This study reports on a novel Smart-Fabric based wireless Body Area Sensor Network for assessing psychological and physiological work risk levels. The combination of smart-sensing fabrics advantages, high electronic miniaturization, and the latest machine learning enables the system to assess the risk level of the worker. The body area sensor network includes a smartphone, an artificial intelligence algorithm for risk assessment, and a set of sensor-nodes integrated into a textile substrate (i.e., activity detection, electrocardiogram (ECG), sweat rate, body temperature, and textile integrated respiration sensors). Preliminary and encouraging results are shown in terms of physiological signals and physical activity detection.

A New Smart-Fabric based Body Area Sensor Network for Work Risk Assessment / Antonio Lanatà; Greco A.; Di Modica S.; Niccolini F.; Vivaldi F.; Di Francesco F.; Tamantini C.; Cordella F.; Zollo L.; Di Rienzo M.; Massaroni C.; Schena E.; Di Sarto M.; Scilingo E.P.. - STAMPA. - (2020), pp. 187-190. (Intervento presentato al convegno 2020 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2020 tenutosi a ita nel 2020) [10.1109/MetroInd4.0IoT48571.2020.9138273].

A New Smart-Fabric based Body Area Sensor Network for Work Risk Assessment

Antonio Lanatà;
2020

Abstract

This study reports on a novel Smart-Fabric based wireless Body Area Sensor Network for assessing psychological and physiological work risk levels. The combination of smart-sensing fabrics advantages, high electronic miniaturization, and the latest machine learning enables the system to assess the risk level of the worker. The body area sensor network includes a smartphone, an artificial intelligence algorithm for risk assessment, and a set of sensor-nodes integrated into a textile substrate (i.e., activity detection, electrocardiogram (ECG), sweat rate, body temperature, and textile integrated respiration sensors). Preliminary and encouraging results are shown in terms of physiological signals and physical activity detection.
2020
2020 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2020 - Proceedings
2020 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2020
ita
2020
Goal 4: Quality education
Antonio Lanatà; Greco A.; Di Modica S.; Niccolini F.; Vivaldi F.; Di Francesco F.; Tamantini C.; Cordella F.; Zollo L.; Di Rienzo M.; Massaroni C.; Schena E.; Di Sarto M.; Scilingo E.P.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1208713
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