{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T10:50:21Z","timestamp":1782989421772,"version":"3.54.5"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686684","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T00:00:00Z","timestamp":1782691200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,6,29]]},"abstract":"<jats:p>Music therapy has been shown to promote emotional well-being by reducing symptoms of mental disorders and improving quality of life. As artificial intelligence (AI) techniques are increasingly used in music analysis and generation, it is important to understand their alignment with human emotional responses. This study presents a preliminary investigation comparing AI-based mood analysis and 21 participants\u2019 skin conductance responses to a negatively valenced classical music excerpt. Results showed a discrepancy between the dominant emotion identified by the AI tool and the intended target emotion in the experimental design. Significant alignment was observed between AI-generated mood probability and skin conductance responses. Findings indicate the potential of AI-based emotion recognition systems for supporting music selection in music-based interventions, while also highlighting the need for careful human validation.<\/jats:p>","DOI":"10.3233\/shti260866","type":"book-chapter","created":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T10:01:26Z","timestamp":1782986486000},"source":"Crossref","is-referenced-by-count":0,"title":["Exploring the Alignment of AI-Based Mood Labelling with Human Responses: Implications for Music-Based Mental Health Interventions"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-8261-6480","authenticated-orcid":false,"given":"Cen","family":"Cong","sequence":"first","affiliation":[{"name":"Newcastle University, Newcastle upon Tyne, NE1 7RU, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Health Sciences Informatics Leads and Empowers the Digital Health Transformation"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI260866","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T10:01:27Z","timestamp":1782986487000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI260866"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,29]]},"ISBN":["9781643686684"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti260866","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,29]]}}}