Preserving Agency During Electrical Muscle Stimulation
Training Speeds up Reaction Time Directly Afer Removing EMS
Shunichi Kasahara

Kazuma Takada

Jun NishidaSony CSL
Japan

Sony CSL & Meiji University
Japan

University of Chicago
United States

Kazuhisa Shibata

Shinsuke Shimojo

Pedro Lopes

RIKEN Center for Brain ScienceJapan

California Institute of Technology
United States

University of Chicago
United States

before training
without EMS?

EMS training

after training
without EMS!

p < 0.01

280
210
140

8.1ms speed up

70
SEP-17-2020 9:00AM

1/4000F1.8

ISO2500

0

SEP-17-2020 9:00AM

1/4000F1.8

ISO2500

Reaction time (ms)Figure 1: We found that preserving the user’s agency while they are accelerated using a haptic device, such as electrical muscle
stimulation (EMS), is key to retaining a faster reaction time afer removing the haptic device. In our study, we used EMS toaccelerate participants as they pressed a button when they saw an LED fash (inspired by taking a photo of a target).

ABSTRACT
Abstract: Force feedback devices, such as motor-based exoskeletons or wearables based on electrical muscle stimulation (EMS),
have the unique potential to accelerate users’ own reaction time
(RT). However, this speedup has only been explored while the device is attached to the user. In fact, very little is known regardingwhether this faster reaction time still occurs after the user removes
the device from their bodies–this is precisely what we investigatedby means of a simple reaction time (RT) experiment, in which participants were asked to tap as soon as they saw an LED fashing.
Participants experienced this in three EMS conditions: (1) fast-EMS,
the electrical impulses were synced with the LED; (2) agency-EMS,
the electrical impulse was delivered 40ms faster than the participant’s own RT, which prior work has shown to preserve one’s senseof agency over this movement; and, (3) late-EMS: the impulse wasdelivered after the participant’s own RT. Our results revealed thatthe participants’ RT was signifcantly reduced by approximately
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https://doi.org/10.1145/3411764.3445147

8ms (up to 20ms) only after training with the agency-EMS condition. This fnding suggests that the prioritizing agency during EMS
training is key to motor-adaptation, i.e., it enables a faster motor
response even after the user has removed the EMS device fromtheir body.

CCS CONCEPTS• Human-centered computing → Human computer interaction (HCI); Haptic devices.

KEYWORDS
agency; electrical muscle stimulation; reaction time
ACM Reference Format:
Shunichi Kasahara, Kazuma Takada, Jun Nishida, Kazuhisa Shibata, Shinsuke Shimojo, and Pedro Lopes. 2021. Preserving Agency During Electrical
Muscle Stimulation Training Speeds up Reaction Time Directly After Removing EMS. In CHI Conference on Human Factors in Computing Systems(CHI ’21), May 8–13, 2021, Yokohama, Japan. ACM, New York, NY, USA,
9 pages. https://doi.org/10.1145/3411764.3445147

1

INTRODUCTION

Our nervous system possesses remarkable plasticity that enables
us to improve our abilities by means of training, i.e., we get fasterat tapping an icon on a screen or at sports by practicing these activities over and over. However, the optimization of our sensory
and motor abilities by means of training is not an trivial task. It

CHI ’21, May 8–13, 2021, Yokohama, Japangenerally requires prolonged training on a task with a high number of repetitions in a trial-and-error fashion to get signifcant
improvement [6]. To accelerate this cycle of learning (i.e., adapting one’s motor patterns to acquire a new skill), researchers havebeen employing haptic devices, especially wearable ones. These arelightweight on-body haptic devices with sufcient force to actuate
the user’s body, and therefore, are able to physically enhance theuser’s motor abilities. As an example, exoskeletons [16] have beenshown to augment users’ grasping force [46] and to even improvetheir musical performance [41].
A more recent and emerging class of haptic devices for skill training are interactive systems based on electrical muscle stimulation(EMS). EMS induces involuntary muscle movements by applying
electric pulses via electrodes attached to the user’s skin. Besides
actuating the user’s muscles, EMS also provides also strong proprioceptive feedback to the user [25]. As such, EMS has been used
to build interactive devices useful for: navigation [31], training a
new skill (e.g., a musical instrument) [8, 42], and even learning how
to operate tools that the user has never seen before [26]. These
EMS-based force feedback devices have the potential to enhance
our abilities and complement the traditional skill training. For example, it has been shown that EMS accelerates users’ reaction time(RT) when EMS is applied before users’ own action (preemptiveEMS) while even preserving their sense of agency [19]. However, itremains unclear whether this speedup only occurs in the presence of
EMS or also after the user removes of the haptic device.
In this work, we tackle precisely this question to understandwhether the accelerated reaction time caused by these devices happens even after the user has removed the device from their body. To
answer this question, we conducted a simple user study in which
participants were trained to press a button whenever they saw
an LED fash (no-decision making involved), inspired by how one
might attempt to take a picture of a fast moving object as soon as
one spots it. Our results, depicted in Figure 1, suggest that timing
the EMS impulses so as to preserve one’s agency allowed participants to retain some of the speedup even after removing the muscle
stimulation device from their bodies.

