In this paper, a novel technique for detection of healthy (H), myopathy, (M) and amyotrophic lateral sclerosis (ALS) electromyography (EMG) signals is proposed employing robust hyperbolic Stockwell transform (HST). HST an efficient signal processing to analyze any nonstationary in joint time–frequency (T–F) plane. However, major issue with the optimum selection Gaussian window parameters since ...

A signal analysis technique is developed for discriminating a set of lower arm and wrist functions using surface EMG signals. Data wete obtained from four electrodes placed around the proximal forearm. The functions analyzed included wrist flexion/extension, wrist abduction/adduction, and forearm pronation/supination. Multivariate autoregression models were derived for each function; discrimina...

This paper introduces a novel and simple algorithm to extract the feature from Surface EMG signals recorded from the skin surface over forearm muscles. Surface EMG signal is decomposed into 16 frequency bands (FB) by wavelet packet transform (WPT), and then wavelet packet entropy (WPE) of every surface EMG signal is calculated by its relative wavelet energy in every FB. WPE is regarded as the f...

Keywords: Biomedical signal processing Prosthetics Myoelectric control Psychophysiology Mother wavelet EMG EEG VPA Pattern recognition Daubechies (db 44) a b s t r a c t During the last two decades, wavelet transform has become a common signal processing technique in various areas. Selection of the most similar mother wavelet function has been a challenge for the application of wavelet transfor...

Surface EMG (electromyography) signal is a complex nonlinear signal with low signal to noise ratio (SNR). This paper is aimed at identifying different patterns of surface EMG signals according to fractal dimension. Two patterns of surface EMG signals are respectively acquired from the right forearm flexor of 30 healthy volunteers during right forearm supination (FS) or forearm pronation (FP). A...

The electromyogram (EMG) signal has potential as an indicator of stimulated muscle fatigue in applications of functional electrical stimulation (FES). In particular, it could be used to detect near lower limb collapse due to the associated muscle fatigue in FES-aided standing systems and thereby prevent falling. Surface EMG measurement, however, is hampered by stimulation artifact during FES. M...

removal of artifacts from bio-signals is a necessary step before automatic processing and obtaining clinical information. recently, many applications of empirical mode decomposition (emd) on biomedical researches have been presented that artifact reduction from bio-signals is one of them. emd separates a time series into finite numbers of its individual oscillations, which are called intrinsic ...

BACKGROUND Electromyographic signals can be used in biomedical engineering and/or rehabilitation field, as potential sources of control for prosthetics and orthotics. In such applications, digital processing techniques are necessary to follow efficient and effectively the changes in the physiological characteristics produced by a muscular contraction. In this paper, two methods based on informa...