Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
11028056 | Computers in Biology and Medicine | 2018 | 14 Pages |
Abstract
Continuous and noninvasive monitoring of blood pressure has numerous clinical and fitness applications. Current methods of continuous measurement of blood pressure are either invasive and/or require expensive equipment. Therefore, we investigated a new method for the continuous estimation of two main features of blood pressure waveform: systolic and diastolic pressures. The estimates were obtained from a photoplethysmography signal as input to the fifth order autoregressive moving average models. The performance of the method was evaluated using beat-to-beat full-wave blood pressure measurements from 15 young subjects, with no known cardiovascular disorder, in supine position as they breathed normally and also while they performed a breath-hold maneuver. The level of error in the estimates, as measured by the root mean square of the model residuals, was less than 5â¯mmHg during normal breathing and less than 8â¯mmHg during the breath-hold maneuver. The mean of model residuals both during normal breathing and breath-hold maneuvers was considered to be less than 3.2â¯mmHg. The dependency of the accuracy of the estimates on the subject data was assessed by comparing the modeling errors for the 15 subjects. Less than 1% of the models showed significant differences (pâ¯<â¯0.05) from the other models, which indicates a high level of consistency among the models.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Armin Soltan Zadi, Raichel Alex, Rong Zhang, Donald E. Watenpaugh, Khosrow Behbehani,