Multichannel Surface EMG Decomposition Based on Measurement Correlation and LMMSE

Journal of Healthcare Engineering - Tập 2018 - Trang 1-12 - 2018
Yong Ning1,2, Yuming Zhao3, Akbarjon Juraboev1, Ping Tan1, Jin Ding1, Jinbao He4
1School of Automation and Electrical Engineering, Zhejiang University Of Science And Technology, Hangzhou, 310023, China
2School of Computing, University of Portsmouth, Portsmouth PO1 3HE, UK
3China Coal Research Institute, Beijing 100013, China
4Ningbo University of Technology, Ningbo, 315211, China

Tóm tắt

A method based on measurement correlation (MC) and linear minimum mean square error (LMMSE) for multichannel surface electromyography (sEMG) signal decomposition was developed in this study. This MC-LMMSE method gradually and iteratively increases the correlation between an optimized vector and a reconstructed matrix that is correlated with the measurement matrix. The performance of the proposed MC-LMMSE method was evaluated with both simulated and experimental sEMG signals. Simulation results show that the MC-LMMSE method can successfully reconstruct up to 53 innervation pulse trains with a true positive rate greater than 95%. The performance of the MC-LMMSE method was also evaluated using experimental sEMG signals collected with a 64-channel electrode array from the first dorsal interosseous muscles of three subjects at different contraction levels. A maximum of 16 motor units were successfully extracted from these multichannel experimental sEMG signals. The performance of the MC-LMMSE method was further evaluated with multichannel experimental sEMG data by using the “two sources” method. The large population of common MUs extracted from the two independent subgroups of sEMG signals demonstrates the reliability of the MC-LMMSE method in multichannel sEMG decomposition.

Từ khóa


Tài liệu tham khảo

2004

10.1152/jn.1996.76.3.1503

10.3389/fneur.2018.00035

10.3233/nre-161402

10.1016/j.jbmt.2016.12.010

10.1016/j.bbr.2017.04.021

10.1002/mus.10358

10.1109/10.764949

10.1007/bf00357632

10.1152/jappl.1990.69.5.1810

10.1007/bf00357919

10.1023/b:abme.0000032463.26331.b3

10.1142/s0129065717500253

10.1109/tnsre.2017.2700890

10.3389/fneur.2018.00002

10.1109/tnsre.2017.2759664

10.1016/j.clinph.2009.11.092

10.1109/tsp.2007.896108

10.1109/tnsre.2015.2412038

10.1007/s11517-012-1029-y

10.1016/s0169-2607(05)80006-9

1993

1990

2017, Space Medicine & Medical Engineering, 30, 191

10.1007/s13534-017-0009-4

10.1016/s0006-3495(66)86642-0

10.1109/TBME.2012.2205249

10.1088/1741-2560/8/3/036028

10.1088/1741-2560/11/1/016008

10.1152/japplphysiol.01282.2005

10.1109/tnsre.2010.2041593

10.1088/1741-2560/1/2/005

10.1113/jphysiol.1982.sp014293

10.1088/1741-2560/9/5/056011

Thông tin
Thông tin xuất bản

Journal of Healthcare Engineering

Tập 2018

1-12

Thông tin tác giả