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| Sensor integration into clothes and sports equipment Biomechanical and physiological measured data are
increasingly contributing
to athletes' training, for health monitoring and to improve
the fitness
during exercise. The miniaturization and performance
improvement of embedded
systems makes the use of small and smart sensors for
fitness
and sports
applications interesting. Multiple body-worn sensors and
sensors in sport
equipment record physiological and biomechanical signals
for
motion
analysis, statistical analysis or activity recognition. | Project manager:
Prof. Dr. Björn Eskofier
Project participants:
Dipl.-Ing. Peter Blank
Keywords:
Embedded systems; body sensor networks; digital sports; hardware development
Duration: 1.11.2015 - 31.12.2018
Sponsored by:
Interdisziplinäres Zentrum für eingebettete Systeme (ESI)
Contact:
Blank, Peter
E-Mail: peter.blank@fau.de
| | Publications |
|---|
Blank, Peter ; Kautz, Thomas ; Eskofier, Björn: Ball impact localization on table tennis rackets using piezo-electric sensors. In: The 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ed.) : Proceedings of the 2016 ACM International Symposium on Wearable Computers (2016 ACM International Symposium on Wearable Computers Heidelberg, Germany 12.09.2016-16.09.2016). Association for Computing Machinery : Association for Computing Machinery, Inc, 2016, pp 72-79. - ISBN 978-1-4503-4460-9
[doi>10.1145/2971763.2971778] | Blank, Peter ; Hofmann, Steffen ; Kulessa, Martin ; Eskofier, Björn: miPod 2: a new hardware platform for embedded real-time processing in sports and fitness applications. In: The 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ed.) : Proceedings of the 2016 ACM International Symposium on Wearable Computers (2016 ACM International Symposium on Wearable Computers Heidelberg, Germany 12.09.2016-16.09.2016). Association for Computing Machinery : Association for Computing Machinery, Inc, 2016, pp 881-884. - ISBN 978-1-4503-4462-3
[doi>10.1145/2968219.2968571] | Jensen, Ulf ; Blank, Peter ; Kugler, Patrick ; Eskofier, Björn: Unobtrusive and Energy-Efficient Swimming Exercise Tracking Using On-Node Processing. In: IEEE Sensors Journal 16 (2016), No. 10, pp 3972-3980
[doi>10.1109/JSEN.2016.2530019] |
Institution: Chair of Computer Science 5 (Pattern Recognition)
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