Facilitative Exercise for Surface Myoelectric Activity Using Robot Arm Control System - Training Scheme with Gradually Increasing Difficulty Level

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https://doi.org/10.20965/jrm.2021.p0851

                                                                                               Facilitative Exercise for Surface Myoelectric Activity

Paper:

      Facilitative Exercise for Surface Myoelectric Activity
                Using Robot Arm Control System
 – Training Scheme with Gradually Increasing Difficulty Level –
               Ryota Hayashi∗, Naoki Shimoda∗∗ , Tetsuya Kinugasa∗ , and Koji Yoshida∗
                              ∗ Department   of Mechanical Systems Engineering, Okayama University of Science
                                                1-1 Ridai-cho, Kita-ku, Okayama 700-0005, Japan
                                            E-mail: {r hayashi, kinugasa, k yoshida}@mech.ous.ac.jp
                                       ∗∗ Graduate School of Engineering, Okayama University of Science

                                                1-1 Ridai-cho, Kita-ku, Okayama 700-0005, Japan
                                                           E-mail: t20tm04sn@ous.jp
                                              [Received January 20, 2021; accepted May 18, 2021]

Various control systems for robot arms using surface
myoelectric signals have been developed. Abundant
pattern-recognition techniques have been proposed to
predict human motion intent based on these signals.
However, it is laborious for users to train the voluntary
control of myoelectric signals using those systems. In
this research, we aim to develop a rehabilitation sup-
port system for hemiplegic upper limbs with a robot
arm controlled by surface myoelectric signals. In this
study, we construct a simple one-link robot arm that
is controlled by estimating the wrist motion from the                                      Fig. 1. Motor impulses from brain to muscles.
surface myoelectric signals on the forearm. We pro-
pose a training scheme with gradually increasing dif-
ficulty level for robot arm manipulation to evoke sur-
face myoelectric signals. Subsequently, we investigate
the possibility of facilitative exercise for the volun-                        science, it has been revealed that the effects of intensive
tary surface myoelectric activity of the desired muscles                       repetitions of facilitation exercises with voluntary move-
through trial experiments.                                                     ments on hemiplegic limbs are significantly greater than
                                                                               those of conventional rehabilitation exercises without vol-
                                                                               untary movements [5, 6]. Therefore, an appropriate train-
Keywords: myoelectric signal, facilitative exercise, re-                       ing method to achieve voluntary control of the SMESs
habilitation, robot arm, manipulation                                          may provide higher usability of control systems of robots
                                                                               using SMESs. In this study, we constructed a simple one-
                                                                               link robot arm that was controlled by estimating the wrist
                                                                               motion from SMESs on the forearm. We propose a train-
1. Introduction
                                                                               ing scheme for robot arm manipulation with gradually in-
   Various control systems have been developed for robots                      creasing difficulty level to evoke SMESs. Subsequently,
using surface myoelectric signals (SMESs) such as myo-                         we investigated the possibility of facilitative exercise for
electric prosthetic hands, and robotic rehabilitation sup-                     voluntary surface myoelectric activity of the desired mus-
port systems have been developed [1, 2]. To improve the                        cles through trial experiments.
usability of these systems, abundant myoelectric pattern
recognition techniques have been investigated to predict
human motion intents based on these signals [3]. How-                          2. SMESs of Hemiplegic Limb
ever, control schemes incorporating pattern recognition
techniques are affected by usability because of signal                            Movements of body parts are controlled by motor im-
stochasticity and transient changes [4]. In this study, our                    pulses (messages) from the brain through nerve pathways
goal is not to develop novel myoelectric pattern recogni-                      to muscles as shown in Fig. 1. During muscle activa-
tion techniques, but to develop schemes to evoke and fa-                       tion, SMESs can be measured. The amplitude of SMESs
cilitate voluntary SMES. In fact, humans have abilities to                     increases with the generated force. When evaluating a
acquire physical motor skills inherently. In rehabilitation                    power assist robot system, the amplitude of the SMESs is
                                                                               applied to assess the performance of the system. The low

Journal of Robotics and Mechatronics Vol.33 No.4, 2021                                                                                               851

                        © Fuji Technology Press Ltd. Creative Commons CC BY-ND: This is an Open Access article distributed under the terms of
                        the Creative Commons Attribution-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nd/4.0/).
Hayashi, R. et al.

