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Accelerometer’s position independent physical activity recognition system for long-term activity monitoring in the elderly

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Abstract

Mobility is a good indicator of health status and thus objective mobility data could be used to assess the health status of elderly patients. Accelerometry has emerged as an effective means for long-term physical activity monitoring in the elderly. However, the output of an accelerometer varies at different positions on a subject’s body, even for the same activity, resulting in high within-class variance. Existing accelerometer-based activity recognition systems thus require firm attachment of the sensor to a subject’s body. This requirement makes them impractical for long-term activity monitoring during unsupervised free-living as it forces subjects into a fixed life pattern and impede their daily activities. Therefore, we introduce a novel single-triaxial-accelerometer-based activity recognition system that reduces the high within-class variance significantly and allows subjects to carry the sensor freely in any pocket without its firm attachment. We validated our system using seven activities: resting (lying/sitting/standing), walking, walking-upstairs, walking-downstairs, running, cycling, and vacuuming, recorded from five positions: chest pocket, front left trousers pocket, front right trousers pocket, rear trousers pocket, and inner jacket pocket. Its simplicity, ability to perform activities unimpeded, and an average recognition accuracy of 94% make our system a practical solution for continuous long-term activity monitoring in the elderly.

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Acknowledgments

This research was supported by the MKE (The Ministry of Knowledge Economy), Korea, under the ITRC (Information Technology Research Center) support program supervised by the NIPA (National IT Industry Promotion Agency) (NIPA-2010-(C1090-1021-0003)). This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2009-1515).

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Authors and Affiliations

  1. Department of Computer Engineering, Kyung Hee University, 1 Seocheon-dong, Giheung-gu, Yongin-si, Gyeonggi-do, 446-701, Republic of Korea

    Adil Mehmood Khan, Young-Koo Lee & Sungyoung Lee

  2. Department of Biomedical Engineering, Kyung Hee University, 1 Seocheon-dong, Giheung-gu, Yongin-si, Gyeonggi-do, 446-701, Republic of Korea

    Tae-Seong Kim

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  1. Adil Mehmood Khan
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Correspondence to Young-Koo Lee.

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Khan, A.M., Lee, YK., Lee, S. et al. Accelerometer’s position independent physical activity recognition system for long-term activity monitoring in the elderly. Med Biol Eng Comput 48, 1271–1279 (2010). https://doi.org/10.1007/s11517-010-0701-3

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