be inter-preted easier, in terms of accuracy and adjustmentsneeded, than solely verbal instructions by our partici-pants

• H3, Addition of haptic feedback will yield a pleasurableexercising experience for the participant.

Our study design and prototype aim to confirm our hypothe-ses.

3.2 Prototype and Control Program

Figure 1: Bending sensor and actuators that wereapplied on the knee.

We developed a wearable haptics prototype, as shown inFigure 2, where we attached our bending sensors and ac-tuators by sawing them on pieces of clothing, as shown inFigure 1, that we prepared for the different joints that wemonitored. Plastic wrap around bending sensors was usedin order to allow the sensor to move back and forth morefreely. We chose to monitor six joints (elbows, wrists andknees) because we felt that these were important areas ofthe body while performing an element as well as it was eas-ier, compared with other parts like the shoulders, to adjustthe bending sensors and actuators while keeping them tightto the body. The pieces of cloth were tightened on the bodyof the participant prior to start performing the exercises.

Figure 2: The wearable component of our prototype.

The sensors and actuators were connected to an Arduinoplatform which was in charge of transferring the data be-tween our custom computer program, developed in C#, andthe sensors/actuators. Six bending sensors were connectedto six analog inputs on the Arduino platform via a voltage

Figure 3: Voltage divider for bending sensors.

Figure 4: Block of relays for actuator controlling.

divider, shown in Figure 3, and six pairs of actuators (to pro-vide strong enough feedback) were connected to the digitaloutput of the Arduino platform via a block of relays, shownin Figure 4. Since all bending sensors we had were having 8-10KOhm resistance in straight condition, 16-20 KOhm whenbent one way and 7-9KOhm when bent the other way. Thatis why we used 10KOhm resistors in voltage dividers con-nected to analog inputs of the Arduino board. Significantdifference between resistance of the bending sensor in op-posite direction can be explained by the fact that we hadone-direction detecting bending sensors.

We used relays to control actuators because digital outputsof the Arduino board are capable of driving electronic equip-ment if it uses less than 40mA of current, whereas our actua-tors need about 60-80mA. Moreover, during our pilot studywe realized that we needed to put 2 actuators at each joint(thus, increasing driving current to 120-160mA) just to makethe feedback noticable enough, because participants might

Figure 5: The static exercise the participants wereasked to perform.

wore thick outfits. This is why we decided to isolate Arduinoboard and actuators, and use a separate power supply forthe actuators controlled by relays. The actuators we hadwere designed to work with maximum of 3.5V of power sup-ply. Since we had only 9V power supplies, we decided tobuilt a voltage divider on the relay board. Resistance ofthe actuators varied between 26 Ohm and 30 Ohm, so weused additional 62 Ohm resistance (combination of 22 and40 Ohm resistors).

Our custom program was used to calibrate the bending sen-sor measurements so as to accommodate for different par-ticipants’ physical shapes. Also it was used to log the dataretrieved from the Arduino platform and to control the com-munication with the platform and provide visual feedback tothe experimenter regarding participant’s posture. Data col-lection frequency was about 40Hz (far less than the abilitiesof the Arduino’s ADC module capabilities, which is 10KHz[2]). Finally, our program was used to set the error mar-gin, in percentage, that we would allow for the execution ofthe exercises. The error was defined as percentage of diver-gence from a predefined posture as executed by one of theexperimenters. The experimenter is a certified trainer.

3.3 Study DesignWe evaluated our prototype in a within-subjects user studyhaving 10 participants performing a static and a dynamicexercise in three conditions three times in each one. Thesequence of the conditions as presented to the participant

Figure 6: The dynamic exercise the participantswere asked to perform (the final position is the sameas the initial).

was counterbalanced so as to accommodate for carry overeffects within the study design. The conditions where thefollowing:

• H. Solely haptic feedback using the actuators.

• V. Solely verbal feedback by one experimenter.

• H-V. Both haptic and verbal feedback.