               Fig. 2. Robot arm with servo motor.                          Fig. 4. Forearm constrained to lie on pedestal.

Fig. 3. Surface electrodes attached to skin on trainee’s forearm.

                                                                               Fig. 5. Configuration of training system.

amplitude of the SMESs during activation of the related
muscles indicates the good performance of the system [7].
   By contrast, when evaluating a rehabilitation exercise           tain threshold level, the reference angle changed clock-
for hemiplegic limbs in stroke patients, a high amplitude           wise at a rate proportional to the SMES intensity. Sub-
of the SMESs during the activation of the desired muscles           sequently, the robot arm rotated clockwise. By contrast,
indicates good exercise efficiency [8]. Similarly, the low          when the subject flexed his/her right wrist (palmar flex-
amplitude of the SMESs of the undesired muscles indi-               ion) and the SMES intensity of the flexor muscles ex-
cates good exercise efficiency. Because the nerve path-             ceeded a certain threshold, the reference angle changed
ways are damaged after a stroke, motor impulses from the            counterclockwise at a rate proportional to the SMES in-
brain are not transported to the desired muscles. There-            tensity. Subsequently, the robot arm rotated counterclock-
fore, the amplitude of the SMESs can be used to assess the          wise. However, when the SMES intensities of both the
efficiency of rehabilitation exercises for recovering motor         flexor and extensor muscles exceeded or did not exceed
function in hemiplegic limbs.                                       the threshold, the reference angle did not change. Con-
                                                                    sequently, the robot arm did not rotate. To maintain uni-
                                                                    form experimental conditions, the forearm of the subject
3. Training System with One-Link Robot Arm                          was constrained to lie on a pedestal with hook and loop
   Controlled Using SMESs                                           fastener bands as shown in Fig. 4, allowing the wrist to
                                                                    move freely.
   We constructed a simple one-link robot arm (1-DOF                   As shown in Fig. 5, the subject can train the robot arm
planar link, length: 0.15 m) with a servo motor (Maxon,             for manipulation using a system comprising the above-
90 W) and an encoder (OMRON, 2000 P/R), which was                   mentioned devices. The sampling time for all sensors and
controlled by simple proportional control such that its ro-         controller was 4 ms, and we used a simple moving aver-
tation angle would coincide with the reference angle. The           age of 10 sampled absolute values of the SMESs as the
reference angle of the robot arm was generated from the             intensity value of the SMES at each time. Prior to the
SMESs on the forearm of the subject (trainee) as shown in           training, we set the threshold value by assessing the data
Fig. 2. Two surface electrodes (Oisaka Electronic Equip-            of the SMESs obtained in the relaxed and strain states.
ment, ID2PAD) were attached to the skin on the fore-                We selected a threshold value that was slightly beyond
arm of the subject, as shown in Fig. 3. One detected                the intensity of the detected signals in the relaxed state to
the SMESs of the wrist extensor muscles, whereas the                avoid the effect of noise. When the SMES intensity of the
other detected those of the wrist flexor muscles. When the          desired muscles exceeded the threshold during the train-
subject extended his/her right wrist (dorsiflexion) and the         ing, the robot arm rotated at an angular velocity that was
SMES intensity of the extensor muscles exceeded a cer-              proportional to the intensity of the SMESs.

