DocumentCode
484964
Title
An automatic parameter extraction method for the 7Ã\x9750m Stroke Efficiency Test
Author
Bächlin, Marc ; Förster, Kilian ; Schumm, Johannes ; Breu, Dominik ; Germann, Jürg ; Troster, Gerhard
Author_Institution
Wearable Comput. Lab., ETH Zurich, Zurich
Volume
1
fYear
2008
fDate
6-8 Oct. 2008
Firstpage
442
Lastpage
447
Abstract
We developed an automatic method to extract the parameters of the 7 times 50 m Stroke Efficiency Test for swimming based on a wrist worn acceleration sensor device. In the wrist acceleration signal we detect characteristic swim events such as wall push-offs, wall-strikes and strokes. Based on this information we compute the distance per stroke and the swimming velocity. The upper error bounds of our automatic method are 1.67% for the velocity and 1.33% for the time per stroke. The velocity measurement accuracy is of comparable order to the manual accuracy. The automatic method clearly outperforms the manual measurement for the time per stroke extraction.
Keywords
acceleration measurement; biomechanics; feature extraction; signal detection; velocity measurement; automatic parameter extraction method; signal detection; stroke efficiency test; swimming; velocity measurement; wrist worn acceleration sensor; Acceleration; Automatic testing; Data mining; Event detection; Life estimation; Parameter extraction; Sensor phenomena and characterization; Signal detection; Wearable sensors; Wrist;
fLanguage
English
Publisher
ieee
Conference_Titel
Pervasive Computing and Applications, 2008. ICPCA 2008. Third International Conference on
Conference_Location
Alexandria
Print_ISBN
978-1-4244-2020-9
Electronic_ISBN
978-1-4244-2021-6
Type
conf
DOI
10.1109/ICPCA.2008.4783628
Filename
4783628
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