Recursive Position Estimation in Sensor Networks
ICNP '01 Proceedings of the Ninth International Conference on Network Protocols
Action coverage formulation for power optimization in body sensor networks
Proceedings of the 2008 Asia and South Pacific Design Automation Conference
Locomotion monitoring using body sensor networks
Proceedings of the 1st international conference on PErvasive Technologies Related to Assistive Environments
BodyNets '09 Proceedings of the Fourth International Conference on Body Area Networks
Results of using a wireless inertial measurirlg system to quantify gait motions in control subjects
IEEE Transactions on Information Technology in Biomedicine
System architecture of a wireless body area sensor network for ubiquitous health monitoring
Journal of Mobile Multimedia
Proceedings of the 2nd Conference on Wireless Health
Proceedings of the 2nd Conference on Wireless Health
Reducing the power consumption of an IMU-Based gait measurement system
PCM'12 Proceedings of the 13th Pacific-Rim conference on Advances in Multimedia Information Processing
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Systems with wearable and wireless motion sensors have been receiving significant attention in the past few years specifically for the applications of human movement monitoring. One important concern in the design of wearable and wireless motion sensors, also referred to as Body Sensor Networks, is the form factor. A smaller form factor makes the device easily portable and wearable, hence improving users' acceptability. The form factor is usually determined by the size of the battery, which in turn is dependent on the power required by the system and the sensors present in it. Most human movement monitoring applications require inertial sensors like accelerometers and gyroscopes. However, the power consumption of a gyroscope is an order of magnitude greater than an accelerometer. In this paper, we examine power savings obtained by turning off the gyroscope for short periods while using Kalman filters to predict the state. The Kalman filter uses previous readings from both accelerometer and gyroscopes for its calculations. Our results show that with this approach, the system can achieve a reasonable reduction in power consumption with an acceptable loss of accuracy.