Towards better measurability - IMU-based feature extractors for motion performance evaluation

Heike Brock, Yuji Ohgi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Capturing human motion performances with inertial measurement units constitutes the future of mobile sports analysis, but requires sophisticated methods to extract relevant information out of the sparse and unintuitive inertial sensor data. Kinematic data like body joint positions and segment orientations can be estimated from a sensor’s accelerations and angular velocities. For further analysis, it is necessary to develop intelligent retrieval strategies that can make sense of the underlying motion information. In this paper, we therefore discuss how to retrieve main motion determinants from raw and processed inertial sensor data. We design methods that extract a motion’s significant technical elements as well as methods that combine several measurable elements over time to extract motion features responsible for the aesthetic impression of a sports performance. In a neural network environment those feature extractors can then give the possibility to automatically evaluate and rank different performances in mobile training and competition systems, which could contribute to a better measurability and objectivity in performance-oriented sports as gymnastics and figure skating.

Original languageEnglish
Title of host publicationAdvances in Intelligent Systems and Computing
PublisherSpringer Verlag
Pages109-116
Number of pages8
Volume392
ISBN (Print)9783319245584
DOIs
Publication statusPublished - 2016
Event10th International Symposium of Computer Science in Sport, IACSS/ISCSS 2015 - Loughborough, United Kingdom
Duration: 2015 Sep 92015 Sep 11

Publication series

NameAdvances in Intelligent Systems and Computing
Volume392
ISSN (Print)21945357

Other

Other10th International Symposium of Computer Science in Sport, IACSS/ISCSS 2015
CountryUnited Kingdom
CityLoughborough
Period15/9/915/9/11

Fingerprint

Sports
Sensors
Units of measurement
Angular velocity
Kinematics
Neural networks

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Brock, H., & Ohgi, Y. (2016). Towards better measurability - IMU-based feature extractors for motion performance evaluation. In Advances in Intelligent Systems and Computing (Vol. 392, pp. 109-116). (Advances in Intelligent Systems and Computing; Vol. 392). Springer Verlag. https://doi.org/10.1007/978-3-319-24560-7_14

Towards better measurability - IMU-based feature extractors for motion performance evaluation. / Brock, Heike; Ohgi, Yuji.

Advances in Intelligent Systems and Computing. Vol. 392 Springer Verlag, 2016. p. 109-116 (Advances in Intelligent Systems and Computing; Vol. 392).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Brock, H & Ohgi, Y 2016, Towards better measurability - IMU-based feature extractors for motion performance evaluation. in Advances in Intelligent Systems and Computing. vol. 392, Advances in Intelligent Systems and Computing, vol. 392, Springer Verlag, pp. 109-116, 10th International Symposium of Computer Science in Sport, IACSS/ISCSS 2015, Loughborough, United Kingdom, 15/9/9. https://doi.org/10.1007/978-3-319-24560-7_14
Brock H, Ohgi Y. Towards better measurability - IMU-based feature extractors for motion performance evaluation. In Advances in Intelligent Systems and Computing. Vol. 392. Springer Verlag. 2016. p. 109-116. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-319-24560-7_14
Brock, Heike ; Ohgi, Yuji. / Towards better measurability - IMU-based feature extractors for motion performance evaluation. Advances in Intelligent Systems and Computing. Vol. 392 Springer Verlag, 2016. pp. 109-116 (Advances in Intelligent Systems and Computing).
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