2

RELATED WORK

Our approach builds on the areas of haptics (such as EMS or exoskeletons), motor skill learning in neuroscience, and theories ofthe sense of agency from cognitive psychology.

2.1

Defning Learning and Motor adaptation

In psychology, learning has been defned as "changes in behavior
as a result of experience" [22]. This defnition applies to many situations involving users interacting with computer interfaces, as wellas to our case (i.e., users pushing a button on a interface). On theother hand, we also acknowledge that this defnition has been apoint of controversy too [7]. As such, we denote the particular typeof process that we are investigating in this paper as "adaptation",
which has been used to indicate motor learning that lasts for shortdurations (in the order of minutes)–from the taxonomy of humansensorimotor learning by Krakauer et. [21]. In their breakdown, sensorimotor learning is comprised of several processes if which motor
adaptation is a key process prior to long term skill learning [21].

Kasahara et al.

2.2

Haptic devices capable of limb actuation(force feedback)Force feedback systems are capable of moving a user’s limbs, typically by applying a force that causes it to move even against theuser’s volition. There are, generally speaking, two main classes ofactuators that provide enough output force to actuate human limbs:
mechanical actuators (e.g., large robotic arms [35] or exoskeletons [14, 41, 46]) and EMS. Mechanically actuated exoskeletons
provide force feedback for a wide range of haptic use cases, suchas power assistance [46] or guiding the motion [41].

2.3Electrical Muscle Stimulation

Electrical Muscle Stimulation (EMS) is an alternative means toachieve force feedback at a much smaller hardware footprint,
i.e., typically interactive systems based on muscle stimulation aresmaller, and therefore wearable, when compared to their mechanical counterparts. EMS originated in rehabilitation medicine asa means to restore lost motor functions, e.g., after spinal cord injuries [40]. Only recently, EMS was used in the domain of interactive
devices, mostly as a technique to create force feedback in virtualenvironments [9, 23, 24, 27], as a method to miniaturize mobile
information access systems [25, 30], and for training and tutorial
purposes [8, 26, 29, 31, 42].
The latter systems that leverage EMS for training are of particularimportance to our research question. For instance, in Stimulated
Percussions, EMS enables the user’s wrists to involuntarily drumon the correct tempo [8]. As another example, the PossessedHand
device electrically actuated the user’s muscles to reproduce thefnger poses required to play stringed musical instruments [42].
These devices hint that EMS actuation is useful to learn a physicalskill. However, all prior EMS research falls short in demonstratingthat EMS provides a beneft to training after the user removed theelectrodes and EMS stimulator. Essentially, a lot is known whileusers are wearing EMS devices but nothing is known after users
have removed these.
A more recent emerging direction for EMS is using it to exceed
the user’s own physical abilities. For instance, in Wired Muscle,
researchers demonstrated that when moved by means of EMS, auser can display an accelerated reaction time; therefore, in thepresence of the EMS assistance the user’s reaction time is fasterthan their own reaction time [29]. Furthermore, by delivering the
EMS impulses in a particular time window (around 80ms fasterthan the user’s own reaction time), researchers have optimized
EMS systems to accelerate the user’s reaction time without entirelycompromising the user’s sense of agency [19]. However, once again,
the question whether the user can achieve this after taking of the
EMS system is unsolved. Is this speedup permanent or only happens
in while the user is connected to the EMS electrodes?

2.4

Reaction time

Reaction time (RT) is one of the fundamental factors in human
computer interaction. The importance is evident in our everyday
interactions with computer systems, be it clicking a target with amouse, pressing a digital camera shutter, pressing a key to jump on
a platform game, or swinging a bat in VR to hit a virtual baseball.

