Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
February 16, 2023SensorsOpen Access

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

View Full Paper
Ask AI
Bookmark
Share

Why the study?

In conditional automated vehicles, fluctuations in driving demands alter driver mental workload, which may affect vehicle take-over capabilities.

Comparison

In-vehicle physiological sensors focusing on cardiovascular and respiratory measures

Design

Systematic review

Authors

ASAshwini Kanakapura SrirangaCoventry UniversityQLQian LuCoventry UniversitySBStewart BirrellCoventry University

Discussion

Loading...

Member takes

Overview

Sensor-based MWL monitoring may enhance take-over safety in conditional automation; leaves open large-scale validation of cardiovascular indices.

Structured PICO

P
Population
Drivers (studies analyzing driver mental workload)
I
Intervention
In-vehicle physiological sensors focusing on cardiovascular and respiratory measures
O
Outcome
Driver mental workload (MWL)surrogate

This systematic review provides an overview of how cardiovascular and respiratory sensors are used to monitor driver mental workload in the context of automated vehicles.

Cite This Study

Sriranga et al. (2023) studied this question.

synapsesocial.com/papers/6a85577ed8017c721f4e18e4https://doi.org/10.3390/s23042214
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 4 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1A review of human factors principles for the design and implementation of medication safety alerts in clinical information systems2010 · 226 citations
  2. 2Multiclass Classification of Driver Perceived Workload Using Long Short-Term Memory based Recurrent Neural Network2018 · 40 citations
  3. 3The Measurement of Cognitive Workload in Surgery Using Pupil Metrics: A Systematic Review and Narrative Analysis2022 · 38 citations
  4. 4Measuring Mental Workload with EEG+fNIRS2017 · 239 citations