Title :
Patient-centric on-body sensor localization in smart health systems
Author :
Saeedi, Ramyar ; Amini, Navid ; Ghasemzadeh, Hassan
Author_Institution :
Embedded & Pervasive Syst. Lab., Washington State Univ., Pullman, WA, USA
Abstract :
A major obstacle in widespread adoption of current wearable monitoring systems is that sensors must be worn on predefined locations on the body. In order to continuously detect sensor locations, we propose a localization algorithm that allows patients to wear the sensors on different body locations without having to adhere to a specific installation protocol. Our approach achieves localization accuracy of 90.8% even when the sensor nodes are mis-oriented. Integration of the resulting location information as a feature in an activity recognition classifier significantly increased the recognition accuracy from 23.5% to 99.5%.
Keywords :
biomechanics; body sensor networks; medical signal processing; patient monitoring; activity recognition classifier; localization algorithm; patient-centric on-body sensor localization; pedometer; recognition accuracy; smart health systems; wearable monitoring systems; Accelerometers; Accuracy; Biomedical monitoring; Feature extraction; Machine learning algorithms; Monitoring; Smart phones;
Conference_Titel :
Signals, Systems and Computers, 2014 48th Asilomar Conference on
Print_ISBN :
978-1-4799-8295-0
DOI :
10.1109/ACSSC.2014.7094840