From pulse to pixel: artificial intelligence-enhanced pulse diagnosis for cardiovascular diseases
- Author:
Xilong Zheng
- Publication Type:Journal Article
- Keywords:
Pulse diagnosis;
Traditional Chinese medicine;
Artificial intelligence;
Cardiovascular disease;
Machine learning
- From:
Digital Chinese Medicine
2026;9(2):161-172
- CountryChina
- Language:English
-
Abstract:
Traditional Chinese medicine (TCM) pulse diagnosis is a non-invasive approach used to infer cardiovascular status, but its interpretation is relatively subjective, limiting reproducibility and diagnostic precision. This review summarizes progress in digitized radial pulse assessment using modern sensors and artificial intelligence (AI), and evaluates reported applications in cardiovascular screening and decision support. We searched PubMed, IEEE Xplore, and Web of Science Core Collection from inception through November 30, 2025, for studies that acquired wrist/radial pulse signals with electronic devices and applied quantitative analysis or machine learning/deep learning to characterize pulse patterns or assess cardiovascular conditions. Across the literature, pressure-sensor arrays, wearable photoplethysmography (PPG) surrogates, and hybrid platforms enabled more standardized pulse acquisition, while AI models reported promising performance for tasks such as blood pressure estimation, hypertension screening, coronary artery disease identification, heart failure risk stratification, and arrhythmia detection. However, methodological heterogeneity, limited sample sizes, inconsistent labeling standards, and insufficient external validation remain key barriers to clinical translation. Overall, AI-enhanced digital pulse diagnosis may improve the objectivity of TCM pulse assessment and complement conventional cardiovascular diagnostics, provided that future studies adopt rigorous protocols, transparent reporting, and clinically meaningful prospective validation.
- Full text:2026062719041428765（已压缩）zhengxilong.pdf
