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.

Wearable band for hand gesture recognition based on strain sensors

Maita F;Maiolo L;Castiello A;Pecora A;
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.
2016
Inglese
6th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)
2016-July
1319
1322
http://www.scopus.com/record/display.url?eid=2-s2.0-84983406519&origin=inward
Sì, ma tipo non specificato
26-29/0672016
Singapore
smart wristband
strain gauge sensors
gesture recognition
wearable device
machine learning
4
none
Ferrone A.; Maita F.; Maiolo L.; Arquilla M.; Castiello A.; Pecora A.; Jiang X.; Menon C.; Ferrone A.; Colace L.
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/355992
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 59
  • ???jsp.display-item.citation.isi??? ND
social impact