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Wearable band for hand gesture recognition based on strain sensors

Contributo in Atti di convegno
Data di Pubblicazione:
2016
Abstract:
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.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
smart wristband; strain gauge sensors; gesture recognition; wearable device; machine learning
Elenco autori:
Maita, Francesco; Castiello, Andrea; Pecora, Alessandro; Maiolo, Luca
Autori di Ateneo:
MAIOLO LUCA
MAITA FRANCESCO
PECORA ALESSANDRO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/355992
Pubblicato in:
PROCEEDINGS OF THE ... IEEE/RAS-EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL ROBOTICS AND BIOMECHATRONICS (PRINT)
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http://www.scopus.com/record/display.url?eid=2-s2.0-84983406519&origin=inward
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