Do accuracy requirements change bimanual and unimanual control processes similarly?

TouchView: Mid-Air Touch on Zoomable 2D View for Distant Freehand Selection on a Virtual Reality User Interface

Selection is a fundamental interaction element in virtual reality (VR) and 3D user interfaces (UIs). Raycasting, one of the most common object selection techniques, is known to have difficulties in selecting small or distant objects. Meanwhile, recent advancements in computer vision technology have enabled seamless vision-based hand tracking in consumer VR headsets, enhancing accessibility to freehand mid-air interaction and highlighting the need for further research in this area. This study proposes a new technique called TouchView, which utilizes a virtual panel with a modern adaptation of the Through-the-Lens metaphor to improve freehand selection for VR UIs. TouchView enables faster and less demanding target selection by allowing direct touch interaction with the magnified object proxies reflected on the panel view. A repeated-measures ANOVA on the results of a follow-up experiment on multitarget selection with 23 participants showed that TouchView outperformed the current market-dominating freehand raycasting technique, Hybrid Ray, in terms of task performance, perceived workload, and preference. User behavior was also analyzed to understand the underlying reasons for these improvements. The proposed technique can be used in VR UI applications to enhance the selection of distant objects, especially for cases with frequent view shifts.

The influence of accuracy constraints on bimanual and unimanual sequence learning

An experiment was designed to determine whether accuracy constraints can influence how unimanual and bimanual motor sequences are produced and learned. The accuracy requirements of the task were manipulated using principles derived from Fitts' Law to create relatively low (ID = 3) and high (ID = 5) accuracy demands. Right-limb dominant participants (N = 28, age = 21.9 yrs; 15 females and 13 males) were required to produce unimanual left, unimanual right or bimanual movement sequences using elbow extension and flexion movements to hit a series of illuminated targets. The targets were illuminated in a repeating sequence of 16 elements. Participants performed 20 practice trials. Thirty minutes following the practice trials participants performed a retention test. Element duration (time interval between target hits) and segment harmonicity (hesitations/adjustments in movement pattern) were calculated. The results indicate longer element duration and lower harmonicity values (more adjustments) when the task required higher accuracy demands (ID = 5) compared to low accuracy demands (ID = 3). Element duration was shorter and harmonicity was higher at ID = 5 for both unimanual groups than the bimanual group. However, element duration was shorter and harmonicity was higher at ID = 3 for the bimanual group than for both unimanual groups. These results indicate that the accuracy demands of the task can influence both performance and learning of motor sequences and suggest differences between unimanual and bimanual motor sequence learning. It appears there is a bimanual advantage for tasks with lower accuracy demands whereas performance is more accurate with unimanual performance, regardless of limb, with higher accuracy demands. These results are consistent with recent research indicating that accuracy requirements change the control processes for bimanual performance differently than for unimanual tasks.

An inverse optimization approach to understand human acquisition of kinematic coordination in bimanual fine manipulation tasks

Tasks that require the cooperation of both hands and arms are common in human everyday life. Coordination helps to synchronize in space and temporally motion of the upper limbs. In fine bimanual tasks, coordination enables also to achieve higher degrees of precision that could be obtained from a single hand. We studied the acquisition of bimanual fine manipulation skills in watchmaking tasks, which require assembly of pieces at millimeter scale. It demands years of training. We contrasted motion kinematics performed by novice apprentices to those of professionals. Fifteen subjects, ten novices and five experts, participated in the study. We recorded force applied on the watch face and kinematics of fingers and arms. Results indicate that expert subjects wisely place their fingers on the tools to achieve higher dexterity. Compared to novices, experts also tend to align task-demanded force application with the optimal force transmission direction of the dominant arm. To understand the cognitive processes underpinning the different coordination patterns across experts and novice subjects, we followed the optimal control theoretical framework and hypothesize that the difference in task performances is caused by changes in the central nervous system's optimal criteria. We formulated kinematic metrics to evaluate the coordination patterns and exploit inverse optimization approach to infer the optimal criteria. We interpret the human acquisition of novel coordination patterns as an alteration in the composition structure of the central nervous system's optimal criteria accompanied by the learning process.