The act of puncturing a surface with a hand-held tool is a ubiquitous but complex motor behavior that requires precise force control to avoid potentially severe consequences. We present a detailed model of puncture over a time-course of approximately 1000 ms, which is fit to kinematic data from individual punctures, obtained via a simulation with high-fidelity force feedback. The model describes puncture as proceeding from purely physically determined interactions between the surface and tool, through decline of force due to biomechanical viscosity, to cortically mediated voluntary control. When fit to the data, it yields parameters for the inertial mass of the tool/person coupling, time-characteristic of force decline, onset of active braking, stopping time and distance, and late oscillatory behavior, all of which the analysis relates to physical variables manipulated in the simulation. While the present data characterize distinct phases of motor performance in a group of healthy young adults, the approach could potentially be extended to quantify the performance of individuals from other populations, e.g., with sensory-motor impairments. Applications to surgical force-control devices are also considered.
Objective This study investigated the effectiveness of force augmentation in haptic perception tasks. Background Considerable engineering effort has been devoted to developing force augmented reality (AR) systems to assist users in delicate procedures like microsurgery. In contrast, far less has been done to characterize the behavioral outcomes of these systems, and no research has systematically examined the impact of sensory and perceptual processes on force augmentation effectiveness. Method Using a handheld force magnifier as an exemplar haptic AR, we conducted three experiments to characterize its utility in the perception of force and stiffness. Experiments 1 and 2 measured, respectively, the user’s ability to detect and differentiate weak force (<0.5 N) with or without the assistance of the device and compared it to direct perception. Experiment 3 examined the perception of stiffness through the force augmentation. Results The user’s ability to detect and differentiate small forces was significantly improved by augmentation at both threshold and suprathreshold levels. The augmentation also enhanced stiffness perception. However, although perception of augmented forces matches that of the physical equivalent for weak forces, it falls off with increasing intensity. Conclusion The loss in the effectiveness reflects the nature of sensory and perceptual processing. Such perceptual limitations should be taken into consideration in the design and development of haptic AR systems to maximize utility. Application The findings provide useful information for building effective haptic AR systems, particularly for use in microsurgery.
Abstract-We present a novel and relatively simple method for clustering pixels into homogeneous patches using a directed graph of edges between neighboring pixels. For a 2D image, the mean and variance of image intensity is computed within a circular region centered at each pixel. Each pixel stores its circle's mean and variance, and forms the node in a graph, with possible edges to its 4 immediate neighbors. If at least one of those neighbors has a lower variance than itself, a directed edge is formed, pointing to the neighbor with the lowest variance. Local minima in variance thus form the roots of disjoint trees, representing patches of relative homogeneity. The method works in n-dimensions and requires only a single parameter: the radius of the circular (spherical, or hyperspherical) regions used to compute variance around each pixel. Setting the intensity of all pixels within a given patch to the mean at its root pixel significantly reduces image noise while preserving anatomical structure, including location of boundaries. The patches may themselves be clustered using techniques that would be computationally too expensive if applied to the raw pixels. We demonstrate such clustering to identify fascicles in the median nerve in high-resolution 2D ultrasound images, as well as white matter hyperintensities in 3D magnetic resonance images.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.