Preserving Agency During Electrical Muscle Stimulation Training Speeds up Reaction Time Directly Afer Removing EMSGenerally speaking, speeding up one’s reaction time ofers a simple way to speed up interactions with computer systems. Moreover,when any system interface with human lives, it is critical even forsurvival, e.g., the shorter the reaction time of a pedestrian startled
by a horn of an incoming vehicle is, the more time they have to
avoid the danger. Psychophysical studies have long measured thereaction time of participants in response to visual stimuli, which
has been found to be around 250 ms [18]; this metric became an
important parameter in engineering interactive systems. Moreover,while one’s reaction time appears relatively stable it is of course
infuenced by other physiological parameters, such as physical exhaustion [3, 28] or sleep deprivation [37]. Many other parameters
are thought to potentially infuence one’s reaction time, for instanceadrenaline excretion; however, some studies did not fnd evidence
to support it [28].
Naturally, reaction time decreases with training, i.e., one becomes
faster at reacting [1, 43]. For instance, Taniguchi et al. and Ando,et al. showed a reduction in reaction time in a simple reaction
task with three weeks training. As these previous works suggest,a user’s reaction time can be improved (i.e., sped up/shortened)through training [1, 2, 43]. In light of this, we ask our researchquestion again: if we accelerate a user’s reaction time externallyduring training, e.g., by means of EMS, does this user still exhibit anaccelerated reaction time after they remove the EMS device fromtheir body?
The key diference between a movement that is accelerated by
EMS and one that is not (e.g., during voluntary training) is thelack of agency experienced during EMS, i.e., with EMS, the user is
moved by the EMS system rather than self-propelled. As such, one
would not expect that much of the improvements that EMS can doon the user’s reaction time would last after the user has removed
the device. However, previous work has shown that even whenstimulated by means of EMS one can conserve some agency if the
EMS impulses arrive within a certain time window (as found in [19]).
So, we put forward a new hypothesis: could this type of EMS that
preserves agency lead to more speedup after training whencompared to naive EMS?

3OVERVIEW OF STUDIES AND OUR
HYPOTHESISWe hypothesize that agency is key to retain the accelerated reaction
time that one experienced by means of EMS training. Simply put,
we expect that without feeling that we have performed an action
by ourselves, it is unlikely that we become better at it. With thisinsight in mind, we formulated our hypothesis: efects of training
should more pronounced when participants felt agency of their action
during the EMS training. This is precisely what we set out to study
in our main experiment.
To measure participants’ reaction times, we employed a standard
visual reaction task with fnger tapping. To understand if there wasa improvement in participants’ reaction time, we compared reaction
times before (pre) and after (post) training with EMS-actuated fnger
movements. Note that both pre and post measurements are taken
without the participants wearing an EMS device. Only in between
these two phases they train using EMS.

CHI ’21, May 8–13, 2021, Yokohama, Japan

In order to investigate whether agency is key to this motoradaptation efect, we need to use an EMS approach that allows
participants to preserve some sense of agency, even though theirreaction time is actually accelerated; this is achieved by adjusting
the timing of the EMS impulses so that it is closer to the user’s
own voluntary reaction time and becomes somewhat imperceptible
to the user–this is the so called "Preemptive Action" [19]. To estimate the preemptive time window (how early the EMS is applied)for our main study, we frst replicated the study by Kasahara etal. from [19]. Given that our apparatus was diferent from that of
Kasahara et al’s (i.e., we utilized a more precise touch detection
system at a sampling rate of 1KHz), this also implied the needed
replication. We therefore conducted two studies: (1) determination of preemptive timing (replication study) and (2) is agency
the key for user’s adaptation to faster motor responses?; thelatter is our main study.

4

STUDY#1: DETERMINATION OF
PREEMPTIVE TIMINGThe objective of our frst study was to investigate the relationshipbetween EMS acceleration and perceived sense of agency in our
experimental design, so as to fnd the best EMS stimulus timingthat accelerates one’s reaction time while also preserving one’s
sense of agency. Our study was approved by our local ethics
committee.

4.1

Task

To measure participants’ reaction times, we employed a standard
visual reaction task with fnger tapping, as in [19]: participants saw
a light fash (using an LED) and tapped on a button as fast as they
could, which is depicted in Figure 2 (a).
We used this standard and simple visual reaction time task to
avoid potential confounds, such as other factors that can be modulated one’s reaction time, such as stimulus complexity [17, 20, 32],
stimulus-response compatibility [13, 38, 39], number of potential responses [5, 10, 15], intensity of the stimulus [4, 44], and an expectedlevel of response accuracy [11, 12, 33].
During each trial, participant’s reaction time was accelerated bymeans of EMS. The time window of preemptive stimulation (EMS
ofset time) ranged from -100ms (i.e., 100ms before the visual stimulus) to 300ms after the LED blink, in steps of 20ms. We randomized
the EMS ofset time for every trial. After each trial (i.e., observe light
fash and tap on the button), participants were presented with theirreaction time followed by a questionnaire regarding their perceived
sense of agency. We follow the typical agency questionnaire, i.e., a
Likert scale question with 1 = "I did not do it" and 7 = "I did it", asin [19].

