Starfish-inspired wearable bioelectronic systems for physiological signal monitoring during motion and real-time heart disease diagnosis

Soft bioelectronics enable noninvasive, continuous monitoring of physiological signals, essential for precision health care. However, capturing biosignals during physical activity, particularly biomechanical signals like cardiac mechanics, remains challenging due to motion-induced interference. Inspired by starfish's pentaradial symmetry, we introduce a starfish-like wearable bioelectronic system designed for high-fidelity signal monitoring during movement. The device, featuring five flexible, free-standing sensing arms connected to a central electronic hub, substantially reduces mechanical interference and enables high-fidelity acquisition of cardiac electrical (electrocardiogram) and mechanical (seismocardiogram and gyrocardiogram) signals during motion when coupled with signal compensation and machine learning. Using these three cardiac signal types as inputs, machine learning models deployed on smart devices achieve real-time, high-accuracy (more than 91%) diagnoses of heart conditions such as atrial fibrillation, myocardial infarction, and heart failure. These findings open previously undiscovered avenues by leveraging bioinspired device concepts combined with cutting-edge data science to boost bioelectronic performance and diagnostic precision.

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Publication Details

Journal
Science Advances
Published
2025-04-02
DOI
https://doi.org/10.1126/sciadv.adv2406
Citations
27
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
18.20
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article

Starfish-inspired wearable bioelectronic systems for physiological signal monitoring during motion and real-time heart disease diagnosis

Yaguo Lei, Ganggang Zhao, Bernard Ghanem, Zheng Yan et al.
27 citations
Science Advances
Advanced Sensor and Energy Harvesting Materials
18.20
article

Starfish-inspired wearable bioelectronic systems for physiological signal monitoring during motion and real-time heart disease diagnosis

Yaguo Lei, Ganggang Zhao, Bernard Ghanem, Zheng Yan, Can Li, Jianlin Jack Cheng, Xianglin Meng, Xuan-Bo Miao, Zehua Chen, Sicheng Chen, Yibo Yang, Sandeep Gautam, Qunle Ouyang
article en
27 citations

Abstract

Soft bioelectronics enable noninvasive, continuous monitoring of physiological signals, essential for precision health care. However, capturing biosignals during physical activity, particularly biomechanical signals like cardiac mechanics, remains challenging due to motion-induced interference. Inspired by starfish's pentaradial symmetry, we introduce a starfish-like wearable bioelectronic system designed for high-fidelity signal monitoring during movement. The device, featuring five flexible, free-standing sensing arms connected to a central electronic hub, substantially reduces mechanical interference and enables high-fidelity acquisition of cardiac electrical (electrocardiogram) and mechanical (seismocardiogram and gyrocardiogram) signals during motion when coupled with signal compensation and machine learning. Using these three cardiac signal types as inputs, machine learning models deployed on smart devices achieve real-time, high-accuracy (more than 91%) diagnoses of heart conditions such as atrial fibrillation, myocardial infarction, and heart failure. These findings open previously undiscovered avenues by leveraging bioinspired device concepts combined with cutting-edge data science to boost bioelectronic performance and diagnostic precision.

Science AdvancesVol. 11(14)
Harbin Medical University (CN), Dolby (United States) (US), First Affiliated Hospital of Harbin Medical University (CN), King Abdullah University of Science and Technology (SA), University of Missouri (US), Xi'an Jiaotong University (CN)
Good health and well-being
Openalex Percentile: Top 0%
Advanced Sensor and Energy Harvesting Materials
18.20
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