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A Miniaturized Batteryless and Wireless Biopotential Recorder With Dynamic Bandwidth and Data Rate Update for Power
Summary
This study introduces a miniaturized, wireless biopotential recorder with dynamic bandwidth and data rate adjustments. This low-power device efficiently captures various biopotential signals, including neural recordings, for improved medical monitoring.
Area of Science:
- Biomedical Engineering
- Wearable Technology
- Signal Processing
Background:
- Biopotential signals vary widely in bandwidth, necessitating adaptable recording systems.
- Existing biopotential recorders often lack dynamic tuning capabilities for bandwidth and data rates, impacting efficiency.
- Efficient power consumption is critical for long-term, implantable, or wearable monitoring devices.
Purpose of the Study:
- To develop a miniaturized, low-power, batteryless, wireless biopotential recorder with dynamic bandwidth and data rate update capabilities.
- To enable efficient operation by adapting to the varying bandwidth requirements of different biopotential signals.
- To validate the performance of the proposed system through chip verification and in-vivo measurements.
Main Methods:
- Implementation of an automated tuning approach for analog front-end bandwidth (0.25-10 kHz) and transmitter data rate (10.5-420 kbps).
- Design of a System-on-Chip (SoC) with nominal power consumption of 32 µW at 21 kbps.
- Adaptive adjustment of sensing bandwidths and data rates for multi-band sensing.
- Chip verification and in-vivo rodent electrocardiogram (ECG) measurements.
Main Results:
- Demonstrated dynamic bandwidth tuning from 0.25 kHz to 10 kHz.
- Achieved data rate adaptability from 10.5 kbps to 420 kbps.
- Validated low power consumption (32 µW at 21 kbps) and effective in-vivo ECG recording.
- Showcased multi-band sensing capability for signals of interest that change over time.
Conclusions:
- The developed biopotential recorder offers efficient, adaptive, and low-power operation for diverse biopotential signal acquisition.
- Dynamic tuning of bandwidth and data rate enhances energy efficiency and enables selective neural signal capture (e.g., LFPs and APs).
- The system's adaptability is crucial for advanced neural recording applications, facilitating high-fidelity data capture with minimal power usage.
