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Sensors 2016, 16(8), 1341; doi:10.3390/s16081341

Recognition of Daily Gestures with Wearable Inertial Rings and Bracelets

The BioRobotics Institute, Scuola Superiore Sant’Anna, Viale Rinaldo Piaggio, 34, Pontedera 56025, Italy
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Author to whom correspondence should be addressed.
Academic Editors: Yun Liu, Han-Chieh Chao, Pony Chu and Wendong Xiao
Received: 30 June 2016 / Revised: 3 August 2016 / Accepted: 11 August 2016 / Published: 22 August 2016
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Abstract

Recognition of activities of daily living plays an important role in monitoring elderly people and helping caregivers in controlling and detecting changes in daily behaviors. Thanks to the miniaturization and low cost of Microelectromechanical systems (MEMs), in particular of Inertial Measurement Units, in recent years body-worn activity recognition has gained popularity. In this context, the proposed work aims to recognize nine different gestures involved in daily activities using hand and wrist wearable sensors. Additionally, the analysis was carried out also considering different combinations of wearable sensors, in order to find the best combination in terms of unobtrusiveness and recognition accuracy. In order to achieve the proposed goals, an extensive experimentation was performed in a realistic environment. Twenty users were asked to perform the selected gestures and then the data were off-line analyzed to extract significant features. In order to corroborate the analysis, the classification problem was treated using two different and commonly used supervised machine learning techniques, namely Decision Tree and Support Vector Machine, analyzing both personal model and Leave-One-Subject-Out cross validation. The results obtained from this analysis show that the proposed system is able to recognize the proposed gestures with an accuracy of 89.01% in the Leave-One-Subject-Out cross validation and are therefore promising for further investigation in real life scenarios. View Full-Text
Keywords: wearable sensors; gesture recognition; activities of daily living; machine learning; sensor fusion wearable sensors; gesture recognition; activities of daily living; machine learning; sensor fusion
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Moschetti, A.; Fiorini, L.; Esposito, D.; Dario, P.; Cavallo, F. Recognition of Daily Gestures with Wearable Inertial Rings and Bracelets. Sensors 2016, 16, 1341.

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