Motion Analysis for the Standing Long Jump

[[abstract]]The standing long jump is a standard test for primary school students. It can be used to evaluate the development of basic sports skills of a child. This paper presents a system that can automatically detect the motion during a standing long jump from a video sequence. The silhouette of the jumper in the film is segmented from the background first for all frames. A stick model is applied to the silhouette found in the first frame. Then a GA-based search algorithm is used to find the stick models for the rest of the frames. The stick model points out the important joints of a person and can be used to represent the pose of the jumper in each frame. From the pose change in consecutive frames, we will be able to analyze the movement of the jumper.[[conferencetype]]國際[[conferencedate]]20060704~20060707[[conferencedate]]Lisboa, Portugal[[iscallforpapers]]

THE INFLUENCE OF WARM-UP EXERCISES ON KNEE AND ELBOW JOINT MOTION FOR STANDING LONG JUMP PERFORMANCE

The purpose of this study was to analyse the influences of the motion angles of the knee and elbow joints on the standing long jump performance of high school students. Twenty-nine participants were assigned to either a control group to perform static and dynamic joint exercises or an experimental group to perform basic sprinting drill warm-up exercises. Both groups performed pre-, control, and post-standing long jump tests. Motion analysis of the knee and elbow joints was conducted in the sagittal plane by using video recording. Our findings support that basic sprint drill warm-up exercises can enhance the jump length in the youth. The implementation of warm-up exercises with basic sprint drills and motion analysis could be useful for determining the ranges of motion of the elbow and knee joints and improving standing long jump performance

ESTIMATION OF TAKEOFF-ANGLE IN THE LONG JUMP BY USING WiMAS

There have been many studies on the biomechanics of the long jump, and the typical method has been video analysis. These studies provided a lot of new angles about movement of jumping (Jaitner et ai, 2001). However, video analysis has a flaw in that it takes a long time for the analysis. We produced a motion analysis system by using telemeter and micro sensor IC. We named this system WiMAS. WiMAS stands for Wireless Motion Analysis System. WiMAS has two merits. One of them ,is that it doesn't restrain the subject's motion, and the other is real-time feedback. In previous studies, we had measured the height of vertical jumps, and have recently developed a method for estimating a takeoff-angle in the standing long jump by using WiMAS. The purpose of this study was to develop a method for estimating the takeoff-angle in the long jump

THE EFFECT OF COUNTER MOVEMENT JUMP PERFORMANCE IN MIDDLEAGED ELDERLY PRACTICING TAI-CHI EXERCISE

The purpose of this study was to investigate biomechanical effects of Tal-Chi exercise on the lower-extremity in middle-aged elders during counter-movement jump. Twelve middle-aged elders with regular Tai Chi exercise experience and twelve healthy middle-aged elders participated in this study. Ten Vicon Motion System cameras, two Kistler force plates were used simultaneously to capture the kinematic and dynamlc parameters of standing vertical jumps. Independent samples &test was performed for statistical analysis ( u = .05 ). Since the jump height of Tai Chi group was significantly higher ( p c .05 ). It showed that practicing Tai Chi exercise could effectively slow down the degeneration of the moment and power at the hip Joint. Therefore, middle-aged elders were recommended to engage in long-term Tai Chi exercise

Human Shape-Motion Analysis In Athletics Videos for Coarse To Fine Action/Activity Recognition Using Transferable BeliefModel

We present an automatic human shape-motion analysis method based on a fusion architecture for human action and activity recognition in athletic videos. Robust shape and motion features are extracted from human detection and tracking. The features are combined within the Transferable Belief Model (TBM framework for two levels of recognition. The TBM-based modelling of the fusion process allows to take into account imprecision, uncertainty and conflict inherent to the features. First, in a coarse step, actions are roughly recognized. Then, in a fine step, an action sequence recognition method is used to discriminate activities. Belief on actions are made smooth by a Temporal Credal Filter and action sequences, i.e. activities, are recognized using a state machine, called belief scheduler, based on TBM. The belief scheduler is also exploited for feedback information extraction in order to improve tracking results. The system is tested on real videos of athletics meetings to recognize four types of actions (running, jumping, falling and standing) and four types of activities (high jump, pole vault, triple jump and long jump). Results on actions, activities and feedback demonstrate the relevance of the proposed features and as well the efficiency of the proposed recognition approach based on TBM

