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From Raw to Big Data in Endurance Running : Application of Data Science Techniques for Knowledge Creation from Wearable Sensor Data

Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: FAU Studien aus der InformatikPublisher: Erlangen : FAU University Press, 2022Description: 1 Online-Ressource (1 electronic resource 179 p.)ISBN:
  • 9783961475384
  • 9783961475391
Subject(s): Online resources: 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 presentedPPN: PPN: 1983978051Package identifier: Produktsigel: ZDB-94-OAB
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Open Access. Unrestricted online access star

Namensnennung 4.0 International CC BY 4.0 cc:

https://creativecommons.org/licenses/by/4.0/

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