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A novel fully wearable system based on a smart wristband equipped with stretchable strain gauge sensors and readout electronics have been assembled and tested to detect a set of movements of a hand crucial in rehabilitation procedures. The high sensitivity of the active devices embedded on the wristband do not need a direct contact with the skin, thus maximizing the comfort on the arm of the tester. The gestures done with the device have been auto-labeled by comparing the signals detected in real-time by the sensors with a commercial infrared device (Leap motion). Finally, the system has been evaluated with two machine-learning algorithms Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM), reaching a reproducibility of 98% and 94%, respectively.
Publication date: 
26 Jun 2016

Andrea Ferrone, Francesco Maita, Luca Maiolo, M Arquilla, A Castiello, A Pecora, X Jiang, Carlo Menon, Lorenzo Colace

Biblio References: 
Pages: 1319-1322
2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)