Abstract
As the concept of the metaverse fuels a growing interest in VR and other technologies that track users’ arm movements [46], virtual hand reaching will continue to be a common way for users to select and manipulate the virtual objects presented in these displays. Kinematic analysis (KA) metrics quantify different useful properties of virtual hand reaches, including the speed, efficiency, and smoothness of these movements. These measures can provide valuable insights into users’ movement behaviors to support emerging uses of VR technology in stroke rehabilitation (e.g., [144]) and motor skills training (e.g., [1]).
Past research suggests that some KA metrics can change when users perform reaching movements in different directions (i.e., movement direction). Furthermore, the effect of movement direction on these metrics may be different for reaches that occur on the same or opposite side of the user’s body from the reaching arm (i.e., interaction hemispace), for reaches performed using the dominant or non-dominant arm (i.e., hand dominance), and for users with longer or shorter arms (i.e., arm length). However, no studies to-date have yet explored if and how all four of these factors may interact to influence the kinematic properties of virtual hand reaches. In the present work, we began to address this gap.
First, we performed an exploratory study that provided an initial look at how the first three factors (movement direction, hand dominance, and interaction hemispace) interact to influence the kinematic properties of virtual hand reaches (Chapter 2). A sample of 20 users performed virtual hand reaches in five cardinal directions (up, down, left, right, or away), on both sides of their bodies, using both their dominant and non-dominant hands. The results (1) revealed for the first time that these three factors interact to influence the kinematic properties of goal-directed reaches, and (2) provided a novel account of how each KA metric changes as a function of movement direction when users reach on either side of their body using either hand.
In the second study, we took a more detailed look at how KA metrics change as a function of movement direction for reaches performed on each side of the body using each hand (Chapter 3). Based on our results in the first study, we focused on reaches in 12 different directions that either involved moving inward (toward the body midline) or outward (away from the body midline). As in the first study, 20 users reached in each direction on both the left and right sides of their body, using both their dominant and non-dominant hands. The results replicated our principal findings from Chapter 2 and provided a more fine-grained account of how the kinematic properties of virtual hand reaches change as a function of movement direction when users reach on either side of their body using either hand. In short, we found that the influence of movement direction on reaching kinematics is (1) vastly different for each KA metric and (2) depends heavily on both the hand used to perform movements and the side of the body on which movements occur.
In the third study, we examined if individual differences in arm length moderate the effects of movement direction on KA metrics, when users reach on each side of their body using each hand (Chapter 4). A sample of 40 users with a range of different arm lengths performed the same reaching task used in Chapter 3, and the length of each user’s arms was measured using standard anthropometric procedures. We then examined (1) if the largest effects of movement direction on KA metrics that we observed in previous studies emerged differently for different individual users, and (2) if these effects were systematically different for users with shorter arms than for users with longer arms. The results indicated that there were meaningful differences between users concerning how they adapted the kinematic properties of their reaches to move in different directions, for reaches on each side of their body using each hand. However, in most cases, the effects of movement direction on KA metrics were not systematically different for users with shorter arms than for users with longer arms. This indicates that between-participant variation in the effects we examined was likely caused by individual differences in factor(s) other than arm length.
Together, these three studies provide the first empirical account of how movement direction, hand dominance, interaction hemispace, and individual differences in arm length interact to influence the kinematic properties of virtual hand reaches. Indeed, to our knowledge, this represents the first time that the joint influence of these four factors on movement kinematics has been explored for goal-directed reaches performed in any context, including for reaches performed to physical targets. Our findings have practical implications for work in several areas at the intersection of movement science and virtual reality, including laboratory research on motor control processes, predictive modeling of 3D reaching movements in VR, and the emerging use of VR-based kinematic analyses in applied contexts such as stroke rehabilitation, motor skills training, and usability assessment.
