NDLI: Predicting the near-future impact of daily activities on heart rate for at-risk populations

Content Provider	IEEE Xplore Digital Library
Author	Velikic, G. Modayil, J. Thomsen, M. Bocko, M. Pentland, A.
Copyright Year	2011
Description	Author affiliation: Center for Future Health, University of Rochester, NY USA (Bocko, M.; Pentland, A.) \|\| Dep. of Computing Science, University of Alberta, Canada (Modayil, J.) \|\| ECE, CFH, University of Rochester, NY, USA (Velikic, G.) \|\| SUNY Geneseo, NY USA (Thomsen, M.)
Abstract	In this paper we demonstrate the ability to predict changes to heart rate due to changes in levels of activity, up to an hour into the future. Activity levels are calculated from data collected by a worn accelerometer for a person performing daily activities outside a laboratory environment. People with congestive heart failure must take care not to excessively stress their heart. This can be a challenge due to the difficulty of predicting how much stress an activity is exerting on the heart. We propose to model the relationship between motion and heart rate and thus to enable the prediction of heart rate changes prior to performing an activity. We explored three methods to predict current and future heart rate from activity level: a continuous state Kalman Filter, two simple linear models, and a nonlinear model given in the literature [5]. The results from healthy subjects and subjects with congestive heart failure show that using the proposed models, the heart rate can be predicted an hour into the future using accelerometer data.
Starting Page	94
Ending Page	97
File Size	693975
Page Count	4
File Format	PDF
ISBN	9781612846958
e-ISBN	9781612846972
e-ISBN	9781612846965
DOI	10.1109/HEALTH.2011.6026795
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Heart rate activity level Heart Rate Kalman Filter Hidden Markov models Predictive models Electrocardiography prediction Acceleration nonlinear models Monitoring
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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