We present an embedded system designed for enabling telemedicine and remote monitoring of the people's progresses during physical rehabilitation tasks. The system consists of a modular electronics designed to interface a matrix of 32 bendable force sensors (piezoresistive or piezoelectric) assembled on a flexible PCB. It implements the analog conditioning and digital processing of sensors readout to build a pressure map of the patients' activity with up to 62.5 ksps sampling rate. Moreover, the Wi-Fi interface integrated on the microcontroller allows a live communication between user and physician, in addition to standard local logging of workout information. The reduced power consumption in live streaming conditions (less than 750mW) permits more than 8 hours autonomy of the system with a standard battery supply. Results demonstrate the performance of the proposed mapping system.

Remote rehabilitation monitoring with an IoT-enabled embedded system for precise progress tracking / Rossi, Maurizio; Rizzi, Andrea; Lorenzelli, Leandro; Brunelli, Davide. - ELETTRONICO. - (2016), pp. 384-387. (Intervento presentato al convegno 23rd IEEE International Conference on Electronics, Circuits and Systems, ICECS 2016 tenutosi a Montecarlo nel 2016, 12) [10.1109/ICECS.2016.7841213].

Remote rehabilitation monitoring with an IoT-enabled embedded system for precise progress tracking

Rossi, Maurizio;Lorenzelli, Leandro;Brunelli, Davide
2016-01-01

Abstract

We present an embedded system designed for enabling telemedicine and remote monitoring of the people's progresses during physical rehabilitation tasks. The system consists of a modular electronics designed to interface a matrix of 32 bendable force sensors (piezoresistive or piezoelectric) assembled on a flexible PCB. It implements the analog conditioning and digital processing of sensors readout to build a pressure map of the patients' activity with up to 62.5 ksps sampling rate. Moreover, the Wi-Fi interface integrated on the microcontroller allows a live communication between user and physician, in addition to standard local logging of workout information. The reduced power consumption in live streaming conditions (less than 750mW) permits more than 8 hours autonomy of the system with a standard battery supply. Results demonstrate the performance of the proposed mapping system.
2016
2016 IEEE International Conference on Electronics, Circuits and Systems, ICECS 2016
Piscataway, New Jersey, USA
Institute of Electrical and Electronics Engineers Inc.
9781509061136
9781509061136
Rossi, Maurizio; Rizzi, Andrea; Lorenzelli, Leandro; Brunelli, Davide
Remote rehabilitation monitoring with an IoT-enabled embedded system for precise progress tracking / Rossi, Maurizio; Rizzi, Andrea; Lorenzelli, Leandro; Brunelli, Davide. - ELETTRONICO. - (2016), pp. 384-387. (Intervento presentato al convegno 23rd IEEE International Conference on Electronics, Circuits and Systems, ICECS 2016 tenutosi a Montecarlo nel 2016, 12) [10.1109/ICECS.2016.7841213].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/171549
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