Measurement of muscle contraction timing for prosthesis control: a comparison between electromyography and force-myography

被引:19
|
作者
Esposito, Daniele [1 ]
Gargiulo, Gaetano Dario [2 ]
Parajuli, Nawadita [2 ]
Cesarelli, Giuseppe [3 ]
Andreozzi, Emilio [1 ]
Bifulco, Paolo [1 ]
机构
[1] Univ Naples Federico II, Polytech & Basic Sci Sch, Dept Elect Engn & Informat Technol, Naples, Italy
[2] Western Sydney Univ, Sch Comp Engn & Math, Penrith, NSW, Australia
[3] Univ Naples Federico II, Dept Chem Mat & Prod Engn, Naples, Italy
关键词
Electromyography (EMG); active prosthesis control; muscle contraction monitoring; Force Sensitive Resistor (FSR) sensor; FSR vs EMG comparison; HUMAN SKELETAL-MUSCLE; ELECTROMECHANICAL DELAY; EMG;
D O I
10.1109/memea49120.2020.9137313
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Active hand prostheses are usually controlled by electromyography (EMG) signals acquired from few muscles available in the residual limb. In general, it is necessary to estimate the envelope of the EMG in real-time to implement the control of the prosthesis. Recently, sensors based on Force Sensitive Resistor (FSR) proved to be a valid alternative to monitor muscle contraction. However, FSR-based sensors measure the mechanical phenomena related to muscle contraction rather than those electrical. The aim of this study is to test the difference between the EMG and force signal in controlling a prosthetic hand. Particular emphasis has been placed on verify the prosthesis activation speed and their application to fast grabbing hand prosthesis as the "Federica" hand. Indeed, there is an intrinsic electro-mechanical delay during muscle contraction, since the electrical activation of muscle fibres always precedes their mechanical contraction. However, the EMG signal needs to be processed to control prosthesis and such filtering unavoidably causes a delay. On the contrary the force signal doesn't need any processing. Both EMG and force signals were simultaneously recorded from the flexor carpi ulnaris muscle, while subject performed wrist flexions. The raw EMG signals were rectified and low-pass filtered to extract their envelopes. Different widespread operators were used: Moving Average, Root Mean Square, Butterworth low-pass; the cut-off frequency was set to 5 Hz. Afterward, a classic double threshold method was used to compute the muscle contraction onsets (i.e. the signal should exceed a threshold level for a certain time period). Results showed that the lag introduced by the low-pass filtering of the rectified EMG, generates delays greater than those associated with the force sensor. This analysis confirms the possibility of using force sensors as a convenient alternative to EMG signals in the control of prostheses.
引用
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页数:6
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