Clinical validation of smartphone-based activity tracking in peripheral artery disease patients

Author:

Ata Raheel,Gandhi Neil,Rasmussen Hannah,El-Gabalawy Osama,Gutierrez Santiago,Ahmad Alizeh,Suresh Siddharth,Ravi Roshini,Rothenberg KaraORCID,Aalami Oliver

Abstract

AbstractPeripheral artery disease (PAD) is a vascular disease that leads to reduced blood flow to the limbs, often causing claudication symptoms that impair patients’ 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 −7.2% ± 13.8% (mean ± SD) and had a mean percent difference with the Actigraph (Actigraph-iPhone) of 5.7% ± 20.5%. The iPhone CMPedometer distance algorithm overestimated distance with a bias of 43% ± 42% due to overestimation in stride length. Our correction factor improved distance estimation to 8% ± 32%. The Ankle-Brachial Index (ABI) correlated poorly with steps (R = 0.365) and distance (R = 0.413). Thus, in PAD patients, the iPhone’s 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.

Funder

Precision Health and Integrated Diagnostics Center at Stanford. Clinical Translational Research Spectrum Stanford Predictives and Diagnostics Center

Publisher

Springer Science and Business Media LLC

Subject

Health Information Management,Health Informatics,Computer Science Applications,Medicine (miscellaneous)

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