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RESEARCH
Accuracy and repeatability of joint angles measured using a single camera markerless motion capture system
Authors: Anne Schmitz, Mao Ye, Robert Shapiro, Ruigang Yang, Brian Noehren
Background: Markerless motion capture systems have developed in an effort to evaluate human movement in a natural setting. However, the accuracy and reliability of these systems remain understudied.
Objectives: Therefore, the goals of this study were to quantify the accuracy and repeatability of joint angles using a single camera markerless motion capture system and to compare the markerless system performance with that of a marker-based system.
Methods: A jig was placed in multiple static postures with marker trajectories collected using a ten camera motion analysis system. Depth and color image data were simultaneously collected from a single Microsoft Kinect camera, which was subsequently used to calculate virtual marker trajectories. A digital inclinometer provided a measure of ground-truth for sagittal and frontal plane joint angles. Joint angles were calculated with marker data from both motion capture systems using successive body-fixed rotations. The sagittal and frontal plane joint angles calculated from the marker-based and markerless system agreed with inclinometer measurements by <o0.51.
Results: The systems agreed with each other by <o0.51 for sagittal and frontal plane joint angles and <o2 for transverse plane rotation. Both systems showed a coefficient of reliability <o0.51 for all angles.
Conclusion: These results illustrate the feasibility of a single camera markerless motion capture system to accurately measure lower extremity kinematics and provide a first step in using this technology to discern clinically relevant differences in the joint kinematics of patient populations
Accuracy and repeatability of joint angles measured using a single camera markerless motion capture system
Authors: Seung Hak Lee, Chiyul Yoon, Sun Gun Chung , Hee Chan Kim, Youngbin Kwak, Hee-won Park, Keewon Kim
Background: Range of motion (ROM) measurements are essential for the evaluation for and diagnosis of adhesive capsulitis of the shoulder (AC). However, taking these measurements using a goniometer is inconvenient and sometimes unreliable. The Kinect (Microsoft, Seattle, WA, USA) is gaining attention as a new motion detecting device that is nonintrusive and easy to implement.
Methods: This study aimed to apply Kinect to measure shoulder ROM in AC; we evaluated its validity by calculating the agreement of the measurements obtained using Kinect with those obtained using goniometer and assessed its utility for the diagnosis of AC. Both shoulders of 15 healthy volunteers and affected shoulders of 12 patients with AC were included in the study. The passive and active ROM of each were measured with a goniometer for flexion, abduction, and external rotation. Their active shoulder motions for each direction were again captured using Kinect and the ROM values were calculated. The agreement between the two measurements was tested with the intraclass correlation coefficient (ICC). Diagnostic performance using the Kinect ROM was evaluated with Cohen’s kappa value. The cutoff values of the limited ROM were determined in the following ways: the same as passive ROM values, reflecting the mean difference, and based on receiver operating characteristic curves.
Results: The ICC for flexion/abduction/external rotation between goniometric passive ROM and the Kinect ROM were 0.906/0.942/0.911, while those between active ROMs and the Kinect ROMs were 0.864/0.932/0.925. Cohen’s kappa values were 0.88, 0.88, and 1.0 with the cutoff values in the order above.
Conclusion: Measurements of the shoulder ROM using Kinect show excellent agreement with those taken using a goniometer. These results indicate that the Kinect can be used to measure shoulder ROM and to diagnose AC as an alternative to goniometer.
​Kinematic Validation of a Multi-Kinect v2 Instrumented 10-Meter Walkway for Quantitative Gait Assessments
Authors: Geerse, Coolen, Roerdink
Background: Walking ability is frequently assessed with the 10-meter walking test (10MWT), which may be instrumented with multiple Kinect v2 sensors to complement the typical stopwatchbased time to walk 10 meters with quantitative gait information derived from Kinect’s 3D body point’s time series. The current study aimed to evaluate a multi-Kinect v2 set-up for quantitative gait assessments during the 10MWT against a gold-standard motion-registration system by determining between-systems agreement for body point’s time series, spatiotemporal gait parameters and the time to walk 10 meters.
Method: To this end, the 10MWT was conducted at comfortable and maximum walking speed, while 3D full-body kinematics was concurrently recorded with the multi-Kinect v2 set-up and the Optotrak motion-registration system (i.e., the gold standard). Between-systems agreement for body point’s time series was assessed with the intraclass correlation coefficient (ICC). Between-systems agreement was similarly determined for the gait parameters’ walking speed, cadence, step length, stride length, step width, step time, stride time (all obtained for the intermediate 6 meters) and the time to walk 10 meters, complemented by Bland-Altman’s bias and limits of agreement.
