JCSE, vol. 5, no. 3, pp.246-256, September, 2011

DOI: 10.5626/JCSE.2011.5.3.246/

Wearable Intelligent Systems for E-Health

Carmen C. Y. Poon, Qing Liu, Hui Gao, Wan-Hua Lin, Yuan-Ting Zhang
Joint Research Centre for Biomedical Engineering, Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR/ SIAT-Institute of Biomedical and Health Engineering, Chinese Academy of Sciences, Shenzhen, China/ Joint Research Centre for Biomedical Engineering, Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR; SIAT-Institute of Biomedical and Health Engineering & Key Laboratory for Health Informatics, Chinese Academy of Sciences, Shenzhen, China

Abstract: Due to the increasingly aging population, there is a rising demand for assistive living technologies for the elderly to ensure their health and well-being. The elderly are mostly chronic patients who require frequent check-ups of multiple vital signs, some of which (e.g., blood pressure and blood glucose) vary greatly according to the daily activities that the elderly are involved in. Therefore, the development of novel wearable intelligent systems to effectively monitor the vital signs continuously over a 24 hour period is in some cases crucial for understanding the progression of chronic symptoms in the elderly. In this paper, recent development of Wearable Intelligent Systems for e-Health (WISEs) is reviewed, including breakthrough technologies and technical challenges that remain to be solved. A novel application of wearable technologies for transient cardiovascular monitoring during water drinking is also reported. In particular, our latest results found that heart rate increased by 9 bpm (P < 0.001) and pulse transit time was reduced by 5 ms (P < 0.001), indicating a possible rise in blood pressure, during swallowing. In addition to monitoring physiological conditions during daily activities, it is anticipated that WISEs will have a number of other potentially viable applications, including the real-time risk prediction of sudden cardiovascular events and deaths.

Keyword: Wearable intelligent system; E-Health; Cardiovascular monitoring; Water drinking

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