DocumentCode :
677399
Title :
A novel bio-kinematic encoder for human exercise representation and decomposition - Part 1: Indexing and modelling
Author :
Saiyi Li ; Caelli, Terry ; Ferraro, Mario ; Pathirana, Pubudu N.
Author_Institution :
Fac. of Sci. & Technol., Deakin Univ., Geelong, VIC, Australia
fYear :
2013
fDate :
25-28 Nov. 2013
Firstpage :
24
Lastpage :
29
Abstract :
Current bio-kinematic encoders use velocity, acceleration and angular information to encode human exercises. However, in exercise physiology there is a need to distinguish between the shape of the trajectory and its execution dynamics. In this paper we propose such a two-component model and explore how best to compute these components of an action. In particular, we show how a new spatial indexing scheme, derived directly from the underlying differential geometry of curves, provides robust estimates of the shape and dynamics compared to standard temporal indexing schemes.
Keywords :
biology computing; biomechanics; estimation theory; acceleration information; angular information; biokinematic encoder; decomposition; differential geometry; execution dynamics; exercise physiology; human exercise representation; robust estimate; spatial indexing scheme; standard temporal indexing scheme; trajectory; two-component model; velocity information; Hidden Markov models; Indexing; Mathematical model; Noise; Shape; Trajectory; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Automation and Information Sciences (ICCAIS), 2013 International Conference on
Conference_Location :
Nha Trang
Print_ISBN :
978-1-4799-0569-0
Type :
conf
DOI :
10.1109/ICCAIS.2013.6720524
Filename :
6720524
Link To Document :
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