Proceedings of ISon 2013, 4th Interactive Sonification Workshop, Fraunhofer IIS, Erlangen, Germany, December 10, 2013

THE EFFECTIVENESS OF AUDITORY BIOFEEDBACK ON A TRACKING TASK FOR
ANKLE JOINT MOVEMENTS IN REHABILITATION
Masaki Matsubara1
1

Hideki Kadone1

Masaki Iguchi2

Hiroko Terasawa1,3

2
University of Tsukuba
Tsukuba University of Technology
11-2, Kasuga, Tsukuba, Ibaraki 305-8550 Japan
masaki@slis.tsukuba.ac.jp

ABSTRACTIn the field of physical rehabilitation, fall-prevention programs to
improve balance such as bedside ankle motor exercise have beenof great importance. Conventional studies indicate that auditory
biofeedback can improve tracking movements. In this paper, weinvestigated the difference in effectiveness between visual and auditory biofeedback during dorsi- and plantarflexion (movement which
decreases and increases the angle of ankle) specifically in a tracking exercise. Patients were asked to dorsi- and plantar flex theirankle according to the reference movement. To increase patients’awareness and recognition of lower limb movement, we implemented an interactive sonification system that translated the ankle
angle to improve their understanding of movement, and compared
the auditory and visual biofeedback characteristics. In this study,
we investigated the effects using the following three evaluation criteria: position controllability, timing controllability, and subjective
understandability. The experimental results showed that the motor performance of tracking movements with auditory biofeedback(ABF) was not significantly inferior to that with visual biofeedback (VBF) in the scope of rehabilitation exercise. Our results
suggest future applications of ABF for rehabilitative exercise of
bedridden patients and blind patients for whom VBF cannot beapplied.
1. INTRODUCTION
Along with the population aging, the number of elderly patients
who stumble or fall in their everyday movement is increasing. Injury caused by falls can severely decrease independence and quality of life. Even without an actual injury, fear of falling after afall incident restricts an elderly patient’s daily activities. Thus,
fall prevention programs to improve balance such as bedside ankle motor exercise1 have been of great importance in the field ofphysical rehabilitation [1]. Movements in these motor exercises,
are initially instructed by physical therapists through verbal cuesor passive movement, and then patients practiced on their own.
However, these movements may not be reproduced correctly inthe absence of physiotherapists because: (1) motor learning in the
short instruction time is difficult for patients, and (2) patients with
nervous-system damage may have problems in their somatosensory sensation and thus difficulty in sensing movements of thelimbs. In particular, during the chronic phase rehabilitation, patients need to practice their motor task at home and have only alimited opportunity to be assessed by physical therapists.

3

Kenji Suzuki1,3

JST PRESTO

It would be expected that biofeedback (visual, auditory and/or
haptic an informative presentation mapped in real-time from internal biological signals to augment awareness of them) [2, 3] improves the motor performance of patients, and visual biofeedback
is most commonly used among the biofeedback modalities. However, visual biofeedback is not appropriate for patients with limited upper-body mobility to perform bedside exercises at home or
hospital bedrooms because visual displays require postural challenges such as sitting. Former studies have suggested that auditory
biofeedback improves motor performances not only in blind patients [4], but also in healthy people [5, 6, 7, 8]. Conventional studies [9] indicate that auditory biofeedback can improve patients’
tracking movements. However other studies shows that visual
biofeedback also can support learning and improve movement [10,11]. Thus, we need to investigate the difference in effectivenessbetween visual and auditory biofeedback.
In this paper, we investigated the differences in effectivenessof visual and auditory biofeedback during dorsi- and plantarflexion (movement that decreases and increases the angle of ankle)
especially in tracking exercises. In this exercise, participants wereasked to move their ankle according to the reference movement. To
compare the characteristics between auditory and visual biofeedback, we implemented interactive sonification and visualization
system that translate the angle of the ankle to improve participants
understanding of movements. We applied this method to healthy
participants to explore the future possibility of this application topatients.

Figure 1: A picture of the experimental set-up and instrumentation. Participants were asked to perform voluntary ankle dorsiplantarflexion movements.

1 (i.e., motor exercise a patient conducts by oneself while still in the bed

during recovery from illness).

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2. METHODS
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2.1. Participants and general experiment design

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Six healthy volunteers (5 males, 1 female; aged 22–31) participated in the study. All gave their informed consent to the experimental procedure. Each participant was asked to perform a tracking motor task of the ankle joint repetitively under two conditions:visual biofeedback (VBF) and auditory biofeedback (ABF). Prior
to the start of each task, enough time was spent for practice under
the same biofeedback condition used in the following motor task.
Figure 1 gives a general description of the experimental set-up.

