Evidence map›Paper›PMID 38257638›Full record

ArticleSensors (Basel, Switzerland)2024

In-Car Environment Control Using an SSVEP-Based Brain-Computer Interface with Visual Stimuli Presented on Head-Up Display: Performance Comparison with a Button-Press Interface.

Seonghun Park, Minsu Kim, Hyerin Nam, Jinuk Kwon, Chang-Hwan Im

Open access · goldAbstract readComparative Study
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.7field-weighted citation impact, top 18% of its field
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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Motion artifact-controlled micro-brain sensors between hair follicles for persistent augmented reality brain-computer interfaces.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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

5 authors at 1 institution in 1 country.

Seonghun ParkDepartment of Electronic Engineering, Hanyang University, Seoul 04763, Republic of Korea.ORCID 0000-0002-8676-1286
Minsu KimDepartment of Artificial Intelligence, Hanyang University, Seoul 04763, Republic of Korea.ORCID 0000-0002-5202-5993
Hyerin NamDepartment of Artificial Intelligence, Hanyang University, Seoul 04763, Republic of Korea.
Jinuk KwonDepartment of Electronic Engineering, Hanyang University, Seoul 04763, Republic of Korea.
Chang-Hwan ImDepartment of Electronic Engineering, Hanyang University, Seoul 04763, Republic of Korea.ORCID 0000-0003-3795-3318
Hanyang University · KR

Funding

KIST Institutional Program 2E32341-23-043Korean government (MSIT) NRF-2021M3E5D2A01019547
6 · The paper itself

Abstract

Controlling the in-car environment, including temperature and ventilation, is necessary for a comfortable driving experience. However, it often distracts the driver's attention, potentially causing critical car accidents. In the present study, we implemented an in-car environment control system utilizing a brain-computer interface (BCI) based on steady-state visual evoked potential (SSVEP). In the experiment, four visual stimuli were displayed on a laboratory-made head-up display (HUD). This allowed the participants to control the in-car environment by simply staring at a target visual stimulus, i.e., without pressing a button or averting their eyes from the front. The driving performances in two realistic driving tests-obstacle avoidance and car-following tests-were then compared between the manual control condition and SSVEP-BCI control condition using a driving simulator. In the obstacle avoidance driving test, where participants needed to stop the car when obstacles suddenly appeared, the participants showed significantly shorter response time (1.42 ± 0.26 s) in the SSVEP-BCI control condition than in the manual control condition (1.79 ± 0.27 s). No-response rate, defined as the ratio of obstacles that the participants did not react to, was also significantly lower in the SSVEP-BCI control condition (4.6 ± 14.7%) than in the manual control condition (20.5 ± 25.2%). In the car-following driving test, where the participants were instructed to follow a preceding car that runs at a sinusoidally changing speed, the participants showed significantly lower speed difference with the preceding car in the SSVEP-BCI control condition (15.65 ± 7.04 km/h) than in the manual control condition (19.54 ± 11.51 km/h). The in-car environment control system using SSVEP-based BCI showed a possibility that might contribute to safer driving by keeping the driver's focus on the front and thereby enhancing the overall driving performance.

Indexed as

Brain-Computer InterfacesAutomobilesEvoked Potentials, VisualEyeHumansLaboratoriesadvanced driver assistancebrain-computer interfaces (BCIs)head-up display (HUD)safe drivingsteady-state visual evoked potential (SSVEP)

Identifiers

PMID38257638
PMCPMC10819861
OpenAlexW4390876263

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.