Analysis of Control Characteristics between Dominant and Non-Dominant Hands by Transient Responses of Circular Tracking Movements in 3D Virtual Reality Space

Park, Wookhyun; Choi, Woong; Jo, Hanjin; Lee, Geonhui; Kim, Jaehyo

doi:10.3390/s20123477

Cited by 5 publications

(3 citation statements)

References 59 publications

(146 reference statements)

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“…For FF control, we did not observe a remarkable performance for the dominant hand (see Figure 4), suggesting that both hands have a similar capability to acquire internal models. This result is consistent with that of a previous study [44], with a tracer's initial peak speed and the corresponding initial peak time showing no difference in FF control of the dominant and non-dominant hands. Therefore, a difference in the performance of both arms in FF control [44,45] may not be attributable to the differences in muscle torque control for multi-joint movements.…”

Section: Motor Control In Single-joint Movementssupporting

confidence: 93%

Analysis of Differences in Single-Joint Movement of Dominant and Non-Dominant Hands for Human-like Robotic Control

Kim,

Min,

Kim

et al. 2023

Sensors

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Although several previous studies on laterality of upper limb motor control have reported functional differences, this conclusion has not been agreed upon. It may be conjectured that the inconsistent results were caused because upper limb motor control was observed in multi-joint tasks that could generate different inter-joint motor coordination for each arm. Resolving this, we employed a single wrist joint tracking task to reduce the effect of multi-joint dynamics and examined the differences between the dominant and non-dominant hands in terms of motor control. Specifically, we defined two sections to induce feedback (FB) and feedforward (FF) controls: the first section involved a visible target for FB control, and the other section involved an invisible target for FF control. We examined the differences in the position errors of the tracer and the target. Fourteen healthy participants performed the task. As a result, we found that during FB control, the dominant hand performed better than the non-dominant hand, while we did not observe significant differences in FF control. In other words, in a single-joint movement that is not under the influence of the multi-joint coordination, only FB control showed laterality and not FF control. Furthermore, we confirmed that the dominant hand outperformed the non-dominant hand in terms of responding to situations that required a change in control strategy.

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Section: Motor Control In Single-joint Movementssupporting

confidence: 93%

Analysis of Differences in Single-Joint Movement of Dominant and Non-Dominant Hands for Human-like Robotic Control

Kim,

Min,

Kim

et al. 2023

Sensors

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“…More recently, some authors have used 3D virtual environments to examine the control characteristics of dominant and nondominant hands during a circular tracking task with varying target speeds in healthy adults (Choi et al, 2018;Choi et al, 2021;Jo et al, 2020;Park et al, 2020). Their results showed a decrease in initial peak velocity in both hands as target speed increased.…”

Section: Introductionmentioning

confidence: 99%

Impact of task constraints on a 3D visuomotor tracking task in virtual reality

Baillet,

Burin-Chu,

Lejeune

et al. 2023

Front. Virtual Real.

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Objective: The aim of the present study was to evaluate the impact of different task constraints on the participants’ adaptation when performing a 3D visuomotor tracking task in a virtual environment.Methods: Twenty-three voluntary participants were tested with the HTC Vive Pro Eye VR headset in a task that consisted of tracking a virtual target moving in a cube with an effector controlled with the preferred hand. Participants had to perform 120 trials according to three task constraints (i.e., gain, size, and speed), each performed according to four randomized conditions. The target-effector distance and elbow range of movement were measured.Results: The results showed an increase in the distance to the target when the task constraints were the strongest. In addition, a change in movement kinematics was observed, involving an increase in elbow amplitude as task constraints increased. It also appeared that the depth dimension played a major role in task difficulty and elbow amplitude and coupling in the tracking task.Conclusion: This research is an essential step towards characterizing interactions with a 3D virtual environment and showing how virtual constraints can facilitate arm’s involvement in the depth dimension.

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“…With the recent development of virtual reality (VR) technology, it was possible to implement various human movement experiments in a 3D virtual space. Some previous studies analyzed circular tracking motion in a 3D space, including depth information, using these VR devices [16][17][18][19]. In these studies, the tracking movement with constant velocity was conducted on the frontal and sagittal planes.…”

Section: Introductionmentioning

confidence: 99%

Analysis of motor control strategy for frontal and sagittal planes of circular tracking movements using visual feedback noise from velocity change and depth information

Lee

Choi

et al. 2020

PLoS ONE

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We aim to investigate a control strategy for the circular tracking movement in a three-dimensional (3D) space based on the accuracy of the visual information. After setting the circular orbits for the frontal and sagittal planes in the 3D virtual space, the subjects track a target moving at a constant velocity. The analysis is applied to two parameters of the polar coordinates, namely, ΔR (the difference in the distance from the center of a circular orbit) and Δω (the difference in the angular velocity). The movement in the sagittal plane provides different depth information depending on the position of the target in orbit, unlike the task of the frontal plane. Therefore, the circular orbit is divided into four quadrants for a statistical analysis of ΔR. In the sagittal plane, the error was two to three times larger in quadrants 1 and 4 than in quadrants 2 and 3 close to the subject. Here, Δω is estimated using a frequency analysis; the lower the accuracy of the visual information, the greater the periodicity. When comparing two different planes, the periodicity in the sagittal plane was approximately 1.7 to 2 times larger than that of the frontal plane. In addition, the average angular velocity of the target and tracer was within 0.6% during a single cycle. We found that if the amount of visual information is reduced, an optimal feedback control strategy can be used to reduce the positional error within a specific area.

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Analysis of Control Characteristics between Dominant and Non-Dominant Hands by Transient Responses of Circular Tracking Movements in 3D Virtual Reality Space

Cited by 5 publications

References 59 publications

Analysis of Differences in Single-Joint Movement of Dominant and Non-Dominant Hands for Human-like Robotic Control

Analysis of Differences in Single-Joint Movement of Dominant and Non-Dominant Hands for Human-like Robotic Control

Impact of task constraints on a 3D visuomotor tracking task in virtual reality

Analysis of motor control strategy for frontal and sagittal planes of circular tracking movements using visual feedback noise from velocity change and depth information

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