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This research presents a low-power 32-bit ECG processor based on the ARM Cortex-M0+ Instruction Set Architecture (ISA) for arrhythmia identification. The CPU uses the energy-efficient Cortex-M0+ architecture with advanced signal processing algorithms for real-time ECG signal analysis while cutting off power usage. By utilizing hardware acceleration and software optimization, the proposed method balances processing power and energy efficiency. The design efficacy had been confirmed by extensive arrhythmia detection research studies, showing that it could be useful for wearable and remote monitoring applications where a longer battery life is essential. In order to develop portable healthcare solutions, the research provides an affordable and power-efficient approach for processing ECG data.

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An ECG Processor with Low-Power Arrhythmia Detection for Wearable Devices

  • 会议论文

  • 发表日期：

    2025年

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  • Mohit Kumar,
  • Shikhar Varshney,
  • Lalita Gupta

摘要

This research presents a low-power 32-bit ECG processor based on the ARM Cortex-M0+ Instruction Set Architecture (ISA) for arrhythmia identification. The CPU uses the energy-efficient Cortex-M0+ architecture with advanced signal processing algorithms for real-time ECG signal analysis while cutting off power usage. By utilizing hardware acceleration and software optimization, the proposed method balances processing power and energy efficiency. The design efficacy had been confirmed by extensive arrhythmia detection research studies, showing that it could be useful for wearable and remote monitoring applications where a longer battery life is essential. In order to develop portable healthcare solutions, the research provides an affordable and power-efficient approach for processing ECG data.