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

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          Abstract

          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.

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          ISway: a sensitive, valid and reliable measure of postural control

          Martina Mancini, Arash Salarian, Patricia Carlson-Kuhta … (2012)
          Background Clinicians need a practical, objective test of postural control that is sensitive to mild neurological disease, shows experimental and clinical validity, and has good test-retest reliability. We developed an instrumented test of postural sway (ISway) using a body-worn accelerometer to offer an objective and practical measure of postural control. Methods We conducted two separate studies with two groups of subjects. Study I: sensitivity and experimental concurrent validity. Thirteen subjects with early, untreated Parkinson’s disease (PD) and 12 age-matched control subjects (CTR) were tested in the laboratory, to compare sway from force-plate COP and inertial sensors. Study II: test-retest reliability and clinical concurrent validity. A different set of 17 early-to-moderate, treated PD (tested ON medication), and 17 age-matched CTR subjects were tested in the clinic to compare clinical balance tests with sway from inertial sensors. For reliability, the sensor was removed, subjects rested for 30 min, and the protocol was repeated. Thirteen sway measures (7 time-domain, 5 frequency-domain measures, and JERK) were computed from the 2D time series acceleration (ACC) data to determine the best metrics for a clinical balance test. Results Both center of pressure (COP) and ACC measures differentiated sway between CTR and untreated PD. JERK and time-domain measures showed the best test-retest reliability (JERK ICC was 0.86 in PD and 0.87 in CTR; time-domain measures ICC ranged from 0.55 to 0.84 in PD and from 0.60 to 0.89 in CTR). JERK, all but one time-domain measure, and one frequency measure were significantly correlated with the clinical postural stability score (r ranged from 0.50 to 0.63, 0.01 < p < 0.05). Conclusions Based on these results, we recommend a subset of the most sensitive, reliable, and valid ISway measures to characterize posture control in PD: 1) JERK, 2) RMS amplitude and mean velocity from the time-domain measures, and 3) centroidal frequency as the best frequency measure, as valid and reliable measures of balance control from ISway.
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            Accuracy of the Microsoft Kinect sensor for measuring movement in people with Parkinson's disease.

            Dan Jackson, Lynn Rochester, Dadirayi Mhiripiri … (2014)
            The Microsoft Kinect sensor (Kinect) is potentially a low-cost solution for clinical and home-based assessment of movement symptoms in people with Parkinson's disease (PD). The purpose of this study was to establish the accuracy of the Kinect in measuring clinically relevant movements in people with PD. Nine people with PD and 10 controls performed a series of movements which were measured concurrently with a Vicon three-dimensional motion analysis system (gold-standard) and the Kinect. The movements included quiet standing, multidirectional reaching and stepping and walking on the spot, and the following items from the Unified Parkinson's Disease Rating Scale: hand clasping, finger tapping, foot, leg agility, chair rising and hand pronation. Outcomes included mean timing and range of motion across movement repetitions. The Kinect measured timing of movement repetitions very accurately (low bias, 95% limits of agreement 0.9 and Pearson's r>0.9). However, the Kinect had varied success measuring spatial characteristics, ranging from excellent for gross movements such as sit-to-stand (ICC=.989) to very poor for fine movement such as hand clasping (ICC=.012). Despite this, results from the Kinect related strongly to those obtained with the Vicon system (Pearson's r>0.8) for most movements. The Kinect can accurately measure timing and gross spatial characteristics of clinically relevant movements but not with the same spatial accuracy for smaller movements, such as hand clasping. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.
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              Comparative abilities of Microsoft Kinect and Vicon 3D motion capture for gait analysis.

