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Med."],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Peripheral artery disease (PAD) is a vascular disease that leads to reduced blood flow to the limbs, often causing claudication symptoms that impair patients\u2019 ability to walk. The distance walked during a 6-min walk test (6MWT) correlates well with patient claudication symptoms, so we developed the VascTrac iPhone app as a platform for monitoring PAD using a digital 6MWT. In this study, we evaluate the accuracy of the built-in iPhone distance and step-counting algorithms during 6MWTs. One hundred and fourteen (114) participants with PAD performed a supervised 6MWT using the VascTrac app while simultaneously wearing an ActiGraph GT9X Activity Monitor. Steps and distance-walked during the 6MWT were manually measured and used to assess the bias in the iPhone CMPedometer algorithms. The iPhone CMPedometer step algorithm underestimated steps with a bias of \u22127.2%\u2009\u00b1\u200913.8% (mean\u2009\u00b1\u2009SD) and had a mean percent difference with the Actigraph (Actigraph-iPhone) of 5.7%\u2009\u00b1\u200920.5%. The iPhone CMPedometer distance algorithm overestimated distance with a bias of 43%\u2009\u00b1\u200942% due to overestimation in stride length. Our correction factor improved distance estimation to 8%\u2009\u00b1\u200932%. The Ankle-Brachial Index (ABI) correlated poorly with steps (<jats:italic>R<\/jats:italic>\u2009=\u20090.365) and distance (<jats:italic>R<\/jats:italic>\u2009=\u20090.413). Thus, in PAD patients, the iPhone\u2019s built-in distance algorithm is unable to accurately measure distance, suggesting that custom algorithms are necessary for using iPhones as a platform for monitoring distance walked in PAD patients. Although the iPhone accurately measured steps, more research is necessary to establish step counting as a clinically meaningful metric for PAD.<\/jats:p>","DOI":"10.1038\/s41746-018-0073-x","type":"journal-article","created":{"date-parts":[[2018,12,5]],"date-time":"2018-12-05T10:46:11Z","timestamp":1544006771000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":50,"title":["Clinical validation of smartphone-based activity tracking in peripheral artery disease patients"],"prefix":"10.1038","volume":"1","author":[{"given":"Raheel","family":"Ata","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neil","family":"Gandhi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hannah","family":"Rasmussen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Osama","family":"El-Gabalawy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Santiago","family":"Gutierrez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alizeh","family":"Ahmad","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siddharth","family":"Suresh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roshini","family":"Ravi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5123-5876","authenticated-orcid":false,"given":"Kara","family":"Rothenberg","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Oliver","family":"Aalami","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,12,11]]},"reference":[{"key":"73_CR1","doi-asserted-by":"publisher","first-page":"1317","DOI":"10.1001\/jama.286.11.1317","volume":"286","author":"AT Hirsch","year":"2001","unstructured":"Hirsch, A. 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