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Personalized physical activity monitoring on the move

Published: 01 November 2013 Publication History

Abstract

Accurate Energy Expenditure (EE) estimation is key in understanding how behavior and daily Physical Activity (PA) patterns affect health. Mobile phones and wearable sensors (e.g. accelerometers (ACC) and heart rate (HR) monitors) have been widely used to monitor PA. In this paper we present a real-time implementation of activity-specific EE estimation algorithms, using an Health Patch and an iPhone. Our approach to continuous monitoring of PA targets personalized behavior and health status assessment, by automatically accounting for a person's cardiorespiratory fitness level (CRF), which is the main cause of inter-individual variation in HR during moderate to vigorous activities. The proposed system opens new opportunities for personalized health assessment in daily life, using ubiquitous devices.

References

[1]
M. Altini, J. Penders, O. Amft. Personalizing Energy Expenditure Estimation Using a Cardiorespiratory Fitness Predicate. Pervasive Health 2013. in-press.
[2]
J. D. George et al. Development of a submaximal treadmill jogging test for fit college-aged individuals. Med Sci Sports Exerc. 1993; 25: 643--647.
[3]
M. Altini et al. An ECG patch combining a customized ultra-low-power ECG SoC with Bluetooth low energy for long term ambulatory monitoring. in Proceedings of the 2nd Conference on Wireless Health. 2011, ACM: San Diego, California. p. 1--2

Cited By

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  • (2016)Cardiorespiratory fitness estimation using wearable sensors: Laboratory and free-living analysis of context-specific submaximal heart ratesJournal of Applied Physiology10.1152/japplphysiol.00519.2015120:9(1082-1096)Online publication date: 1-May-2016
  • (2015)Personalization of Energy Expenditure Estimation in Free Living Using Topic ModelsIEEE Journal of Biomedical and Health Informatics10.1109/JBHI.2015.241825619:5(1577-1586)Online publication date: Sep-2015

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  1. Personalized physical activity monitoring on the move

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      cover image ACM Other conferences
      WH '13: Proceedings of the 4th Conference on Wireless Health
      November 2013
      91 pages
      ISBN:9781450322904
      DOI:10.1145/2534088
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      • NSF: National Science Foundation

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 01 November 2013

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      • Demonstration

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      WH '13
      Sponsor:
      • NSF
      WH '13: Wireless Health 2013
      November 1 - 3, 2013
      Maryland, Baltimore

      Acceptance Rates

      WH '13 Paper Acceptance Rate 7 of 33 submissions, 21%;
      Overall Acceptance Rate 35 of 139 submissions, 25%

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      Cited By

      View all
      • (2016)Cardiorespiratory fitness estimation using wearable sensors: Laboratory and free-living analysis of context-specific submaximal heart ratesJournal of Applied Physiology10.1152/japplphysiol.00519.2015120:9(1082-1096)Online publication date: 1-May-2016
      • (2015)Personalization of Energy Expenditure Estimation in Free Living Using Topic ModelsIEEE Journal of Biomedical and Health Informatics10.1109/JBHI.2015.241825619:5(1577-1586)Online publication date: Sep-2015

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