Results: Body point’s time series agreed well between the motion-registration systems, particularly so for body points in motion. For both comfortable and maximum walking speeds, the between-systems agreement for the time to walk 10 meters and all gait parameters except step width was high (ICC 0.888), with negligible biases and narrow limits of agreement. Conclusion: Hence, body point’s time series and gait parameters obtained with a multi-Kinect v2 set-up match well with those derived with a gold standard in 3D measurement accuracy. Future studies are recommended to test the clinical utility of the multi-Kinect v2 set-up to automate 10MWT assessments, thereby complementing the time to walk 10 meters with reliable spatiotemporal gait parameters obtained objectively in a quick, unobtrusive and patient-friendly manner.
Development and Validation of a Portable and Inexpensive Tool to Measure the Drop Vertical Jump Using the Microsoft Kinect V2
Authors: Aaron D. Gray, Brad W. Willis, Marjorie Skubic, Zhiyu Huo, Swithin Razu, Seth L. Sherman, Trent M. Guess
Background: Noncontact anterior cruciate ligament (ACL) injury in adolescent female athletes is an increasing problem. The knee-ankle separation ratio (KASR), calculated at initial contact (IC) and peak flexion (PF) during the drop vertical jump (DVJ), is a measure of dynamic knee valgus. The Microsoft Kinect V2 has shown promise as a reliable and valid marker-less motion capture device.
Hypothesis: The Kinect V2 will demonstrate good to excellent correlation between KASR results at IC and PF during the DVJ, as compared with a “gold standard” Vicon motion analysis system. Study
Design: Descriptive laboratory study. Level of
Evidence: Level 2.
Methods: Thirty-eight healthy volunteer subjects (20 male, 18 female) performed 5 DVJ trials, simultaneously measured by a Vicon MX-T40S system, 2 AMTI force platforms, and a Kinect V2 with customized software. A total of 190 jumps were completed. The KASR was calculated at IC and PF during the DVJ. The intraclass correlation coefficient (ICC) assessed the degree of KASR agreement between the Kinect and Vicon systems.
Results: The ICCs of the Kinect V2 and Vicon KASR at IC and PF were 0.84 and 0.95, respectively, showing excellent agreement between the 2 measures. The Kinect V2 successfully identified the KASR at PF and IC frames in 182 of 190 trials, demonstrating 95.8% reliability.
Conclusion: The Kinect V2 demonstrated excellent ICC of the KASR at IC and PF during the DVJ when compared with the Vicon system. A customized Kinect V2 software program demonstrated good reliability in identifying the KASR at IC and PF during the DVJ
Accuracy and Reliability of the Kinect Version 2 for Clinical Measurement of Motor Function
Author: Otte, Kayser, Mansow-Model, Verrel, Paul, Brandt, Schmitz-Hübsch
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 markeror wearable sensor based system. The Kinect V2 has the potential to be used as a reliable and valid clinical measurement tool.
Accuracy and repeatability of joint angles measured using a single camera markerless motion capture system
Author: Schmitz, Ye, Shapiro, Yang, Noehren
Context: The Landing Error Scoring System (LESS) can be used to identify individuals with an elevated risk of lower extremity injury. The limitation of the LESS is that raters identify movement errors from video replay, which is time-consuming and, therefore, may limit its use by clinicians. A markerless motion-capture system may be capable of automating LESS scoring, thereby removing this obstacle. Objective: To determine the reliability of an automated markerless motion-capture system for scoring the LESS.
Design: Cross-sectional study.
Setting: United States Military Academy. Patients or Other Participants: A total of 57 healthy, physically active individuals (47 men, 10 women; age 1⁄4 18.6 6 0.6 years, height 1⁄4 174.5 6 6.7 cm, mass 1⁄4 75.9 6 9.2 kg).
Main Outcome Measure(s): Participants completed 3 jump-landing trials that were recorded by standard video cameras and a depth camera. Their movement quality was evaluated by expert LESS raters (standard video recording) using the LESS rubric and by software that automates LESS scoring (depth-camera data). We recorded an error for a LESS item if it was present on at least 2 of 3 jump-landing trials. We calculated j statistics, prevalence- and bias-adjusted j (PABAK) statistics, and percentage agreement for each LESS item. Interrater reliability was evaluated between the 2 expert rater scores and between a consensus expert score and the markerless motion-capture system score.