852                                                                  Journal of Robotics and Mechatronics Vol.33 No.4, 2021
Facilitative Exercise for Surface Myoelectric Activity

4. Facilitative Exercise for Voluntary Surface
   Myoelectric Activity
4.1. Training Task
   We established a training task for robot arm manipula-
tion. It is noteworthy that although the training system is
applicable for both the left and right wrists, we describe
the task based on the right wrist in the following.                                       (i) Arm angle
   Before commencing the training, the subject relaxed
his/her right wrist and the robot arm was set in the
3 o’clock direction (9 o’clock direction in the case of the
left wrist), where the rotational angle of the robot arm
was measured as 0◦ . When the robot arm rotated coun-
terclockwise (clockwise in the case of the left wrist), the
rotational angle of the robot arm was measured as a pos-
itive value. We set 45◦ and 135◦ as the two target angles
of the robot arm. During the training, the subject had to                          (ii) Intensity of flexor SMES
manipulate the robot arm to perform reciprocating rotary
motions rapidly between the two target angles in a limited
time of 40 s. We can evaluate the skill of the subject by
investigating the number of reciprocating rotary motions.

4.2. Facilitative Effect by Reducing Difficulty of
       Training Task
   To achieve the training task described above, the sub-                        (iii) Intensity of extensor SMES
ject must be able to control the voluntary SMESs of the             Fig. 6. Training experiment without added assistance.
desired muscles. However, some healthy subjects were
not adept at controlling voluntary SMESs [9, 10]. It is
difficult for stroke patients with hemiplegic arms to per-
form the training task, because motor impulses from the        able to rotate promptly to the target angle of 45◦ . In the
brain are not transported to the desired muscles.              training experiment without assistance, the subject could
   Hence, we incorporated assistance to perform the train-     not achieve more than two reciprocating rotary motions.
ing task easily, as follows. If the SMES intensity of the      This implies that it is difficult for the subject, who is a
desired muscles exceeds the threshold at least once when       beginner trainee, to reduce the SMES intensities of the
the rotational angle of the robot arm is one of the target     undesired muscles, particularly those of the extensor mus-
angles, then the reference angle of the robot arm changes      cles. After this training experiment without assistance, the
at a constant velocity until it crosses the other target an-   subject attempted another training experiment for the left
gle. Subsequently, the robot arm rotates to the other target   wrist by incorporating assistance. The thresholds for the
angle at a constant angular velocity via automatic control,    flexor and extensor SMESs were set at 0.1 V and 0.2 V,
despite the SMES intensity of the undesired muscles. Af-       respectively. The experimental results are presented in
ter the reference angle of the robot arm crosses the other     Fig. 7. The rotation angle of the robot arm and the in-
target angles, it stops at this target angle until the SMES    tensities of the flexor and extensor SMESs, are shown in
intensity of the next desired muscles exceeds the thresh-      Figs. 7(i), (ii), and (iii). In Fig. 7, t f k (k = 1, 2, . . .) and
old. This reduces the difficulty of the training task.         tek (k = 1, 2, . . .) denote the start times for the flexor and
   In a pilot study, a first-time beginner (right-handed       extensor motions, respectively. At the beginning of the
healthy young male: age 21 years) attempted to conduct a       flexor motion, once the intensity of the flexor SMESs of
training experiment for the left wrist without incorporat-     the desired muscles exceeded the threshold, the robot arm
ing assistance. The thresholds for the flexor and extensor     started rotating to a target angle of 135◦ at a constant an-
SMESs were set at 0.1 V and 0.2 V respectively. The ex-        gular velocity via automatic control, despite the intensity
perimental results are presented in Fig. 6. The rotation       of the extensor SMESs of the undesired muscles. In the
angle of the robot arm and the intensities of the flexor and   following extensor motion, the robot arm rotated symmet-
extensor SMESs are shown in Figs. 6(i), (ii), and (iii), re-   rically to the target angle of 45◦ . In the training exper-
spectively. At the beginning of the flexor motion, as both     iment with assistance, the subject successfully achieved
intensities of the flexor and extensor SMESs exceeded the      five reciprocating rotary motions. Although the subject
thresholds simultaneously, the robot arm could not rotate      did not acquire the desired skills for robot arm manipula-
promptly to the target angle of 135◦ . In the following ex-    tion, he/she managed to repeat the exercise for controlling
tensor motion, because the intensity of the flexor SMESs       voluntary SMESs in the training experiment by incorpo-
of the undesired muscles remained low, the robot arm was       rating assistance.

