Evidence map›Paper›PMID 39288164›Full record

ArticlePloS one2024

Optimization of stimulus properties for SSVEP-based BMI system with a heads-up display to control in-vehicle features.

Hossein Hamidi Shishavan, Raheli Roy, Kia Golzari, Abhishek Singla, David Zalozhin, Danny Lohan, Muhamed Farooq, Ercan M Dede, Insoo Kim

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Hossein Hamidi ShishavanDepartment of Medicine, University of Connecticut School of Medicine, Farmington, Connecticut, United States of America.ORCID 0000-0001-8467-9169
Raheli RoyDepartment of Medicine, University of Connecticut School of Medicine, Farmington, Connecticut, United States of America.
Kia GolzariDepartment of Biomedical Engineering, University of Connecticut, Storrs, Connecticut, United States of America.
Abhishek SinglaDepartment of Biomedical Engineering, University of Connecticut, Storrs, Connecticut, United States of America.
David ZalozhinDepartment of Biomedical Engineering, University of Connecticut, Storrs, Connecticut, United States of America.
Danny LohanToyota Research Institute of North America, Ann Arbor, Michigan, United States of America.
Muhamed FarooqToyota Research Institute of North America, Ann Arbor, Michigan, United States of America.
Ercan M DedeToyota Research Institute of North America, Ann Arbor, Michigan, United States of America.ORCID 0000-0001-6740-5916
Insoo KimDepartment of Medicine, University of Connecticut School of Medicine, Farmington, Connecticut, United States of America.ORCID 0000-0001-6539-1776

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the years, the driver-vehicle interface has been improved, but interacting with in-vehicle features can still increase distraction and affect road safety. This study aims to introduce brain-machine interface (BMI)- based solution to potentially enhance road safety. To achieve this goal, we evaluated visual stimuli properties (SPs) for a steady state visually evoked potentials (SSVEP)-based BMI system. We used a heads-up display (HUD) as the primary screen to present icons for controlling in-vehicle functions such as music, temperature, settings, and navigation. We investigated the effect of various SPs on SSVEP detection performance including the duty cycle and signal-to-noise ratio of visual stimuli, the size, color, and frequency of the icons, and array configuration and location. The experiments were conducted with 10 volunteers and the signals were analyzed using the canonical correlation analysis (CCA), filter bank CCA (FBCCA), and power spectral density analysis (PSDA). Our experimental results suggest that stimuli with a green color, a duty cycle of 50%, presented at a central location, with a size of 36 cm2 elicit a significantly stronger SSVEP response and enhanced SSVEP detection time. We also observed that lower SNR stimuli significantly affect SSVEP detection performance. There was no statistically significant difference observed in SSVEP response between the use of an LCD monitor and a HUD.

Indexed as

Brain-Computer InterfacesEvoked Potentials, VisualPhotic StimulationAdultAutomobile DrivingElectroencephalographyFemaleHumansMaleSignal-To-Noise RatioYoung Adult

Identifiers

PMID39288164
PMCPMC11407624

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.