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2.2. Instrumentation
In the study, sitting participants were asked to perform voluntaryright ankle dorsi-plantarflexion movements. The angles of the hipand knee joints were 120 and 160 degrees, respectively (Figure1). In order to limit the degree of freedom in movement direction,
participants wore an ankle-foot orthosis (AFO) (TO-230R, Tokuda
Ortho Tech, Japan) (Figure 2). The AFO is commonly used forankle rehabilitation [12, 13, 14]. The angle of the ankle joint wasmeasured by a goniometer (P-00246, Supertech Electronic Co.,
Ltd., Taiwan) and sent to a computer via Bluetooth serial communication. During the movements, participants were asked toobserve a computer screen positioned in front of them and listen
to sounds from the headphones (MDR-CD780, Sony Ltd., Japan).

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time (sec)Figure 3: The 6 reference passive movements were recorded withthe help of a physical therapist. Each motor task consisted of 4–7
movements with different speeds and the total duration was 60–70
sec. Each movement took 6–10 sec. The neutral stand position isa degree of zero. A positive angle indicates dorsiflexion.

2.3.1. Practice session
Prior to performing the task, the participants practiced enough tobe able to move their ankle and track the reference movement easily. To learn the relationship between the ankle angle and graph/sound representations, each participant was given up to 10 minutes
non-tracking training at the beginning of the practice. During thetraining, the participant could observe the display or listen to thesound while changing the angle of his or her ankle. After the training of two biofeedback conditions, the motor tracking tasks were
performed. Figure 4 shows an example of movement tracking. A
practice reference movement for the actual task was also recorded.
Figure 2: A picture of the ankle-foot orthosis (AFO). The angle ofankle joint was measured by a goniometer and sent to a PC via
Bluetooth serial communication.

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2.3. Protocol
Each participant perform in a 30-minutes session of a lower-limb
visuo- or audio-motor tracking task. A physical therapist moved
the participant’s ankle with AFO to record six reference movements (Figure 3)2 . Each motor task consisted of a combination of
4–7 movements with different speeds and the total duration was
60–70 sec. Each movement was about 25 degrees of dorsi- and30 degrees of plantarflexion, and took 6–10 sec. The session consisted of a practice and 20 minutes performing task under two conditions. The order of the two conditions was alternated with-ineach movement and randomized across participants. After finishing the motor task, we asked participants to rate the level of understanding how to perform the tasks.

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time (sec)Figure 4: A plot of single-movement tracking (the reference is an
8 sec. movement).

2 reference data are available in online (see Appendix B)

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Proceedings of ISon 2013, 4th Interactive Sonification Workshop, Fraunhofer IIS, Erlangen, Germany, December 10, 2013

ankle angle (degree)

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time (sec)Figure 5: Parameter mapping between the ankle angle and thesound frequency.

Figure 6: An example of experimental results in a tracking taskwith VBF and ABF.

2.3.2. Visual biofeedback (VBF) and visuo-motor task
to the reference movement from the left ear, and the sounds that
corresponded to their movement from the right ear. The soundfrequency was varied and corresponded to movement in real-time.

Visual biofeedback (VBF) was conducted as follows: The position of the ankle joint (measured by the goniometer in 10 Hz) was
represented as a cursor point on the computer screen. The cursor moved automatically from left to right. Participants were able
to control the up-and-down movement of the cursor by performing ankle dorsi- and plantarflexions. During dorsiflexion, the cursor moved upward, while during plantarflexion the cursor moved
downward. Following Perez et. al. [10], a whole reference movement was statically plotted as a line graph before participants started
the performance. In the visuo-motor tracking task, the participants
were asked to track the reference movement by moving the cursor
so that it tracked the line graph.
We also investigated bar plotting and real-time line plotting[9] for reference representation in the pilot experiment; however,the performance did not show a major difference from the above
condition. Since the line-graph presentation of biological signals
are commonly used in rehabilitation, we adopted this presentation
for the task.

