Relating Noninvasive Cardiac Output and Total Peripheral Resistance Estimates to Physical Activity in an Ambulatory Setting
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HaslamAAAI2011.pdf
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Author(s)
Haslam, Bryan Todd
Gordhandas, Ankit
Ricciardi, Catherine E.
Heldt, Thomas
Verghese, George C.
Date Issued
March 2011
Journal
Papers from the AAAI Spring Symposium 2011 - Computational Physiology
Publisher
American Association for Artificial Intelligence
Citation
Haslam, Bryan et al. "Relating Noninvasive Cardiac Output and Total Peripheral Resistance Estimates to Physical Activity in an Ambulatory Setting." Computational Physiology, Papers from the 2011 AAAI Spring Symposium, Technical Report SS-11-04, Stanford, California, USA, March 21-23, 2011. AAAI 2011.
Version
Final published version
Abstract
The prevalence and cost of heart disease indicate the need for better methods of detecting, diagnosing and treating this pervasive problem. Appropriate monitoring outside of the hospital can potentially lead to earlier diagnosis and reduced costs. We use electrocardiogram (ECG) and continuous arterial blood pressure (ABP) data collected in an ambulatory setting to examine two important cardiovascular quantities, namely cardiac output (CO) and total peripheral resistance (TPR), over a range of physical activities. CO and TPR can be estimated from heart rate, pulse pressure and mean arterial blood pressure, which in turn are directly obtained from the ECG and ABP signals. More specifically, we employ a wearable cardiac and motion monitor designed by colleagues at MIT to simultaneously record ECG and 3-axis acceleration to onboard memory. The acceleration data is used to generate an estimate of physical activity at each time point. Additionally, we use a Portapres continuous blood pressure monitor to concurrently record the ABP waveform. We present representative results from data collected in a controlled ambulatory setting. Heart rate, mean ABP, CO and TPR responses to physical activity are generally consistent with what might be expected from cardiovascular physiology. The longer-term challenge is to correlate the dynamic behavior of these quantities with the state of cardiac health.
MIT Department
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Massachusetts Institute of Technology. Clinical Research Center
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Research Laboratory of Electronics
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DOI of Published Version
http://www.aaai.org/ocs/index.php/SSS/SSS11/paper/view/2497/2901