4.2

Procedure

Before engaging in the study, participants were briefed on the study
protocol. Then, as depicted in Figure 2 (b), participants were asked
to perform 30 trials to record their average reaction time without
EMS. Then, we asked participants to perform two sessions of thesimple visual reaction time test (40 trials), totalling 80 trials per
participant. Participants took 5 minute breaks between sessions.

CHI ’21, May 8–13, 2021, Yokohama, Japan(a)

VisualStimlus

Beep

2-3 sec

EMS

Kasahara et al.

Touch

DisplayRate

RT: 200ms

1234567

(b)

Rest

Rest

5min

5min

EMS offset
Base RT (30 Trials)

EMS (40 Trials)

EMS (40 Trials)

Reaction Time

Figure 2: (a) In our study participants are asked to touch the bar as soon as the LED goes on. Then, an EMS impulse stimulates
their fnger to contract (from -100ms before the LED to 300ms after). After each touch, participants rated perceived agency ona scale from 1 to 7. (b) Procedure of Study #1. After measuring the average reaction time, participants performed the task with
2 blocks.

4.3

Apparatus

Our experimental setup is depicted in Figure 3-(a). To assist readersin replicating our experiment, we provide the necessary technicaldetails and the complete source code1 . Participants were actuatedusing the bioSync EMS device used also in [19]).
a
LED (visual cue)b(side view)

ring finger

EMS electrode

touch sensor

EMS
electrode
EMS device

capacitive sensing

aluminum bar

ArduinoFigure 3: (a) Setup for our visual reaction task. (b) Side viewof our capacitive touch sensor mechanism.
Hand and fnger posture: In this study, the experimental setup
was controlled to eliminate possible disturbances such as posturechange, decline of concentration, EMS responsiveness change, andvisual stimulus size change. The fnger-holder and the touch detection bar were adjusted per participant, ensuring the hand is anatural rested pose (Figure 3-(b)). Furthermore, this prevents participants’ muscles from quickly getting tired.
Measuring reaction time: We utilized an Arduino-based capacitive touch sensor system with LED light as visual stimulus.
This system measured the reaction time from the duration between
the LED on and user’s touch on an aluminum bar embedded in thefnger-holder with less than 1ms of latency (which was verifed
using a high speed camera).
Electrode placement: A pair of electrodes was placed on eachparticipant’s fexor digitorum profundus muscle. This muscle fexes
the ring fnger clearly. We actuated the ring fnger since, as found byother previous EMS researcher, one can "robustly actuate it without
any parasitical motion of neighboring muscles" [19].
EMS calibration: We interactively adjusted the stimulation parameters to actuate the ring fnger robustly for our task (i.e., totouch the button). The parameters used in EMS calibration were: apulse width from 100-300 microseconds and the number of pulses,
1 https://lab.plopes.org/#EMSspeedup

between 1-4 repetitions. We chose this since prior research suggeststhat shorter stimulation is less noticeable [24].
Robust muscle stimulation: We performed an EMS stability
test per participant to ensure that the EMS can actuate the ring
fnger stably. Participants are asked to relax their muscles whilein the apparatus. Then, EMS impulses induced involuntary fnger
movements. After 30 trials, we evaluated the variance of the duration (TEMStoT ouch ) between the moment of triggering EMS andthe moment of touch detection. When the variance of TEMStoT ouch
was below 4ms, we consider this stable, otherwise we re-calibrated
the EMS.

4.4

Participants

We recruited 18 participants (4 self-identifed as female, 14 as male,
M=23 years old; SD=2.60) from our local institution. Participants
performed the experiment for a total of four days and received
70 USD as compensation for their time. With their prior writtenconsent, we transcribed their comments. The study design wasapproved by the local ethics committee and all participants provided
written informed consent prior to their participation.

4.5

Results

We collected 80 trials per each participant, with two data points pertrial: reaction time and assessment of agency. We found participants’
average reaction time to be M=203.8ms (SD=15.0ms), which is close
to fndings in psychophysics research depicting a reaction time of
250 ms in response to visual stimuli [18].
Then, we normalized the data by subtracting each participant’sbaseline reaction time (their own voluntary reaction time, acquired
prior to the study) to each trial’s reaction time (with EMS actuation).
This allows us to instead depict the time gained by means of preemption, which Kasahara et al. defned as preemptive gain [19].
Moreover, following [19], we also normalized the agency axis from0 to 1.
Figure 4 depicts results for the relationship between preemptive gain and perceived sense of agency. Following the protocolof [19], we computed a logistic regression. This resulted in a mean
ft of R2=0.74 (with SD=0.073, MIN=0.60, MAX=0.85) for our logistic model. This demonstrates that the participant’s curves are in
most cases similar and relatively consistent, as suggested by the

