Title :
A novel method for the automatic segmentation of activity data from a wrist worn device: Preliminary results
Author :
Amor, James D. ; Ahanathapillai, Vijayalakshmi ; James, Christopher J.
Author_Institution :
Inst. of Digital Healthcare, Univ. of Warwick, Coventry, UK
Abstract :
Activity monitoring is used in a number of fields in order to assess the physical activity of the user. Applications include health and well-being, rehabilitation and enhancing independent living. Data are often gathered from multiple accelerometers and analysis focuses on multi-parametric classification. For longer term monitoring this is unsuitable and it is desirable to develop a method for the precise analysis of activity data with respect to time. This paper presents the initial results of a novel approach to this problem which is capable of segmenting activity data collected from a single accelerometer recording naturalized activity.
Keywords :
accelerometers; biomedical measurement; body sensor networks; medical signal processing; patient monitoring; patient rehabilitation; signal classification; activity data analysis; activity monitoring; automatic segmentation; health; independent living; multiparametric classification; multiple accelerometers; naturalized activity; physical activity; rehabilitation; single accelerometer; well-being; wrist worn device; Accelerometers; Accuracy; Educational institutions; Legged locomotion; Monitoring; Spectrogram; Wrist;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
DOI :
10.1109/EMBC.2014.6944864
