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A new approach to estimating the frequency compression of the surface EMG signal during cyclical dynamic exercise is described. The basic properties of the method are first developed using simulated EMG signals. Spectral compression is measured by defining the instantaneous median frequency from time-frequency representations of the signal derived from a(More)
The time-dependent shift in the spectral content of the surface myoelectric signal to lower frequencies has proven to be a useful tool for assessing localized muscle fatigue. Unfortunately, the technique has been restricted to constant-force, isometric contractions because of limitations in the processing methods used to obtain spectral estimates. A novel(More)
Experimental electromyogram (EMG) data from the human biceps brachii were simulated using the model described in [10] of this work. A multichannel linear electrode array, spanning the length of the biceps, was used to detect monopolar and bipolar signals, from which double differential signals were computed, during either voluntary or electrically elicited(More)
This paper describes an in vitro method for comparing surface-detected electromyographic median frequency (MF) and conduction velocity (CV) parameters with histochemical measurements of muscle fiber type composition and cross-sectional area (CSA). Electromyographic signals were recorded during electrically elicited tetanic contractions from rat soleus,(More)
A study was performed to investigate the existence of any distinction in the fatiguability of corresponding contralateral muscles in the hand as a function of hand dominance. The first dorsal interosseous muscle was studied. The median frequency of the myoelectric signal was employed to describe the fatigue behavior of the muscle. It was found that during(More)
The purpose of this article is to provide an overview of research to develop surface electromyographic (EMG) measurements for classification of paraspinal muscle impairments in persons with low back pain (LBP). The process of developing laboratory and clinically based protocols is described. Results of studies to evaluate the reliability of these(More)
Technologies for decomposing the electromyographic (EMG) signal into its constituent motor unit action potential trains have become more practical by the advent of a non-invasive methodology using surface EMG (sEMG) sensors placed on the skin above the muscle of interest (De Luca et al 2006 J. Neurophysiol. 96 1646-57 and Nawab et al 2010 Clin.(More)
We present a dynamic neural network (DNN) solution for detecting time-varying occurrences of tremor and dyskinesia at 1 s resolution from time series data acquired from surface electromyographic (sEMG) sensors and tri-axial accelerometers worn by patients with Parkinson's disease (PD). The networks were trained and tested on separate datasets, each(More)
Automatic tracking of movement disorders in patients with Parkinson's disease (PD) is dependent on the ability of machine learning algorithms to resolve the complex and unpredictable characteristics of wearable sensor data. The challenge reflects the variety of movement disorders that fluctuate throughout the day which can be confounded by voluntary(More)
STUDY DESIGN Clinical commentary. OBJECTIVE To discuss the method of coordination training to enhance motor skills in persons after spinal cord injury (SCI). METHOD From the literature and clinical experience, we learn that basic motor skills like walking are refined and maintained through the millions of repetitions that take place as part of normal(More)