Theresa Roland, Werner Baumgartner, Sebastian Amsüss, Michael Friedrich Russold,
"Capacitively coupled EMG detection via ultra-low-power microcontroller STFT."
: Conference proceeding: IEEE Engineering in Medicine and Biology Society 2017, PubMed, Vereinigte Staaten, Seite(n) 410-4013, 7-2017
Original Titel:
Capacitively coupled EMG detection via ultra-low-power microcontroller STFT.
Sprache des Titels:
Englisch
Original Buchtitel:
Conference proceeding: IEEE Engineering in Medicine and Biology Society 2017
Original Kurzfassung:
As motion artefacts are a major problem with electromyography sensors, a new algorithm is developed to differentiate artefacts to contraction EMG. The performance of myoelectric prosthesis is increased with this algorithm. The implementation is done for an ultra-low-power microcontroller with limited calculation resources and memory. Short Time Fourier Transformation is used to enable real-time application. The sum of the differences (SOD) of the currently measured EMG to a reference contraction EMG is calculated. The SOD is a new parameter introduced for EMG classification. The satisfactory error rates are determined by measurements done with the capacitively coupling EMG prototype, recently developed by the research group.