Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, Alberta, Canada.
Human Performance Laboratory, Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada.
PLoS One. 2021 Apr 1;16(4):e0249657. doi: 10.1371/journal.pone.0249657. eCollection 2021.
Human gait is as unique to an individual as is their fingerprint. It remains unknown, however, what gait characteristics differentiate well between individuals that could define the uniqueness of human gait. The purpose of this work was to determine the gait characteristics that were most relevant for a neural network to identify individuals based on their running patterns. An artificial neural network was trained to recognize kinetic and kinematic movement trajectories of overground running from 50 healthy novice runners (males and females). Using layer-wise relevance propagation, the contribution of each variable to the classification result of the neural network was determined. It was found that gait characteristics of the coronal and transverse plane as well as medio-lateral ground reaction forces provided more information for subject identification than gait characteristics of the sagittal plane and ground reaction forces in vertical or anterior-posterior direction. Additionally, gait characteristics during the early stance were more relevant for gait recognition than those of the mid and late stance phase. It was concluded that the uniqueness of human gait is predominantly encoded in movements of the coronal and transverse plane during early stance.
人类的步态与指纹一样具有个体独特性。然而，目前尚不清楚哪些步态特征可以很好地区分个体，从而定义人类步态的独特性。本研究的目的是确定步态特征，以便神经网络可以根据跑步模式识别个体。我们训练了一个人工神经网络，以识别 50 名健康新手跑步者（男性和女性）的地面跑步的运动学和运动学轨迹。使用逐层相关性传播，确定了每个变量对神经网络分类结果的贡献。结果发现，冠状面和横断面上的步态特征以及中侧地面反作用力比矢状面和垂直或前后方向上的地面反作用力提供了更多的信息来识别个体。此外，早期支撑阶段的步态特征比中晚期支撑阶段的特征更能识别步态。研究结论认为，人类步态的独特性主要编码在早期支撑阶段的冠状面和横断面上的运动。