Each participant executed first the static exercise three timesin each condition until he had performed all three conditions.Then he executed the dynamic exercise three times in eachconditions. Upon finishing both the static and dynamic ex-ercises, an online survey was administrated that helped usaccumulate qualitative feedback regarding the participants’experience using the prototype as well as their perceptionon how helpful the different feedback modes were. Finally,we assembled demographic and prior haptic exposure data.

3.3.1 Static ExercisesWe wanted to investigate how our feedback can assist usersin performing static exercises or achieve postures (e.g., danc-ing positions). Also, we wanted to investigate whether pro-viding solely haptic feedback or augmenting the verbal in-structions with haptic feedback would yield any better re-sults, in terms of time needed to assume a given position,compared to the traditional way of solely verbal instruc-tions. Time is a common metric in gymnastics when thetrainee has to perform an exercise [15] and we felt that it

would be an objective criterion that we could measure in allthree conditions. We requested our participants to performa static exercise by assuming a predefined body posture, asshown in Figure 5, in as little time as possible, utilizing thefeedback it was available to them at each time and keep theposture for three seconds. If the participant lost the correctposture during the three seconds that were required he hadto re-assume it and maintain it for another three seconds.Although the exercise was simple and easy to achieve wefelt that it was appropriate for our purposes as it requiredbalancing but also accurate positioning of the participants’elbows and wrists in an unusual position. The combinationof these two was challenging enough for most of our partici-pants. One of the experimenters had recorded the exercise inadvance while wearing the prototype and the measurementswere calibrated each time a new participant was wearing thedevice. The participant had to assume the position mimick-ing the recorded posture of the experimenter within a smalldivergence error, set at 7.5%. This divergence was chosen,after piloting our prototype, so as to make the exercise chal-lenging for our participants.

In the H condition the participant was receiving haptic feed-back for as long as their posture was not the correct one.When all the joints under observation achieved the correctpositions (within a 7.5% divergence) the actuators wouldstop providing feedback and the participant had to maintainthe posture for three seconds. During the V condition theparticipant was receiving verbal instructions (i.e., feedback)from one of the experimenters regarding the correctness ofhis current posture and how he should adjust it. The pro-gram would give visual feedback to the instructor, whichaid him to accurately judge whether the participant had as-sumed the correct posture. When he achieved the correctposture he was notified and instructed to maintain it forthree seconds. Finally, a combination of the two previousprocedures was used during the H-V condition with one ex-perimenter providing verbal instructions and the actuatorsproviding vibrations as feedback.

The computer program was recording the time it took eachparticipant to complete the exercise in each condition andnotified the experimenter when a successful completion ofthe exercise had been achieved.

3.3.2 Dynamic ExercisesWanting to test further the utility of our haptic feedbackin exercise training we devised a dynamic exercise that werequested our participant to perform. The purpose for thisexercise was to observe whether the addition of haptic feed-back would lead to less time while performing a series of pos-tures, as it is done in real life training, where trainees learnnew moves by analyzing and learning each main posture ofthe exercise. Also, we sought to investigate whether the ad-dition of haptic feedback would assist the memorability ofthe posture sequence. Persumambly, if in one condition thefeedback aided the memorability of the exercise we wouldsee better results in time.

We provided each participant with instructions for the dy-namic exercise after he had successfully completed the staticexercise. He had to perform the whole sequence of 9 posi-tions correctly in as few time and doing as few errors as

possible. The first sequence of the positions are shown inFigure 6. The ninth position is the same as the initial one.The instructor verbally guided participants both in H-V andV. All participants received instructions on how to performthe sequence in advance and we started capturing data oncethey told us that they felt comfortable with rememberingthe sequence.

