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From Raw to Big Data in Endurance Running

Body-worn sensors, so-called wearables, are getting more and more popular in the sports domain. Wearables offer real-time feedback to athletes on technique and performance, while researchers can generate insights into the biomechanics and sports physiology of the athletes in real-world sports enviro...

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Hovedforfatter: Zrenner, Markus
Format: Online
Sprog:engelsk
Udgivet: FAU University Press 2025
Fag:
Machine Learning
Maschinelles Lernen
Big Data
Wearable Computer
Data Science
Marathonlauf
Endurance Running
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJS Sensors
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general::GPH Data science and analysis: general
Online adgang:ONIX_20251215T160703_9783961475391_6
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Summary:Body-worn sensors, so-called wearables, are getting more and more popular in the sports domain. Wearables offer real-time feedback to athletes on technique and performance, while researchers can generate insights into the biomechanics and sports physiology of the athletes in real-world sports environments outside of laboratories. One of the first sports disciplines, where many athletes have been using wearable devices, is endurance running. With the rising popularity of smartphones, smartwatches and inertial measurement units (IMUs), many runners started to track their performance and keep a digital training diary. Due to the high number of runners worldwide, which transferred their data of wearables to online fitness platforms, large databases were created, which enable Big Data analysis of running data. This kind of analysis offers the potential to conduct longitudinal sports science studies on a larger number of participants than ever before. In this dissertation, both studies showing how to extract endurance running-related parameters from raw data of foot-mounted IMUs as well as a Big Data study with running data from a fitness platform are presented.

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