Is simulator-based driver rehabilitation missing motion feedback?

William, Howard; Kinder, Christian M.; Lodha, Neha; Smith, Brendan W.

doi:10.1109/icorr.2019.8779414

Cited by 2 publications

(8 citation statements)

References 23 publications

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“…A linear regression yielded the following relation: ln(SD SS ) = −0.630 + 0.752 ln(SSQ) . Using this relation, we imputed the SD for studies where it was not reported and where it could also not be retrieved from figures (Park et al 2005;Hohorst et al 2019;Boustila et al 2017). These imputed values were then used in the meta-regression (see: "Data analysis").…”

Section: Sickness Scoringmentioning

confidence: 99%

“…Visualization modality We distinguish between four types of visualization modalities. Out of all studies, 20 used monitors, in 36 conditions (Zou et al 2021;Gemonet et al 2021;Almallah et al 2021;Parduzi et al 2020;Suwarno et al 2019;Hohorst et al 2019;Walch et al 2017;Romano et al 2016;Bridgeman et al 2014;Park et al 2005;Sekar et al 2020;Parduzi et al 2019;Ujike and Watanabe 2011;Garcia et al 2010;Stelling et al 2020;Somrak et al 2019;Mittelstaedt et al 2018;Häkkinen et al 2006;Klüver et al 2016); 16 studies used projection systems, in 54 conditions (Talsma et al 2022;Jurisch et al 2020;Benz et al 2019;Weidner et al 2017;Aykent et al 2014;Park et al 2005;Lin et al 2002b;Colombet et al 2016;Parduzi et al 2019;Will et al 2017;Schmieder et al 2017;Keshavarz and Hecht 2012;Boustila et al 2017;Emoto et al 2008;Damveld et al 2010;Klüver et al 2016); 21 studies used HMDs, in 54 conditions (Zou et al 2021;Sawada et al 2020;Parduzi et al 2020;Suwarno et al 2019;…”

Section: Visual Fidelitymentioning

confidence: 99%

“…Field-of-View Following the consensus on the subdivision of the human FoV, we binned studies with visualizations that covered only (part of) the central FoV < 60 Emoto et al 2008;Häkkinen et al 2006); both the central and peripheral FoV 60 • − 180 • , yielding 29 studies and 89 conditions (Zou et al 2021;Almallah et al 2021;Sawada et al 2020;Parduzi et al 2020;Suwarno et al 2019;Hohorst et al 2019;Walch et al 2017;Weidner et al 2017;Romano et al 2016;Aykent et al 2014;Park et al 2005;Colombet et al 2016;Lucas et al 2020;Sekar et al 2020;Parduzi et al 2019;Hartfiel and Stark 2019;Eftekharifar et al 2021;Jung et al 2021;Kaufeld and Alexander 2019;Keshavarz and Hecht 2012;Stelling et al 2020;Somrak et al 2019;Mittelstaedt et al 2018;Boustila et al 2017;Emoto et al 2008;Kovácsová et al 2020;Klüver et al 2016); full FoV ( > 180 • ), 11 studies and 36 conditions (Talsma et al 2022;Gemonet et al 2021;Jurisch et al 2020;Lin et al 2002b;Colombet et al 2016;Parduzi et al 2019;Will et al 2017;Schmieder et al 2017;Garcia et al 2010;…”

Section: Visual Fidelitymentioning

confidence: 99%

“…Stereoscopy Thirty-three studies used (biocular) non-stereoscopic visualizations in 79 experimental conditions (Talsma et al 2022;Zou et al 2021;Gemonet et al 2021;Almallah et al 2021;Jurisch et al 2020;Parduzi et al 2020;Suwarno et al 2019;Benz et al 2019;Hohorst et al 2019;Walch et al 2017;Weidner et al 2017;Romano et al 2016;Bridgeman et al 2014;Aykent et al 2014;Park et al 2005;Sekar et al 2020;Parduzi et al 2019;Will et al 2017;Schmieder et al 2017;Eftekharifar et al 2021;Keshavarz and Hecht 2012;Moss and Muth 2011;Ujike and Watanabe 2011;Garcia et al 2010;Stelling et al 2020;Somrak et al 2019;Mittelstaedt et al 2018;Boustila et al 2017;Emoto et al 2008;Häkkinen et al 2006;Damveld et al 2010;Klüver et al 2016), with a mean sickness score of 0.067; 28 studies used stereoscopic 3D, in 69 experimental conditions (Talsma et al 2022;Zou et al 2021;Gemonet et al 2021;Sawada et al 2020;Parduzi et al 2020;Suwarno et al 2019;Benz et al 2019;…”

