Isometric Finger Pose Recognition with Sparse Channel SpatioTemporal EMG Imaging

Publication Type:
Conference Proceeding
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2018, 2018-July pp. 5232 - 5235
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© 2018 IEEE. High fidelity myoelectric control of prostheses and orthoses isparamount to restoring lost function to amputees and neuro-muscular disease sufferers. In this study we prove that patio-temporal imaging can be used to allow convolutional neural networks to classify sparse channel EMG samples from a consumer-grade device with over 94% accuracy. 10,572 images are generated from 960 samples of simple and complex isometric finger poses recorded from 4 fully intact subjects. Real-time classification of 12 poses is achieved with a 250ms continuous overlapping window.
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