$558 Journal of Biomechanics 2006, Vol. 39 (Suppl 1) Poster Presentations

[4] Andreoni G., Santambrogio G., Rabuffetti M., Pedotti A. (2002). Method of the analysis of posture and interface pressure of car drivers. Applied Ergonomics 33:511-522.

[5] Aggarwal J.K., Cai Q. (1999). Human motion analysis: A review. Computer Vision and Image Understanding 73(3): 428-440.

[6] Khoo B.C, Goh J.C., Bode K. (1995). Biomechanical model to determine lum- bosacral loads during single stance phase in normal gait. Medical Engineering & Physics 17(1): 27-35.

[7] Kejonen P., Kauanen K., Vanharanta H. (2003). The relationship between anthropometric factors and body-balancing movements in postural balance. Archives of Physical Medicine & Rehabilation 84(1): 17-22.

[8] Chaffin D. (2002). On simulating human reach motions for ergonomics analyses. Human Factors and Ergonomics in Manufacturing 12(3): 235-247.

[9] Maiteh B. (2003). An application of digital human modeling and ergonomics analysis in workplace design. American Society of Mechanical Engineers, Manufacturing Engineering Division 14: 731-735.

6861 Mo-Tu, no. 66 (P61) Using the change of angular momentum and muscle elect romyography data to qualify the muscle function in tennis forehand vol ley

H.-T. Lin 1 , L.-'~ Guo 1 , W.-L. Wu 1 , L.-H. Wang 2. 1Faculty of Sports Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan, 2Department of Physical Education, National Cheng Kung University, Tainan, Taiwan

Muscles may play different roles in some complex motions. However, from the traditional electromyography (EMG) data could not clearly describe the muscle function. The action of muscle in segmental movement is producing the moment relative to the joint. The angular momentum of the segment has been broadly applied in the momentum transfer analysis in sports. Applied the change rate of angular momentum of the segment in moment production analysis is few. The purpose of this study was to combine the change rate of angular momentum and muscle activation to qualify the muscle function in tennis volley. Six male tennis players were recruited in this study. The motion capture system was used for tennis punch and drop volley kinematics data collection, and 21 reflective markers were placed on selected anatomic landmarks unilaterally to define the segment motion of the trunk, pelvis, upper arm, forearm and hand. A surface EMG system was used for muscle activities detection and eight muscles on upper extremity were tested. The results showed that the change rate of angular momentum in punch volley is larger than in drop volley. The moment productions in flexion/extension and abduction/adduction in upper arm and forearm are larger than other directions. The pectoralis major and anterior deltoid contributed upper arm adduction moment, while brachioradialis produced forearm flexion moment. The flexor carpi radialis and extensor carpi radilis showed significant muscle activities; however, it helped to fix wrist stability instead of moment production in tennis forehand volley. Results from this study have been clearly described the muscle functions in tennis volley. Understanding the mechanism in tennis volley could help player have better performance and prevent injury. It is also helpful for the physicians and therapists in diagnosis and treatment of tennis injury.

6355 Mo-Tu, no. 67 (P61) Statistically appropriate computation of mean segment orientation J.H. Challis. Biomechanics Laboratory, The Pennsylvania State University, University Park, PA, USA

In many biomechanical applications three-dimensional kinematics are ana- lyzed. Angular kinematics can be described using a variety of conventions (e.g., Euler parameters, quaternions, Euler angles, Cardan angles). Given a set of, for example, Cardan angles researchers can average the data to produce a group mean, or average repeat trials to produce a mean trial for a subject. The statistics of orientation parameters are similar to directional statistics, and similarly require appropriate processing to determine descriptive statistics. The purpose of this study is to present a maximum likelihood estimator of the mean orientation of a rigid body. Descriptors of the orientation of a rigid body are extracted from a matrix (R), the attitude matrix. If the mean of a set of angles is to be determined, the averaging of the angles does not provide a statistically optimal estimate of the mean. To model the distribution for the orientation data the Fisher (or Fisher- von Mises) distribution is used (Fisher, 1953). Given this distribution the mean of the attitude matrices, from which the angles are determined, not the mean of the angles should be computed, /~ = ( l / n ) ~ = 1 Ri. The singular value decomposition of the mean matrix 15, is then computed,

= [U][W][V] T, where [U] and [V] are orthogonal matrices, and [W] is a diagonal matrix which contains the singular values of matrix /~. The mean angles can then be extracted from/~, which is computed from/~ = [U][V] m. Simulations of rigid body orientations indicated that this maximum likelihood estimator of the mean orientation of a rigid body provides estimates which are

up to 2 degrees different from that computed by simply taking the mean of the angles.

