Wireless body area network node localization using small-scale spatial information

We present a new scheme to automatically identify the locations of wearable sensor nodes in a wireless body area network (WBAN). Instantaneous atmospheric air pressure readings are compared to map nodes in physical space. This enhancement enables unassisted sensor node placement, providing a practical solution to obtain and continuously monitor node locations without anchor nodes or beacons. To validate this localization scheme, a statistical analysis is conducted on a set of air pressure sensors and a prototype WBAN to examine the performance and limitations. Based on a 60 cm separation between nodes, indicative of the expected separation between limbs and placement positions along a patient's body, the measurements consistently exceeded p -value reliability within a 95% confidence interval. We also present and experimentally demonstrate an enhancement aiming to reduce false-positive (Type I) errors in conventional accelerometer-based on-body fall detection schemes. Our statistical analysis has shown that by continuously monitoring the patient's limb positions, the WBAN would be better able to discriminate “fall-like” motions from actual falls.