Automatic Location Of Muscle Innervation Zones From Multi-Channel Surface EMG Signals

2006 ◽  
Author(s):  
C. Cescon
Keyword(s):  
Surface Emg ◽  
Automatic Location ◽  
Channel Surface ◽  
Muscle Innervation

Robust hand gesture recognition with a double channel surface EMG wearable armband and SVM classifier

2018 ◽  
Vol 46 ◽  
pp. 121-130 ◽  
Author(s):  
Mahmoud Tavakoli ◽  
Carlo Benussi ◽  
Pedro Alhais Lopes ◽  
Luis Bica Osorio ◽  
Anibal T. de Almeida
Keyword(s):  
Gesture Recognition ◽  
Surface Emg ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Svm Classifier ◽  
Channel Surface ◽  
Double Channel

Analysis of Conducting Waves Using Multi-Channel Surface EMG Depends on Difference in Shape of Electrodes

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

Analysis of end-plate using multi-channel surface EMG

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

scholarly journals Three-Dimensional Innervation Zone Imaging from Multi-Channel Surface EMG Recordings

2015 ◽  
Vol 25 (06) ◽  
pp. 1550024 ◽  
Author(s):  
Yang Liu ◽  
Yong Ning ◽  
Sheng Li ◽  
Ping Zhou ◽  
William Z. Rymer ◽  
...  
Keyword(s):  
High Performance ◽  
Unmet Need ◽  
Three Dimensional ◽  
Motor Units ◽  
Decomposition Methods ◽  
Surface Emg ◽  
Source Imaging ◽  
Dynamic Propagation ◽  
Channel Surface ◽  
Density Surface

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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