A gait signal acquisition and parameter characterization method based on foot pressure detection combined with Azure Kinect system.
10.7507/1001-5515.202210026
- Author:
Guofeng XU
1
;
Kai CHEN
1
;
Ying YANG
1
Author Information
1. School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou 310018, P. R. China.
- Publication Type:Journal Article
- Keywords:
Azure Kinect system;
Consistency analysis;
Gait acquisition;
Gait parameters;
Wearable
- MeSH:
Humans;
Biomechanical Phenomena;
Gait;
Lower Extremity;
Foot;
Gait Analysis;
Reproducibility of Results
- From:
Journal of Biomedical Engineering
2023;40(2):350-357
- CountryChina
- Language:Chinese
-
Abstract:
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.