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This study presents a method for detecting sleep apnea using data from the Apple Watch\u2019s inertial measurement unit (IMU).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>An algorithm was developed to extract seismocardiographic and respiratory signals from IMU data, analyzing features such as breathing and heart rate variability, respiratory dips, and body movements. In a cohort of 61 adults undergoing polysomnography, we analyzed 52,337 30-second epochs, with 12,373 (23.6%) identified as apnea\/hypopnea episodes. Machine learning models using five classifiers (Logistic Regression, Random Forest, Gradient Boosting, k-Nearest Neighbors, and Multi-layer Perceptron) were trained on data from 41 subjects and validated on 20 subjects.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The Random Forest classifier performed best in per-epoch respiratory event detection, achieving an AUC of 0.827 and an F1 score of 0.572 in the training group, and an AUC of 0.831 and an F1 score of 0.602 in the test group. The model\u2019s per-subject predictions strongly correlated with the apnea-hypopnea index (AHI) from polysomnography (\n                      <jats:italic>r<\/jats:italic>\n                      \u2009=\u20090.93) and identified subjects with AHI\u2009\u2265\u200915 with 100% sensitivity and 90% specificity.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Utilizing the widespread availability of the Apple Watch and the low power requirements of the IMU, this approach has the potential to significantly improve sleep apnea screening accessibility.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s11325-025-03255-w","type":"journal-article","created":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T08:42:11Z","timestamp":1738399331000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Detection of sleep apnea using only inertial measurement unit signals from apple watch: a pilot-study with machine learning approach"],"prefix":"10.1007","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5340-6325","authenticated-orcid":false,"given":"Junichiro","family":"Hayano","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mine","family":"Adachi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yutaka","family":"Murakami","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fumihiko","family":"Sasaki","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1865-7735","authenticated-orcid":false,"given":"Emi","family":"Yuda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,2,1]]},"reference":[{"key":"3255_CR1","doi-asserted-by":"publisher","first-page":"233","DOI":"10.2147\/nss.S6844","volume":"2","author":"T Gharibeh","year":"2010","unstructured":"Gharibeh T, Mehra R (2010) Obstructive sleep apnea syndrome: natural history, diagnosis, and emerging treatment options. 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Y.M. is employed by Sony Group Corporation. The other authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"All procedures were performed in accordance with the Regulations Concerning the Conduct of Life Science and Medical Research Involving Human Subjects at Tohoku University, Japan, the Ethical Guidelines for Medical Research Involving Human Subjects issued by the Japanese Ministry of Health, Labor and Welfare, and the 1964 Declaration of Helsinki and its subsequent amendments. The study protocol was approved by the Research Ethics Committee of the Graduate School of Information Sciences, Tohoku University, Japan (approved number 23\u00a0A-02). All subjects who participated in this study gave written informed consent, including consent to the publication of this paper.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"All subjects who participated in this study gave written informed consent, including consent to the publication of this paper.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}}],"article-number":"91"}}