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Med."],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>As wearable technologies are being increasingly used for clinical research and healthcare, it is critical to understand their accuracy and determine how measurement errors may affect research conclusions and impact healthcare decision-making. Accuracy of wearable technologies has been a hotly debated topic in both the research and popular science literature. Currently, wearable technology companies are responsible for assessing and reporting the accuracy of their products, but little information about the evaluation method is made publicly available. Heart rate measurements from wearables are derived from photoplethysmography (PPG), an optical method for measuring changes in blood volume under the skin. Potential inaccuracies in PPG stem from three major areas, includes (1) diverse skin types, (2) motion artifacts, and (3) signal crossover. To date, no study has systematically explored the accuracy of wearables across the full range of skin tones. Here, we explored heart rate and PPG data from consumer- and research-grade wearables under multiple circumstances to test whether and to what extent these inaccuracies exist. We saw no statistically significant difference in accuracy across skin tones, but we saw significant differences between devices, and between activity types, notably, that absolute error during activity was, on average, 30% higher than during rest. Our conclusions indicate that different wearables are all reasonably accurate at resting and prolonged elevated heart rate, but that differences exist between devices in responding to changes in activity. This has implications for researchers, clinicians, and consumers in drawing study conclusions, combining study results, and making health-related decisions using these devices.<\/jats:p>","DOI":"10.1038\/s41746-020-0226-6","type":"journal-article","created":{"date-parts":[[2020,2,10]],"date-time":"2020-02-10T11:02:57Z","timestamp":1581332577000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":549,"title":["Investigating sources of inaccuracy in wearable optical heart rate sensors"],"prefix":"10.1038","volume":"3","author":[{"given":"Brinnae","family":"Bent","sequence":"first","affiliation":[]},{"given":"Benjamin A.","family":"Goldstein","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5622-7659","authenticated-orcid":false,"given":"Warren A.","family":"Kibbe","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3241-8183","authenticated-orcid":false,"given":"Jessilyn P.","family":"Dunn","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,2,10]]},"reference":[{"key":"226_CR1","unstructured":"Chronic Diseases in America | CDC. https:\/\/www.cdc.gov\/chronicdisease\/resources\/infographic\/chronic-diseases.htm (2019)."},{"key":"226_CR2","unstructured":"Health Care Cost and Utilization Report 2017 (2019)."},{"key":"226_CR3","unstructured":"Older Americans Drive Growth of Wearables. eMarketer https:\/\/www.emarketer.com\/content\/older-americans-drive-growth-of-wearables (2018)."},{"key":"226_CR4","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1111\/nyas.13117","volume":"1375","author":"B Munos","year":"2016","unstructured":"Munos, B. et al. 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