4.7 Article

Stable and Dynamic Multiparameter Monitoring on Chests Using Flexible Skin Patches with Self-Adhesive Electrodes and a Synchronous Correlation Peak Extraction Algorithm

期刊

ADVANCED HEALTHCARE MATERIALS
卷 12, 期 11, 页码 -

出版社

WILEY
DOI: 10.1002/adhm.202202629

关键词

adhesive electrodes; flexible electronics; motion artifact suppression; vital signs monitoring

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Advances in wearable bioelectronics have provided important tools for non-invasive measurements of physiological parameters. This system demonstrates the capability to simultaneously and accurately monitor electrocardiogram, photoplethysmogram, body temperature, and acceleration, allowing for dynamic multiparameter recording with low disturbance from motion artifacts. It holds potential for large-scale health monitoring and assisting in public health crisis management.
Advances in wearable bioelectronics interfacing directly with skin offer important tools for non-invasive measurements of physiological parameters. However, wearable monitoring devices majorly conduct static sensing to avoid signal disturbance and unreliable contact with the skin. Dynamic multiparameter sensing is challenging even with the advanced flexible skin patches. This epidermal electronics system with self-adhesive conductive electrodes to supply stable skin contact and a unique synchronous correlation peak extraction (SCPE) algorithm to minimize motion artifacts in the photoplethysmogram (PPG) signals. The skin patch system can simultaneously and precisely monitor electrocardiogram (ECG), PPG, body temperature, and acceleration on chests undergoing daily activities. The low latency between the ECG and the PPG signals enables the SCPE algorithm that leads to reduced errors in deduced heart rates and improved performance in oxygen level determination than conventional adaptive filtering and wavelet transformation approaches. Dynamic multiparameter recording over 24 h by the system can reflect the circadian patterns of the wearers with low disturbance from motion artifacts. This demonstrated system may be applied for health monitoring in large populations to alleviate pressure on medical systems and assist management of public health crisis.

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