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IEEE-802.15.4-based low-power body sensor node with RF energy harvester
Thang Viet Tran1, Wan-Young Chung1
1Department of Electronic Engineering, Pukyong National University, Busan 608-737, Korea.
Bio-Medical Materials and Engineering
|September 18, 2014
Summary
This study presents a low-voltage, low-power wireless body sensor node for collecting electrocardiography (ECG) and photoplethysmography (PPG) signals. The design integrates an RF energy harvester and achieves 14 mW power consumption for extended battery life in wireless body sensor networks (BSNs).
Area of Science:
- Biomedical Engineering
- Wireless Sensor Networks
- Low-Power Electronics
Background:
- Wireless Body Sensor Networks (BSNs) are crucial for remote health monitoring.
- Existing BSN nodes often face limitations in power consumption and size.
- Efficient collection of physiological signals like ECG and PPG is essential for diagnostics.
Purpose of the Study:
- To design and implement a compact, low-voltage, and ultra-low-power body sensor node.
- To enable simultaneous collection of electrocardiography (ECG) and photoplethysmography (PPG) signals.
- To integrate an RF energy harvester for extended operational lifetime.
Main Methods:
- Development of a ZigBee mote integrating a DC-DC booster, PPG interface, and low-current ECG front-end.
- Implementation using nesC language within the TinyOS environment for flexible configuration.
- Incorporation of an RF energy harvester for continuous battery charging.
- Achieved ultra-low power consumption of 14 mW in working mode.
Main Results:
- The proposed node operates with a wide input voltage range (0.65 V to 3.3 V).
- Demonstrated successful simultaneous collection of ECG and PPG signals.
- Achieved a power consumption of 14 mW, significantly prolonging battery life.
- Configurable as a standalone node or part of a wireless BSN.
Conclusions:
- The designed body sensor node offers a low-voltage, low-power solution for wireless health monitoring.
- The integrated RF energy harvester enhances the node's sustainability and operational duration.
- The platform facilitates the creation of efficient wireless BSNs for real-time physiological data acquisition.

