{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T20:46:59Z","timestamp":1793134019409,"version":"4.5.0"},"reference-count":64,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T00:00:00Z","timestamp":1780617600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Medicina"],"abstract":"<jats:p>Heart rate variability (HRV) is widely used as a non-invasive marker of autonomic regulation and physiological adaptability, with relevance across cardiovascular, metabolic, neuropsychiatric, and stress-related conditions. HRV biofeedback has emerged as a non-pharmacological intervention intended to influence autonomic function through paced breathing, resonance-frequency training, and real-time physiological feedback. Although this approach has shown promise in improving stress regulation, emotional symptoms, autonomic balance, and selected cardiovascular outcomes, its effects are not consistent across individuals or clinical states. The reasons for this variability remain insufficiently conceptualized. In this narrative conceptual review, we propose the concept of autonomic non-responsiveness during HRV biofeedback as a descriptive framework for situations in which expected autonomic engagement is weakened, absent, or fails to translate into meaningful physiological or clinical benefit. We discuss potential contributors to non-response, including reduced autonomic flexibility, impaired baroreflex function, disease burden, fatigue, stress-related overload, dysfunctional breathing, methodological limitations, and cognitive-behavioral constraints. We then consider the clinical implications of recognizing non-response as a potentially informative state rather than a simple negative outcome. Finally, we outline a future research agenda focused on operational definition, candidate biomarkers, temporal characterization, and minimally adaptive closed-loop systems.<\/jats:p>","DOI":"10.3390\/medicina62061102","type":"journal-article","created":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T08:43:04Z","timestamp":1780648984000},"page":"1102","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Autonomic Non-Responsiveness in HRV Biofeedback: A Narrative Conceptual Review and Future Directions for AI-Guided Closed-Loop Adaptive Systems"],"prefix":"10.3390","volume":"62","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3424-1588","authenticated-orcid":false,"given":"Alexandru","family":"Burlacu","sequence":"first","affiliation":[{"name":"Faculty of Medicine, University of Medicine and Pharmacy \u201cGrigore T Popa\u201d, 700115 Iasi, Romania"},{"name":"Institute of Cardiovascular Diseases \u201cProf. Dr. George I.M. Georgescu\u201d, 700503 Iasi, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6253-3203","authenticated-orcid":false,"given":"Crischentian","family":"Brinza","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, University of Medicine and Pharmacy \u201cGrigore T Popa\u201d, 700115 Iasi, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3564-8440","authenticated-orcid":false,"given":"Adrian","family":"Iftene","sequence":"additional","affiliation":[{"name":"Computer Science Department, Faculty of Informatics, Alexandru Ioan Cuza University, 700506 Iasi, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roxana-Elena","family":"Bogdan-Goroftei","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, \u201cDunarea de Jos\u201d University, 800010 Galati, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oana","family":"Geman","sequence":"additional","affiliation":[{"name":"Division of Data Science and Artificial Intelligence, Computer Science and Engineering, Chalmers University of Technology, 412 96 Gothenburg, Sweden"},{"name":"Division of Data Science and Artificial Intelligence, Computer Science and Engineering, University of Gothenburg, 405 30 Gothenburg, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,5]]},"reference":[{"key":"ref_1","unstructured":"Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology (1996). 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