The integration of wearable technology in healthcare is gaining attention thanks to its potential to revolutionize patient monitoring and diagnostics. This study focuses on enhancing auscultation methods by utilizing both Micro Electro-Mechanical Systems (MEMS) microphones and accelerometers. The goal is to improve the quality and reliability of chest sounds acquisition in wearable devices, particularly under noisy conditions. Our research highlights the implementation of a heterogeneous sensor architecture designed for auscultation, the validation of signal processing techniques necessary to deal with operative noise, and the evaluation of the system’s performance in such conditions. The results demonstrate promising improvements in the detection of heartbeat signal, with a Signal-to-Noise Ratio (SNR) gain of 3 dB with respect to previous architectures, and more than 8 dB when relying on the newly integrated accelerometer sensor.
Celli, R., Zauli, M., Zonzini, F., Arcobelli, V.A., Mellone, S., Spadotto, A., et al. (2025). Improving Auscultation in Wearable Health Devices Integrating MEMS Microphones and Accelerometers. Cham : Springer Nature [10.1007/978-3-031-84100-2_11].
Improving Auscultation in Wearable Health Devices Integrating MEMS Microphones and Accelerometers
Roberto Celli
Primo
;Matteo Zauli
;Federica Zonzini;Valerio Antonio Arcobelli;Sabato Mellone;Alberto Spadotto;Igor Diemberger;Luca De MarchiUltimo
2025
Abstract
The integration of wearable technology in healthcare is gaining attention thanks to its potential to revolutionize patient monitoring and diagnostics. This study focuses on enhancing auscultation methods by utilizing both Micro Electro-Mechanical Systems (MEMS) microphones and accelerometers. The goal is to improve the quality and reliability of chest sounds acquisition in wearable devices, particularly under noisy conditions. Our research highlights the implementation of a heterogeneous sensor architecture designed for auscultation, the validation of signal processing techniques necessary to deal with operative noise, and the evaluation of the system’s performance in such conditions. The results demonstrate promising improvements in the detection of heartbeat signal, with a Signal-to-Noise Ratio (SNR) gain of 3 dB with respect to previous architectures, and more than 8 dB when relying on the newly integrated accelerometer sensor.| File | Dimensione | Formato | |
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ApplePies2024_mic_acc__AcceptedManuscript.pdf
embargo fino al 08/03/2026
Tipo:
Postprint / Author's Accepted Manuscript (AAM) - versione accettata per la pubblicazione dopo la peer-review
Licenza:
Licenza per accesso libero gratuito
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1.03 MB
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Adobe PDF
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