Title :
Sensor Placement for Activity Detection Using Wearable Accelerometers
Author :
Atallah, Louis ; Lo, Benny ; King, Rachel ; Yang, Guang-Zhong
Author_Institution :
Dept. of Comput., Imperial Coll. London, London, UK
Abstract :
Activities of daily living are important for assessing changes in physical and behavioural profiles of the general population over time, particularly for the elderly and patients with chronic diseases. Although accelerometers are widely integrated with wearable sensors for activity classification, the positioning of the sensors and the selection of relevant features for different activity groups still pose interesting research challenges. This paper investigates wearable sensor placement at different body positions and aims to provide a framework that can answer the following questions: (i) What is the ideal sensor location for a given group of activities? (ii) Of the different time-frequency features that can be extracted from wearable accelerometers, which ones are most relevant for discriminating different activity types?
Keywords :
accelerometers; biomechanics; biomedical telemetry; body sensor networks; feature extraction; medical signal processing; signal classification; activity classification; activity detection; sensor positioning; time-frequency feature extraction; wearable accelerometers; wearable sensor placement; Accelerometers; Biomedical monitoring; Body sensor networks; Computer networks; Educational institutions; Intelligent sensors; Sensor phenomena and characterization; Wearable computers; Wearable sensors; Wrist; Body sensor networks; Wearable sensors; feature selection; sensor positioning;
Conference_Titel :
Body Sensor Networks (BSN), 2010 International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-5817-2
DOI :
10.1109/BSN.2010.23
