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Article

Event Detection of Muscle Activation Using an Electromyogram

Department of Electronic Engineering and Department of Software Convergence, Soongsil University, Seoul 07040, Korea
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Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(16), 5593; https://doi.org/10.3390/app10165593
Received: 10 July 2020 / Revised: 3 August 2020 / Accepted: 8 August 2020 / Published: 12 August 2020
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
In this study, we proposed a precise onset and offset detection algorithm for muscle activation by using an electromyogram (EMG). The adaptive threshold was determined using the constant false alarm rate algorithm. The EMG signal was refined by morphological hole filling, which is used to close up and fill out missing information. By exploiting the EMG amplitude ratio in two channels, we significantly improved the offset detection performance. The proposed method does not require a training process, unlike conventional methods. The experimental results indicated that the estimated errors for both the onset and offset detection are lower than those obtained using two of the conventional methods. View Full-Text
Keywords: EMG; muscle activation; onset detection; offset detection; hand movements EMG; muscle activation; onset detection; offset detection; hand movements
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MDPI and ACS Style

Kang, K.; Rhee, K.; Shin, H.-C. Event Detection of Muscle Activation Using an Electromyogram. Appl. Sci. 2020, 10, 5593. https://doi.org/10.3390/app10165593

AMA Style

Kang K, Rhee K, Shin H-C. Event Detection of Muscle Activation Using an Electromyogram. Applied Sciences. 2020; 10(16):5593. https://doi.org/10.3390/app10165593

Chicago/Turabian Style

Kang, Kimoon, Kiwon Rhee, and Hyun-Chool Shin. 2020. "Event Detection of Muscle Activation Using an Electromyogram" Applied Sciences 10, no. 16: 5593. https://doi.org/10.3390/app10165593

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