Agency score (normalized)

Preserving Agency During Electrical Muscle Stimulation Training Speeds up Reaction Time Directly Afer Removing EMS

Preemptive gain (ms)Figure 4: Results for the preemptive gain timing. We depict the relationship between sense of agency [0-1] vs. preemptive gain (timing of EMS in respect to the participant’s
own baseline). The solid lines represent regression curves
derived from a logistic regression for each participant.

low standard deviation. From this curve, we found that 40ms ofpreemptive gain would provide a preserved sense of agency larger
than 0.5 for 15 in our 18 participants. This mid-point in the sense ofagency (0.5) was chosen accordingly to [19]. Therefore, we defned
our agency-preserving EMS timing as 40ms, which we will use in
our next study. Last, this result appears consistent with [19] since:(1) the curve distribution is similar; and, (2) while the value is lower,
this is likely due to our use of a more precise hardware apparatus(i.e., our touch sensor was implemented at the microcontroller level,
instead of a via a laptop touchscreen).

5

5.1

of agency according to previous experiment. The EMS ofset time
was calculated by subtracting TEMStoT ouch (EMS trigger to thetouch detection) and preemptive gain (40ms) from TBaseRT eachparticipant’s baseline reaction time (obtained pre-study). To sum
it up, this condition enables a slightly faster reaction time, while
preserving some degree of agency (from [19]).
3. late-EMS: EMS actuated participants’ ring fnger but only
after the participant’s baseline reaction time. The EMS ofset timeis defned as 1.2 * TBaseRT of each participant’s baseline reaction
time (i.e., participants are expected to be tap faster than the EMS
assistance). In this EMS condition, participants will have complete
sense of agency (or close to it, from [19]) but the reaction time will
not be faster.
We added these conditions to allow us to make the proper comparisons. Only having agency as a variable would not allow us to
exclude whether an EMS condition that makes subjects act faster(speed) could alone explain the gain in post-EMS reaction time.
Thus, to have both speed and agency as variables it required us to
the aforementioned design with these three conditions.
a FAST EMS

2-3 sec

Conditions

We designed three experimental conditions, which are depicted in
Figure 5. These were:
1.fast-EMS: EMS actuated participants’ ring fnger at the sametime as the LED fashed ( depicts an EMS ofset time of 0ms). Therefore, the measured reaction time is expected to be very fast; in fact,"super-humanly fast". Conversely, because the resulting reaction
time is super-humanly fast, this condition results in no/very-low
sense of agency (from [19]).
2.agency-EMS: EMS actuated participants’ ring fnger at 40ms
of preemptive gain, where we expected to preserve some degree

EMS

RT = 40ms

Reaction Timeb AGENCY EMS

EMS
2-3 sec

RT = 160ms

EMS offset

Reaction Timec LATE EMSEMSSTUDY#2: IS AGENCY THE KEY FOR
ADAPTATION TO FASTER MOTORRESPONSES?

The purpose of our main study is to shine light of whether preemptive EMS is the key for a motor adaptation efect, i.e., it allows
users to become faster than they were, even after removing the
EMS device. As such, we employed a standard pre/post learning
study. We measure participants’ reaction time prior to the study(we call this pre-RT). Then, we trained participants to perform areaction test under a series of conditions (the same simple reaction
tap-test from our previous study). Lastly, we measure their reaction
time after this training (we call this post-RT).
This study uses precisely the same apparatus and calibration
procedures as our previous experiment.

CHI ’21, May 8–13, 2021, Yokohama, Japan

2-3 sec

RT = 200ms

EMS offset

Reaction Time

Figure 5: We utilized three study conditions: (a) fast-EMS(fastest but no sense of agency), (b) agency-EMS (fasterand preserves some sense of agency), and (c) late-EMS (nospeedup but with full sense of agency).

Base RT (30Trial)

Rest

Rest

2min

2min

PRE (30Trial)

EMS (30Trial)

POST (30Trial)

EMS (30Trial)

POST (30Trial)

Figure 6: The EMS training blocks were preceded and succeed by a block that measured, respectively, the participant’s
pre and post reaction times.

5.2

Hypothesis

Our hypothesis is: if agency is the key for motor adaptation, we
should measure the largest adaptation efects (i.e., largest speedup
in reaction time post-training) in the agency-EMS condition, whencompared to any other condition.

