A wireless ECG acquisition and classification system for body sensor networks.

Area of Science:

• Biomedical Engineering
• Wearable Technology
• Signal Processing

Background:

• Electrocardiogram (ECG) monitoring is crucial for cardiac health.
• Existing wireless ECG systems often face challenges with power consumption and data transmission efficiency.
• The need for long-term, low-power wearable health monitoring solutions is increasing.

Purpose of the Study:

• To develop and demonstrate a compact, low-power wireless ECG acquisition and classification system.
• To optimize power consumption for extended wearable operation.
• To integrate efficient signal processing for accurate ECG analysis.

Main Methods:

• Implementation of a bio-signal processor (BSP) with a low-noise amplifier and high-pass sigma-delta modulator.
• Utilizing a super-regenerative on-off keying (OOK) transceiver for low-power wireless communication.
• Adoption of a digital signal processor (DSP) for signal processing and analysis in the receiver.
• System fabrication using TSMC 0.18 µm 1P6M CMOS process at 1.2 V.

Main Results:

• The near-body node (BSP and transmitter) consumes only 587 µW.
• The system enables approximately 100 days of operation using two PR44 zinc-air batteries (605 mAh).
• The receiving node (receiver and DSP) exhibits a power consumption of 926 µW.

Conclusions:

• The developed wireless ECG system offers a highly power-efficient solution for remote cardiac monitoring.
• The low power consumption and extended battery life make it suitable for long-term wearable applications.
• The integrated BSP and DSP ensure effective ECG signal acquisition and analysis.