A Novel Framework Based on FastICA for High Density Surface EMG Decomposition
نویسندگان
چکیده
منابع مشابه
Progressive FastICA Peel-Off and Convolution Kernel Compensation Demonstrate High Agreement for High Density Surface EMG Decomposition
Decomposition of electromyograms (EMG) is a key approach to investigating motor unit plasticity. Various signal processing techniques have been developed for high density surface EMG decomposition, among which the convolution kernel compensation (CKC) has achieved high decomposition yield with extensive validation. Very recently, a progressive FastICA peel-off (PFP) framework has also been deve...
متن کاملHigh-yield decomposition of surface EMG signals.
OBJECTIVE Automatic decomposition of surface electromyographic (sEMG) signals into their constituent motor unit action potential trains (MUAPTs). METHODS A small five-pin sensor provides four channels of sEMG signals that are in turn processed by an enhanced artificial intelligence algorithm evolved from a previous proof-of-principle. We tested the technology on sEMG signals from five muscles...
متن کاملFastICA peel-off for ECG interference removal from surface EMG
BACKGROUND Multi-channel recording of surface electromyographyic (EMG) signals is very likely to be contaminated by electrocardiographic (ECG) interference, specifically when the surface electrode is placed on muscles close to the heart. METHODS A novel fast independent component analysis (FastICA) based peel-off method is presented to remove ECG interference contaminating multi-channel surfa...
متن کاملA thin, flexible multielectrode grid for high-density surface EMG.
Although the value of high-density surface electromyography (sEMG) has already been proven in fundamental research and for specific diagnostic questions, there is as yet no broad clinical application. This is partly due to limitations of construction principles and application techniques of conventional electrode array systems. We developed a thin, highly flexible, two-dimensional multielectrod...
متن کاملDecomposition of surface EMG signals.
This report describes an early version of a technique for decomposing surface electromyographic (sEMG) signals into the constituent motor unit (MU) action potential trains. A surface sensor array is used to collect four channels of differentially amplified EMG signals. The decomposition is achieved by a set of algorithms that uses a specially developed knowledge-based Artificial Intelligence fr...
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ژورنال
عنوان ژورنال: IEEE Transactions on Neural Systems and Rehabilitation Engineering
سال: 2016
ISSN: 1534-4320,1558-0210
DOI: 10.1109/tnsre.2015.2412038