As in the static exercise study, all participants were exposedto 3 different feedback types: H,V and H-V. If during per-forming this exercise it took more than two seconds for par-ticipant to achieve the next posture correctly and it was acase with haptic feedback, our haptic trainer provided themwith a feedback on the joint which was bent incorrectly. Avibration, for 150 ms, on all actuators was provided whenparticipant assumed the correct posture indicating that hecould move to the next position. In contrast to the static ex-ercise we used only 0.5s as the duration threshold for whichthe participant had to keep the posture. In real exercises,this time, usually, should be as small as possible (hence itis a dynamic exercise) but we decided to use 0.5s so as tobe sure that our subjects performed postures correctly. Inthe condition when only verbal feedback was administrated,the participant was instructed verbally until he reached thecorrect position and once he had successfully assumed theposition and he was instructed to move to the next one.

The most challenging part of this component of our exper-iment was the need for participants to not only assume aposition that required them to bend different joints in un-usual positions but also, that it required them to rememberthe correct sequence of the positions. The latter was thereason why decided to have our dynamic exercise being con-sisted by nine positions as this number sits on the upperlimit people can easily remember [12].

4. RESULTS4.1 RecruitmentFor the purpose of evaluating our prototype we recruited 10participants. The majority of our participant are between 18and 30 years old (90%) and 7 are male while the rest female.Out of the 10, 5 had no experience in training with personalor group trainers and 6 had personal experience with feed-back devices, either using a gaming console or participatingin a study around haptics.

4.2 Static ExerciseTime, in seconds, needed by each participant to assume thecorrect posture in each condition was recorded over threeattempts in each feedback condition. For each participantwe averaged the time needed in each condition and we con-ducted a one-way repeated measures ANOVA to comparethe average time needed in each condition to complete thestatic exercise successfully. There was a statistical signifi-cant effect for condition (i.e. feedback type), Wilks’ Lambda= .45, F (2,8) = 4.87, p = .041, multivariate partial etasquared = .55 indicating a large effect using Cohen’s guide-lines. Pairwise comparisons, using the Bonferroni test, wereconducted to identify where, among the groups, the differ-ence exists. A statistical significant difference between thehaptic condition and the verbal one was observed. The de-scriptive statistics are presented in Table 1.

There was no statistical significant difference between thetime needed between H-V and V conditions.

Table 1: Descriptive Statistics for the Time Neededto Perform the Static Exercise

Condition Mean Standard Deviation N

Haptic 8.79 4.86 10Haptic-Verbal 10.76 4.69 10

Verbal 15.43 4.99 10

4.3 Dynamic ExerciseTime in seconds, that participants needed to complete thedynamic exercise was recorded over three attempts in eachfeedback condition. For each participant we averaged thetime needed we conducted a one-way repeated measuresANOVA to compare the average time needed in each con-dition to complete the dynamic exercise successfully. Therewas no statistical effect observed for feedback type in thiscase. The descriptive statistics for time are presented inTable 2.

Table 2: Descriptive Statistics for the Time Neededto Perform the Dynamic Exercise

Condition Mean Standard Deviation N

Haptic 63.89 24.24 10Haptic-Verbal 59.29 4.69 10

Verbal 67.73 20.04 10

4.4 Qualitative FeedbackAfter completing both types of exercises participants wereasked to provide feedback on their experience using our pro-totype through an online survey. We were particularly in-terested in their response to the question “Please order thetypes of feedback in terms of how helpful it was for you”.In the static exercise 9 out of 10 claimed that it was thecombination of haptic and verbal that they found to be themost helpful in order to complete the exercises. Similarly inthe dynamic exercise, 7 responded that it was combinationof the two types of feedback that found to be most helpful.Participants, in both exercises, that did not indicated theH-V condition as the most usefull prefered the V condition.

When asked to rate on a 5-point Likert scale how helpfuleach feedback was, with 1 being not helpful at all and 5very helpful, the solely haptic feedback condition was ratedwith an average of 3.9 in the static exercise and 4.2 in the dy-namic, the verbal-haptic feedback condition was rated with4.4 and 4.78 in the static and dynamic exercises respectivelyand finally the solely verbal instructions condition receivedan average of 3.60 and 3.70 in static and dynamic exercises.

