{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,2]],"date-time":"2026-11-02T22:38:58Z","timestamp":1793659138235,"version":"4.5.1"},"reference-count":29,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"the China Key Scientific Grant","award":["Grant No. 2021YFC0122500"],"award-info":[{"award-number":["Grant No. 2021YFC0122500"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["DIGITAL HEALTH"],"published-print":{"date-parts":[[2025,5]]},"abstract":"\n Background<\/jats:title>\n \n COPD underdiagnosis persists in China due to limited spirometry access. Smart wearables enabling cough and physiological monitoring (SpO\n 2<\/jats:sub>\n , respiratory rate) offer a scalable screening solution.\n <\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n Participants were randomly allocated to training and validation cohorts. All underwent cough sound recordings, smartwatch monitoring (heart rate variability, respiratory rate, oxygen saturation), and pre-\/post-bronchodilator spirometry. Machine learning algorithms extracted cough sound features to predict lung function (evaluated via MAE, Pearson correlation, and Bland-Altman analysis). These predictions were combined with physiological data in a multimodal COPD screening model, with diagnostic performance assessed against physician diagnosis.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n The training cohort included 178 patients (112 males) with COPD or pulmonary dysfunctions, aged 54.42\u2009\u00b1\u200914.77 years, BMI 24.81\u2009\u00b1\u20093.73 kg\/m\u00b2, FVC 3.64\u2009\u00b1\u20091.09 L, and FEV\n 1<\/jats:sub>\n 2.42\u2009\u00b1\u20090.96 L, alongside 298 healthy volunteers (151 males) aged 35.3\u2009\u00b1\u200912.35 years, BMI 22.62\u2009\u00b1\u20093.12 kg\/m\u00b2, FVC 3.63\u2009\u00b1\u20090.89 L, and FEV\n 1<\/jats:sub>\n 3.14\u2009\u00b1\u20090.73 L. The validation cohort comprised 47 COPD patients (35 males) aged 65.53\u2009\u00b1\u20097.62 years, BMI 25.38\u2009\u00b1\u20094.38 kg\/m\u00b2, FVC 3.27\u2009\u00b1\u20090.59 L, and FEV\n 1<\/jats:sub>\n 1.91\u2009\u00b1\u20090.50 L, and 71 healthy controls (27 males) aged 45.51\u2009\u00b1\u200912.15 years, BMI 25.79\u2009\u00b1\u20094.00 kg\/m\u00b2, FVC 3.35\u2009\u00b1\u20090.80 L, and FEV\n 1<\/jats:sub>\n 2.72\u2009\u00b1\u20090.67 L. Using cough sounds, the model's mean absolute error for FEV\n 1<\/jats:sub>\n \/FVC, FVC%, and FEV\n 1<\/jats:sub>\n % prediction was 7.4%, 10.6%, and 17.78% (\n Table 3<\/jats:xref>\n \n \u2013\n 5<\/jats:xref>\n ), respectively, compared to spirometry. Significant correlations were found between predicted and measured FVC (r\u2009=\u20090.798, P\u2009<\u20090.001), FEV\n 1<\/jats:sub>\n (r\u2009=\u20090.752, P\u2009<\u20090.001), and FEV\n 1<\/jats:sub>\n \/FVC (r\u2009=\u20090.784,\u2009<\u20090.001) (\n Table 6<\/jats:xref>\n ). Combined with physiological parameters, our model's overall accuracy, sensitivity, and specificity for differentiating between COPD and normal controls were 87.82%, 86.96%, and 87.73% (\n Table 9<\/jats:xref>\n ).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n Our wearable-based algorithm effectively screens for ventilatory dysfunction and COPD, showing potential for large-scale population screening to reduce medical burdens.<\/jats:p>\n <\/jats:sec>\n \n Trial Registration<\/jats:title>\n \n Chinese Clinical Trial Registry of the International Clinical Trials Registry Platform of the World Health Organization ChiCTR2100050843; Registration Date: 2021-9-4 Clinical Trial Number: ChiCTR2100050843.\n https:\/\/www.chictr.org.cn\/showproj.html?proj=126556<\/jats:ext-link>\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1177\/20552076251377938","type":"journal-article","created":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T17:53:08Z","timestamp":1758131588000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":5,"title":["Smartwatch-based ventilatory assessment for COPD screening: A diagnostic accuracy study"],"prefix":"10.1177","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7444-3088","authenticated-orcid":false,"given":"Yibing","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lu","family":"Cao","sequence":"additional","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dahui","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Song","family":"Meng","sequence":"additional","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Li","sequence":"additional","affiliation":[{"name":"Senior Department of Pulmonary and Critical Care Medicine, Chinese PLA General Hospital, Beijing, 100091, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Li","sequence":"additional","affiliation":[{"name":"Huawei Device Co., Ltd, Shenzhen, 518129, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuqi","family":"Cui","sequence":"additional","affiliation":[{"name":"Huawei Device Co., Ltd, Shenzhen, 518129, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lixin","family":"Xie","sequence":"additional","affiliation":[{"name":"Senior Department of Pulmonary and Critical Care Medicine, Chinese PLA General Hospital, Beijing, 100091, China"},{"name":"Chinese Association of Geriatric Research, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,9,17]]},"reference":[{"key":"e_1_3_3_2_2","first-page":"585","article-title":"Prevalence and attributable health burden of chronic respiratory diseases, 1990-2017: a systematic analysis for the global burden of disease study 2017","volume":"8","author":"GBD Chronic Respiratory Disease Collaborators","unstructured":"GBD Chronic Respiratory Disease Collaborators. 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