Using Force Feedback Devices to Train and Assess Recognition of Force Signals as a Component of Professional Skill

University Of Iowa, Iowa City IA

Investigators

Abstract

This research is intended to develop and evaluate a haptic simulator suitable for training people to detect very small features in a physical surface such as a human tooth. A driving force behind the apparent demise of professional haptic skill in recent years may simply be a failure to develop and maintain sufficiently rigorous standards of skill specification, training and assessment. Haptic information is not readily amenable to either verbal or visual clarification, and yet professionals such as dentists, jewelers and engravers must learn haptic skills. Limitations of our language make it difficult to accurately describe haptic techniques; our haptic vocabulary consists of vague words such as "tough," "spongy," and "sticky." It is also difficult to visually demonstrate or assess haptic skills. Instructors are unable to see exactly how hard a student presses. Unlike visual information, instructors are generally unable to share a haptic experience with a student. The salvation of haptic skills may lie with computers, strain gauges and motors. These devices can accurately record, visually display, and endlessly reproduce haptic signals. Together, these technologies present an opportunity to reestablish a robust, rewarding culture of haptic skill in the professional workplace. Such a workplace would more productively and thoroughly engage the whole scope of human capability. Training dentists to elicit and recognize force signals is the primary design challenge for the simulator. It will be refined and developed around this simple criterion, placing force signal fidelity above all other competing design criteria including: 1) the geometry of the tooth surface, 2) the visual appearance of the tooth, 3) the precise shape and feel of the dental tool handle, 4) the spatial resolution of the simulator device and 5) the simulated hardness of the tooth itself. Ultimately the project will compare the clinical performance of dentists trained with the simulator against those trained with traditional methods. This work will provide an important contribution to the field of haptic simulation by suggesting a method to empirically identify force signals, benchmark a simulator's performance for reproducing these signals, and demonstrating a tangible, practical benefit to haptic simulator training.