Mobile Cloud-Based Physical Activity Advisory System Using Biofeedback Sensors

Physical inactivity has gained a wide attention due to its negative influence on human wellness. Physical activity advisory systems consider a promising solution for this phenomenon. In this paper, we propose a mobile cloud-based physical activity advisory system utilizing biofeedback sensors and environmental context data based on calories expenditure from performing various activities by tracking user’s physical movements. To evaluate the proposed system, we conducted in total a three-month experiment on six users. For each user, we tracked the amount of burnt calories from the physical movements for a two-week period. During the first week, the system did not send any advice, while during the second week, the system was advising the user on activities to perform. The compared results of the two weeks collected data (without and with advice) reflect the positive effect of the proposed system on participants’ physical activity level. The system motivates them to reach or exceed the recommended number of calories to be burned daily.



Hawazin Albadawi, Haiwei Dong and Abdulmotaleb El Saddik, “Mobile Cloud-Based Physical Activity Advisory System Using Biofeedback Sensors” Elsevier Future Generation Computer Systems (doi:10.1016/j.future.2015.11.005)

Amal Dandashi, Sawsan Saad, Abdel Ghani Karkar, Zaara Barhoumi, Jihad Al-Jaam and Abdulmotaleb El Saddik, “Enhancing the Cognitive and Learning Skills of Children with Intellectual Disability through Physical Activity and Edutainment Games”, International Journal of Distributed Sensor Networks, Volume 2015, pp. 165165:1-165165:11, 2015.

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