This paper proposes a new electromyogram (EMG) pattern classification method using probabilistic neuralnetworks based on boosting approach [1]. Since the proposed method automatically constructs a suitable classification network from measured EMG signals, there is no need to set the structure of network in advance. To verify the feasibility of the proposed method, phoneme classification experim...

Frequency analysis may have some advantages over back-averaging in the neurophysiological assessment of patients with suspected cortical myoclonus in whom myoclonic EMG bursts repeat rhythmically at high frequency. However, the clinical utility of EEG-EMG coherence and related EMG-EMG coherence is not established. Equally, there is an incomplete understanding of the physiology of the systems co...

The selection of most suitable mother wavelet function is still an open research problem in various signal and image processing applications. This paper presents a comparative study of different wavelet families (Daubechies, Symlets, Coiflets, and Biorthogonal) for analysis of wrist motions from electromyography (EMG) signals. EMG signals are decomposed into three levels using discrete wavelet ...

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...

Assistive robotic technology can play a major role to improve the quality of life of the physically weak people such as aged, injured, disabled or handicapped. Many assistive devices have been developed according to the needs of such individuals. Especially, upper-limb power-assist exoskeletons have been able to draw attention, as the upper limb motions are very important for the daily activiti...