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Tsinghua Science and Technology 2015, 20(4): 348-363 https://doi.org/10.1109/TST.2015.7173451
Open Access | Issue | Published: 03 August 2015

SmartCare: Energy-Efficient Long-Term Physical Activity Tracking Using Smartphones

Show Author's Information Hui Liu,  Rui Li,  Sicong Liu,  Shibian Tian,  Junzhao Du( )
School of Software and Institute of Software Engineering, Xidian University, and Science and Technology on Infomation Transmission and Dissemination in Communication Networks Lab., Xi’an 710126, China.
Keywords:
physical activity tracking, hybrid classifier, health feedback
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Liu H, Li R, Liu S, et al. SmartCare: Energy-Efficient Long-Term Physical Activity Tracking Using Smartphones. Tsinghua Science and Technology, 2015, 20(4): 348-363. https://doi.org/10.1109/TST.2015.7173451
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Abstract Full text About this article

Lack of physical activity is becoming a killer of our healthy life. As a solution for this negative impact, we propose SmartCare to help users to set up a healthy physical activity habit. SmartCare can monitor a user’s activities over a long time, and then provide activity quality assessment and suggestion. SmartCare consists of three parts, activity recognition, energy saving, and health feedback. Activity recognition can recognize nine kinds of daily activities. A hybrid classifier that uses less power and memory with satisfactory accuracy was designed and implemented by utilizing the periodicity of target activity. In addition, a learning-based energy saver was introduced to reduce energy consumption by adjusting sampling rates and the set of features adaptively. Based on the type and duration of the activity recorded, health feedback in terms of the calorie burned was given. The system could provide quantitative activity quality assessment and recommend future physical activity plans. Through extensive real-life testing, the system is shown to achieve an average recognition accuracy of 98.0% with a minimized energy expenditure.


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About this article

SmartCare: Energy-Efficient Long-Term Physical Activity Tracking Using Smartphones

Show Author's information Hui Liu, Rui Li, Sicong Liu, Shibian Tian, Junzhao Du( )
School of Software and Institute of Software Engineering, Xidian University, and Science and Technology on Infomation Transmission and Dissemination in Communication Networks Lab., Xi’an 710126, China.

Abstract

Lack of physical activity is becoming a killer of our healthy life. As a solution for this negative impact, we propose SmartCare to help users to set up a healthy physical activity habit. SmartCare can monitor a user’s activities over a long time, and then provide activity quality assessment and suggestion. SmartCare consists of three parts, activity recognition, energy saving, and health feedback. Activity recognition can recognize nine kinds of daily activities. A hybrid classifier that uses less power and memory with satisfactory accuracy was designed and implemented by utilizing the periodicity of target activity. In addition, a learning-based energy saver was introduced to reduce energy consumption by adjusting sampling rates and the set of features adaptively. Based on the type and duration of the activity recorded, health feedback in terms of the calorie burned was given. The system could provide quantitative activity quality assessment and recommend future physical activity plans. Through extensive real-life testing, the system is shown to achieve an average recognition accuracy of 98.0% with a minimized energy expenditure.

Keywords: physical activity tracking, hybrid classifier, health feedback

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Publication history

Received: 10 April 2015
Revised: 15 June 2015
Accepted: 29 June 2015
Published: 03 August 2015
Issue date: August 2015

Copyright

© The authors 2015

Acknowledgements

This work was partially supported by the National Natural Science Foundation of China (Nos. 61190110, 61272456, and 61472312), the open fund ITD-U14004/KX142600011. This work was also supported by the overall innovation project of Shaanxi Province Science and Technology Plan (No. 2012KTZD02-03-03), and the Fundamental Research Funds for the Central Universities (Nos. JB151002, K5051323005, and BDY041409).

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