Extracting Control Information from Multi-channel Surface EMG Signals to Drive a Musculoskeletal Model

Author(s):  
Ruyi Wang ◽  
Kun Zhu ◽  
Ziang Zhang ◽  
Jianmin Li ◽  
Lizhi Pan
2018 ◽  
Vol 46 ◽  
pp. 121-130 ◽  
Author(s):  
Mahmoud Tavakoli ◽  
Carlo Benussi ◽  
Pedro Alhais Lopes ◽  
Luis Bica Osorio ◽  
Anibal T. de Almeida

2021 ◽  
Vol 141 (4) ◽  
pp. 539-545
Author(s):  
Kohei Okura ◽  
Tota Mizuno ◽  
Marzieh Aliabadi Farahani ◽  
Yu Matsumoto ◽  
Kazuyuki Mito ◽  
...  
Keyword(s):  

2019 ◽  
Vol 24 (3) ◽  
pp. 390-395
Author(s):  
Marzieh Aliabadi Farahani ◽  
Hiroki Yamada ◽  
Kota Akehi ◽  
Kazuyuki Mito ◽  
Tota Mizuno ◽  
...  

2015 ◽  
Vol 25 (06) ◽  
pp. 1550024 ◽  
Author(s):  
Yang Liu ◽  
Yong Ning ◽  
Sheng Li ◽  
Ping Zhou ◽  
William Z. Rymer ◽  
...  

There is an unmet need to accurately identify the locations of innervation zones (IZs) of spastic muscles, so as to guide botulinum toxin (BTX) injections for the best clinical outcome. A novel 3D IZ imaging (3DIZI) approach was developed by combining the bioelectrical source imaging and surface electromyogram (EMG) decomposition methods to image the 3D distribution of IZs in the target muscles. Surface IZ locations of motor units (MUs), identified from the bipolar map of their MU action potentials (MUAPs) were employed as a prior knowledge in the 3DIZI approach to improve its imaging accuracy. The performance of the 3DIZI approach was first optimized and evaluated via a series of designed computer simulations, and then validated with the intramuscular EMG data, together with simultaneously recorded 128-channel surface EMG data from the biceps of two subjects. Both simulation and experimental validation results demonstrate the high performance of the 3DIZI approach in accurately reconstructing the distributions of IZs and the dynamic propagation of internal muscle activities in the biceps from high-density surface EMG recordings.


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