Evidence map›Paper›PMID 36850812›Full record

SynthesisSensors (Basel, Switzerland)2023

A Systematic Review of In-Vehicle Physiological Indices and Sensor Technology for Driver Mental Workload Monitoring.

Ashwini Kanakapura Sriranga, Qian Lu, Stewart Birrell

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis 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 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
9.7field-weighted citation impact, top 2% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Detection of Cognitive Load Modulation by EDA and HRV.Sensors (Basel, Switzerland) · 2025
    Article
  5. Article
  6. Review
  7. Article
  8. Texting While Driving: A Literature Review on Driving Simulator Studies.International journal of environmental research and public health · 2023
    Review
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

3 authors at 1 institution in 1 country.

Ashwini Kanakapura SrirangaInstitute for Clean Growth and Future Mobility, Coventry University, Coventry CV1 5FB, UK.ORCID 0000-0002-2328-0979
Qian LuInstitute for Clean Growth and Future Mobility, Coventry University, Coventry CV1 5FB, UK.
Stewart BirrellInstitute for Clean Growth and Future Mobility, Coventry University, Coventry CV1 5FB, UK.
Coventry University · GB

Funding

Coventry University BDN68KDUX
6 · The paper itself

Abstract

The concept of vehicle automation ceases to seem futuristic with the current advancement of the automotive industry. With the introduction of conditional automated vehicles, drivers are no longer expected to focus only on driving activities but are still required to stay alert to resume control. However, fluctuations in driving demands are known to alter the driver's mental workload (MWL), which might affect the driver's vehicle take-over capabilities. Driver mental workload can be specified as the driver's capacity for information processing for task performance. This paper summarizes the literature that relates to analysing driver mental workload through various in-vehicle physiological sensors focusing on cardiovascular and respiratory measures. The review highlights the type of study, hardware, method of analysis, test variable, and results of studies that have used physiological indices for MWL analysis in the automotive context.

Indexed as

Automobile DrivingTechnologyAutomationCognitionWorkloadconditional automationHRHRVmental workloadrespiration

Identifiers

PMID36850812
PMCPMC9963326
OpenAlexW4321096730

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.