Evidence map›Paper›PMID 37896483›Full record

ArticleSensors (Basel, Switzerland)2023

A Neuroergonomic Approach Fostered by Wearable EEG for the Multimodal Assessment of Drivers Trainees.

Gianluca Di Flumeri, Andrea Giorgi, Daniele Germano, Vincenzo Ronca, Alessia Vozzi, Gianluca Borghini, Luca Tamborra, Ilaria Simonetti, Rossella Capotorto, Silvia Ferrara and 3 more

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

11 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. 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

13 authors at 2 institutions in 2 countries.

Gianluca Di FlumeriLaboratory of Industrial Neuroscience, Department of Molecular Medicine, Sapienza University of Rome, 00185 Rome, Italy.ORCID 0000-0003-4426-051X
Andrea GiorgiBrainSigns srl, 00198 Rome, Italy.ORCID 0000-0001-6220-3389
Daniele GermanoLaboratory of Industrial Neuroscience, Department of Molecular Medicine, Sapienza University of Rome, 00185 Rome, Italy.
Vincenzo RoncaBrainSigns srl, 00198 Rome, Italy.ORCID 0000-0002-7174-6331
Alessia VozziBrainSigns srl, 00198 Rome, Italy.ORCID 0000-0002-8584-5023
Gianluca BorghiniLaboratory of Industrial Neuroscience, Department of Molecular Medicine, Sapienza University of Rome, 00185 Rome, Italy.ORCID 0000-0001-8560-5671
Luca TamborraBrainSigns srl, 00198 Rome, Italy.ORCID 0000-0003-4200-9110
Ilaria SimonettiBrainSigns srl, 00198 Rome, Italy.
Rossella CapotortoLaboratory of Industrial Neuroscience, Department of Molecular Medicine, Sapienza University of Rome, 00185 Rome, Italy.ORCID 0009-0005-0842-2915
Silvia FerraraBrainSigns srl, 00198 Rome, Italy.
Nicolina SciaraffaBrainSigns srl, 00198 Rome, Italy.
Fabio BabiloniLaboratory of Industrial Neuroscience, Department of Molecular Medicine, Sapienza University of Rome, 00185 Rome, Italy.ORCID 0000-0002-4962-176X
Pietro AricòBrainSigns srl, 00198 Rome, Italy.ORCID 0000-0002-3831-6620
Sapienza University of Rome · ITHangzhou Dianzi University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

When assessing trainees' progresses during a driving training program, instructors can only rely on the evaluation of a trainee's explicit behavior and their performance, without having any insight about the training effects at a cognitive level. However, being able to drive does not imply knowing how to drive safely in a complex scenario such as the road traffic. Indeed, the latter point involves mental aspects, such as the ability to manage and allocate one's mental effort appropriately, which are difficult to assess objectively. In this scenario, this study investigates the validity of deploying an electroencephalographic neurometric of mental effort, obtained through a wearable electroencephalographic device, to improve the assessment of the trainee. The study engaged 22 young people, without or with limited driving experience. They were asked to drive along five different but similar urban routes, while their brain activity was recorded through electroencephalography. Moreover, driving performance, subjective and reaction times measures were collected for a multimodal analysis. In terms of subjective and performance measures, no driving improvement could be detected either through the driver's subjective measures or through their driving performance. On the other side, through the electroencephalographic neurometric of mental effort, it was possible to catch their improvement in terms of mental performance, with a decrease in experienced mental demand after three repetitions of the driving training tasks. These results were confirmed by the analysis of reaction times, that significantly improved from the third repetition as well. Therefore, being able to measure when a task is less mentally demanding, and so more automatic, allows to deduce the degree of users training, becoming capable of handling additional tasks and reacting to unexpected events.

Indexed as

Automobile DrivingWearable Electronic DevicesAccidents, TrafficAdolescentElectroencephalographyHumansReaction Timecar simulatordriving educationlearningmental effortneuroergonomicsPassive Brain–Computer Interface (BCI)road safetywearable EEG

Identifiers

PMID37896483
PMCPMC10610858
OpenAlexW4387539921

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.