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We describe a system for the evaluation of the sleep macrostructure on the basis of Emfit sensor foils placed into bed mattress and of advanced signal processing. The signals on which the analysis is based are heart-beat interval (HBI) and movement activity obtained from the bed sensor, the relevant features and parameters obtained through a time-variant autoregressive model (TVAM) used as feature...
Although the mechanomyogram (MMG) has been demonstrated as a viable representation of muscle activity, its potential as a multifunction (>2) control signal has not yet been investigated. This study investigates the discriminability of multiple hand motions using multichannel forearm MMG. With nine able-bodied participants, MMG signals from six sites could be differentiated among eight classes of...
The present study compares several methods with regard to feature extraction and classification of motor unit action potentials (MUAPs) for electromyography (EMG) signal decomposition. The technique was applied to single-channel, short-period real myoelectric signals from normal subjects and artificially generated EMG recordings. All the real EMG recordings were made from the biceps brachii of healthy...
We developed a multi-channel electromyogram acquisition system using PSOC microcontroller to acquire multi-channel EMG signals. The two channel surface electrodes were used to measure and record EMG signals on forearm muscles. These two channels of EMG signals were performed a blind signal separation by using an independent component analysis (ICA) technique. The well known ICA algorithm called FASTICA...
Myoelectric signals (MES) are the electrical manifestation of muscular contractions and they can be used to create myoelectric prosthesis which is able to function with the amputee's muscle movements. This signal recorded at the surface of the skin of the forearm has been exploited to provide recognition of the movement of the hand and finger movements of healthy subject. The objective of the paper...
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