Journal of Robotics and Mechatronics Vol.33 No.4, 2021                                                                       853
Hayashi, R. et al.

                                                                   rotational angle of the robot arm is one of the tar-
                                                                   get angles, then the robot arm rotates to the other
                                                                   target angle at a constant angular velocity via auto-
                                                                   matic control. However, when the SMES intensity
                                                                   of the undesired muscles exceeds the threshold, the
                                                                   robot arm rotates at a reduced constant angular ve-
                                                                   locity via automatic control. Although the subject
                                                                   need not maintain the tension of both the flexor and
                              (i) Arm angle
                                                                   extensor muscles, he/she must release the tension of
                                                                   the undesired muscles during each one-way rotation
                                                                   of the robot arm. We assume that the subject can
                                                                   train the skill of releasing the tensions of the unde-
                                                                   sired muscles under the conditions of Level-2.
                                                                (Level-3): If the SMES intensity of the desired muscles
                                                                  exceeds the threshold for a short duration when the
                                                                  rotational angle of the robot arm is one of the target
                      (ii) Intensity of flexor SMES               angles, then the robot arm starts rotating to the other
                                                                  target angle at a constant angular velocity via auto-
                                                                  matic control. However, when the SMES intensity
                                                                  of the undesired muscles exceeds the threshold, then
                                                                  the robot arm rotates at a reduced constant angular
                                                                  velocity via automatic control. The subject need not
                                                                  maintain the tension of both the flexor and extensor
                                                                  muscles during the rotation of the robot arm; how-
                                                                  ever, he/she must maintain the tension of the desired
                     (iii) Intensity of extensor SMES             muscles for a short duration when the rotational an-
                                                                  gle of the robot arm is one of the target angles. Fur-
       Fig. 7. Training experiment with added assistance.
                                                                  thermore, he/she must release the tension of the un-
                                                                  desired muscles during each one-way rotation of the
                                                                  robot arm. We assume that the subject can acquire
5. Training Scheme with Gradually Increasing                      the skills for tensing the desired muscles for a cer-
   Difficulty Level                                               tain duration and releasing the tension of the unde-
                                                                  sired muscles.
5.1. Difficulty Levels of Training Task                         (Level-4): When the SMES intensity of the desired
   A low difficulty level of the training task will not al-       muscles exceeds the threshold, the robot arm rotates
low the subject to acquire the desired skills for robot arm       to the target angle at a constant angular velocity via
manipulation. Herein, we propose a training scheme for            automatic control, despite the SMES intensity of the
robot arm manipulation with gradually increasing diffi-           undesired muscles. The subject must maintain the
culty level to evoke voluntary SMESs. We define a plain           tension of the desired muscles during each one-way
condition without incorporating assistance as Level-7,            rotation of the robot arm. We assume that the subject
which is the most difficult level for the training task. Fur-     can acquire the skill for maintaining the tension of
thermore, we define the condition with assistance incor-          the desired muscles under the condition of Level-4.
porated as Level-1, which is the easiest level for the train-
ing task. Subsequently, we considered seven difficulty          (Level-5): When the SMES intensity of the desired
levels as follows.                                                muscles exceeds the threshold, the robot arm rotates
                                                                  to the target angle at a constant angular velocity via
  (Level-1): If the SMES intensity of the desired mus-            automatic control. However, when the SMES inten-
    cles exceeds the threshold at least once when the ro-         sity of the undesired muscles exceeds the threshold,
    tational angle of the robot arm is one of the target          the robot arm rotates at a reduced constant angu-
    angles, then the robot arm rotates to the other tar-          lar velocity via automatic control. The subject must
    get angle at a constant angular velocity via automatic        maintain the tension of the desired muscles during
    control, despite the SMES intensity of the undesired          each one-way rotation of the robot arm. We assume
    muscles. The subject need not maintain the tension            that the subject can acquire the skills for maintaining
    of both the flexor and extensor muscles during the            the tension of the desired muscles and releasing the
    rotation of the robot arm. This reduces the difficulty        tensions of the undesired muscles under the condi-
    of the training task.                                         tion of Level-5.
  (Level-2): If the SMES intensity of the desired mus-          (Level-6): When the SMES intensity of the desired
    cles exceeds the threshold at least once when the             muscles exceeds the threshold, the robot arm rotates