CHI ’21, May 8–13, 2021, Yokohama, Japan

Kasahara et al.

Figure 7: Reaction time (in ms) for all conditions: (top) fast-ems; (center) agency-EMS; and, (bottom) late-EMS.

Procedure

Figure 6 depicts our study design. First, we measured the participant’s baseline reaction time (TBase RT ). As described above, eachparticipant’s baseline is used to compute the precise timing of thestimulation in the agency-EMS condition (preemptive gain - baseline).
After this, participants engaged in two additional sessions, as
depicted in Figure 6. The frst session was comprised of three blocks:
30 trials without EMS (pre-RT), 30 trials with EMS (training), and30 trials without EMS (post-RT). The second session was shorter,with one block of 30 trials with EMS (training) and one without(post-RT).
In order to isolate the infuence of each condition, the three
conditions were performed on diferent days. Our main study was
conducted for a total of nine days, with breaks of three days in
between. The order of these conditions was counter balanced. Lastly,
participants were interviewed about their experience.

5.4

Participants

We invited 17 participants from the previous study (4 self-identifed
as female, 13 as male), only one participant (from the previous 18)
was excluded due to low agency score on the previous study. This
study occurred weeks after the previous one.

5.5

Results

We collected a total of 510 trials for pre-RT and 1020 for post-RT,
for each conditions, totalling 1530 data points. Figure 7 depicts theraw reaction times for each condition. As expected, we observedthat the measured reaction time was shorter during EMS session
for both fast-EMS and agency-EMS condition, in contrast, the measured reaction time was longer in the late-EMS condition. The mainquestion is whether there is a signifcant increase in post-RT thatis dependent on agency, which will analyze next.
Note that before analyzing data, we excluded outliers. We removed data points with reaction time less than 100 ms (accidental
activation of the touch sensor) or over 300ms (distracted participant). In total, we fltered 7% data from all data. Since the changeof session may cause distraction, we also excluded frst two sample
data points from each session.
Furthermore, we confrmed that there was no session order efectthroughout the study. We did not observed a decrease the reaction
time over our study, since no correlation between the study orderand the baseline reaction time on each day (R2 < 0.0001). We also
confrmed that there was no after efect over the each sessions,since we found no correlation between the gain in the reaction timewithin study session and the change in base reaction time between
sessions (R2 = 0.146).

5.6

Analysis of the accelerated reaction time

Since the reaction time varies with participants and their conditionin each day, we focus on the gain in reaction time after EMS session in each participant and each study session, i.e., a participant’s
post-RT - pre-RT. We depict this in Figure 8 denoting how eachparticipant’s reaction time (median) changed after EMS session for
all conditions.
fast-EMS

agency-EMS

late-EMS

Reaction time (ms)

5.3

PRE

POST

PRE

POST

PRE

POST

Figure 8: Changes in pre-RT (reaction time before training,
without EMS) and post-RT (after training, also without EMS),
for all three conditions. Colored data points represent thediferent participants.

To test whether the three EMS conditions led to diferential gains
in reaction times, we analyzed the gain in reaction time for these
conditions by taking in the data from the two post-EMS blocks(Figure 9). Since no signifcant violation of normality was foundin any data in median reaction times across participants (ShapiroWilk Test), we used parametric methods to evaluate a signifcanceof statistical comparisons.
First, we performed one-sample t-test between the gain of median reaction times in each EMS condition and 0 ms to check thevalid gain of reaction time. p-value was adjusted by the Bonferroni
method. A signifcant gain was found in the agency-EMS condition(t 16 = 4.47, p = 0.0011). However, no gain was found for either the
fast-EMS condition (t 16 = 2.16, p = 0.139) or the late-EMS condition(t 16 = -0.63, p = 1.0 ). Second, a one-way repeated ANOVA on thePreserving Agency During Electrical Muscle Stimulation Training Speeds up Reaction Time Directly Afer Removing EMS

Reaction time gain (ms)gains indicated that the gains were signifcantly diferent among
the conditions (F 2,32 = 7.06, p = 0.002). Post-hoc analysis using
Tukey method showed a signifcant diference in mean gain of reaction time between agency-EMS and late-EMS condition (p<.01). In
contrast, other combinations of condition were not signifcant(fastEMS: M = 3.88, SD. = 7.41, agency-EMS:M = 8.09, SD. = 7.46, lateEMS:M = -0.91, SD. = 5.99). Collectively, participants’ reaction times
were kept accelerated after EMS-actuated training that involves
the sense of agency. These results are in accord with our main
hypothesis: retaining agency during training led to a moreefective motor adaptation after EMS training. In other words,
only the agency-EMS condition revealed a signifcant diference
from the baseline, indicating that only agency-EMS had an efectof the motor adaptation after the participants removed the EMS
device.