Motor Control For Human Jumping To A Target

Investigating how humans perform dynamic movements is important for applications such as movement rehabilitation, sports training, humanoid robot design and control, and human-robot interaction. There are several hypotheses as to how humans perform dynamic movements based on movement variability, task optimization, and motor learning concepts. This thesis develops a methodology for analyzing dynamic movements, determining what factors are crucial to task success, and understanding the motor learning process. The jumping to a target movement was chosen as the exemplar motion for investigating human dynamic motor control because of the following reasons: the movement difficulty can be scaled to a person's physical characteristics and ability; jumping to a target is a movement that many people can perform but few have practiced, making it a good candidate for investigating motor learning; jumping to target has a clear metric for success, enabling novice-expert classification of participants based on objective task performance. Additionally, existing human jumping research has focused primarily on maximum height vertical jumping or maximum distance long jumping. This thesis is the first known work to investigate the kinematics and motor control of the standing broad jump to a target. An experiment was conducted to collect motion capture data of 22 participants (ages 19-34 years, 9 females and 13 males), each performing 12 jumps to three specified targets of various distances. These motion capture data were used with Extended Kalman Filter pose estimation to extract the kinematic joint trajectories of each jump, and the center of mass (CoM) trajectories were then computed. Analysis of these trajectories then proceeded in two stages. A kinematic trajectory analysis was performed to identify trends between the jumping trajectories and jump success. The identified trends, and other information found in the literature, were used to generate hypotheses for using a sliding window Inverse Optimal Control (IOC) approach for identifying optimized motor control tasks. The findings from the kinematic trajectory analysis of jumping motion trajectories suggest a strong relation between the jumper controlling the velocity of their CoM at takeoff and the success of the jump. The angle and magnitude of the takeoff velocity must be matched to generate an appropriate ballistic trajectory to reach the desired target. At landing, the jumper can use their foot placement pose to correct for inaccuracy in their takeoff velocity and CoM trajectory to still land on the target. Novice jumpers demonstrated more consistent CoM takeoff velocities as they performed more jumps, however it was less likely that their foot placement control improved noticeably during the study. Expert jumpers were observed to control their foot placement pose more effectively, therefore making higher jumping success rates possible even when the variability of their CoM takeoff velocity was greater than some novice jumpers. A sliding window IOC approach was used to estimate what motor control tasks jumpers optimize throughout the movement. The cost terms of the objective function were designed based on jumping-specific control tasks and criteria relevant to general human motion. The recovered IOC cost term weights were averaged over different sets of jump features. Changes in average cost term weights were observed relative to jump grade, target distance, and jump performance. Experts were observed to optimize CoM forward velocity before takeoff more than novice jumpers, who optimized CoM height more. As novice jumpers improved their success rate during the experiment, their motor control behavior more closely resembled that of experts. The IOC approach demonstrates evidence for a repeatable, general optimal motor control method for jumping to a target. Parallels were also drawn between the kinematic trajectory results and IOC motor control task results. Optimizing for the CoM velocity control task before takeoff and toe velocity control task prior to landing, as identified in the IOC results, can be related to controlling takeoff velocity and foot placement pose respectively, as observed in the kinematic analysis. Finally, the IOC sliding window approach was used alongside unsupervised clustering techniques to identify four jump styles into which experiment participants could be categorized into. All style groups included novice and expert jumpers, and were independent of jump success or motor learning, suggesting there are multiple general motor control patterns that can be used for successfully jumping to a target. This analysis framework can be extended to analyzing jumping motions in varied environment conditions, or be used to define the motor control methods of other dynamic human motions

Analysis of standing vertical jumps using a force platform

A force platform analysis of vertical jumping provides an engaging demonstration of the kinematics and dynamics of one-dimensional motion. The height of the jump may be calculated (1) from the flight time of the jump, (2) by applying the impulse–momentum theorem to the force–time curve, and (3) by applying the work–energy theorem to the force-displacement curve

The Association of Dorsiflexion Flexibility on Knee Kinematics and Kinetics during a Drop Vertical Jump in Healthy Female Athletes

Purpose While previous studies have examined the association between ankle dorsiflexion flexibility and deleterious landing postures, it is not currently known how landing kinetics are influenced by ankle dorsiflexion flexibility. The purpose of this study was to examine whether ankle dorsiflexion flexibility was associated with landing kinematics and kinetics that have been shown to increase the risk of anterior cruciate ligament (ACL) injury in female athletes. Methods Twenty-three female collegiate soccer players participated in a preseason screening that included the assessment of ankle dorsiflexion flexibility and lower-body kinematics and kinetics during a drop vertical jump task. Results The results demonstrated that females with less ankle dorsiflexion flexibility exhibited greater peak knee abduction moments (r = −.442), greater peak knee abduction angles (r = .355), and less peak knee flexion angles (r = .385) during landing. The range of dorsiflexion flexibility for the current study was between 9° and 23° (mean = 15.0°; SD 3.9°). Conclusion Dorsiflexion flexibility may serve as a useful clinical measure to predict poor landing postures and external forces that have been associated with increased knee injury risk. Rehabilitation specialists can provide interventions aimed at improving dorsiflexion flexibility in order to ameliorate the impact of this modifiable factor on deleterious landing kinematics and kinetics in female athletes