854                                                             Journal of Robotics and Mechatronics Vol.33 No.4, 2021
Facilitative Exercise for Surface Myoelectric Activity

     to the target angle at an angular velocity that is pro-
     portional to the SMES intensity. However, when the
     SMES intensity of the undesired muscles exceeds the
     threshold, the robot arm stops rotating. The subject
     must tense the desired muscles and release the ten-
     sions of the undesired muscles during each one-way
     rotation of the robot arm. We assume that the subject
     can acquire the skills for tensing the desired muscles
                                                                                          (i) Arm angle
     and releasing the tensions of the undesired muscles
     such that the robot arm rotates at a high angular ve-
     locity under the condition of Level-6.
  (Level-7): When the SMES intensity of the flexor mus-
    cles exceeds the threshold, the robot arm rotates to a
    target angle of 135◦ at an angular velocity that is pro-
    portional to the SMES intensity. By contrast, when
    the SMES intensity of the extensor muscles exceeds
    the threshold, the robot arm rotates to a target angle                         (ii) Intensity of flexor SMES
    of 45◦ at an angular velocity that is proportional to
    the SMES intensity. However, when the SMES in-
    tensities of both the flexor and extensor muscles ex-
    ceed or do not exceed the threshold simultaneously,
    the robot arm does not rotate. This is the plain con-
    dition without incorporating assistance.
  As described above, the difficulty of the training task
increases from Level-1 to Level-7.                                               (iii) Intensity of extensor SMES

                                                                  Fig. 8. Experimental result for condition of Level-7 before
5.2. Changing Condition of Difficulty Level                       training is performed for evaluation.
   The manner by which the difficulty level is to be
changed must be considered as it can affect the training
and fatigue in the subject. If the changing condition is        Subsequently, we evaluated the training effects by com-
laborious for the subject, he/she is less likely to continue    paring the results before and after training.
with the training. In the trial experiments of this study,         The experimental result of subject B under the condi-
we set the changing condition of the difficulty level as        tion of Level-7 prior to the training experiments is shown
follows. We regarded the achievement of more than three         in Fig. 8 based on examples. It was clear that the sub-
reciprocating rotary motions of the robot arm as success-       ject could not achieve more than three reciprocating ro-
ful training for each difficulty level. We increased the dif-   tary motions. This implies that it was difficult for the sub-
ficulty level after the subject performed two consecutive       ject, who was a beginner trainee, to control the voluntary
tasks successfully. Additionally, we set the rest period to     SMESs of the extensor muscles. The experimental result
2 or 3 min between the training experiments.                    of subject B under the condition of Level-7 after the train-
                                                                ing experiments is shown in Fig. 9. It was clear that the
                                                                subject achieved almost five reciprocating rotary motions.
6. Training Experiment with Gradually                           This implies that the subject became to be able to control
   Increasing Difficulty Level                                  the voluntary SMESs of the extensor muscles.
                                                                   The number of training sessions for each subject is
   We conducted several training experiments for the left       shown in Table 1. The results show that every subject
wrist through the voluntary cooperation of three subjects       performed the training tasks successfully and easily un-
(A, B, C) who were right-handed healthy young males             der the conditions of Level-1 to Level-7. The training
(age A: 21 years, B: 21 years, and C: 22 years). For every      effect was evaluated based on the number of reciprocat-
subject, the thresholds for the flexor and extensor SMESs       ing rotary motions in the experiments of robot arm ma-
were set to 0.1 V and 0.2 V, respectively. In these trial ex-   nipulation before and after the training as shown in Ta-
periments, none of the subjects ceased continuous training      ble 2. The results show that subjects A and B acquired
under the conditions of Level-1 to Level-7. For every sub-      the desired skills for robot arm manipulation. Meanwhile,
ject, we conducted an experiment on robot arm manipula-         we assumed that subject C possessed inherent aptitude for
tion under the conditions of Level-7 prior to the training      robot arm manipulation using SMESs.
experiments. Furthermore, we conducted another experi-
ment on robot arm manipulation under the conditions of
Level-7 for every subject after the training experiments.

