Biomechanics Division, University School of Physical Education in Wroclaw, Wroclaw 51-612, Poland.
Department of Biology and Motor Sports Fundamentals, University School of Physical Education in Wroclaw, Wroclaw 51-612, Poland.
Biomed Res Int. 2019 Jan 3;2019:9232430. doi: 10.1155/2019/9232430. eCollection 2019.
Normal gait pattern is the key component in the investigation of pathological gait patterns. In computer motion analysis there is a need to include data from participants with different somatic structures to develop a normative database or to limit the database results to a specific population. The aim of this study was to determine kinematic gait patterns for young, active women walking with low, preferred, and self-selected speeds with regard to their somatic characteristics. Laboratory-based gait analysis was performed on 1320 gait cycles taken from 20 young, active women walking with three different speeds. Comprehensive anthropometric measurements and descriptive statistics were used to describe spatiotemporal and angular variables at each walking condition. The results demonstrated some significant differences in young, active women walking between different speeds and compared to the literature. This suggests that there is a need to include data from participants with different somatic structures to develop a normative database or limit the database results to a specific population. Detailed linear and angular kinematic variables allow for proper adjustment of parameters depending on the gait speed of people with locomotion disorders.
正常步态模式是病理性步态模式研究的关键组成部分。在计算机运动分析中，需要纳入具有不同体结构的数据，以开发一个正常数据库，或将数据库结果限制在特定人群。本研究的目的是确定年轻、活跃的女性在以低、偏好和自选择速度行走时的运动学步态模式，以及她们的体结构特征。对 20 名年轻、活跃的女性在三种不同速度下行走的 1320 个步态周期进行了基于实验室的步态分析。综合人体测量学测量和描述性统计用于描述每个行走条件下的时空和角度变量。结果表明，不同速度下年轻、活跃的女性之间以及与文献相比存在一些显著差异。这表明，需要纳入具有不同体结构的数据，以开发一个正常数据库，或将数据库结果限制在特定人群。详细的线性和角度运动学变量可以根据运动障碍患者的步态速度适当调整参数。