Results: We observed reliability between the 2 expert LESS raters (average j 1⁄4 0.45 6 0.35, average PABAK 1⁄4 0.67 6 0.34; percentage agreement 1⁄4 0.83 6 0.17). The markerless motion-capture system had similar reliability with consensus expert scores (average j 1⁄4 0.48 6 0.40, average PABAK 1⁄4 0.71 6 0.27; percentage greement 1⁄4 0.85 6 0.14). However, reliability was poor for 5 LESS items in both LESS score comparisons.
Conclusions: A markerless motion-capture system had the same level of reliability as expert LESS raters, suggesting that an automated system can accurately assess movement. Therefore, clinicians can use the markerless motion-capture system to reliably score the LESS without being limited by the time requirements of manual LESS scoring.
Evaluation of Kinect 3D Sensor for Healthcare Imaging
Authors: Stefanie Po¨hlmann, Elaine F. Harkness, Christopher J. Taylor, Susan M. Astley
Background: Microsoft Kinect is a three-dimensional (3D) sensor originally designed for gaming that has received growing interest as a cost-effective and safe device for healthcare imaging. Recent applications of Kinect in health monitoring, screening, rehabilitation, assistance systems, and intervention support are reviewed here. The suitability of available technologies for healthcare imaging applications is assessed. The performance of Kinect I, based on structured light technology, is compared with that of the more recent Kinect II, which uses time-of-flight measurement, under conditions relevant to healthcare applications.
Method: The accuracy, precision, and resolution of 3D images generated with Kinect I and Kinect II are evaluated using flat cardboard models representing different skin colors (pale, medium, and dark) at distances ranging from 0.5 to 1.2 m and measurement angles of up to 75.
Results: Both sensors demonstrated high accuracy (majority of measurements \2 mm) and precision (mean point to plane error\2 mm) at an average resolution of at least 390 points per cm2. Kinect I is capable of imaging at shorter measurement distances, but Kinect II enables structures angled at over 60 to be evaluated. Kinect II showed significantly higher precision and Kinect I showed significantly higher resolution (both p\0.001). The choice of object color can influence measurement range and precision.
Conclusion: Although Kinect is not a medical imaging device, both sensor generations show performance adequate for a range of healthcare imaging applications. Kinect I is more approriate for shortrange imaging and Kinect II is reappropriate for imaging highly curved surfaces such as the face or breast.
Digital data acquisition of shoulder range of motion and arm motion smoothness using Kinect v2
Authors: Zulkarnain, Kim, Adikrishna, Hong, Kim, Jeon
Background: Range of motion (ROM) is a clinically important parameter in evaluating joint function. However, dynamic evaluation to determine the quality of the arm motion using digitized measurement is often overlooked during clinical assessment. We evaluated the accuracy of Kinect v2 (Microsoft, Redmond, WA, USA) as a digital tool for measuring shoulder ROM objectively and proposed a concept of motion smoothness reflecting the quality of arm motion.
Methods: Ten male participants were included in a 2-stage experiment. First, shoulder ROM was measured in 4 static poses (flexion, abduction, external rotation, and internal rotation) with Kinect v2, a 3-dimensional (3D) motion analysis system, and goniometry. Second, participants performed a point-topoint arm motion as naturally as possible. Kinematic data were collected with Kinect v2 and the 3D motion analysis system and then postprocessed to acquire parameters related to motion smoothness, including peak to mean velocity ratio, acceleration to movement time ratio, and number of peaks.
Results: Kinect v2 resulted in very good agreement of ROM measurement (r > 0.9) with the 3D motion analysis (95% limits of agreement < ±8°) compared with goniometry (95% limits of agreement < ±10°). Kinect v2 also showed a good correlation and agreement of measurement of motion quality parameters compared with the 3D motion analysis (peak to mean velocity ratio, acceleration to movement time ratio, and number of peaks: r = 0.769, discrepancy = ±0.1; r = 0.922, discrepancy = ±5%; and mean = 1 ± 0, respectively).
Conclusions: We show that Kinect v2 can be used as a reliable tool to measure shoulder ROM and arm motion smoothness.
Validation of Attitude and Heading Reference System and Microsoft Kinect for Continuous Measurement of Cervical Range of Motion Compared to the Optical Motion Capture System
Authors: Young Seop Song, Kyung Yong Yang, Kibum Youn, Chiyul Yoon, Jiwoon Yeom, Hyeoncheol Hwang, Jehee Lee, Keewon
Objective: To compare optical motion capture system (MoCap), attitude and heading reference system (AHRS) sensor, and Microsoft Kinect for the continuous measurement of cervical range of motion (ROM).