2.3.4. Subjective understandability rating
After finishing the motor tasks, we asked participants to rate thelevel of understanding how to perform the tasks. The ratings wereas follows: 1 = very difficult, 2 = difficult, 3 = ordinary, 4 = easy
and 5 = very easy. Also participants were asked to give free comments about difficulty, enjoyment, and fatigue.
2.4. Angle recording
The angle of the ankle was caputured through the electrical goniometer and recorded (10 Hz) on the computer using MATLAB(version 8.2.0.701, R2013b, Mathworks, Natick, MA, USA) for
later analysis.
2.5. Data analysis

2.3.3. Auditory biofeedback (ABF) and audio-motor task

To measure the motor performance, the error was calculated as thedifference between the reference and the actual movement. The
differences of timing and position of the ankle joint at the peaks(maximum dorsi- and plantarflexion) were calculated as the error.
These peaks were calculated with MATLAB findpeaks function,
which finds the local maximum or minimum point in each movement. A mean absolute error (MAE) was obtained for each movement, which is defined as the following equation:

Auditory biofeedback (ABF) was conducted as follows: in addition to the VBF mentioned above, the angle of the ankle joint
was captured and sonified to the sound. We adopted a parameter mapping sonification method [16]. As described by a previous
study [8], the frequency of the sinusoidal that corresponding to
the participant’s movement was continuously varied. In this study
we set the maximum dorsiflexion to 500 Hz and the maximum
plantarflexion to 250 Hz. During dorsiflexion, the frequency increased, while during plantarflexion the frequency decreased (Figure 5). We also implemented some auditory icons like a fingersnapping sound, which corresponded to the maximum dorsi- andplantarflexion (More details are described in Appendix A).
In the audio-motor tracking task, paricipants were asked to
track the reference movement by listening to the sonified sound.
As in the Sussman’s method [15], in order to increase separated
recognition between sounds of reference and participant movements, the two sounds are panned to left and right, and their timbres are pulse (reference) and sinusoidal (participant), respectively.
Thus, participants could easily hear the sounds that corresponded

n

MAE =

1
| fi
n i=1

n

yi | =

1|ei | ,
n i=1

(1)

where fi is an actual movement value and yi is a reference value.
Error ei is calculated by the difference of the actual movements
and the reference movements.
In order to investigate how effective these two biofeedback
conditions are, we calculated the average and variance of MAE
within participants across biofeedback type. A paired Student’s T
test was performed on significant comparisons (with a significancelevel of 0.05).

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timing error

**!

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0.8
p < 0.01!

Mean Absolute Error (sec)!

Mean Absolute Error (degree)!

position error

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ABF

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ABF

Figure 7: The bar raph demonstrates average and standard deviation of the mean absolute error of ankle-angle positioning in the
tracking tasks with VBF or ABF (n = 6).

Figure 8: The bar graph demonstrates average and standard deviation of the mean absolute error of ankle-movement timing in the
tracking tasks with VBF or ABF (n = 6).

3. RESULTS

4. DISCUSSION

In this study, we compared the effectiveness of VBF and ABF
with the following three evaluation criteria: position controllability, timing controllability, and subjective understandability. Figure
6 shows an example of the experimental results in the tracking taskwith VBF and ABF.

The timing controllability showed a significant difference between
ABF and VBF, in which ABF led to a larger delay than VBF
behind the reference movement. However, the delay in timing
was 0.64 sec on average. Since sampling frequency of ankle signal is 10 Hz, the consistent delay occurs up to 0.1 sec in bothconditions. The consistent delay is possible to be reduced whensampling frequency becomes higher. In physical rehabilitation,a training method are designed depending on what goals the patients would like to accomplish. For example, in an activity suchas overarm throwing, skilled throwers can release a ball with anaccuracy of a few milliseconds [18]. If a training task requires
precise timing, the pitch-modulation sonification method we usedin the present study is probably not the best choice. Although
the statistical analysis indicated that both the timing and angle
errors were greater for the auditory biofeedback compared withthe visual biofeedback, the angle of error was very close and all
the participants were able to track the target with just ABF only.
This means that auditory biofeedback can be used in rehabilitation where repetitive movements are required. Repetitive movements are often used in rehabilitation, for example, when a patientneeds to learn a new motor task. Studies have shown that a newtask can be learned with visual biofeedback, but whether we canlearn a new task through auditory biofeedback would be an interesting topic for further research. Sufficiently appropriate movements were produced under both conditions.
Subjective understandability showed a preference for ABF over
VBF, though it was not statistically significant. This was due to theclose correspondence between the somatosensory and sound, asreported by many participants. Some participants commented that
ABF was more comfortable than VBF because ABF did not cause
eye strain when looking at the display. ABF reduces eye fatigue
and allows for more variety of positions, which is important forrehabilitation. Some participants commented that they did not feel
physical fatigue under both conditions, but felt mental fatigue in
VBF. On the other hand, a longer practice session was indispensable for ABF especially participant without professional musicaltraining, because the task could be more challenging when the participants’ movements got away from the reference movements.
Modifying the sonification design could increase the effective-

