Improving the Accessibility of Smartwatches as Research Tools by Developing a Software Library

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dc.contributor.authorWanjara, Dhwan Devendraen
dc.contributor.committeechairBuehrer, Richard M.en
dc.contributor.committeechairLester, Luke F.en
dc.contributor.committeememberMartin, Thomas L.en
dc.contributor.committeememberVolpe, Stella L.en
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2022-06-14T08:00:22Zen
dc.date.available2022-06-14T08:00:22Zen
dc.date.issued2022-06-13en
dc.description.abstractOver the past 10 years, smartwatches have become increasingly popular for commercial use. Their ever-increasing capabilities, accuracy, and sophistication of smartwatches is making them increasingly appealing to physical activity researchers as a valuable research tool. The non-invasive nature, prevalence, and versatility of smartwatches is being utilized to track heart rate, blood-oxygen levels, activity and movement, and sleep. However, the current state of the art lacks a uniform method to extract, organize, and analyze data collected from these devices. The objective of this research was to develop a Python software library that is widely available, highly capable, and easy to use with the data collected by the Apple Watch. The library was designed to offer data science, visualization, and mining features that help physical activity research find and communicate patterns in the Apple Health data. The custom-built caching system of the library provides near-instant runtime to parse and analyze large files without trading off on memory usage. The Wanjara Smartwatch Library has significantly better performance, proven reliability and robustness, and improved usability than the alternatives discovered in the review of the literature.en
dc.description.abstractgeneralOver the past 10 years, smartwatches have become increasingly popular for commercial use. Their ever-increasing capabilities, accuracy, and sophistication of smartwatches is making them increasingly appealing to physical activity researchers as a valuable research tool. The non-invasive nature, prevalence, and versatility of smartwatches is being utilized to track heart rate, blood-oxygen levels, activity and movement, and sleep. However, the current state of the art lacks a uniform method to extract, organize, and analyze data collected from these devices. The objective of this research was to develop a Python software library that is widely available, highly capable, and easy to use with the data collected by the Apple Watch. The library was designed to offer data science, visualization, and mining features that help physical activity research find and communicate patterns in the Apple Health data. The custom-built caching system of the library provides near-instant runtime to parse and analyze large files without trading off on memory usage. The Wanjara Smartwatch Library has significantly better performance, proven reliability and robustness, and improved usability than the alternatives discovered in the review of the literature.en
dc.description.degreeMaster of Scienceen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:34814en
dc.identifier.urihttp://hdl.handle.net/10919/110763en
dc.language.isoenen
dc.publisherVirginia Techen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectApple Watchen
dc.subjectApple Health Dataen
dc.subjectPython Libraryen
dc.subjectHealth and Exerciseen
dc.subjectSmartwatchen
dc.subjectsoftware libraryen
dc.titleImproving the Accessibility of Smartwatches as Research Tools by Developing a Software Libraryen
dc.typeThesisen
thesis.degree.disciplineComputer Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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