Telos: enabling ultra-low power wireless research
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Accelerometer-based human abnormal movement detection in wireless sensor networks
Proceedings of the 1st ACM SIGMOBILE international workshop on Systems and networking support for healthcare and assisted living environments
Hybrid tracking of human operators using IMU/UWB data fusion by a Kalman filter
Proceedings of the 3rd ACM/IEEE international conference on Human robot interaction
TEMPO 3.1: A Body Area Sensor Network Platform for Continuous Movement Assessment
BSN '09 Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks
Mercury: a wearable sensor network platform for high-fidelity motion analysis
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
BodyANT: miniature wireless sensors for naturalistic monitoring of daily activity
BodyNets '09 Proceedings of the Fourth International Conference on Body Area Networks
IEEE Transactions on Robotics
IEEE Transactions on Information Technology in Biomedicine
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Long term continuously monitoring of human physical activities in free living environments provides valuable information for a wide range of applications. This paper presents the design and implementation of a Physical Activity Monitoring System (PAMS) that can capture human motions which potentially provide many new types of human health assessment and intervention mechanisms for obesity management, rehabilitation, assisted living and human robot interaction. A low power design is applied for PAMS in the hardware/middleware design and the signal processing/filtering algorithms to reduce the number of packets transmitted to the gateway. A full 6-DoF Inertial Measurement Unit is integrated in PAMS to achieve highly reliable inertial data. With highly reliable inertial data, PAMS is designed for a spectrum of applications in healthcare monitoring, electronic entertainment and biokinetics researches. Case studies of real-time human motion tracking via PAMS are demonstrated and performances are evaluated.