Abstract:
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As of its latest 2016 data, the World Health Organization posits that the top two leading causes of death in the world stem from cardiovascular etiologies. Due to the large and increasing incidence rate of cardiovascular illness around the world, the analysis of data from clinical trials can play a fundamental role in identifying potential signals indicating an improvement in disease status or patient quality of life. The implementation of wearable devices in clinical trials are of particular interest due to their ability to continuously capture data, as opposed to traditional data collection methods which only occur at scheduled visits. In our current study, we used a Medtronic Avivo device, which captured time-series data at several different resolutions. Patients in the study wore the device in 7-day intervals at three separate periods throughout the study. The device collected summary data, such as activity intensity at hourly and daily resolutions, as well as high-resolution data at a 4-second interval, containing triaxial accelerometer counts. Our work examines methods of processing this high-resolution data along with additional insights gained from the high-resolution data.
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