Finally, all participants stated that they found the feedbackprovided by the prototype useful and that they enjoyed usingit despite limitations such as lack of directional feedback orbulkiness of the apparatus.

5. DISCUSSIONOur goal in this work is not to propose an alternative totraditional training technics. It is rather, to propose a novelidea that would assist and augment trainee experience oftraining outside a group or without a human personal trainer.

The main interest in this research was to investigate whetherhaptic feedback can aid performance while training. An-other point of interest, for us, was to investigate whetherusers would feel comfortable receiving verbal instructionswhile receiving feedback in the form of vibrations. Our re-sults in both exercises indicate that the haptic feedback aswell as the coupling of verbal instruction with haptic feed-back have been beneficial. Even if there was no statisticalsignificant differences observed between V and H-V in eitherexercise types the mean time needed for completing the exer-cise is lower than providing solely verbal instructions. This,in addition to the qualitative feedback we received by ourparticipants, where they demonstrated a strong preferencefor both verbal and haptic feedback, is a strong indicationthat our scheme can be appealing to trainees who choose totrain on their own, as well as that the addition of hapticsdoes not pose an interfierence to the interpretartion of in-structions by the participant rather it aids him. Thus our H1and H3 have been confirmed. However, we have no concreteevidence that confirms our H2. This hypothesis remains tobe investigated further in a later iteration of our prototypeand study design.

Solely haptic feedback led to less time needed to completethe static exercise. This, however, was an expected resultdue to the well documented, fast interpretation of such feed-back by humans as well as the overhead of response time onthe part of the instructor added to the the verbal instruc-tions condition, for the cases that such instructions wereneeded in order to correct the posture of the participant. Asthe instructor, except for his own judgement, had to consultthe program’s visual feedback, from time to time, we believethat his response time to the visual feedback, although verysmall, has been added in the time needed by the partici-pant to receive and interpret feedback needed to completethe exercise. In future iterations of the prototype, we planto automate the verbal feedback, through pre-recorded in-structions played back as audio so as to focus solely on theresponse time of the participant.

However, of particular interest is the fact that haptic feed-back when coupled with verbal instructions did not maintainthe same, or better, improvement in time compared to theV and H conditions, as we expected. This can be inter-preted as an interference effect between the two modalitiesand how participants process instructions and feedback cog-nitively. It is a point that has to be investigated further us-ing additional participants and controlling for response timeand instruction type (i.e., investigate optium verbal instruc-tions that the participant can interprert fast) on the part ofthe instructor when an error is present. It is, however, ofinterest that this was the condition most participants iden-tified as the most helpful, when asked to judge how mucheach feedback type helped them in completing the exercise.This indicates that haptic feedback is better understood, orat least interpreted, when augmenting an already familiarprocess, like verbal instructions.

When looking at the dynamic exercise’s results, we foundthat it took significantly more time for participants to com-plete the exercise than we anticipated. We attribute this tothe fact that the feedback provided by the prototype wouldlet the participant know that there was an error with theexecution of the exercise but there was no way to differen-tiate whether the error lied in a wrong positioning of thearm while attempting the correct posture in the sequenceor whether they were attempting a completely wrong pos-ture (i.e., they had omitted a posture in the sequence com-pletely). We believe that adding a way to differentiate be-tween errors in posture accuracy and errors in posture se-quence will hugely improve the time needed for the condi-tions that include a haptic component. We purposely didnot guide participants in respect to errors in the sequence,when giving verbal instructions, so as not to keep all theconditions equal.

Although participants before starting the exercise claimedthat they remembered the sequence, on many occassions,they got confused and had to start over. Further investiga-tion is needed to see if this has to do with the presense ofthe feedback at this early stage of learning the sequence.

