11
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The Accuracy of the Microsoft Kinect V2 Sensor for Human Gait Analysis. A Different Approach for Comparison with the Ground Truth

      research-article

      Read this article at

          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Several studies have examined the accuracy of the Kinect V2 sensor during gait analysis. Usually the data retrieved by the Kinect V2 sensor are compared with the ground truth of certified systems using a Euclidean comparison. Due to the Kinect V2 sensor latency, the application of a uniform temporal alignment is not adequate to compare the signals. On that basis, the purpose of this study was to explore the abilities of the dynamic time warping (DTW) algorithm to compensate for sensor latency (3 samples or 90 ms) and develop a proper accuracy estimation. During the experimental stage, six iterations were performed using the a dual Kinect V2 system. The walking tests were developed at a self-selected speed. The sensor accuracy for Euclidean matching was consistent with that reported in previous studies. After latency compensation, the sensor accuracy demonstrated considerably lower error rates for all joints. This demonstrated that the accuracy was underestimated due to the use of inappropriate comparison techniques. On the contrary, DTW is a potential method that compensates for the sensor latency, and works sufficiently in comparison with certified systems.

          Related collections

          Most cited references28

          • Record: found
          • Abstract: found
          • Article: not found

          Comparative abilities of Microsoft Kinect and Vicon 3D motion capture for gait analysis.

          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.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Accuracy and Reliability of the Kinect Version 2 for Clinical Measurement of Motor Function

            Background The introduction of low cost optical 3D motion tracking sensors provides new options for effective quantification of motor dysfunction. Objective The present study aimed to evaluate the Kinect V2 sensor against a gold standard motion capture system with respect to accuracy of tracked landmark movements and accuracy and repeatability of derived clinical parameters. Methods Nineteen healthy subjects were concurrently recorded with a Kinect V2 sensor and an optical motion tracking system (Vicon). Six different movement tasks were recorded with 3D full-body kinematics from both systems. Tasks included walking in different conditions, balance and adaptive postural control. After temporal and spatial alignment, agreement of movements signals was described by Pearson’s correlation coefficient and signal to noise ratios per dimension. From these movement signals, 45 clinical parameters were calculated, including ranges of motions, torso sway, movement velocities and cadence. Accuracy of parameters was described as absolute agreement, consistency agreement and limits of agreement. Intra-session reliability of 3 to 5 measurement repetitions was described as repeatability coefficient and standard error of measurement for each system. Results Accuracy of Kinect V2 landmark movements was moderate to excellent and depended on movement dimension, landmark location and performed task. Signal to noise ratio provided information about Kinect V2 landmark stability and indicated larger noise behaviour in feet and ankles. Most of the derived clinical parameters showed good to excellent absolute agreement (30 parameters showed ICC(3,1) > 0.7) and consistency (38 parameters showed r > 0.7) between both systems. Conclusion Given that this system is low-cost, portable and does not require any sensors to be attached to the body, it could provide numerous advantages when compared to established marker- or wearable sensor based system. The Kinect V2 has the potential to be used as a reliable and valid clinical measurement tool.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Gait assessment using the Microsoft Xbox One Kinect: Concurrent validity and inter-day reliability of spatiotemporal and kinematic variables.

              The revised Xbox One Kinect, also known as the Microsoft Kinect V2 for Windows, includes enhanced hardware which may improve its utility as a gait assessment tool. This study examined the concurrent validity and inter-day reliability of spatiotemporal and kinematic gait parameters estimated using the Kinect V2 automated body tracking system and a criterion reference three-dimensional motion analysis (3DMA) marker-based camera system. Thirty healthy adults performed two testing sessions consisting of comfortable and fast paced walking trials. Spatiotemporal outcome measures related to gait speed, speed variability, step length, width and time, foot swing velocity and medial-lateral and vertical pelvis displacement were examined. Kinematic outcome measures including ankle flexion, knee flexion and adduction and hip flexion were examined. To assess the agreement between Kinect and 3DMA systems, Bland-Altman plots, relative agreement (Pearson's correlation) and overall agreement (concordance correlation coefficients) were determined. Reliability was assessed using intraclass correlation coefficients, Cronbach's alpha and standard error of measurement. The spatiotemporal measurements had consistently excellent (r≥0.75) concurrent validity, with the exception of modest validity for medial-lateral pelvis sway (r=0.45-0.46) and fast paced gait speed variability (r=0.73). In contrast kinematic validity was consistently poor to modest, with all associations between the systems weak (r<0.50). In those measures with acceptable validity, the inter-day reliability was similar between systems. In conclusion, while the Kinect V2 body tracking may not accurately obtain lower body kinematic data, it shows great potential as a tool for measuring spatiotemporal aspects of gait.
                Bookmark

                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                07 August 2020
                August 2020
                : 20
                : 16
                : 4405
                Affiliations
                [1 ]Centre for Automation and Robotics (CAR UPM-CSIC), Universidad Politécnica de Madrid, 28012 Madrid, Spain; alberto.brunete@ 123456upm.es (A.B.); miguel.hernando@ 123456upm.es (M.H.)
                [2 ]Universidad Tecnológica Equinoccial (UTE), Santo Domingo 230208, Ecuador
                [3 ]Department of Human Health and Performance, Faculty of Sports Sciences, Universidad Politécnica de Madrid, 28040 Madrid, Spain; javier.ruedao@ 123456alumnos.upm.es (J.R.); enrique.navarro@ 123456upm.es (E.N.C.)
                Author notes
                [* ]Correspondence: d.guffanti@ 123456alumnos.upm.es ; Tel.: +34-698-872767
                Author information
                https://orcid.org/0000-0002-1244-291X
                https://orcid.org/0000-0001-9873-232X
                https://orcid.org/0000-0001-9997-0266
                https://orcid.org/0000-0001-6593-0055
                https://orcid.org/0000-0003-4824-4525
                Article
                sensors-20-04405
                10.3390/s20164405
                7472493
                32784586
                1ef0e14f-207a-43ae-852e-1fc6bf4978a3
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 07 July 2020
                : 03 August 2020
                Categories
                Article

                Biomedical engineering
                kinect sensor,gait analysis,dynamic time warping,latency
                Biomedical engineering
                kinect sensor, gait analysis, dynamic time warping, latency

                Comments

                Comment on this article