Logan Clark
ABSTRACT
In recent years, virtual reality (VR) technology has shown promise as a means of delivering rehabilitative care to restore arm function in stroke patients. At the same time, limitations of traditional clinical scales for measuring arm function recovery have led to the more widespread use of kinematic metrics. These metrics quantify useful properties of patients’ movements using motion tracking data captured while the patient performs different types of assessment tasks. Given modern consumer VR systems already collect the data needed to calculate many common kinematic metrics, these systems could eventually be used to both deliver stroke rehabilitation programs and administer kinematic assessments to monitor patients’ recovery. However, it is not yet clear how the properties of VR-based assessment tasks may systematically impact the values of kinematic metrics used to assess arm function post-stroke. To begin addressing this question, we examined the influence of two task properties (movement direction and hand dominance) on a set of 10 kinematic metrics during a discrete reaching task performed by healthy participants using an Oculus Quest 2 VR headset. Our findings indicate that all 10 metrics were significantly impacted by these task properties, confirming that kinematic metrics captured in this context are sensitive to task properties. Our results also provide an initial account of how the metrics were influenced by each task property and highlight needs for future work to further understand the influence of assessment task properties on VR-based kinematic assessments.
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- VR-Based Kinematic Assessments: Examining the Effects of Task Properties on Arm Movement Kinematics
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