■证明了女性和男性执行的步态之间存在差异,出现在选定身体部位的运动中。尽管有许多与运动捕获数据的判别分析相关的最新研究,信号复杂性和不确定性的度量是否可以为性别区分问题提取有价值的特征的问题仍然存在。这是论文的主题。
■相关维度,以及近似和样本熵,被选择来描述运动数据。在数值实验中,收集的数据集包含25名女性和30名男性的884个样本。测量发生在人体运动实验室(HML),配备了一个高度精确的运动捕捉系统。研究了数据表示的两种变体-时间序列,其中包含所采取的骨骼模型的关节旋转以及附着在人体上的标记的位置。最后,使用描述性统计对女性和男性人群进行比较分析,非参数估计,并进行了统计假设验证。
■所采取的措施在统计学上具有显着的性别差异。总的来说,下肢的运动导致女性更大的关联维度和熵值,而选定的上半身部位对男性也有类似的作用。差异主要在髋部观察到,脚踝,肩膀,和头部动作。
■相关维度和熵度量提供了运动捕获数据的强大和可解释的特征,并对人类运动系统进行了有价值的描述。因此,除了发现女性和男性之间差异的重要性之外,他们的解释和理解也是已知的。
UNASSIGNED: It is proved that there are differences between gait performed by females and males, which appear in movements of selected body parts. Despite numerous state-of-the-art studies related to the discriminative analysis of motion capture data, the question of whether measures of signal complexity and uncertainty can extract valuable features for the problem of sex distinction still remains open. It is the subject of the paper.
UNASSIGNED: Correlation dimension, as well as approximate and sample entropies, are selected to describe motion data. In the numerical experiments, the collected dataset with 884 samples of 25 females and 30 males was used. The measurements took place in the Human Motion Laboratory (HML), equipped with a highly precise motion capture system. Two variants of data representation were investigated-time series that contain joint rotations of taken skeleton model as well as positions of the markers attached to the human body. Finally, a comparative analysis between the populations of females and males using descriptive statistics, non-parametric estimation, and statistical hypotheses verification was carried out.
UNASSIGNED: There are statistically significant sex differences extracted by the taken measures. In general, the movements of lower limbs result in greater values of correlation dimension and entropies for females, while selected upper body parts play a similar role for males. The dissimilarities are mainly observed in hip, ankle, shoulder, and head movements.
UNASSIGNED: Correlation dimension and entropy measures provide robust and explainable features of motion capture data with a valuable description of the human locomotion system. Thus, beyond the importance of discovered differences between females and males, their interpretation and understanding are also known.