Force estimation by surface electromyography during functional electrical stimulation
Yuki Shimizu, Masao Sugi, Misato Ohdaira, Soichiro Morishita, Tatsuhiro Nakamura, Ryu Kato, Hiroshi Yokoi
Abstract
Yuki Shimizu, Masao Sugi, Misato Ohdaira, Soichiro Morishita, Tatsuhiro Nakamura, Ryu Kato, Hiroshi Yokoi
Abstract
In recent years, a rehabilitation method in which a quadriplegic person can perform training without a therapist has been proposed, and studies that use functional electrical stimulation (FES) have been promoted. However, FES induces muscle contractions that tend to be stronger than voluntary contractions, and hence increases the muscle load too easily. Accordingly, the resultant excessive contractions induce early muscle fatigue. Therefore, the state of muscle fatigue must be determined to prevent injury during rehabilitation. Here we employed surface electromyography (SEMG) to estimate the muscle force. We confirmed that the estimation method in a previous study, which filters out noise due to FES, is applicable to SEMG signals during FES. Consequently, we suggest that the aforementioned estimation method may be used during FES.
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In recent years, a rehabilitation method in which a quadriplegic person can perform training without a therapist has been proposed, and studies that use functional electrical stimulation (FES) have been promoted. However, FES induces muscle contractions that tend to be stronger than voluntary contractions, and hence increases the muscle load too easily. Accordingly, the resultant excessive contractions induce early muscle fatigue. Therefore, the state of muscle fatigue must be determined to prevent injury during rehabilitation. Here we employed surface electromyography (SEMG) to estimate the muscle force. We confirmed that the estimation method in a previous study, which filters out noise due to FES, is applicable to SEMG signals during FES. Consequently, we suggest that the aforementioned estimation method may be used during FES.
Key concepts: Functional electrical stimulation, Electromyography, Muscle fatigue, Rehabilitation, Physical medicine and rehabilitation, Noise (video), Stimulation, Computer science