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Discrimination of vascular aging using the arterial pulse spectrum and machine-learning analysis
- Source :
- Microvascular research. 139
- Publication Year :
- 2021
-
Abstract
- Aging contributes to the progression of vascular dysfunction and is a major nonreversible risk factor for cardiovascular disease. The aim of this study was to determine the effectiveness of using arterial pulse-wave measurements, frequency-domain pulse analysis, and machine-learning analysis in distinguishing vascular aging. Radial pulse signals were measured noninvasively for 3 min in 280 subjects aged 40–80 years. The cardio-ankle vascular index (CAVI) was used to evaluate the arterial stiffness of the subjects. Forty frequency-domain pulse indices were used as features, comprising amplitude proportion (Cn), coefficient of variation of Cn, phase angle (Pn), and standard deviation of Pn (n = 1–10). Multilayer perceptron and random forest with supervised learning were used to classify the data. The detected differences were more prominent in the subjects aged 40–50 years. Several indices differed significantly between the non-vascular-aging group (aged 40–50 years; CAVI 80%, and the AUC was >0.8). For subjects aged 50–60 and 60–70 years, the detection accuracies of the two trained algorithms were around 80%, with AUCs of >0.73 for both, which indicated acceptable discrimination. The present method of frequency-domain analysis may improve the index reliability for further machine-learning analyses of the pulse waveform. The present noninvasive and objective methodology may be meaningful for developing a wearable-device system to reduce the threat of vascular dysfunction induced by vascular aging.
- Subjects :
- Adult
Male
medicine.medical_specialty
Aging
Coefficient of variation
Biochemistry
Standard deviation
Peripheral Arterial Disease
Predictive Value of Tests
Internal medicine
medicine
Humans
Arterial Pressure
Risk factor
Aged
Aged, 80 and over
Pulse (signal processing)
business.industry
Phase angle
Age Factors
Reproducibility of Results
Blood Pressure Determination
Cell Biology
Middle Aged
medicine.disease
Blood pressure
Multilayer perceptron
Pulsatile Flow
Radial Artery
Arterial stiffness
Cardiology
Female
Supervised Machine Learning
Cardiology and Cardiovascular Medicine
business
Subjects
Details
- ISSN :
- 10959319
- Volume :
- 139
- Database :
- OpenAIRE
- Journal :
- Microvascular research
- Accession number :
- edsair.doi.dedup.....ae35c0cc0c0296dbfad231a392e0b5cd