Abstract
The increased prevalence of chronic disease in elderly people is placing requirements for new approaches to support efficient health status monitoring and reporting. Advances in sensor technologies have provided an opportunity to perform continuous point-of-care physiological and activity-related measurement and data capture. Context-aware physiological pattern analysis with regard to activity performance has great potential for health monitoring in addition to the detection of abnormal lifestyle patterns. In this paper, the successful capture of the relationships between physiological and activity profile information is presented. Experiments have been designed to collect ECG data during the completion of five predefined everyday activities using wearable wireless sensors. The impact of these activities on heart rate has been captured through the analysis of changes in heart rate patterns. This has been achieved using CUSUM with change points corresponding to the transition between activities. From this initial analysis a future mechanism for context aware health status monitoring based on sensors is proposed.
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© 2011 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Zhang, S., Galway, L., McClean, S., Scotney, B., Finlay, D., Nugent, C.D. (2011). Deriving Relationships between Physiological Change and Activities of Daily Living Using Wearable Sensors. In: Par, G., Morrow, P. (eds) Sensor Systems and Software. S-CUBE 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 57. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23583-2_17
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DOI: https://doi.org/10.1007/978-3-642-23583-2_17
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