              Alexandra Pfister, Alexandre M West, Shaw Bronner … (2014)
              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.
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                Author and article information

                Contributors
                Natasha M. Maurits: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS ONE
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Electronic): 1932-6203
                Publication date Collection: 2016
                Publication date (Electronic): 18 November 2016
                Volume: 11
                Issue: 11
                Electronic Location Identifier: e0166532
                Affiliations
                [1 ]Motognosis UG (haftungsbeschränkt), Berlin, Germany
                [2 ]Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
                [3 ]NeuroCure Clinical Research Center and Clinical and Experimental Multiple Sclerosis Research Center, Charité – Universitätsmedizin Berlin, Berlin, Germany
                [4 ]Department of Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
                [5 ]Experimental and Clinical Research Center, Max Delbrück Center for Molecular Medicine and Charité – Universitätsmedizin Berlin, Berlin, Germany
                Universitair Medisch Centrum Groningen, NETHERLANDS
                Author notes

                Competing Interests: Authors SMM and AUB hold stocks of Motognosis UG. Motognosis UG filed for patent (DE201410013828) using Kinect technology in postural control. Authors TSH, FP and JV report nothing to disclose. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                • Conceptualization: KO BK SMM JV FP AUB TSH.

                • Data curation: KO BK SMM JV.

                • Formal analysis: KO BK SMM AUB TSH.

                • Investigation: KO BK SMM JV AUB TSH.

                • Methodology: KO BK SMM JV AUB TSH.

                • Project administration: KO JV TSH.

                • Resources: KO BK SMM JV.

                • Software: KO BK SMM.

                • Supervision: JV AUB TSH.

                • Validation: KO BK SMM JV AUB TSH.

                • Visualization: KO BK SMM.

                • Writing – original draft: KO BK SMM TSH.

                • Writing – review & editing: KO BK SMM JV FP AUB TSH.

                Author information
                http://orcid.org/0000-0002-3518-5274
                Article
                Publisher ID: PONE-D-16-23167
                DOI: 10.1371/journal.pone.0166532
                PMC ID: 5115766
                PubMed ID: 27861541
                SO-VID: e709f9fc-84c4-42dc-9d77-08687cc0250b
                Copyright © © 2016 Otte et al
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 9 June 2016
                Date accepted : 31 October 2016
                Page count
                Figures: 2, Tables: 4, Pages: 17
                Funding
                Funded by: Motognosis UG
                The company “Motognosis UG” provided support in the form of salaries for authors KO, BK and SMM, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.
                Categories
                Subject: Research Article
                Subject: Biology and Life Sciences
                Subject: Anatomy
                Subject: Musculoskeletal System
                Subject: Medicine and Health Sciences
                Subject: Anatomy
                Subject: Musculoskeletal System
                Subject: Biology and Life Sciences
                Subject: Biomechanics
                Subject: Biological Locomotion
                Subject: Walking
                Subject: Biology and Life Sciences
                Subject: Physiology
                Subject: Biological Locomotion
                Subject: Walking
                Subject: Medicine and Health Sciences
                Subject: Physiology
                Subject: Biological Locomotion
                Subject: Walking
                Subject: Engineering and Technology
                Subject: Signal Processing
                Subject: Audio Signal Processing
                Subject: Physical Sciences
                Subject: Physics
                Subject: Acoustics
                Subject: Acoustic Signals
                Subject: Biology and Life Sciences
                Subject: Anatomy
                Subject: Musculoskeletal System
                Subject: Limbs (Anatomy)
                Subject: Legs
                Subject: Feet (Anatomy)
                Subject: Medicine and Health Sciences
                Subject: Anatomy
                Subject: Musculoskeletal System
                Subject: Limbs (Anatomy)
                Subject: Legs
                Subject: Feet (Anatomy)
                Subject: Engineering and Technology
                Subject: Signal Processing
                Subject: Signal to Noise Ratio
                Subject: Biology and Life Sciences
                Subject: Anatomy
                Subject: Musculoskeletal System
                Subject: Limbs (Anatomy)
                Subject: Legs
                Subject: Knees
                Subject: Medicine and Health Sciences
                Subject: Anatomy
                Subject: Musculoskeletal System
                Subject: Limbs (Anatomy)
                Subject: Legs
                Subject: Knees
                Subject: Biology and Life Sciences
                Subject: Anatomy
                Subject: Musculoskeletal System
                Subject: Limbs (Anatomy)
                Subject: Legs
                Subject: Ankles
                Subject: Medicine and Health Sciences
                Subject: Anatomy
                Subject: Musculoskeletal System
                Subject: Limbs (Anatomy)
                Subject: Legs
                Subject: Ankles
                Custom metadata
                Data Availability All files are available from the open science framework database ( https://osf.io/5jpyh/).

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