Preprint Article Version 1 This version not peer reviewed

Tactile Sensors for Measuring Effects of Sight, Movement, and Sound on Handgrip Forces during Hand-Tool Interaction

Version 1 : Received: 14 November 2017 / Approved: 15 November 2017 / Online: 15 November 2017 (04:25:33 CET)

How to cite: Batmaz, A.U..; Falekh, M.A..; Mathelin, M.D..; Dresp-Langley, B. Tactile Sensors for Measuring Effects of Sight, Movement, and Sound on Handgrip Forces during Hand-Tool Interaction. Preprints 2017, 2017110093 (doi: 10.20944/preprints201711.0093.v1). Batmaz, A.U..; Falekh, M.A..; Mathelin, M.D..; Dresp-Langley, B. Tactile Sensors for Measuring Effects of Sight, Movement, and Sound on Handgrip Forces during Hand-Tool Interaction. Preprints 2017, 2017110093 (doi: 10.20944/preprints201711.0093.v1).

Abstract

Using tactile sensing to measure grip force variations during hand-tool interaction reveals effects of sensory feed-back signals on individual handgrip forces in surgical simulator training. A biosensor system was designed for recording grip-force signals from different loci of measurement in the palm, the fingers, and the fingertips of the dominant and non-dominant hands of eleven novice surgeons. To test for effects of sound, movement, and sight on grip force signals, subjects had to pick up two tools, then hold them still or move them upwards and downwards for ten seconds while listening to soft or hard musical tones, with their eyes open and blindfolded. We found significant effects of movement, sight, and sound on average maximum peak forces. Stronger grip force signals were recorded from the dominant hand moving the tools. In specific sensor loci in the fingertips, significantly stronger grip forces were recorded in the absence of visual input (blindfolded condition). Grip forces recorded from the palm of the hands were significantly stronger with exposure to hard musical tones. It is concluded that handgrip force is significantly influenced by sensory signals from the auditory and visual sensory modalities. Such interactions could be effectively exploited for guiding simulator training.

Subject Areas

tactile sensors; grip force variations; tool movements; sensory feed-back; surgical simulators; skill evolution

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