References Fisher R. (1953). Dispersion on a sphere. Proceedings of the Royal Society of

London Series A, Mathematical and Physical Sciences 217(1130): 295-305.

5856 Mo-Tu, no. 68 (P61) Biomechanical validation of reaction tests T. Mayer, B. Pr~torius, T.L. Milani. Chemnitz University of Technology - Institute of Sport Science, Chemnitz, Germany

Introduction: Scientific studies show a change of motor abilities of children in the last 20 years [2]. This phenomenon leads to problems as bad posture, obe- sity etc. To understand this development motor abilities have to be quantified as exactly as possible. Validation played a minor role for the development of coordination tests in the past. Valid coordination tests are needed. These facts led to the question how the biomechanical validation of coordination tests - in particular of a reaction test - can be realised. Methods: Hirtz published 1985 a test to quantify complex reaction abilities [1]. For validation the performance was divided in two phases: the reaction time and the time of movement. The reaction time was expected to correlate with the results of the reaction test. For validation a device composed of an accelerometer and 'contact-gloves' as triggers was developed. The measuring frequency of this device was 1000Hz. 115 children, from 6 to 11 years, participated in the study. Every subject performed the test three times. Results: The correlation between the averaged reaction time and the averaged test results is significant (p <0.01, R 2 =0.435). The correlation between the averaged movement time and the averaged test results is also significant (p<0.01, R 2 =0.453). Discussion: The examined test of complex reaction abilities is not valid. The importance of biomechanical validation is shown. Theoretical consider- ation and expert ratings are insufficient to validate motor tests. Therefore available motor tests have to be reconsidered and valid motor tests must be developed. This study has shown that the biomechanical validation of coordination tests is possible. Valid tests are necessary to report the changes of motor abilities of children.

References Hirtz P, editor. Koordinative F~higkeiten im Schulsport. 1985, Berlin. Pr~torius B, Milani TL. Motorische Leistungsf~higkeit bei Kindern. DZS 2004;

55(7+8).

5642 Mo-Tu, no. 69 (P61) Use of video-computer modeling of sports technique dur ing competitions M. Mirtskhulava, A. Egoyan, D. Chitashvili, C. Moistrapishvili, R. Salukvadze, G. Piranashvili, T. Kotorashvili, I. Khipashvili, E. Korinteli, G. Eradze, Z. Pkhaladze. Physiology Lab., State Academy of Physical Education and Sport of Georgia, Tbilisi, Georgia

In the Georgian State Academy of Physical Education and Sport was devel- oped and successfully applied a new markerless method for video-computer modeling. This method is based on the well-known principle of forward kinematics. In the recent publications were presented our results for video- computer modeling of long jumps [1]. Computer program makes modeling of a captured motion faster and more reliable, keeping individual proportions of the sportsman's body fixed. The program provides an interface for changing these proportions, weights of body parts and positions of their centers of gravity. The program calculates graphs of the trajectories of the centers of gravity and joints, their velocities and accelerations. This markerless method is especially good during competitions when markers can not be applied. For video calibration and object space reconstruction we use two-dimensional and three-dimensional DLT and MDLT methods. During competitions when time is limited and large metallic constructions for video calibration can not be used we provide an option for simplified MDLT method [2]. The advantage of this software package is its simplicity and complex math- ematical algorithms, manual processing of video-data is fast because of the user friendly interface and does not require the views from all cameras to be processed. According to the principle of forward kinematics the computer program itself calculates the positions of joints if it is possible. The user has only to adjust them. The number of video cameras is not restricted as well as the number of the sportsmen. The software was successfully applied for video-computer modeling of gymnastics.

References [1] Egoyan A., Piranashvili G., Mirtskhulava M. Use of video computer 3D modeling

on the basis of forward kinematics for improvement of sports results, In: VII International Congress "Modern Olympic Sports and Sports for All", Russian Academy of Sports, Moscow, 24-27 May, 2003, Vol. II, pp. 244-245.