{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,26]],"date-time":"2026-10-26T12:16:51Z","timestamp":1793017011788,"version":"4.5.0"},"reference-count":29,"publisher":"Frontiers Media SA","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":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52402444"],"award-info":[{"award-number":["52402444"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Hum. Neurosci."],"abstract":"<jats:sec><jats:title>Introduction<\/jats:title><jats:p>Motion sickness often causes passengers to experience negative emotions such as tension, which in turn triggers symptoms like dizziness and nausea, seriously affecting the travel experience of passengers. Previous studies have shown that music can alleviate negative emotions such as tension, but its effect on motion sickness remains unclear, and the differences in the alleviation effect of different types of music on motion sickness need to be quantitatively evaluated.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We collected Electroencephalogram (EEG) data from 30 subjects in a simulated driving environment and constructed a motion sickness recognition model by combining time-and frequency-domain features (mean, variance, skewness, kurtosis, power spectral density) with classification algorithms. The model achieved accurate identification of passenger motion sickness states. Based on this model, the intervention effects of four types of music (joyful, sad, stirring, and soft) on motion sickness were further evaluated and compared with the control group (taking natural recovery measures).<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The results showed that soft and joyful music had better intervention effects (average reduction of 56.7 and 57.3%, respectively), followed by passionate and sad music (average reduction of 48.3 and 40%, respectively), among which the alleviation effect of sad music was lower than that of the control group (average reduction of 43.3%). In addition, it was verified that the EEG Kolmogorov-Chaitin complexity in the occipital region was significantly negatively correlated with the motion sickness grade <jats:italic>p<\/jats:italic> = \u22120.625, <jats:italic>p<\/jats:italic> &amp;lt; 0.005).<\/jats:p><\/jats:sec><jats:sec><jats:title>Discussion<\/jats:title><jats:p>The study suggests that personalized music intervention strategies may effectively alleviate motion sickness symptoms of passengers, thereby increasing cabin comfort and improving the travel experience of passengers.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fnhum.2025.1636109","type":"journal-article","created":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T05:37:10Z","timestamp":1756877830000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["A study on the mitigating effect of different music types on motion sickness based on EEG analysis"],"prefix":"10.3389","volume":"19","author":[{"given":"Yilun","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bingjie","family":"Luo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bangbei","family":"Tang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qizong","family":"Yue","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,9,3]]},"reference":[{"key":"ref1","first-page":"730218","article-title":"Methods of Eeg signal features extraction using linear analysis in frequency and time-frequency domains","volume":"2014","author":"Al-Fahoum","year":"2014","journal-title":"Int. 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