Abstract

Low-cost, portable, and easy-to-use Kinect-based systems achieved great popularity in out-of-the-lab motion analysis. The placement of a Kinect sensor significantly influences the accuracy in measuring kinematic parameters for dynamics tasks. We conducted an experiment to investigate the impact of sensor placement on the accuracy of upper limb kinematics during a typical upper limb functional task, the drinking task. Using a 3D motion capture system as the golden standard, we tested twenty-one Kinect positions with three different distances and seven orientations. Upper limb joint angles, including shoulder flexion/extension, shoulder adduction/abduction, shoulder internal/external rotation, and elbow flexion/extension angles, are calculated via our developed Kinect kinematic model and the UWA kinematic model for both the Kinect-based system and the 3D motion capture system. We extracted the angles at the point of the target achieved (PTA). The mean-absolute-error (MEA) with the standard represents the Kinect-based system’s performance. We conducted a two-way repeated measure ANOVA to explore the impacts of distance and orientation on the MEAs for all upper limb angles. There is a significant main effect for orientation. The main effects for distance and the interaction effects do not reach statistical significance. The post hoc test using LSD test for orientation shows that the effect of orientation is joint-dependent and plane-dependent. For a complex task (e.g., drinking), which involves body occlusions, placing a Kinect sensor right in front of a subject is not a good choice. We suggest that place a Kinect sensor at the contralateral side of a subject with the orientation around to for upper limb functional tasks. For all kinds of dynamic tasks, we put forward the following recommendations for the placement of a Kinect sensor. First, set an optimal sensor position for capture, making sure that all investigated joints are visible during the whole task. Second, sensor placement should avoid body occlusion at the maximum extension. Third, if an optimal location cannot be achieved in an out-of-the-lab environment, researchers could put the Kinect sensor at an optimal orientation by trading off the factor of distance. Last, for those need to assess functions of both limbs, the users can relocate the sensor and re-evaluate the functions of the other side once they finish evaluating functions of one side of a subject.

Highlights

  • Three-dimensional (3D) motion analysis is a systematic study of human movement

  • The result of two-way repeated measure ANOVA is demonstrated in Table 2, which explores the impact of distance and orientation on the accuracy of upper limb kinematic measurement by the Kinect-based system

  • It is clear that the performance in kinematic measurement is quite different when the Kinect is placed at different orientations

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Summary

Introduction

Three-dimensional (3D) motion analysis is a systematic study of human movement. Three-dimensional motion analysis is widely used in studying the human neuromusculoskeletal system [1], assisting sports training [2], determining risk factors of musculoskeletal injury [3], diagnosing pathologies and planning treatment for individuals with musculoskeletal conditions [4], providing feedback for rehabilitation retraining [5], or assisting design of prosthetics or robotics [6]. Kinect SDK features real-time skeletal tracking of 3D locations for skeletal joints, with its RGB-D sensor and human pose estimation algorithm [9]. Such low-cost, portable Kinect sensors achieved great popularity in motion analysis [10,11,12,13]

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