Journal of Robotics and Mechatronics Vol.33 No.4, 2021                                                                       855
Hayashi, R. et al.

                                                                    7. Conclusion
                                                                       In this study, we constructed a simple one-link robot
                                                                    arm that was controlled by simple proportional control
                                                                    such that its rotation angle would coincide with the ref-
                                                                    erence angle. The reference angle of the robot arm was
                                                                    generated from the SMESs on the forearm of the subject
                                                                    (trainee). Subsequently, we proposed a training scheme
                                 (i) Arm angle
                                                                    for robot arm manipulation with gradually increasing dif-
                                                                    ficulty level using SMESs. We discovered that a first-time
                                                                    beginner successfully repeated the exercise to control vol-
                                                                    untary SMESs from the beginning of the training by incor-
                                                                    porating assistance. In the training experiments, all sub-
                                                                    jects performed the training tasks successfully and easily
                                                                    by applying our proposed scheme. In our opinion, the
                                                                    training effect of our proposed scheme will facilitate the
                                                                    voluntary surface myoelectric activity of the desired mus-
                       (ii) Intensity of flexor SMES                cles. In fact, we demonstrated the feasibility of the pro-
                                                                    posed system by conducting several training experiments
                                                                    involving healthy young subjects. Further training experi-
                                                                    ments are required to identify more suitable conditions for
                                                                    changing the difficulty level. We intend to conduct clini-
                                                                    cal experiments using our proposed system in the future,
                                                                    although the applicable targets (patients) will be limited.
                                                                    It is difficult to use our proposed system on hemiplegic
                                                                    patients who have no kinetic sense, or who cannot gener-
                     (iii) Intensity of extensor SMES               ate SMES at all. However, we assume that patients pos-
  Fig. 9. Experimental result for Level-7 after training is per-    sessing fragile senses and abilities will be able to perform
  formed for evaluation.                                            repetitive training using our proposed system. We believe
                                                                    that the results of this study will contribute to the devel-
                                                                    opment and promotion of rehabilitation support systems
  Table 1. Number of training times from Level-1 to Level-7.        for hemiplegic upper limbs.
        Difficulty      Subject A        Subject B      Subject C
         Level-1             2                   2            2     Acknowledgements
         Level-2             2                   2            2     This study was supported by JSPS KAKENHI Grant Number
                                                                    JP20K11199.
         Level-3             2                   2            2
         Level-4             2                   2            2
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                                          face myoelectric signals,” J. of Physics, Conf. Series, No.1065, doi:                              Professor, Department of Mechanical Systems
                                          10.1088/1742-6596/1065/17/172004, 2018.                                                            Engineering, Okayama University of Science
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                                          oelectric Potential,” Proc. of the 12th SICE System Integration Di-
                                          vision Annual Conf., pp. 98-102, 2011 (in Japanese).
                                                                                                                  Address:
                                                                                                                  1-1 Ridai-cho, Kita-ku, Okayama 700-0005, Japan
                                                                                                                  Brief Biographical History:
                                                                                                                  1999- Assistant Professor, Tsuyama National College of Technology
                                                                                                                  2002- Lecturer, Okayama University of Science
                                                             Name:                                                2008- Associate Professor, Okayama University of Science
                                                             Ryota Hayashi                                        2015- Professor, Okayama University of Science
                                                                                                                  Main Works:
                                                             Affiliation:                                         • “Analysis of body undulation using dynamic model with frictional force
                                                             Professor, Department of Mechanical Systems          for myriapod robot,” Artificial Life and Robotics, Vol.26, pp. 29-34, 2021.
