Analysis of gait kinematic parameters of Chinese children based on human pose estimation algorithm

Abstract

Background The change and development of gait in children is of great importance to clinicians; however, reference data for the quantitative analysis of gait in Chinese children is lacking. This study aimed to describe the gait kinematics of Chinese children aged 3–12 years. In addition, we wanted to explore whether there are differences in the gait kinematics parameters in Chinese children of different age groups and establish a database of gait kinematics parameters of Chinese children with average development. Methods A total of 198 children with average development were included in the study and divided into three age groups: group A (3–5 years), group B (6–8 years), and group C (9–12 years). Two smartphone camera were used to record the sagittal and coronal planes of the participants while walking. At least three complete walking videos were recorded for each participant. The video was imported into a computer terminal. Gait evaluation software based on the human posture estimation algorithm was used to analyse the video, and the gait kinematic parameter data of the sagittal and coronal planes were extracted. Analysis of variance was used to determine whether there were differences in the data among the three groups. Results The comparison of walking posture among the three age groups showed that there were significant differences in the maximum flexion angle of hip joint, the maximum extension angle, the maximum flexion angle of knee joint and the minimum flexion value of knee joint in sagittal plane (P < 0.05). There were significant differences in knee joint swing amplitude and ankle joint swing amplitude in coronal direction (p < 0.05). the post hoc comparisons revealed that it was found that there were significant differences in the above-mentioned kinematic gait parameters between group A and group C (p < 0.05). In addition, the objective reference data of various kinematic parameters varying with age are established, and the confidence band and prediction band of each age are drawn. Conclusions Age is an important factor that affects kinematic gait parameters in children. With increasing age, the kinematic parameters of walking posture exhibited a certain trend of change. Therefore, establishing a standard gait database that varies with age is necessary. Through this method, children of each age have corresponding objective reference data, providing scientific quantitative data and clinical significance for clinicians and parents.