Novel Wearable Dry-Electrode Sensors for Long-term Multi-Parameter Cardiorespiratory monitoring
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Author
Zhou, Lingchuan
Banderet, Grégoire
Pfeuti, Jean-Nicolas
Farnier, Alexandre
Bonzon, Noémie
Chételat, Olivier
DOI
10.1515/bmt-2025-1001
Abstract
Methods The system, built around an ultra-low-power microcontroller and an analog front-end (AFE) chip, leverages CSEM’s patented "pass-through" technology to mitigate skin-electrode impedance effects and to reduce cabling from two shielded wires to one unshielded wire (possibility non-insulated). Multi-parameter data (ECG, bioimpedance, skin temperature, and 9-axis IMU motion) are processed by embedded algorithms to generate cardiac metrics, respiratory rate, energy expenditure, posture, step count, and activity classification. Data are stored in onboard flash memory and transmitted via BLE to an Android app. The device complies with IEC 60601-1 medical safety standards and features electrode-based charging, eliminating external ports for waterproofing. ECG performance was validated against a commercial reference device.
Results ECG signal quality demonstrated equivalent signal-to-noise ratios and waveform fidelity to the reference device. Dry electrodes performed comparably to gel-based systems, with CSEM algorithms delivering precise HR, HRV, IBI, and respiratory metrics. Motion sensors and skin temperature measurements enabled accurate activity tracking and energy expenditure estimation. The system maintained five-day continuous operation during preliminary testing, with intermittent app connectivity for signal streaming. Participants highlighted ease of wear and minimal disruption to routines.
Conclusion This wearable system overcomes traditional monitoring constraints, enabling continuous multi-parameter assessment in real-world settings. Upcoming clinical validation at Inselspital will confirm its efficacy for advancing personalized healthcare and clinical research. Its gel-free design, compliance with medical standards, and clinical-grade performance position it as an ideal tool for long-term health monitoring.
Publication Reference
BMT 2025, Muttenz (Switzerland)
Year
2025-09-11