{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T05:16:00Z","timestamp":1783055760470,"version":"3.54.6"},"reference-count":65,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T00:00:00Z","timestamp":1783036800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Radial pulse harmonic analysis has emerged as a quantitative frequency-domain approach for non-invasive assessment of cardiovascular and metabolic physiology through characterization of arterial hemodynamics. By decomposing radial pressure pulse waveforms into harmonic components, this method provides physiologically interpretable information regarding arterial compliance, wave reflection, vascular resistance, and ventricular\u2013arterial coupling that may not be fully captured by conventional blood pressure measurements or time-domain indices.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This mini review summarizes the theoretical foundations, signal-processing framework, methodological developments, and clinical applications of radial pulse harmonic analysis. Particular emphasis is placed on its role in the assessment of hypertension, diabetes mellitus, coronary artery disease, vascular aging, and autonomic dysfunction, as well as its integration with emerging computational cardiovascular technologies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The reviewed evidence demonstrates that harmonic parameters are consistently associated with arterial stiffness, endothelial dysfunction, autonomic dysregulation, vascular remodeling, and age-related hemodynamic alterations. Advances in sensor technology, signal acquisition protocols, signal-processing algorithms, and computational modeling have improved the reproducibility and translational potential of harmonic analysis. In addition to established cardiometabolic applications, emerging approaches such as Reservoir-Excess Pressure Analysis, photoplethysmography-derived biomarkers, wearable sensing technologies, and computational fluid dynamics-based vascular modeling may further enhance the physiological interpretation and clinical utility of pulse waveform analysis. Collectively, these developments support the use of harmonic analysis as a complementary biomarker framework for non-invasive cardiovascular assessment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Radial pulse harmonic analysis represents a promising computational and translational framework for non-invasive vascular assessment and cardiometabolic risk evaluation. By providing quantitative insights into vascular function and systemic hemodynamics, harmonic analysis may complement existing cardiovascular biomarkers and contribute to precision cardiovascular medicine. Nevertheless, further methodological standardization, mechanistic validation, and large-scale prospective studies are required before broader clinical implementation can be established.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2026.1867056","type":"journal-article","created":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T04:21:46Z","timestamp":1783052506000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Radial pulse harmonic analysis for cardiometabolic assessment: a computational and translational mini review"],"prefix":"10.3389","volume":"17","author":[{"given":"Chung-Hung","family":"Wu","sequence":"first","affiliation":[{"name":"Department of Chinese Medicine, Taichung Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation","place":["Taichung, Taiwan"]},{"name":"School of Post-Baccalaureate Chinese Medicine, Tzu Chi University","place":["Hualien, Taiwan"]},{"name":"Graduate Institute of Acupuncture Science, China Medical University","place":["Taichung, Taiwan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian-Jung","family":"Chen","sequence":"additional","affiliation":[{"name":"Graduate Institute of Acupuncture Science, China Medical University","place":["Taichung, Taiwan"]},{"name":"Institute of Medical Sciences, Tzu Chi University","place":["Hualien, Taiwan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hsientsai","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Dong Hwa University","place":["Hualien, Taiwan"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,3]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104358","article-title":"Computational traditional Chinese medicine diagnosis: a literature 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