The pulse waveform quantification method basing on contour and derivative.
Ji Jin1, Haiying Zhang1, Xingguang Geng1
1Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, P.R. China; School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, P.R. China.
Computer Methods and Programs in Biomedicine
|April 11, 2022
Summary
This study introduces a new pulse waveform quantification method using Kalman filters and novel parameters. The method accurately reflects arterial condition changes and shows potential for disease detection.
Area of Science:
- Biomedical Engineering
- Cardiovascular Physiology
- Signal Processing
Background:
- Pulse waveform analysis offers insights into arterial health and disease.
- Quantifying pulse wave changes is crucial for objective assessment.
Purpose of the Study:
- To develop a novel quantification method for pulse waveforms across the entire cardiac cycle.
- To introduce new parameters (k1, k2) for analyzing systolic reflex period changes.
- To integrate multiple parameters using a Kalman filter for optimal estimation.
Main Methods:
- Developed a novel pulse waveform quantification technique.
- Introduced parameters k1 and k2 for systolic reflex period analysis.
- Fused parameters (k0, C1, C2, K, k1, k2) using a Kalman filter.
Main Results:
- New parameters showed a correlation coefficient of 0.7 with the augmentation index (AIx).
- Quantification results demonstrated consistent trends with aging across different age groups.
- Kalman filter estimation showed strong correlation (r > 0.6, up to 0.8) with respiration waves.
Conclusions:
- The developed method quantifies pulse waveform changes related to physiological status.
- The quantification parameters provide detailed insights into different cardiac cycle periods.
- This approach has potential for improving waveform recognition accuracy and disease detection.
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