{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T06:47:57Z","timestamp":1789541277615,"version":"build-2803163510"},"reference-count":33,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T00:00:00Z","timestamp":1756857600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Research Foundation of Korea (NRF)","award":["NRF-2022R1A2C1005797"],"award-info":[{"award-number":["NRF-2022R1A2C1005797"]}]},{"name":"National Research Foundation of Korea (NRF)","award":["HI22C0520"],"award-info":[{"award-number":["HI22C0520"]}]},{"name":"National Research Foundation of Korea (NRF)","award":["P0018138"],"award-info":[{"award-number":["P0018138"]}]},{"name":"Ministry of Health &amp; Welfare, Republic of Korea","award":["NRF-2022R1A2C1005797"],"award-info":[{"award-number":["NRF-2022R1A2C1005797"]}]},{"name":"Ministry of Health &amp; Welfare, Republic of Korea","award":["HI22C0520"],"award-info":[{"award-number":["HI22C0520"]}]},{"name":"Ministry of Health &amp; Welfare, Republic of Korea","award":["P0018138"],"award-info":[{"award-number":["P0018138"]}]},{"name":"Korea Institute for Advancement of Technology","award":["NRF-2022R1A2C1005797"],"award-info":[{"award-number":["NRF-2022R1A2C1005797"]}]},{"name":"Korea Institute for Advancement of Technology","award":["HI22C0520"],"award-info":[{"award-number":["HI22C0520"]}]},{"name":"Korea Institute for Advancement of Technology","award":["P0018138"],"award-info":[{"award-number":["P0018138"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Objectives: Virtual reality (VR) has emerged as a promising tool for assessing anxiety-related disorders through immersive exposure and physiological monitoring. This study aimed to evaluate whether multimodal data, including heart rate variability (HRV), skin conductance response (SCR), and self-reported anxiety, collected during VR exposure could classify patients with panic disorder and agoraphobia using machine learning models. Methods: Seventy-six participants (38 patients with panic disorder and agoraphobia, 38 healthy controls) completed 295 total VR exposure sessions. Each session involved two road and two supermarket scenarios designed to induce anxiety. Inside the sessions, self-reported anxiety was measured along with physiological signals recorded by photoplethysmography and SCR sensors. HRV measures of heart rate, standard deviation of normal-to-normal intervals, and low-frequency to high-frequency ratio were extracted along with SCR peak frequency and average amplitude. These features were analyzed using Gaussian Na\u00efve Bayes (GNB), k-Nearest Neighbors (k-NN), Logistic Ridge Regression (LRR), C-Support Vector Machine (SVC), Random Forest (RF), and Stochastic Gradient Boosting (SGB) classifiers. Results: The best model achieved an accuracy of 0.83. Most models showed specificity and precision \u22650.80, while sensitivity varied across models, with several reaching \u22650.82. Performance was stable across major hyperparameters, VR-stimulus settings, and medication status. The patients reported higher subjective anxiety but exhibited blunted physiological responses, particularly in SCR amplitude. Self-reported anxiety demonstrated higher feature importance scores compared to other physiological properties. Conclusion: VR exposure with self-reported anxiety and physiological measures may serve as a feasible diagnostic aid for panic disorder and agoraphobia. Further refinement is needed to improve sensitivity and clinical applicability.<\/jats:p>","DOI":"10.3390\/diagnostics15172239","type":"journal-article","created":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T15:15:57Z","timestamp":1756912557000},"page":"2239","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Virtual Reality-Based Multimodal Approach to Diagnosing Panic Disorder and Agoraphobia Using Physiological Measures: A Machine Learning Study"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8294-5451","authenticated-orcid":false,"given":"Han Wool","family":"Jung","sequence":"first","affiliation":[{"name":"Department of Psychiatry, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin 16995, Republic of Korea"},{"name":"Department of Integrative Medicine, Yonsei University College of Medicine, Seoul 06229, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyun","family":"Park","sequence":"additional","affiliation":[{"name":"Division of Software, Hallym University, Chuncheon 24252, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5645-6531","authenticated-orcid":false,"given":"Seon-Woo","family":"Lee","sequence":"additional","affiliation":[{"name":"Division of Software, Hallym University, Chuncheon 24252, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9387-9688","authenticated-orcid":false,"given":"Ki Won","family":"Jang","sequence":"additional","affiliation":[{"name":"Mind-Neuromodulation Laboratory, Hallym University College of Medicine, Chuncheon 24253, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9573-7413","authenticated-orcid":false,"given":"Sangkyu","family":"Nam","sequence":"additional","affiliation":[{"name":"Mind-Neuromodulation Laboratory, Hallym University College of Medicine, Chuncheon 24253, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jong Sub","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Psychology, Hallym University, Chuncheon 24252, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0151-544X","authenticated-orcid":false,"given":"Moo Eob","family":"Ahn","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine, Hallym University College of Medicine, Chuncheon 24253, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6714-850X","authenticated-orcid":false,"given":"Sang-Kyu","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, Hallym University College of Medicine, Chuncheon 24253, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6564-3774","authenticated-orcid":false,"given":"Yeo Jin","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Neurology, Kangdong Sacred Heart Hospital, Seoul 05355, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7242-9496","authenticated-orcid":false,"given":"Daeyoung","family":"Roh","sequence":"additional","affiliation":[{"name":"Mind-Neuromodulation Laboratory, Hallym University College of Medicine, Chuncheon 24253, Republic of Korea"},{"name":"Department of Psychiatry, Hallym University College of Medicine, Chuncheon 24253, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2393","DOI":"10.1017\/S003329171700040X","article-title":"Virtual reality in the assessment, understanding, and treatment of mental health disorders","volume":"47","author":"Freeman","year":"2017","journal-title":"Psychol. 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