                                                             Engineering, Okayama University of Science           • “Development of a small and lightweight myriapod robot using passive
                                                                                                                  dynamics,” Artificial Life and Robotics, Vol.22, Issue 4, pp. 429-434,
                                                                                                                  2017.
                                                                                                                  Membership in Academic Societies:
                                                                                                                  • The Japan Society of Mechanical Engineers (JSME)
                                                                                                                  • The Robotics Society of Japan (RSJ)
                                   Address:                                                                       • The Society of Instrument and Control Engineers (SICE)
                                   1-1 Ridai-cho, Kita-ku, Okayama 700-0005, Japan                                • The Institute of Electrical and Electronics Engineers (IEEE)
                                   Brief Biographical History:                                                    • The Institute of Systems, Control and Information Engineers (ISCIE)
                                   1996- Assistant Professor, Kinki University                                    • The Palaeontological Society of Japan (PSJ)
                                   2000- Lecturer, Kagoshima University
                                   2009- Associate Professor, Kagoshima University
                                   2016- Professor, Okayama University of Science
                                   Main Works:
                                   • “Mobile Robot Utilizing Arm Rotations – Performance of Mobile Robot
                                   Under a Gravity Environment –,” J. Robot. Mechatron., Vol.32, No.1,                                       Name:
                                   pp. 254-263, 2020.                                                                                        Koji Yoshida
                                   • “On facilitating method for skill acquisition of robot arm manipulation
                                   using surface myoelectric signals,” J. of Physics: Conf. Series (IMEKO                                    Affiliation:
                                   2018), 1065 172004, 2018.                                                                                 Professor, Department of Mechanical Systems
                                   Membership in Academic Societies:                                                                         Engineering, Okayama University of Science
                                   • The Japan Society of Mechanical Engineers (JSME)
                                   • The Robotics Society of Japan (RSJ)
                                   • The Society of Instrument and Control Engineers (SICE)
                                   • The Institute of Electrical and Electronics Engineers (IEEE)
                                                                                                                  Address:
                                                                                                                  1-1 Ridai-cho, Kita-ku, Okayama 700-0005, Japan
                                                                                                                  Brief Biographical History:
                                                                                                                  1993- Research Assistant, University of Osaka Prefecture
                                                             Name:                                                1997- Lecturer, Okayama Prefectural University
                                                             Naoki Shimoda                                        2006- Associate Professor, Okayama University of Science
                                                                                                                  2008- Professor, Okayama University of Science
                                                             Affiliation:                                         Main Works:
                                                             Graduate Student, Graduate School of Engineer-       • “A condition on the trajectories of planar torque-unit manipulator for
                                                             ing, Okayama University of Science                   controlling all state variables,” Mechanical Engineering J., Vol.5, No.4,
                                                                                                                  2018.
                                                                                                                  Membership in Academic Societies:
                                                                                                                  • The Institute of Electrical and Electronics Engineers (IEEE)
                                                                                                                  • The Japan Society of Mechanical Engineers (JSME)
                                                                                                                  • The Robotics Society of Japan (RSJ)
                                   Address:                                                                       • The Society of Instrument and Control Engineers (SICE)
                                   1-1 Ridai-cho, Kita-ku, Okayama 700-0005, Japan                                • The Institute of Systems, Control and Information Engineers (ISCIE)
                                   Brief Biographical History:
                                   2016- Undergraduate Student, Faculty of Engineering, Okayama
                                   University of Science
                                   2020- Graduate Student, Graduate School of Engineering, Okayama
                                   University of Science
                                   Main Works:
                                   • “Robotic Arm Manipulation Training Support System to Promote the
                                   Generation of Voluntary Surface Myoelectric Signals,” Proc. of The 21th
                                   SICE SI2020, pp. 248-252, 2020.

                                   Journal of Robotics and Mechatronics Vol.33 No.4, 2021                                                                                                 857

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