Haptics Experiments
The sense of touch is critical to medical treatment, especially in surgery, dermatology, and other specialities in which the physician makes judgements based partly on the biomechanical characteristics of part of the anatomy. Haptics feedback is now feasible in simulators and is increasing available in surgical training simulations. To make effective use of touch in networked simulators, it is essential to understand how network communications this sense for individual and collaborative work in surgical simulation.
Prior work in this laboratory has explored how network latency, packet loss, and other network factors influence visual perception and performance in learning tasks. Our goal is to extend this work to haptic interfaces, to characterize such perception in real and virtual materials, and to determine parameters for effective use of haptic presentation. In this work we focused on network latency as the primary network parameter to adjust.
We performed a series of experiments to measure haptic perception using both real and simulated forces. We first created a durometer containing latex sheets of various thickness. Users probed these using laparoscopic tools, but without visual feedback. Subjects are able to feel differences in elasticity and can correctly rank the sheets in order of stiffness.
Virtual membranes with haptic output were modeled using the SPRING platform, comparing objects with four different constant stiffnesses to an unknown that matched one of the other four. The task is to pick the closest match to the center object by probing and sensing force differences. Network latency was also introduced, adding a time delay from from 0 to 100 milliseconds between probing and the force feedback. This apparently simple task proved to be difficult for most subjects.
We tested several profiles of force feedback as a function of penetration depth. Although learners judged the profile that increases force as the square of the depth (quadratic) to be most realistic, subjects performed at the same level with both linear and quadratic force profiles. In an apparently simpler task, comparing two virtual surfaces using a low-friction, finger held haptic interface, subjects can usually pick the difference in the force levels reliably when one force is twice the magnitude of the other. A significant number of errors are made with smaller force differences.
When both membranes resist with similar force, but a network delay greater than 50 ms is introduced in sensing force on one membrane, subjects usually interpreted the two forces as being different. This is compatible with our earlier studies that indicated 100 ms as the maximum loop delay before a position-following task became unstable.