Category
Methods
Document Type
Paper
Abstract
Athletes’ movement biomechanics are of high interest to predict injury risk, especially in maximum effort cutting manoeuvres. However, using a standard optical measurement set-up with cameras and force plates influences the athlete’s performance. Therefore, alternative methods, e.g. Neural Networks, have been used to predict kinetic parameters based on easier to measure kinematic parameters. A previous study has evoked the question, whether the filtering processes of the input and output parameters used for training a feedforward neural network affect the prediction accuracy. To answer this question, four different filter combinations have been used during the pre-processing of joint angles, ground reaction force and joint moments of fast cutting manoeuvres, which were used to train a feedforward neural network. The results revealed a dependency.
Recommended Citation
David, Sina; Mundt, Marion; Koeppe, Arnd; Bamer, Franz; Markert, Bernd; and Potthast, Wolfgang
(2019)
"THE INFLUENCE OF FILTER PARAMETERS ON THE PREDICTION ACCURACY OF THE GROUND REACTION FORCE AND JOINT MOMENTS,"
ISBS Proceedings Archive: Vol. 37:
Iss.
1, Article 105.
Available at:
https://commons.nmu.edu/isbs/vol37/iss1/105