Methods: Fifteen healthy adult subjects were asked to sit in front of the Kinect camera with optical markers and AHRS sensors attached to the body in a room equipped with optical motion capture camera. Subjects were instructed to independently perform axial rotation followed by flexion/extension and lateral bending. Each movement was repeated 5 times while being measured simultaneously with 3 devices. Using the MoCap system as the gold standard, the validity of AHRS and Kinect for measurement of cervical ROM was assessed by calculating
correlation coefficient and Bland–Altman plot with 95% limits of agreement (LoA).
Results: MoCap and ARHS showed fair agreement (95% LoA<10o ), while MoCap and Kinect showed less favorable agreement (95% LoA>10o ) for measuring ROM in all directions. intraclass correlation coefficient (ICC) values between MoCap and AHRS in –40o to 40o range were excellent for flexion/extension and lateral bending (ICC>0.9). ICC values were also fair for axial rotation (ICC>0.8). ICC values between MoCap and Kinect system in –40o to 40o range were fair for all motions.
Conclusion: Our study showed feasibility of using AHRS to measure cervical ROM during continuous motion with an acceptable range of error. AHRS and Kinect system can also be used for continuous monitoring of flexion/ extension and lateral bending in ordinary range.
Validation of Attitude and Heading Reference System and Microsoft Kinect for Continuous Measurement of Cervical Range of Motion Compared to the Optical Motion Capture System
Authors: Young Seop Song, Kyung Yong Yang, Kibum Youn, Chiyul Yoon, Jiwoon Yeom, Hyeoncheol Hwang, Jehee Lee, Keewon
Objective: To compare optical motion capture system (MoCap), attitude and heading reference system (AHRS) sensor, and Microsoft Kinect for the continuous measurement of cervical range of motion (ROM).
Methods: Fifteen healthy adult subjects were asked to sit in front of the Kinect camera with optical markers and AHRS sensors attached to the body in a room equipped with optical motion capture camera. Subjects were instructed to independently perform axial rotation followed by flexion/extension and lateral bending. Each movement was repeated 5 times while being measured simultaneously with 3 devices. Using the MoCap system as the gold standard, the validity of AHRS and Kinect for measurement of cervical ROM was assessed by calculating
correlation coefficient and Bland–Altman plot with 95% limits of agreement (LoA).
Results: MoCap and ARHS showed fair agreement (95% LoA<10o ), while MoCap and Kinect showed less favorable agreement (95% LoA>10o ) for measuring ROM in all directions. intraclass correlation coefficient (ICC) values between MoCap and AHRS in –40o to 40o range were excellent for flexion/extension and lateral bending (ICC>0.9). ICC values were also fair for axial rotation (ICC>0.8). ICC values between MoCap and Kinect system in –40o to 40o range were fair for all motions.
Conclusion: Our study showed feasibility of using AHRS to measure cervical ROM during continuous motion with an acceptable range of error. AHRS and Kinect system can also be used for continuous monitoring of flexion/ extension and lateral bending in ordinary range.
Determination of Repeatability of Kinect Sensor
Authors: Bruno Bonnechere, Victor Sholukha, Bart Jansen, L. Omelina, Marcel Rooze and Serge Van Sint Jan
Background: The Kinect™ (Microsoft™, Redmond, WA) sensor, originally developed for gaming purposes, may have interesting possibilities for other fields such as posture and motion assessment. The ability of the Kinect sensor to perform biomechanical measurements has previously been studied and shows promising results. However, interday repeatability of the device is still not known.
Methods: This study assessed the intra- and interday repeatability of the Kinect sensor compared with a standard stereophotogrammetric device during posture assessment for measuring segment lengths. Forty subjects took part in the study. Five motionless captures were performed in one session to assess posture. Data were simultaneously recorded with both devices.
Results: Similar intraclass correlations coefficient (ICC) values were found for intraday (ICC=0.94 for the Kinect device and 0.98 for the stereophotogrammetric device) and interday (ICC=0.88 and 0.87, respectively) repeatability.
Conclusions: Results of this study suggest that a cost-effective, easy-to-use, and portable single markerless camera offers the same repeatability during posture assessment as an expensive, time-consuming, and nontransportable marker-based device.