A novel bio-kinematic encoder for human exercise representation and decomposition - Part 2 : Robustness and Optimisation

Li, Saiyi, Caelli, Terry, Ferraro, Mario and Pathirana, Pububu N. 2013, A novel bio-kinematic encoder for human exercise representation and decomposition - Part 2 : Robustness and Optimisation, in Proceedings of the 2nd International Conference on Control Automation and Information Sciences; ICCAIS 2013, IAMI, Nha Trang, Vietnam, pp. 30-35.

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Title A novel bio-kinematic encoder for human exercise representation and decomposition - Part 2 : Robustness and Optimisation
Author(s) Li, Saiyi
Caelli, Terry
Ferraro, Mario
Pathirana, Pububu N.
Conference name Control Automation and Information Sciences Conference (2nd : 2013 : Nha Trang, Vietnam)
Conference location Nha Trang, Vietnam
Conference dates 25-28 Nov. 2013
Title of proceedings Proceedings of the 2nd International Conference on Control Automation and Information Sciences; ICCAIS 2013
Editor(s) [Unknown]
Publication date 2013
Conference series Control Automation and Information Sciences Conference
Start page 30
End page 35
Total pages 6
Publisher IAMI
Place of publication Nha Trang, Vietnam
Summary Bio-kinematic characterisations of human exercises constitute dealing with parameters such as velocity, acceleration, joint angles, etc. A majority of these are measured directly from various sensors ranging from RGB cameras to inertial sensors. However, due to certain limitations associated with these sensors, such as inherent noise, filters are required to be implemented to subjugate the effect from the noise. When the two-component (trajectory shape and dynamics) bio-kinematic encoding model is being established to represent an exercise, reducing the effect from noise embedded in raw data will be important since the underlying model can be quite sensitive to noise. In this paper, we examine and compare some commonly used filters, namely least-square Gaussian filter, Savitzky-Golay filter and optimal Kalman filter, with four groups of real data collected from Microsoft Kinectc , and assert that Savitzky- Golay filter is the best one when establishing an underlying model for human exercise representation.
ISBN 1467308137
9781467308137
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
090609 Signal Processing
110317 Physiotherapy
Socio Economic Objective 920403 Disability and Functional Capacity
HERDC Research category E1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30060761

Document type: Conference Paper
Collection: School of Engineering
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