Wireless Design of a Multisensor System for Physical Activity Monitoring

• Published in: IEEE transactions on biomedical engineering Vol. 59; no. 11; pp. 3230 - 3237
• Main Authors: Mo, Lingfei, Liu, Shaopeng, Gao, Robert X., John, Dinesh, Staudenmayer, John W., Freedson, Patty S.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.11.2012
• Subjects: Activities of Daily Living; Adult; Algorithms; Data synchronization; Electronics, Medical - instrumentation; energy efficiency; Equipment Design; Female; Humans; Male; Monitoring, Ambulatory - instrumentation; Monitoring, Ambulatory - methods; Movement - physiology; physical activity (PA) monitoring; Protocols; Sensors; Signal Processing, Computer-Assisted; Synchronization; Telemetry - instrumentation; Telemetry - methods; Tin; Wireless communication; Wireless sensor networks; Wireless Technology - instrumentation; Zigbee
• ISSN: 0018-9294; 1558-2531; 1558-2531
• DOI: 10.1109/TBME.2012.2208458

Real-time monitoring of human physical activity (PA) is important for assessing the intensity of activity and exposure to environmental pollutions. A wireless wearable multisenor integrated measurement system (WIMS) has been designed for real-time measurement of the energy expenditure and breathing volume of human subjects under free-living conditions. To address challenges posted by the limited battery life and data synchronization requirement among multiple sensors in the system, the ZigBee communication platform has been explored for energy-efficient design. Two algorithms have been developed (multiData packaging and slot-data-synchronization) and coded into a microcontroller (MCU)-based sensor circuitry for real-time control of wireless data communication. Experiments have shown that the design enables continued operation of the wearable system for up to 68 h, with the maximum error for data synchronization among the various sensor nodes (SNs) being less than 24 ms. Experiment under free-living conditions have shown that the WIMS is able to correctly recognize the activity intensity level 86% of the time. The results demonstrate the effectiveness of the energy-efficient wireless design for human PA monitoring.