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Masters Thesis
Measurement and Processing of Electromyogram Signals for Grip Detection
Research in the field of electromyography is advancing day by day. In this paper, a system for identification of grip and basic hand movements is proposed using surface electromyogram (sEMG) signals in healthy subjects. Experiments were performed to gather the data using myoWare Muscle sensor. The recorded data from the sensor is then stored using LabVIEW via a data acquisition unit (DAQ) and then plotted and processed in MATLAB software. Analysis of the data is done and with the help of Normalized 2-D cross-correlation and it detects the registered movements. After the analysis, we were able to identify and detect the movements up to perfection which can further be used for the prosthesis
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