Geometry-based Computational Methodology to Reduce Markers Deviation

Abstract

Nowadays, determination of the ankle angular displacement and angular velocity are very common in sports biomechanics. The determined human biomechanics can be used to evaluate the surgical outcome of patients after surgery and the effects of ankle supportive braces (Figures 1). Human biomechanics are usually determined by the marker-based motion capture system. In order to compute the biomechnaics of ankle joint, markers are usually attached to the the fifth metatarsal head, heel, lateral malleolus and medial malleolus (Figure 2). Nevertheless, it is known that computation of human biomechanics is significantly affected by the deviation of markers positions [2, 3]. Particularly, the markers at the lateral malleolus and medial malleolus will have large deviation with the original position when the subjects are wearing ankle supportive braces (Figure 1b). In order to reduce the computational errors due to the deviation of markers positions, a simple and fast geometry-based computational methodology is proposed. The methodology makes use of the simple human anatomical geometry and the thickness of the brace compartments to estimate the original position of the markers (Figure 3). Then, the estimated position of the markers are used to determine the biomechanics of the ankle. In order to validate our methodology, experimental results of a subject with and without applying the proposed methodology were compared with the biomechancis of a subject without wearing ankle supportive brace. Experimental results showed that the proposed methodology can reduce the error of ankle biomechanics due to the deviations of the markers effectively. (a) (b) (c) Figure 1: (a) An ankle supportive brace; several markers were attached the subject ankle positions to determine the ankle biomechanics when a subject: (b) with; (c) without wearing supportive brace

Full text

2nd International Symposium on Computational Mechanics (ISCM II)
12th International Conference on Enhancement and Promotion of Computational Methods in Engineering and Science (EPMESC XII)
November 30 – December 3, 2009
Hong Kong – Macau
Geometry-based Computational Methodology to Reduce Markers Deviation
Y. M. Tang,
The Hong Kong Polytechnic University,
Department of Industrial and Systems Engineering, Hong Kong SAR, China;
mfymtang@inet.polyu.edu.hk
Keywords: ankle, braces, biomechanics, markers, motion capture system.
ABSTRACT
Nowadays, determination of the ankle angular displacement and angular velocity are very
common in sports biomechanics. The determined human biomechanics can be used to evaluate
the surgical outcome of patients after surgery and the effects of ankle supportive braces (Figures
1). Human biomechanics are usually determined by the marker-based motion capture system. In
order to compute the biomechnaics of ankle joint, markers are usually attached to the the fifth
metatarsal head, heel, lateral malleolus and medial malleolus (Figure 2). Nevertheless, it is
known that computation of human biomechanics is significantly affected by the deviation of
markers positions [2, 3]. Particularly, the markers at the lateral malleolus and medial malleolus
will have large deviation with the original position when the subjects are wearing ankle
supportive braces (Figure 1b). In order to reduce the computational errors due to the deviation of
markers positions, a simple and fast geometry-based computational methodology is proposed.
The methodology makes use of the simple human anatomical geometry and the thickness of the
brace compartments to estimate the original position of the markers (Figure 3). Then, the
estimated position of the markers are used to determine the biomechanics of the ankle. In order
to validate our methodology, experimental results of a subject with and without applying the
proposed methodology were compared with the biomechancis of a subject without wearing ankle
supportive brace. Experimental results showed that the proposed methodology can reduce the
error of ankle biomechanics due to the deviations of the markers effectively.
(a) (b) (c)
Figure 1: (a) An ankle supportive brace; several markers were attached the subject ankle
positions to determine the ankle biomechanics when a subject: (b) with; (c) without wearing
supportive brace

Figure 2: The markers positios. 1: the fifth metatarsal head; 2: heel; 3: lateral malleolus; 4:
medial malleolus. [1]
Figure 3: Location of the skin markers position and the estimated maker position.
REFERENCES
[1] C.L. Vaughan, B.L. Davis and J.C. O'Conner, Dynamics of Human Gait, Champaign, 1992.
[2] A. Cappozzo, “Three-dimensional analysis of human walking: experimental methods and
associated artifacts”, Hum Movement Sci, Vol. 10, Issue 5, pp. 589-602, (1991).
[3] A. Leardini, L. Chiari, U.D. Croce and A. Cappozzo, “Human movement analysis using
stereophotogrammetry Part 3. Soft tissue artifact assessment and compensation”, Gait
Posture, Vol. 21, Issue 2, pp. 212-25, (2005).