Accuracy of KinectOne to quantify kinematics of the upper body

Abstract

Motion analysis systems deliver quantitative information, e.g. on the progress of rehabilitation programs aimed at improving range of motion. Markerless systems are of interest for clinical application because they are low-cost and easy to use. The first generation of the Kinect™ sensor showed promising results in validity assessment compared to an established marker-based system. However, no literature is available on the validity of the new 'Kinect™ for Xbox one' (KinectOne) in tracking upper body motion. Consequently, this study was conducted to analyze the accuracy and reliability of the KinectOne in tracking upper body motion. Twenty subjects performed shoulder abduction in frontal and scapula plane, flexion, external rotation and horizontal flexion in two conditions (sitting and standing). Arm and trunk motion were analyzed using the KinectOne and compared to a marker-based system. Comparisons were made using Bland Altman statistics and Coefficient of Multiple Correlation. On average, differences between systems of 3.9±4.0° and 0.1±3.8° were found for arm and trunk motion, respectively. Correlation was higher for the arm than for the trunk motion. Based on the observed bias, the accuracy of the KinectOne was found to be adequate to measure arm motion in a clinical setting. Although trunk motion showed a very low absolute bias between the two systems, the KinectOne was not able to track small changes over time. Before the KinectOne can find clinical application, further research is required analyzing whether validity can be improved using a customized tracking algorithm or other sensor placement, and to analyze test-retest reliability.

Kinect and wearable inertial sensors for motor rehabilitation programs at home: state of the art and an experimental comparison

“…This is mainly due to a combination of the type of performed exercises (large motions with a relatively low dynamic) and their short duration, which allow also ACC or GYR estimates to have limited RMSE. The IMU estimates employing sensor fusion algorithms outperform the Kinect's output, though by a limited margin, revealing that both approaches (by sensors or cameras) have a good overall performance, with errors in the range of 3 to 8 degree for all the joint angles analyzed, which is consistent with existing literature [39,55,[59][60][61]68]. As expected, the exercises performed while wearing clothes show a slightly higher RMSE and deviations; however, they are consistent with the standard GA case.…”

“…Focusing on human motion capture applications, the use of the Kinect v1 in such scenario was triggered by the release of reverse-engineered open-source drivers and tracking software [34] and then propelled by the release of the Microsoft's SDK [35]. The second-generation device and its updated algorithm have been validated further within the context of clinical motion analysis, with applications such as posture and balance evaluation [36,37], fall detection [38], rehabilitation exercises [39][40][41], and gait assessment [42][43][44]. Moreover, the usability of Kinect-based home rehabilitation systems has been investigated, providing insights on the user acceptance with good results and indications for future improvements [45,46].…”

“…However, Microsoft's solution is the de-facto standard thanks to its robustness and ease of use. For these reasons, it was used in several validation and exploitation studies [36,39,42,43] and is also used in the present work. The provided data are only low-pass filtered to eliminate noise.…”

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

“…Previous publications showed, that Kinect V1 and V2 measurements of landmark angles [16, 20, 21] and length of body parts [22] derived from different movements may lack accuracy. Therefore, we focused on parameters based on single ‘stable’ landmarks with the exception of POCO, where foot landmarks were integrated into an anchor point for the sway vector.…”

Investigating the impact of a motion capture system on Microsoft Kinect v2 recordings: A caution for using the technologies together

“…Hence, many scientific studies have been conducted to evaluate the reliability and validity of the calculated skeleton joints [11,19–24]. The majority of these studies employed marker-based motion capture systems as a golden standard.…”