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A dry-electrode enabled ECG-on-Chip with arrhythmia-aware data transmission

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Abstract

Early detection and treatment of cardiovascular diseases (CVDs) can be significantly enhanced through the use of flexible wearable electrocardiogram (ECG) sensors, potentially reducing CVD-related mortality. This paper introduces an ECG-on-Chip (EoC) solution tailored for flexible ECG sensors, incorporating novel features to address common challenges in wearable ECG technology. The EoC integrates a chopper-stabilized capacitively-coupled instrumentation amplifier (CS-CCIA), ensuring a high common-mode rejection ratio (CMRR) and low noise performance. Performance is further boosted via a positive feedback loop (PFL) and a programmable gain amplifier (PGA) with shared on-chip calibration logic, which enhances input impedance and minimizes gain variability to ensure consistent algorithm performance. Additionally, a secondary chopping technique is employed to further reduce noise, achieving an input-referred noise level of 454 nVrms. The embedded algorithm within the EoC is designed to extract clinically meaningful features, facilitating robust real-time arrhythmia analysis. Fabricated using a 0.18 µm CMOS process, the EoC consumes 14.9 µW with a supply voltage of 1.2 V. The algorithm’s efficacy has been validated over 0.4 million heartbeats, demonstrating a sensitivity of over 99.7% for R-peak detection and 98.3% for arrhythmia analysis. To demonstrate practical application, the EoC has been integrated with a commercial Bluetooth low energy (BLE) transceiver, forming a wireless arrhythmia monitoring sensor equipped with dry electrodes. This system consumes 292.04 µW in arrhythmia-aware transmission mode, supporting 13 days of operation with a 30 mAh thin-film battery.

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Acknowledgements

This work was supported in part by National Natural Science Foundation of China (Grant Nos. 62350710216, 62104145) and National Key Research and Development Program of China (Grant No. 2019YFB2204500).

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Author notes

  1. Xu X Z and Suo Y X have the same contribution to this work.

Authors and Affiliations

  1. Department of Micro-Nano Electronics and MoE Key Lab of Artificial Intelligence, Shanghai Jiao Tong University, Shanghai, 200240, China

    Xinzi Xu, Yanxing Suo, Yang Zhao, Peiyi Zhou, Xiao Han, Qiao Cai, Min Wang, Yongfu Li, Guoxing Wang & Yong Lian

  2. Pediatric AI Clinical Application and Research Center, Shanghai Engineering Research Center of Intelligence Pediatrics (SERCIP), Child Health Advocacy Institute, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China

    Jiajun Yuan

  3. Shanghai Engineering Research Center of Intelligence Pediatrics (SERCIP), Xin Hua Hospital Affiliate to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China

    Liebin Zhao

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  1. Xinzi Xu
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  2. Yanxing Suo
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Correspondence to Yang Zhao.

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Xu, X., Suo, Y., Zhao, Y. et al. A dry-electrode enabled ECG-on-Chip with arrhythmia-aware data transmission. Sci. China Inf. Sci. 68, 122405 (2025). https://doi.org/10.1007/s11432-024-4196-0

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  • DOI: https://doi.org/10.1007/s11432-024-4196-0

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