3.1. Position controllability
Figure 7 shows the average and standard deviation of the ankleangle positioning MAE in VBF and ABF. There is a significant
difference between VBF and ABF (p = 0.00389). The maximum
MAE position in VBF was 0.9 degree, and the maximum MAE
position in ABF was 1 degree. The total degree of movement in
the task was about 55 degrees, thus these errors were less than 2%
degrees of the movement.
3.2. Timing controllability
Figure 8 shows the average and standard deviation of the anklemovement timing MAE in VBF and ABF. There is a significant
difference between VBF and ABF (p = 0.00097). However, theaverage of MAE timing in VBF was 0.29 sec, and the average of
MAE timing in ABF was 0.64 sec. The duration of each movementin the task was more than 6 sec, thus these errors comprised lessthan about 10% of the total duration.
3.3. Subjective understandability
To achieve effective biofeedback, it should be easy for users tounderstand how to perform the task. Therefore, a subjective understandability, which has been shown to be important as an objective measure [17], was included in this study. We found no
significant difference between VBF and ABF (p = 0.2955). As
for the difficulty of the tasks, some participants reported that VBF
was easier compared with ABF but there was no significant difference between them. In the comments, some participants reported
that they enjoyed both ABF and VBF tasks like they were playing
video games.

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this study has the potential not only for physical rehabilitation, butalso for health care and playful rehabilitation for children.

Subjective understandability
5!"#$%&'(%)*+',-!

6. ACKNOWLEDGEMENTS
4This work was funded by JST PRESTO. We thank T. Ohba forhelp in implementation of the orthosis, A. Maruyama for help inrecording the reference movements, and Dr. C. Miyama, Dr. A.
Morishima and Dr. T. Kitahara for kind discussion. We would liketo thank everyone who kindly participated in our experiment.

3

2

Appendix A. SOUND SYNTHESIS
1VBF

Sound generation and parameter control is realized with Supercollider 3, an open source package for real-time audio synthesis
programming available from http://www.audiosynth.com.

ABF

Figure 9: Bar graph demonstrates average and standard deviationof subjective understandabilty in tracking task between VBF andABF (n=6). (The ratings were as follows: 1 = very difficult, 2 =difficult, 3 = ordinary, 4 = easy and 5 = very easy)
ness of biofeedback in rehabilitation yet the design should carefully reflect purpose, scope, expected functionality, and user capability for the task to be conducted. The sonification method employed in this study varied the pitch corresponding to the angleof the ankle with minimal data preprocessing. In general, the degree of data preprocessing defines the sonification as being moreanalogical or more symbolic [19]. When data preprocessing is
minimal, the sonification is more analogical, reflecting the original data more directly and continuously. Analogical sonification
is more suitable for exploratory observation of data. Meanwhile,when data preprocessing is heavy, the sonification becomes more
symbolic, reflecting the intended perspective of the data analysis.
Symbolic sonification is more suitable for the observation of predefined characteristics, such as alarming of an electrocardiogram,
auditory icon, earcon, etc. Of these two extremes, our current approach is more analogical, allowing broad applications independent of the type of motor task. With this kind of analogical sonification, users can explore characteristics of their own movements,
and reflect an understanding in realizing/reproducing movements.
Indeed, there is a successfully applied analogical sonification in
the Olympic rower training program, reflecting motion-sensor data
onto the pitch of the synthesized sound [8]. Following Tsubouchi
et. al. [20], we also need to investigate the comparison among
other analogical sonification methods.

A.1. Synthesizer Definition
SynthDef “Clip” is an auditory icon that indicates the maximum
dorsi- or plantarflexion. The sound file (snap.wav) was downloaded from Freesound.org3 . SynthDef “participantABF” and SynthDef “referenceABF” are the auditory biofeedback synthesizer
definition of participant movement or reference movement. Thesesound timbres are sinusoidal or low-pass-filtered pulse waves. Bothsounds employ the reverberation effect.
Listing 1: Synthesizer Definition
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SynthDef (" Clip ",{arg amp = 0.8, speed = 1;
a = PlayBuf .ar(1, Buffer .read(s, " sounds /snap.wav "),speed , doneAction :2);
OffsetOut .ar(0, (a * amp ). dup );}). load;

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SynthDef (" participantABF ", {arg freq = 250, amp = 0.8, pan = 1;
var src = SinOsc .ar(Lag.kr(freq ,1)) * amp;
OffsetOut .ar(0, FreeVerb .ar(Pan2.ar(src ,pan ) ,0.4 ,0.3 ,0.5));}). load;

