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The scientific researches in the field of rehabilitation engineering are increasingly providing mechanisms in order to help people with disability to perform simple tasks of day-to-day. Several studies have been carried out highlighting the advantages of using muscle signal in order to control rehabilitation devices, such as experimental prostheses. This paper presents a study investigating the use...
In this paper we present a method for optimization of spatial selectivity of multi-pad electrode during transcutaneous Functional Electrical Stimulation (FES). The presented method is based on measurement of individual muscle twitches using Micro-Electro-Mechanical Systems (MEMS) accelerometers positioned on hand, while stimulating with low frequency electrical stimulation via pads within multi-pad...
The present paper proposes a multiple neural network to determine the movement intended by an amputee from electromyogram (EMG) signals. Most previous approaches to the discrimination of movements using EMG signals have required measurement data with a relative long period exceeding 200 ms. Our approach is possible to identify the amputee's intended movement based on EMG signals of 70 ms long in an...
We developed a multi-channel electromyogram acquisition system using PSOC microcontroller to acquire multi-channel EMG signals. An array of 4 times 4 surface electrodes was used to record the EMG signal. The obtained signals were classified by a back-propagation-type artificial neural network. B-spline interpolation technique has been utilized to map the EMG signal on the muscle surface. The topological...
This paper describes a real-time isometric pinch force prediction algorithm using surface electromyogram (sEMG). The activities of seven muscles related to the movements of the thumb and index finger joints, which are observable using surface electrodes, were recorded during pinch force experiments. For the successful implementation of the real-time prediction algorithm, an off-line analysis was performed...
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