*** p = .001

fast-EMS

agency-EMS

late-EMS

Figure 9: Gain in reaction time (in ms) for all EMS conditions. Colored plots depict a participant’s median gain of reaction time from pre-session (before training, without EMS)
to post-session (after training, also without EMS). The blacksolid plot depicts average gain across all participants.

5.7

Qualitative results

We here describe the qualitative aspect of our study from postinterviews with participants. We structured each interview aroundthree key questions, which were asked regarding each study condition: (1) "How did you feel in the trials?"; (2) "Did you feel any
change in your behavior between start and end of this study?"; and,(3) "Did you feel in control of your actions in the trials?". These
questions were used to initiate the conversation, often participants
added more observations, which we present below.
First, in late-EMS condition, we observed two types of reactions
from participants, both expected. In some situations, participants
did not recognize the EMS sensation during the tapping action, as
they mentioned "I was not confdent to have stimulation in this[EMS] session"(P5) and "I did not feel the [EMS] feeling at all" (P7).
Yet, in other trials participants, were certain about their sense ofagency of the tapping action: "I felt EMS stimulation but I moved
my fnger completely by my self" (P5), "I clearly felt that EMS
stimulation came after my movement " (P7). Either way, they wereconfdent that they touched the sensor by themselves. Moreover,most stated that, similarly to P13, "I didn’t fell any change in myreaction time".

CHI ’21, May 8–13, 2021, Yokohama, Japan

In fast-EMS condition, almost all participants reported that theyfelt some sort of EMS impulse much earlier than their own movement. They unlikely felt any agency, as we observed many comments such as "[EMS] it was really fast, I didn’t feel that I touched
it by myself (P14)", "At the moment when I found the light is on, myfnger fnished the touch motion (P10)", and "I felt that my fnger
was completely actuated by EMS" (P8). Interestingly, three participants explicitly mentioned negative emotional valence connected
to a loss of motivation, such as "I found catching up the speed of
EMS [fast condition] is impossible, therefore I wanted to give up
for the touch task" (P13), and even "I lose my motivation to moveby myself because I know EMS will exceed my speed (P4)". These
comments indicate that too much assistance is not benefcial. Thisis corroborated by research in motor learning [34, 36].
Conversely, in the agency-EMS condition, participants described a more integrated feeling of movement such as "I felt goodtiming" (P11), more specifcally "EMS actuate me during [my] own
touch" (P9). A reminder that while they reported a synchronizedtiming with EMS and self motion, the moment of actual EMS impulse was earlier then they do. In this view, this comment represents
the internal feeling of EMS ; "It feeling like EMS helps me in righttime between my intention and my movement"(P1). Other comments also aligned with the perceived sense of agency as "withthis one [agency-EMS], I felt that I could touch faster even with
my own touch, it was positive for me" (P11, and similarly P5). We
observed analogous comments from other participants such as "Iknow EMS was triggered when the LED is on, but still I felt mycontrol"(P4). Those observations are also consistent with previous
research [19]. This further indicated that our agency-EMS with 40
ms of preemptive gain successfully preserved a partial sense ofagency even with EMS acceleration. We also noted a more positive
emotional valence relating to motivation, such as "I could more
focus on the task (...) gives me motivation for better performance"(P11).

6DISCUSSION OF OUR STUDY’S
LIMITATIONS

Our study revealed that one’s reaction time shortened after the
EMS training session in which participants’ sense of agency on
their action was preserved (so called preemptive-EMS). However,for the sake of completeness and for assisting future researchers tobuild on our work, we discuss our study’s limitations.

6.1

EMS-specifc

First, we focused on using EMS as the force feedback device thatprovided the "accelerated" reaction-time experience. We chose EMS
since it allowed us to actuate the user rapidly and safely at speeds
faster than the user’s own reaction time. Furthermore, the electrodesof EMS do not interfere by covering the user’s fngers (as mostmechanically actuated devices do), and EMS is a emergent area in
HCI, which appears to many researchers as a promising approach inminiaturization of haptic actuation [23, 24, 26, 27]. However, otherforce-feedback devices such as exoskeletons are also promising
for movement-assistance and rehabilitation. Therefore, an open
question is whether one should extend our fndings to exoskeleton
and other haptic devices; we believe that warrants future work.