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SynthDef (" referenceABF ", {arg freq = 250, amp = 0.8, pan = -1;
var src = Pulse.ar(Lag.kr(freq ,1)) * amp;
OffsetOut .ar(0, FreeVerb .ar(Pan2.ar(LPF.ar(src ,400) , pan ) ,0.4 ,0.3 ,0.5));}). load;

A.2. Open Sound Control Function

5. CONCLUSION
In this paper, we have examined the effectiveness of auditory biofeedback in tracking a motor task for ankle joint rehabilitation. The experimental results showed that motor performance of the tracking
movement with ABF was not significantly inferior to that of VBF
in the scope of rehabilitation exercise. The study suggests futureapplications of ABF for rehabilitative exercise of bedridden andblind patients whose visual deprivation prevents VBF. Our future
perspective is to explore more engaging sonification method on the1aesthetic aspect, such as more selections of sound effects, introduc- 2
ing musical contents in the interaction, etc. We also plan to apply 3
the method to patients under physiotherapeutic treatment as well 45
as blind and elderly patients. Combined with visual and/or haptic
biofeedback, the technology of auditory biofeedback described in

Auditory biofeedback is achieved with Open Sound Control (OSC)
message. The OSC function, which processes the OSC message,
is defined as follows. The OSC functions generate the sinusoidal
or pulse wave and their frequency changing corresponds to movement. The difference between the two functions below is that thefunction for participant movement synthesizes the auditory icon.
Listing 2: OSC function
OSCFunc ({| msg , time , addr , recvPort |var angle = msg [1], freq , amp;

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if ((( angle > ˜max )&&(˜ flag != 1)) ,{s. sendMsg ("/ s_new "," Clip",node ,0 ,0 ," speed " ,1);
3 http://www.freesound.org/people/OwlStorm/sounds/151214/

Proceedings of ISon 2013, 4th Interactive Sonification Workshop, Fraunhofer IIS, Erlangen, Germany, December 10, 2013

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˜flag =1;});if ((( angle < ˜min )&&(˜ flag != -1)),{s. sendMsg ("/ s_new "," Clip",node ,0,0," speed " ,0.9);
˜flag = -1;});[7]

L. Chiari, et al., “Audio-biofeedback for balance improvement: an accelerometry-based system,” IEEE Transactions
on Biomedical Engineering, Vol. 52, No. 12, pp. 2108–2111,
2005.

[8]

N. Schaffert, K. Mattes and A. Effenberg, “A sound design for acoustic feedback in elite sports,” Auditory Display,
Springer Lecture Notes in Computer Science, pp. 143–165,
2010.

[9]

G. Rosati, F. Oscari, S. Spagnol, F. Avanzini and S. Masiero,“Effect of task-related continuous auditory feedback during
learning of tracking motion exercises,” Journal of NeuroEngineering and Rehabilitation, Vol. 9, No. 79, 2012.

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freq = 250 * (2 ** (( angle - ˜min) / (˜ max - ˜min )));
amp = 0.9 - ((( angle - ˜min) / (˜ max - ˜min )) * 0.2);
if(freq >500 , {freq =500}); if(freq <250 , {freq =250});

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s. sendMsg ("/ n_set ",˜ parNodeID ," freq",freq ," amp",amp );}, ’/ participant ’, nil
);

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OSCFunc ({| msg , time , addr , recvPort |var angle = msg [1], freq , amp;

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freq = 250 * (2 ** (( angle - ˜min) / (˜ max - ˜min )));
amp = 0.9 - ((( angle - ˜min) / (˜ max - ˜min )) * 0.2);
if(freq >500 , {freq =500}); if(freq <250 , {freq =250});[10] M. A. Perez and J. L .Jensen, “Changes in corticospinal drive
to spinal motoneurones following visuo-motor skill learningin humans,” Journal of Physiology, Vol. 573, No. 3, pp. 843–
855, Physiological Society, 2006.

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s. sendMsg ("/ n_set ",˜ refNodeID ," freq",freq ," amp",amp );}, ’/reference ’, nil);

A.3. Mappings• A local variable angle represents the ankle joint angle that
continuously recieved the OSC message (via Bluetooth) fromthe lower limb orthosis through the goniometer.
• Local variables freq and amp represent the sound parameter (frequency and amplitude) of the auditory biofeedback
sounds.
• A global variable max (maximum dorsiflexion) is stored 20
and min (maximum plantarflexion) is stored -30.
• A global variable flag shows whether the participant’s movement reaches the maximum and minimum angle.
Appendix B. SUPPLEMENTARY DATASound files and supplementary data associated with this article canbe found in the online version, at https://db.tt/EtaC5SZd .
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