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Motion Capturing and classification were used to quantitatively investigate the effects of three emotion induction methods (imagination, music, images) and an experimental method (colored noise) on kinemetric aspects of the human gait. Additionally, the effects of two emotion inductions (imagination, music) on the transition between walking and running on the treadmill, were analyzed as well. The latter took place on the one hand taking into account the transition time and on the other from a system dynamics point of view. With the semi-automatic experiment, a total of 3588 double steps were derived in free walking, 1948 double steps when walking on the treadmill, and 667 transition speeds of altogether eight subjects on four test days. Data were categorized into a two-dimensional model of emotion theory and classification rates were computed by means of support vector machines. Transition speeds were calculated and analyzed, respectively. On the one hand emotion recognition rates within 60%-80% dependent on the emotion induction method were found, on the other hand, the statistical evaluation of the classification rates, gait velocities, heart rates, transition rates, hysteresis and transition parameters suggests that the (induced) emotions act as a force, which modulates the dynamics of the system, especially in the transition between walking and running, where the influence was not only related to the kind of the emotion induction, but also to the nature of the hysteresis. The sport-practical benefit is discussed against the background of selected motor learning models.
keywordsAnalyse Effekte Emotion Emotionsinduktion Emotionsinduktionsmethoden Gang Gangmuster Gehen Klassifikation Laufen Motion Capturing Mustererkennung Sportwissenschaft Systemdynamischer Ansatz
Ihr Werk im Verlag Dr. Kovač
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