It is worth noting that in real life training scenarios, whenverbal instructions prove inadequate to help the trainee cor-rect a mistake, the trainer might try to adjust the correctposture by touching the participant and guiding to the cor-rect position while giving instructions. In our paradigm wecan envision that automatic verbal instructions based onthe sensor readings accompanied by haptic feedback couldbe prove an adequate alternative when human trainers arenot accessible.

5.1 LimitationsDuring our experiments we identified a series of limitationsin our design, mainly with our prototype. Adjusting sensorsand actuators in a way such that they are constantly fixed onthe user’s body is a known issue in the wearable haptics re-search community. Also, prior research has investigated thelimitations of haptic wearable computing and recommenda-tions on the use of such devices have been made in terms offatigue that users might experience while using them [15].

Our current prototype suffered from both limitations of be-ing bulky and in need of frequently adjusting the sensors, inorder to receive better readings. This may have been dis-ruptive to our participant and may have affected their per-formance in terms of focus and remembering the sequence ofpositions in the dynamic exercise. On the other hand, stop-ping the flow of the exercise to adjust the sensors and recal-ibrate them might also enabled some participants to achievebetter performance than others, having received rest fromthe exercise’s fatigue.

In addition, the adjustment of the sensors on the body aswell as the overall fidelity of the prototype was not ideal,resulting in sometimes overly sensitive measurements. Thisrequired some participants to assume inconsistent positionsand forced the instructing experimenter to look at the vi-sual feedback, provided by the prototype, in order to giveinstructions instead of judging from the participants posturewhether they have successfully assumed the position.

Another limitation of our prototype is that it did not ac-commodate for directional feedback. Although participantswould feel a vibration if they hadn’t achieve the correct po-sition, there was no notion towards which direction theyshould move to correct their mistake. We believe that by de-tecting the direction their moving to and adapting the feed-back giving different kind of vibrations (e.g., series shortervibrations for when they are moving towards the correct di-rection) or having vibrators on different positions of the limp(e.g., under and above the wrist that would indicate whetherthe participant need to move upwards or downwards) wecould solve this problem.

Finally, our number and type (one way bending) of sensorsminimized the joints and movements we could detect andprovide feedback. Adding more and/or using two way bend-ing sensors would solve this issue although it would requirea higher fidelity prototype that would be more reliable inregard to sensors’ and vibrators’ attachments to the device.

Although we took into consideration these limitations in de-signing our prototype and study, we were not able to removethem completely. However, we believe that later iterationsof our prototype will make it less bulky and more portableas well as more accurate.

6. CONCLUSION AND FUTURE WORKIn our present work we have proposed a novel approach forassisting training without a human trainer. We created andevaluated a prototype that used bending sensors and actua-tors in order to identify errors in executing exercises and givefeedback that would help users correct them. Our proto-type proved to be well accepted by our participants and theresults recorded indicated that the haptic feedback guidedthem in completing the exercises in less time and in a waythat they felt was more efficient and enjoyable.

Future work would include miniaturization of our proto-type’s electronic components and porting our controllingprogram to a portable device suitable for exercising. Thisis feasible considering the limited computational and mem-ory needs of our program (e.g. dynamic exercise data were108 bytes long, static 12 bytes). Furthermore, we intendon working towards better embedding the sensors and ac-tuators in some form of exercise suitable costume, in a waythat our feedback mechanisms are not obtrusive and are aes-thetically appealing. Finally we will try to evaluate our im-proved prototype with a larger number of participants anda broader spectrum of exercises that will include additionaljoints and body movements. In addition instead of limitingourselves in measuring time we will investigate alternativeroutes of evaluation. An idea would be to group participantsaccording to condition and have the group in each conditionpractice for a period of time using the feedback for thatgroup (i.e., recorded verbal and video instructions, hapticinstructions using our prototype or both). Expert trainerswill judge their performance prior to the introduction to theconditions and after the training period with each conditionhas passed. We believe that this scheme although unfit forthe current fidelity of our prototype will be appropriate toinvestigate the home trainer paradigm.

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