Abstract-We present a technique to discover the position of sensors on the human body. Automatic on-body device localization ensures correctness and accuracy of measurements in health and medical monitoring systems. In addition, it provides opportunities to improve the performance and usability of ubiquitous devices. Our technique uses accelerometers to capture motion data to estimate the location of the device on the user's body, using mixed supervised and unsupervised time series analysis methods. We have evaluated our technique with extensive experiments on 25 subjects. On average, our technique achieves 89% accuracy in estimating the location of devices on the body.
A previous study presents a technique to capture motion data to estimate the positions of sensors on the user's body, employing mixed supervised and unsupervised learning approaches REF .
On-body device localization for health and medical monitoring applications
2011 IEEE International Conference on Pervasive Computing and Communications (PerCom)
2011 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Computer Science