Combining wearable physiological and inertial sensors with indoor user localization network to enhance activity recognition
Author:
Affiliation:
1. The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy. E-mails: laura.fiorini@santannapisa.it, manuele.bonaccorsi@santannapisa.it, stefano.betti@santannapisa.it, dario.esposito@santannapisa.it, filippo.cavallo@santannapisa.it
Publisher
IOS Press
Subject
Software
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3. A cloud robotics solution to improve social assistive robots for active and healthy aging;Bonaccorsi;International Journal of Social Robotics,2016
4. R.F. Brena, J.P. García-Vázquez, C.E. Galván-Tejada, D. Muñoz-Rodriguez, C. Vargas-Rosales and J. Fangmeyer, Evolution of indoor positioning technologies: A survey, Journal of Sensors 2017 (2017), 2630413.
5. UTD-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor
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