Holzreiter S H, Köhle M E
Forschungsinstitut für Orthopädietechnik, Wien, Austria.
J Biomech. 1993 Jun;26(6):645-51. doi: 10.1016/0021-9290(93)90028-d.
A new approach for the assessment of gait patterns is presented. The use of neural network techniques for decision making in gait analysis is for some purposes more effective than biomechanical methods or conventional statistics. To demonstrate this, a neural network was trained to distinguish 'healthy' from 'pathological' gait. The algorithm presented here can be used for several purposes because it learns from examples of diagnosed gait patterns without having any built-in model of gait.
本文提出了一种评估步态模式的新方法。在步态分析中,使用神经网络技术进行决策在某些方面比生物力学方法或传统统计学更有效。为了证明这一点,训练了一个神经网络来区分“健康”和“病理”步态。这里提出的算法可用于多种目的,因为它从已诊断的步态模式示例中学习,而没有任何内置的步态模型。