CHI ’21, May 8–13, 2021, Yokohama, Japan

6.2

Why 8ms of speedup is actually a lot

In our study, the average acceleration gain of reaction time in 17
participants was about 8 ms on a grand average. Here, we would
like emphasize two aspects: (1) the duration of the study sessionthat induced the acceleration was very short yet it still was enoughto trigger the speedup efect. Previous research reported that three
weeks of long-term training accelerate the reaction time approx.
20 ms, and its acceleration would last three weeks [1, 2]. On contrast
in our case, we were able to observe accelerations with only 30 or
60 EMS trials in agency-EMS condition; therefore, it is unsurprisingthat we observed less than the 20 ms seen by [1, 2]. (2) 8 ms is not
small speedup, in professional sports (baseball, tennis, etc) or otheractivities that require very fast movements, 8 ms is considerable,i.e., in a fast tennis serve the ball moves 0.5 meters in a mere 8 ms,
which means if the player cannot react 8 ms faster they would havecompletely missed returning a serve 2 .

6.3

Training period

There are studies that demonstrate how repeated sessions (longer
training) consolidates the learning efect [2]. In this view, we also
expect to enhance and consolidate the efect of acceleration byrepeatedly performing our EMS learning process for a longer periodof time.

7

Kasahara et al.

APPLICATIONS OF OUR FINDINGSWe envision that researchers and practitioners might apply ourfndings to interfaces where short-term accelerations are useful andthe interface does not require predicting complex user intentions.
As such, we now illustrate the applicability of our fndings by meansof two examples, both of which provide the user with short-term
benefts without requiring decision-making. These are useful for
researchers working on haptic interfaces or other interactive use
cases that leverage EMS to provide a speedup of the users’ reactiontime.
1. Speedups for sports requiring fast-reactions. One of themost exciting applications of our work is to take our fndings out of
the lab and into user’s body as they play/perform/train for sportsthat require fast-reactions. In Figure 10 (b) we depict this at theexample of a user who trains for sprint runs by using a wearable
EMS device on their legs (inspired by [45]), which assists the inretaining the speed-up of the starting trigger reaction time.
2. Power-ups that speed up the user, not their video-gamecharacter. Furthermore, the most intriguing and exciting of ourfndings is that our approach provides the experience of boosting
one’s own reaction time even if the context of application notjust ’training’. Figure 10 depicts the example using our fndings totransform the experience of playing a frst person shooter game
(games where players shoot targets as fast as possible). Here, a user
can collect a "speedup power-up" that, rather than just making theiravatars or rife shoot faster, it makes the user shoot faster by meansof preemptive EMS; literally accelerating the user. As a beneft, aftercollecting multiple of these power-ups, which act as a training EMS
session, the user’s own reaction time must get faster–as shown in
our study.
2 https://en.wikipedia.org/wiki/Fastest_recorded_tennis_servesab!

Electrodes

Electrodes

Figure 10: Two applications. (a) In this video-game, the user
collects a "power-up" that instead of making their avatar
shoot faster, it makes the user’s own body shoot faster using
EMS speed-ups. The power-up has a lasting efect because
after the EMS training, the user still benefts from an accelerated reaction time. (b) This user trains for sprint runs witha wearable EMS device on their legs, which assists them inretaining the speedup for the starting trigger reaction time.

8

CONCLUSION

We demonstrated that it is possible to accelerate one’s reaction
time, by means of muscle stimulation, even after the removing the
EMS device and its electrodes. In our study, we measured a user’s
reaction time before and after experiencing EMS in a reaction time
experiment, in which participants were asked to tap as soon as
they saw an LED lighting up in three EMS training conditions: (1)fast-EMS, the electrical impulses were synced with the LED; (2)agency-EMS, which made 40ms faster than the participant’s own
reaction time, thus and preserving their partial sense of agency;
and, (3) late-EMS: the impulse was delivered after the participant’s
own reaction time.
Our study revealed that participants’ reaction time was signifcantly reduced by approximately 8ms (up to 20ms) in agency-EMS
condition, even after removing the device. Our results suggest thatthe sense of agency plays a crucial role in the adaptation process
for acceleration of reaction time.
As for future work, we expect that researchers might expand ourfndings to investigate how agency plays a role in more complex
situations where users fnd themselves accelerated by means of
EMS, yet, are still able to make decisions–a crucial element that we
did not investigate in this paper.

ACKNOWLEDGMENTS
We would like to thank Daisuke Tajima for his advice on the statistical analysis. This work was supported by JST Moonshot R&D
Program (JPMJMS2013), JSPS KAKENHI (19H01041 and 20H05715)
and Grant-in-Aid for JSPS Research Fellow (JP16J03777). This work
is supported in part by NSF grant 2047189. Any opinions, fndings,
and conclusions or recommendations expressed in this material arethose of the authors and do not necessarily refect the views of any
funding agencies.

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