Analysis of the long jump technique in the transition from approach to takeoff based on time‐continuous kinematic data

Abstract

There are many studies on the biomechanics of the long jump, but few researchers have investigated how the athlete has to perform the last strides in order to prepare for takeoff. In this investigation, a pattern recognition approach was applied to analyze the movement structure during the last strides of the approach run and the jump. Time-continuous kinematic data of 57 trials (4.45-6.84 m) was analyzed. Cluster analysis identified at coarse level different movement patterns for each flight and support phase. Above these structural differences, individual movement patterns were diagnosed, especially for the jump. Further, the contribution of single variables on the differences of the complex movement patterns was determined by discriminant analysis. Based on the results, conclusions were drawn concerning the long jump and individuality in training. Overall, the applied pattern recognition method allows for the identification of structural changes of movement patterns as well as individual movement styles. This offers a wide range of application in various areas like sports training and rehabilitation.

Dynamics of Movement Patterning in Learning a Discrete Multiarticular Action

“…Cluster Analysis and Validation. Following the methods used by Schöllhorn (1998) and Jaitner, Mendoza, and Schöllhorn (2001), a cluster analysis approach was used to determine preferred movement patterning. Hip, knee, and ankle-joint range-of-motion data for kicking and nonkicking limbs, as well as trunk and trunklean angles, were selected as input variables during the preprocessing stage because these eight variables have been observed to be the most relevant in describing the kicking movement.…”

“…Based on previous work (e.g., Lees & Nolan, 2002), it was expected that differences between kicking patterns would emerge by comparing these selected variables. The angles were time normalized, and a matrix for each trial was obtained (see Jaitner et al, 2001). Differences between trials were calculated using the Euclidean distance.…”

Cluster Analysis of Movement Patterns in Multiarticular Actions: A Tutorial

“…One research group led by Wolfgang Schöllhorn has commonly adopted cluster analysis approaches for studying various sports movements Jaitner, et al, 2001;Schmidt, Schöllhorn, & Bauer, 1997;Schöllhorn, 1998Schöllhorn, , 2003Schöllhorn, et al, 2002;Schöllhorn, et al, 1999). For example, Schorer et al (2007) investigated movement patterning in five handball players.…”

“…Providing more detailed information about its application and execution may support further applications in the study of multiarticular actions. Cluster analysis has been used to analyze movement patterns in a variety of tasks involving walking (O'Byrne, Jenkinson, & O'Brien, 1998;Schöllhorn, Nigg, Stefanshyn, & Liu, 2002;Schöllhorn, Stefanyshyn, Nigg, & Liu, 1999;Toro, Nester, & Farren, 2007), swimming (Wilson & Howard, 1983), long jump (Jaitner, Mendoza, & Schöllhorn, 2001), handball (Schorer, Fath, Joseph, & Jaitner, 2007), golf (Ball & Best, 2007;Lames, 1992), reaching (d 'Avella, Portone, Fernandez, & Lacquaniti, 2006), and soccer kicking (Chow et al 2008). The present article aims to provide a tutorial style overview of cluster analysis of kinematic data thereby presenting a general framework for the analysis of multiarticular actions.…”

Measurement Methods to Analyze Changes in Coordination During Motor Learning from a Non-linear Perspective

“…The results showed a division of the eight trials into two groups. Jaitner, Mendoza, and Schöllhorn [94] investigated the runup phase in long jumping using a cluster analysis. Based on the obtained clustering the authors were able to determine differences in the execution of the steps prior to the take-off, with great inter-individual differences.…”