TY - GEN
T1 - Design of Myoelectric Control Command of Electric Wheelchair as Personal Mobility for Disabled Person
AU - Nudra Bajantika Pradivta, I. Wayan
AU - Arifin, Achmad
AU - Arrofiqi, Fauzan
AU - Watanabe, Takashi
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - Paralysis is a condition that causes the sufferer to be unable to move the leg muscles or hand muscles. However, a paralyzed subject can still use the electrical activity of other intact muscles as a control command for the electric wheelchair. This system includes instrumentation and processing of electromyography (EMG) signal, and interpretation for controlling the wheelchair to move forward, backward, stop, turn left, and turn right. The EMG signal of the Flexor Carpi Radialis muscles was measured and amplified by a designed instrumentation amplifier. Then, the signal was filtered to eliminate noise and maintain the EMG frequency range of 20500 Hz. After filtering, the signal was processed more to produce a linear envelope and hold the maximum value of the envelope of the EMG signal. Interpretation of command from subject was determined by thresholing method to the envelope of the EMG signal. The results of wheelchair navigation with basic movements had an average success rate of 100% of 8 subjects. The test results past the determined track have an average success rate of 95.83% for 3 subjects. It is expected that in the future, the subjects can use the wheelchair with subject's intention speed.
AB - Paralysis is a condition that causes the sufferer to be unable to move the leg muscles or hand muscles. However, a paralyzed subject can still use the electrical activity of other intact muscles as a control command for the electric wheelchair. This system includes instrumentation and processing of electromyography (EMG) signal, and interpretation for controlling the wheelchair to move forward, backward, stop, turn left, and turn right. The EMG signal of the Flexor Carpi Radialis muscles was measured and amplified by a designed instrumentation amplifier. Then, the signal was filtered to eliminate noise and maintain the EMG frequency range of 20500 Hz. After filtering, the signal was processed more to produce a linear envelope and hold the maximum value of the envelope of the EMG signal. Interpretation of command from subject was determined by thresholing method to the envelope of the EMG signal. The results of wheelchair navigation with basic movements had an average success rate of 100% of 8 subjects. The test results past the determined track have an average success rate of 95.83% for 3 subjects. It is expected that in the future, the subjects can use the wheelchair with subject's intention speed.
KW - Electric Wheelchair
KW - Myoelectric Control Command
UR - http://www.scopus.com/inward/record.url?scp=85085618653&partnerID=8YFLogxK
U2 - 10.1109/IBITeC46597.2019.9091682
DO - 10.1109/IBITeC46597.2019.9091682
M3 - Conference contribution
AN - SCOPUS:85085618653
T3 - 2019 International Biomedical Instrumentation and Technology Conference, IBITeC 2019
SP - 112
EP - 117
BT - 2019 International Biomedical Instrumentation and Technology Conference, IBITeC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 International Biomedical Instrumentation and Technology Conference, IBITeC 2019
Y2 - 23 October 2019 through 24 October 2019
ER -