Literature DB >> 12554399

Multimodal feedback: an assessment of performance and mental workload.

H S Vitense1, J A Jacko, V K Emery.   

Abstract

Multimodal interfaces offer great potential to humanize interactions with computers by employing a multitude of perceptual channels. This paper reports on a novel multimodal interface using auditory, haptic and visual feedback in a direct manipulation task to establish new recommendations for multimodal feedback, in particular uni-, bi- and trimodal feedback. A close examination of combinations of uni-, bi- and trimodal feedback is necessary to determine which enhances performance without increasing workload. Thirty-two participants were asked to complete a task consisting of a series of 'drag-and-drops' while the type of feedback was manipulated. Each participant was exposed to three unimodal feedback conditions, three bimodal feedback conditions and one trimodal feedback condition that used auditory, visual and haptic feedback alone, and in combination. Performance under the different conditions was assessed with measures of trial completion time, target highlight time and a self-reported workload assessment captured by the NASA Task Load Index (NASA-TLX). The findings suggest that certain types of bimodal feedback can enhance performance while lowering self-perceived mental demand.

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Year:  2003        PMID: 12554399     DOI: 10.1080/00140130303534

Source DB:  PubMed          Journal:  Ergonomics        ISSN: 0014-0139            Impact factor:   2.778


  8 in total

1.  In vivo validation of a system for haptic feedback of tool vibrations in robotic surgery.

Authors:  Karlin Bark; William McMahan; Austin Remington; Jamie Gewirtz; Alexei Wedmid; David I Lee; Katherine J Kuchenbecker
Journal:  Surg Endosc       Date:  2012-07-18       Impact factor: 4.584

2.  Combined Auditory and Vibrotactile Feedback for Human-Machine-Interface Control.

Authors:  Elias B Thorp; Eric Larson; Cara E Stepp
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2013-07-31       Impact factor: 3.802

3.  Suture Breakage Warning System for Robotic Surgery.

Authors:  Ahmad Abiri; Syed J Askari; Anna Tao; Yen-Yi Juo; Yuan Dai; Jake Pensa; Robert Candler; Erik P Dutson; Warren S Grundfest
Journal:  IEEE Trans Biomed Eng       Date:  2018-09-10       Impact factor: 4.538

4.  Mental workload during brain-computer interface training.

Authors:  Elizabeth A Felton; Justin C Williams; Gregg C Vanderheiden; Robert G Radwin
Journal:  Ergonomics       Date:  2012-04-16       Impact factor: 2.778

5.  Haptic Guidance Needs to Be Intuitive Not Just Informative to Improve Human Motor Accuracy.

Authors:  Winfred Mugge; Irene A Kuling; Eli Brenner; Jeroen B J Smeets
Journal:  PLoS One       Date:  2016-03-16       Impact factor: 3.240

6.  Human-centric predictive model of task difficulty for human-in-the-loop control tasks.

Authors:  Ziheng Wang; Ann Majewicz Fey
Journal:  PLoS One       Date:  2018-04-05       Impact factor: 3.240

7.  Transfer of training-Virtual reality training with augmented multisensory cues improves user experience during training and task performance in the real world.

Authors:  Natalia Cooper; Ferdinando Millela; Iain Cant; Mark D White; Georg Meyer
Journal:  PLoS One       Date:  2021-03-24       Impact factor: 3.240

8.  The effects of substitute multisensory feedback on task performance and the sense of presence in a virtual reality environment.

Authors:  Natalia Cooper; Ferdinando Milella; Carlo Pinto; Iain Cant; Mark White; Georg Meyer
Journal:  PLoS One       Date:  2018-02-01       Impact factor: 3.240

  8 in total

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