This study reports on the system architecture designed for a Smart-Fabric Wireless Body Area Sensor Network (SF-wBASN) developed within the Sense-Rise project. The system aims at assessing psychological and physiological indexes for the detection of work risk levels. Here, we describe the modules embedded into the SF-wBASN and the basic architecture implemented in the multi-sensor integrated platform. Specifically, SF-wBANS comprises several nodes that allow for acquiring Bio-impedance, Electrocardiogram, Respiration, Temperature and Humidity skin gradient signals. The architecture is tested by acquiring physiological signals from a healthy subject in different physical conditions. Results show the architecture's good performance in terms of size, operating time, precision, and reliability.

Architecture of a wireless wearable body area sensor network for work risk assessment / Di Modica S.; Di Rienzo M.; Di Francesco F.; Scilingo E.P.; Lanata ANTONIO. - ELETTRONICO. - (2021), pp. 429-432. (Intervento presentato al convegno 2021 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2021 nel 2021) [10.1109/MetroInd4.0IoT51437.2021.9488504].

Architecture of a wireless wearable body area sensor network for work risk assessment

Lanata ANTONIO
2021

Abstract

This study reports on the system architecture designed for a Smart-Fabric Wireless Body Area Sensor Network (SF-wBASN) developed within the Sense-Rise project. The system aims at assessing psychological and physiological indexes for the detection of work risk levels. Here, we describe the modules embedded into the SF-wBASN and the basic architecture implemented in the multi-sensor integrated platform. Specifically, SF-wBANS comprises several nodes that allow for acquiring Bio-impedance, Electrocardiogram, Respiration, Temperature and Humidity skin gradient signals. The architecture is tested by acquiring physiological signals from a healthy subject in different physical conditions. Results show the architecture's good performance in terms of size, operating time, precision, and reliability.
2021
2021 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2021 - Proceedings
2021 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2021
2021
Di Modica S.; Di Rienzo M.; Di Francesco F.; Scilingo E.P.; Lanata ANTONIO
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1248941
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