The Accuracy of the Microsoft Kinect V2 Sensor for Human Gait Analysis. A Different Approach for Comparison with the Ground Truth (original) (raw)
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Sensors, 2020
Gait analysis is an important tool for the early detection of neurological diseases and for the assessment of risk of falling in elderly people. The availability of low-cost camera hardware on the market today and recent advances in Machine Learning enable a wide range of clinical and health-related applications, such as patient monitoring or exercise recognition at home. In this study, we evaluated the motion tracking performance of the latest generation of the Microsoft Kinect camera, Azure Kinect, compared to its predecessor Kinect v2 in terms of treadmill walking using a gold standard Vicon multi-camera motion capturing system and the 39 marker Plug-in Gait model. Five young and healthy subjects walked on a treadmill at three different velocities while data were recorded simultaneously with all three camera systems. An easy-to-administer camera calibration method developed here was used to spatially align the 3D skeleton data from both Kinect cameras and the Vicon system. With t...
Precision of Gait Indices Approximation by Kinect Based Motion Acquisition
Studies in Computational Intelligence, 2015
Step length constitutes one of the important gait indices. The research described in the present paper was focused on the method of determination of the step length by means of the Kinect device. Gait sequences recorded in the Human Motion Laboratory of the Polish-Japanese Academy of Information Technology using the Vicon system played the role of the reference data. The group of six subjects participated in the experiments. Conclusions from the comparative analysis of the results of both approaches summarize the paper.
The Use of Microsoft Kinect for Human Movement Analysis
International Journal of Sports Science, 2015
The purpose of this study was to provide evidence of reliability and validity for the use of a Microsoft Kinect system to measure displacement in human movement analysis. Three dimensional (3D) video motion systems are commonly used to analyze human movement kinematics of body joints and segments for many diverse applications related to gait analysis, rehabilitation, sports performance, medical robotics, and biofeedback. These systems, however, have certain drawbacks pertaining to the use of markers, calibration time, number of cameras, and high cost. Microsoft Kinect systems create 3D images and are low cost, portable, not markers required, and easy to set up. They lack, however, evidence of reliability and validity for human movement kinematics analysis. Twenty-six participants were recruited for this study. Peak Motus version 9 and Microsoft Kinect system with customized skeleton software were used to collect data from each subject sitting on a platform moving horizontally at the...
Biomechanical application: exploitation of kinect sensor for gait analysis
2017
Human gait recognition is an important indicator and are extensively studied research area especially with the aging population and rehabilitation applications. Application of gait analysis ranges from diagnosis, monitoring and early detection of potential hazards such as human fall. There are various types of approaches used in gait analysis including wearable, ambient and vision based devices. Microsoft Kinect sensor is well-known among researchers since it can give depth and normal colour images as well. This paper presents a preliminary study on gait analysis of lower body parts. The measurement taken includes step width, step lengths, stride lengths and angles of knee respective hip and ankle while walking. The results showed that the algorithms implemented were able to accurately measure the lengths with low error rate.
Comparative abilities of Microsoft Kinect and Vicon 3D motion capture for gait analysis '14
Biomechanical analysis is a powerful tool in the evaluation of movement dysfunction in orthopaedic and neurologic populations. Three-dimensional (3D) motion capture systems are widely used, accurate systems, but are costly and not available in many clinical settings. The Microsoft Kinect! has the potential to be used as an alternative low-cost motion analysis tool. The purpose of this study was to assess concurrent validity of the Kinect! with Brekel Kinect software in comparison to Vicon Nexus during sagittal plane gait kinematics. Twenty healthy adults (nine male, 11 female) were tracked while walking and jogging at three velocities on a treadmill. Concurrent hip and knee peak flexion and extension and stride timing measurements were compared between Vicon and Kinect!. Although Kinect measurements were representative of normal gait, the Kinect! generally under-estimated joint flexion and over-estimated extension. Kinect! and Vicon hip angular displacement correlation was very low and error was large. Kinect! knee measurements were somewhat better than hip, but were not consistent enough for clinical assessment. Correlation between Kinect! and Vicon stride timing was high and error was fairly small. Variability in Kinect! measurements was smallest at the slowest velocity. The Kinect! has basic motion capture capabilities and with some minor adjustments will be an acceptable tool to measure stride timing, but sophisticated advances in software and hardware are necessary to improve Kinect! sensitivity before it can be implemented for clinical use.
Gait Change Detection Using Parameters Generated from Microsoft Kinect Coordinates
arXiv: Computation, 2019
This paper describes a method to convert Microsoft Kinect coordinates into gait parameters in order to detect a person's gait change. The proposed method can help quantify the progress of physical therapy. Microsoft Kinect, a popular platform for video games, was used to generate 25 joints to form a human skeleton, and then the proposed method converted the coordinates of selected Kinect joints into gait parameters such as spine tilt, hip tilt, and shoulder tilt, which were tracked over time. Sample entropy measure was then applied to quantify the variability of each gait parameter. Male and female subjects walked a three-meter path multiple times in initial experiments, and their walking patterns were recorded via the proposed Kinect device through the frontal plane. Time series of the gait parameters were generated for subjects with and without knee braces. Sample entropy was used to transform these time series into numerical values for comparison of these two conditions.
Accuracy of the Microsoft Kinect™ for measuring gait parameters during treadmill walking
Gait & posture, 2015
The measurement of gait parameters normally requires motion tracking systems combined with force plates, which limits the measurement to laboratory settings. In some recent studies, the possibility of using the portable, low cost, and marker-less Microsoft Kinect™ sensor to measure gait parameters on over-ground walking has been examined. The current study further examined the accuracy level of the Kinect sensor for assessment of various gait parameters during treadmill walking under different walking speeds. Twenty healthy participants walked on the treadmill and their full body kinematics data were measured by a Kinect sensor and a motion tracking system, concurrently. Spatiotemporal gait parameters and knee and hip joint angles were extracted from the two devices and were compared. The results showed that the accuracy levels when using the Kinect sensor varied across the gait parameters. Average heel strike frame errors were 0.18 and 0.30 frames for the right and left foot, respe...
The lack of low cost devices apt to collaborate both researches and clinical intervention s quality for health promotion is quite significant, peculiarly in developing countries. The objective of this study consisted in calculating the accuracy of the hardware Kinect™ by Microsoft™. Methods: anthropometric data were collected from a subject in orthostatic position, at four different distances from the optical axes of the hardware, on X, Y and Z. The normality and the variances homogeinity of the data were stated through Kolmogorov-Smirnov and Barlett’s tests, in this order. It has been adopted a significance P < 0.05 for all the statistical tests, and the size effect for all of the spatial coordinates (in the four different placements) exceeded 0.80. Results: the relative error presented no significant differences in all of those distances in the three spatial axels and the accuracy averaged 0.047m; such result allows to conclude that the hardware presents satisfactory both scientific and clinical applicability, embracing potentially human movement investigations and interventions, as well as orthopedics, physiotherapy, physical education, and sports among others.