Section: Visual Fidelitymentioning

confidence: 99%

“…Motion base We can distinguish between static (fixed-base) simulators, dynamic (moving-base) simulators, and on-road conditions in real vehicles. Static simulators were used in 36 studies with a total of 94 experimental conditions, and average SS of 0.096 (Zou et al 2021;Almallah et al 2021;Sawada et al 2020;Suwarno et al 2019;Hohorst et al 2019;Walch et al 2017;Weidner et al 2017;Romano et al 2016;Bridgeman et al 2014;Aykent et al 2014;Park et al 2005;Lin et al 2002b;Colombet et al 2016;Lucas et al 2020;Sekar et al 2020;Hartfiel and Stark 2019;Will et al 2017;Schmieder et al 2017;Eftekharifar et al 2021;Jung et al 2021;Kaufeld and Alexander 2019;Keshavarz and Hecht 2012;Moss and Muth 2011;Ujike and Watanabe 2011;Garcia et al 2010;Stelling et al 2020;Somrak et al 2019;Mittelstaedt et al 2018;Boustila et al 2017;Emoto et al 2008;Häkkinen et al 2006;Damveld et al 2010;Kovácsová et al 2020;Klüver et al 2016). Dynamic simulators were featured in 21 studies with a total of 43 conditions, and average SS of 0.077 (Talsma et al 2022;Gemonet et al 2021;Sawada et al 2020;Jurisch et al 2020;…”

Section: Mechanical Fidelitymentioning

confidence: 99%

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A meta-analysis of simulator sickness as a function of simulator fidelity

2022

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Driving simulators are an increasingly important tool to develop vehicle functionalities and to study driver or passenger responses. A major hindrance to the use and validity of such studies is Simulator Sickness (SS). Several studies have suggested a positive relation between improvements in simulator fidelity and the likelihood of sickness. We hypothesized that this relation only holds true for static (fixed-base) simulators, and that increased fidelity in fact reduces simulator sickness in dynamic (moving-base) simulators. We performed a meta-analysis investigating the relation between sickness and fidelity in static and dynamic systems. A literature search yielded a total of 41 simulator studies that varied aspects of mechanical and/or visual fidelity and assessed SS for the same driving conditions and the same or equivalent participant groups. Evaluation of a model synthesizing the findings of these studies indicates that SS decreases with visual fidelity, and suggests that this effect may be negated for static simulators. The results of the modeling efforts thereby provide some support for the hypothesis that increased fidelity can reduce SS in dynamic simulators. Based on the evaluation of the literature we also note particular shortcomings and gaps in available research. Finally, we make recommendations for specific experiments that may fill these gaps and allow definitive conclusions on the role of simulator fidelity in SS.

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Section: Sickness Scoringmentioning

confidence: 99%

Section: Visual Fidelitymentioning

confidence: 99%

Section: Visual Fidelitymentioning

confidence: 99%

Section: Visual Fidelitymentioning

confidence: 99%

Section: Mechanical Fidelitymentioning

confidence: 99%

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A meta-analysis of simulator sickness as a function of simulator fidelity

2022

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Feasibility and Validity of a Low-Cost Racing Simulator in Driving Assessment after Stroke

et al. 2020

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There is a myriad of methodologies to assess driving performance after a stroke. These include psychometric tests, driving simulation, questionnaires, and/or road tests. Research-based driving simulators have emerged as a safe, convenient way to assess driving performance after a stroke. Such traditional research simulators are useful in recreating street traffic scenarios, but are often expensive, with limited physics models and graphics rendering. In contrast, racing simulators developed for motorsport professionals and enthusiasts offer high levels of realism, run on consumer-grade hardware, and can provide rich telemetric data. However, most offer limited simulation of traffic scenarios. This pilot study compares the feasibility of research simulation and racing simulation in a sample with minor stroke. We determine that the racing simulator is tolerated well in subjects with a minor stroke. There were correlations between research and racing simulator outcomes with psychometric tests associated with driving performance, such as the Trails Making Test Part A, Snellgrove Maze Task, and the Motricity Index. We found correlations between measures of driving speed on a complex research simulator scenario and racing simulator lap time and maximum tires off track. Finally, we present two models, using outcomes from either the research or racing simulator, predicting road test failure as linked to a previously published fitness-to-drive calculator that uses psychometric screening.

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Is simulator-based driver rehabilitation missing motion feedback?

Cited by 2 publications

References 23 publications

A meta-analysis of simulator sickness as a function of simulator fidelity

A meta-analysis of simulator sickness as a function of simulator fidelity

Feasibility and Validity of a Low-Cost Racing Simulator in Driving Assessment after Stroke

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