Analysis of EMG signals of patients with essential tremor focusing on the change of tremor frequency.
Essential tremor is a disorder that causes involuntary oscillations in patients while engaging in actions or while maintaining a posture. ET patients have serious difficulties in performing activities of daily living such as eating food, drinking water, and writing. We have thus been developing an EMG-controlled exoskeletal robot to suppress tremors. The EMG signal of ET patients involves a mix of voluntary movement and tremor signals. To control the exoskeletal robot accurately, tremor signals must be removed from the patient's EMG signal. To date, we have been developing a filter to remove tremor signals from the patient's EMG. The design of this filter was based on the hypothesis that the rectified tremor signals are able to be approximated by a powered sine wave. This filter was found to have a large effect on removing tremor signals. However, tremor signals are generated both while performing voluntary movement and while maintaining a posture, and the filter was attenuating both signals. To control this robot accurately, the signal generated while performing voluntary movement is expected not to be attenuated. To accomplish this, we try to use a parameter that reflects a state of the patient's movement, performing a voluntary movement or maintaining a posture, as a switch to activate the powered sine filter. This paper provides an analysis of the favorable parameters. We focus on two parameters: the peak-to-peak interval of the rectified EMG signal, and the interval of the flat and low amplitude area of the rectified EMG signal. Through evaluation, it is affirmed that both parameters change with the state of the patient's movement. However, the latter parameter is superior to the former in terms of variability, which indicates that the interval of the flat and low amplitude area of the rectified EMG signal is a more favorable parameter to promote control of the exoskeletal robot. As a future work, we will mount the parameter to the algorithm and evaluate the robotic system.
Graduate School of Creative Science and Engineering, Waseda University, Tokyo, Japan. yy-matsumoto@ruri.waseda.jp
Yuya
Y
Matsumoto
Masatoshi
M
Seki
Takeshi
T
Ando
Yo
Y
Kobayashi
Hiroshi
H
Iijima
Masanori
M
Nagaoka
Masakatsu G
MG
Fujie
D000368:Aged; D000465:Algorithms; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004576:Electromyography / Q000379:methods*; D020329:Essential Tremor / Q000175:diagnosis* / Q000503:physiopathology*; D006801:Humans; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity