Why the study?
Do statistical and fuzzy models incorporating body acceleration and heart rate improve the prediction of ambulatory systolic blood pressure variations compared to current solutions?
Do statistical and fuzzy models incorporating body acceleration and heart rate improve the prediction of ambulatory systolic blood pressure variations compared to current solutions?
Incorporating accelerometer and heart rate data into statistical and fuzzy models improves the prediction of ambulatory systolic blood pressure variations.
Should not yet change ambulatory BP monitoring; hypothesis-generating in small young cohorts and requires larger validation.
A solution to reduce Ambulatory Systolic Blood Pressure (ASBP) variability during the analysis of a 24-h profile is studied and presented in this article. It consists of equipping the portable ASBP recorder device with other sensors, a three-axes accelerometer and a heart rate recorder, so as to enable an analysis of the tensional profile in the light of these concomitant data. A database has been collected, and two models linking ASBP variations with body acceleration and heart rate measurements are developed: a regression one, based on a priori knowledge of ASBP variations, and a fuzzy one, automatically built from experimental data. Their performances are tested in prediction and compared. Then, the results are compared to those obtained with one of the solutions currently used by the physicians to deal with ASBP variability. The results obtained on 16 young subjects from the database are significantly improved and thus, encouraging.
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Charbonnier et al. (2000) studied this question.
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