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Predicting runners’ oxygen consumption on flat terrain using accelerometer data
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2019 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Prediktera löpares syrekonsumtion på platt terräng genom accelerometerdata (Swedish)
Abstract [en]

This project aimed to use accelerometer data and KPIs to predict the oxygen consumption of runners’ during exercises on flat terrain. Based on many studies researching the relationship between oxygen consumption and running economy and a small set of data, a model was constructed which had a prediction accuracy of 81.1% on one individual. Problems encountered during the research include issues with comparing data from different systems, model nonlinearity and data noise. These problems were solved using transformation of data in the R software, model re-specification and identifying outlying observations that could be viewed as noise. The results from this project should be seen as a proof of concept for further studies, showing that it is possible to predict oxygen consumption using a set of accelerometer data and KPIs. With a larger sample set this model can be validated and furthermore implemented in Racefox’s current service as a calibration method of individual results and an early warning system to avoid running economy deficiency.

Abstract [sv]

Detta projekts målsättning var att använda accelerometerdata och KPI-värden för att prediktera syrekonsumtion för löpare på plan mark. Baserat på ett urval av studier om korrelationen mellan syrekonsumtion och löpekonomi samt en liten mängd data så konstruerades en modell med en förklaringsgrad på 81.1% på en individ. Svårigheter under arbetet inkluderar datajämförelser, icke-linjäriteter och databrus. Detta hanterades genom datatransformationer i mjukvaran R, modell-modifikationer och identifikation av avvikande data som kunde klassificeras som brus. Resultaten kan ses som en förstudie som indikerar att det är möjligt att prediktera syrekonsumtion genom accelerometerdata och KPI-värden. En fortsatt större studie med fler individer och mätningar som underlag kan validera denna slutsats samt då implementeras i Racefoxs nuvarande tjänst som en kalibreringsmetod för individuella resultat och som ett varningssystem för att undvika försämrad löpekonomi.

Place, publisher, year, edition, pages
2019.
Series
TRITA-SCI-GRU ; 2019:146
Keywords [en]
Bachelor Thesis, Prediciting oxygen consumption, Accelerometer, Fitness technology
Keywords [sv]
Kandidatexamensarbete, Prediktion av syrekonsumtion, Accelerometer, Träningselektronik
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:kth:diva-252749OAI: oai:DiVA.org:kth-252749DiVA, id: diva2:1333510
External cooperation
Racefox
Subject / course
Applied Mathematics and Industrial Economics
Educational program
Master of Science in Engineering - Industrial Engineering and Management
Supervisors
Examiners
Available from: 2019-07-01 Created: 2019-07-01 Last updated: 2019-07-01Bibliographically approved

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CiteExportLink to record
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