A gait signal acquisition and parameter characterization method based on foot pressure detection combined with Azure Kinect system

步态采集系统可用来进行步态分析。传统的可穿戴式步态采集系统由于传感器佩戴位置不同会导致步态参数出现较大误差。基于标记法的步态采集系统设备成本高昂且需要结合测力系统在康复医师的指导下使用，由于操作复杂，临床应用不便。本文设计了一种足压检测与Azure Kinect系统结合的步态采集系统，组织15名受试者参与步态试验、采集相关数据，提出了步态时空参数与关节角度参数计算方法，并将步态分析结果与摄像机标记法所得结果进行了一致性分析和误差分析。结果表明，本文设计的步态采集系统和作为对照的摄像机系统所获得参数具有较好的一致性（皮尔逊相关系数 r ≥ 0.9， P < 0.05）且具有较小误差（步态参数的均方根误差低于0.1，关节角度的均方根误差低于6）。综上，本文所提步态采集系统及其参数提取方法可为临床医疗上的步态特征分析提供可靠的数据采集结果，可作为理论分析的依据。.; The gait acquisition system can be used for gait analysis. The traditional wearable gait acquisition system will lead to large errors in gait parameters due to different wearing positions of sensors. The gait acquisition system based on marker method is expensive and needs to be used by combining with the force measurement system under the guidance of rehabilitation doctors. Due to the complex operation, it is inconvenient for clinical application. In this paper, a gait signal acquisition system that combines foot pressure detection and Azure Kinect system is designed. Fifteen subjects are organized to participate in gait test, and relevant data are collected. The calculation method of gait spatiotemporal parameters and joint angle parameters is proposed, and the consistency analysis and error analysis of the gait parameters of proposed system and camera marking method are carried out. The results show that the parameters obtained by the two systems have good consistency (Pearson correlation coefficient r ≥ 0.9, P < 0.05) and have small error (root mean square error of gait parameters is less than 0.1, root mean square error of joint angle parameters is less than 6). In conclusion, the gait acquisition system and its parameter extraction method proposed in this paper can provide reliable data acquisition results as a theoretical basis for gait feature analysis in clinical medicine.