Our work aims to demonstrate a multi-sensor integration system for wearable health monitoring using a shirt embedded with a thermocouple for temperature sensing and a force sensing resistor (FSR) for acquiring raw voltage measurements to extract respiratory signals via digital signal processing techniques. These sensors continuously capture physiological and biomechanical data, enabling monitoring of body temperature and recovery of respiratory signals and their time-frequency representations via post-processing using continuous wavelet transform method. To improve signal quality and reduce noise, a moving average filter is applied to ensure stable and reliable body temperature. Signal processing enables the early detection of abnormalities such as fever, physical impact, or poor posture. The proposed wearable platform has strong potential for low-cost, real-time physiological monitoring in both clinical and everyday settings. As health monitoring continues to position multisensor data fusion as a critical advancement in healthcare technology.
Wearable Integrated Multi-Sensor Modality for Real-Time Health Monitoring / Mahar, A., Boodaghian, D., D'Aloia, A.G., Bidsorkhi, H.C., Sarto, M.S.. - (2025), pp. 1-4. (IEEE SENSORS 2025 Vancouver, BC, Canada ) [10.1109/SENSORS59705.2025.11330480].
Wearable Integrated Multi-Sensor Modality for Real-Time Health Monitoring
Mahar A.;D'Aloia A. G.;Sarto M. S.
2025
Abstract
Our work aims to demonstrate a multi-sensor integration system for wearable health monitoring using a shirt embedded with a thermocouple for temperature sensing and a force sensing resistor (FSR) for acquiring raw voltage measurements to extract respiratory signals via digital signal processing techniques. These sensors continuously capture physiological and biomechanical data, enabling monitoring of body temperature and recovery of respiratory signals and their time-frequency representations via post-processing using continuous wavelet transform method. To improve signal quality and reduce noise, a moving average filter is applied to ensure stable and reliable body temperature. Signal processing enables the early detection of abnormalities such as fever, physical impact, or poor posture. The proposed wearable platform has strong potential for low-cost, real-time physiological monitoring in both clinical and everyday settings. As health monitoring continues to position multisensor data fusion as a critical advancement in healthcare technology.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
