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http://arks.princeton.edu/ark:/88435/dsp01p5547t99r
Full metadata record
DC Field | Value | Language |
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dc.contributor.advisor | Funkhouser, Thomas A. | - |
dc.contributor.author | Hanss, Katie | - |
dc.date.accessioned | 2017-07-20T13:26:58Z | - |
dc.date.available | 2017-07-20T13:26:58Z | - |
dc.date.created | 2017-05-04 | - |
dc.date.issued | 2017-5-4 | - |
dc.identifier.uri | http://arks.princeton.edu/ark:/88435/dsp01p5547t99r | - |
dc.description.abstract | Distance and middle distance runners keep detailed logs to understand the relationship betweentheir training, performance and injury. However, the current online running log tools fall shortof helping them achieve this goal. Many websites do not track injuries and performances andnone will display this information alongside training data. Furthermore, the current online run-ning log tools have not integrated the latest sports medicine research which sheds light on therelationship between training and injury. In response to this need, we developed HackTrack: anonline running log that helps athletes understand training, performance and injury. HackTrackincorporates four novel features to achieve this goal: (1) we track an athlete’s session rate of per-ceived exertion (sRPE) to measure their training intensity; (2) we display acute : chronic sRPEand distance – a ratio the literature has shown to be predictive of injury; (3) we allow athletesto log and visualize performance and injury alongside training volume; (4) we allow athletes totrack customizable tags and visualize them alongside training volume. We launched HackTrackto Princeton’s Women’s Cross Country team and 20 athletes used it consistently for 1.5 months.While around 20% of participants were unhappy with HackTrack’s tag visualization, nearly 90%of our users liked the way HackTrack logged and visualized their training. Furthermore, many ofthe users who logged injuries or performances said HackTrack’s visualization tool helped themunderstand training, performance and injury. While we did not collect enough data to formallyinvestigate the relationship between acute : chronic ratio, injury and performance, an initial anal-ysis supports the existing literature by suggesting our athletes who reported injury had relativelyhigh acute : chronic ratios the proceeding week. | en_US |
dc.language.iso | en_US | en_US |
dc.title | HackTrack: Improving Performance, Preventing Injury | en_US |
dc.type | Princeton University Senior Theses | - |
pu.date.classyear | 2017 | en_US |
pu.department | Computer Science | en_US |
pu.pdf.coverpage | SeniorThesisCoverPage | - |
pu.contributor.authorid | 960855846 | - |
pu.contributor.advisorid | 910083875 | - |
Appears in Collections: | Computer Science, 1988-2020 |
Files in This Item:
File | Size | Format | |
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written_final_report.pdf | 3.64 MB | Adobe PDF | Request a copy |
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