Article2023 IEEE 20th International Conference on Smart Communities: Improving Quality of Life using AI, Robotics and IoT (HONET)2023
In-vehicle Sensing and Data Analysis for Older Drivers with Mild Cognitive Impairment.
Article in 2023 IEEE 20th International Conference on Smart Communities: Improving Quality of Life using AI, Robotics and IoT (HONET), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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.
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Who cites it
9 citing papers in PubMed.
- Abnormal Driving Pattern Detection from GPS Trajectories Using Vision Transformer.Research square · 2026Article
- Curve walking gait analysis using depth camera and machine learning for detecting cognitive impairment.Frontiers in neurology · 2026Article
- Endothelial c-Myc and Doxorubicin-Induced Metabolic Alterations: A Multi-Organ Optical Imaging Study.Journal of biophotonics · 2025Article
- Analyzing Mobility Indicators Using Machine Learning to Detect Mild Cognitive Impairment: A Systematic Scoping Review.Applied clinical informatics · 2025Article
- Enhancing road safety: In-vehicle sensor analysis of cognitive impairment in older drivers.Multimedia tools and applications · 2025Article
- Quad-tree Based Driver Classification using Deep Learning for Mild Cognitive Impairment Detection.IEEE access : practical innovations, open solutions · 2025Article
- Multi-Shared-Task Self-Supervised CNN-LSTM for Monitoring Free-Body Movement UPDRS-III Using Wearable Sensors.Bioengineering (Basel, Switzerland) · 2024Article
- Objective estimation of m-CTSIB balance test scores using wearable sensors and machine learning.Frontiers in digital health · 2024Article
- Detection of mild cognitive impairment using various types of gait tests and machine learning.Frontiers in neurology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Driving is a complex daily activity indicating age and disease-related cognitive declines. Therefore, deficits in driving performance compared with ones without mild cognitive impairment (MCI) can reflect changes in cognitive functioning. There is increasing evidence that unobtrusive monitoring of older adults' driving performance in a daily-life setting may allow us to detect subtle early changes in cognition. The objectives of this paper include designing low-cost in-vehicle sensing hardware capable of obtaining high-precision positioning and telematics data, identifying important indicators for early changes in cognition, and detecting early-warning signs of cognitive impairment in a truly normal, day-to-day driving condition with machine learning approaches. Our statistical analysis comparing drivers with MCI to those without reveals that those with MCI exhibit smoother and safer driving patterns. This suggests that drivers with MCI are cognizant of their condition and tend to avoid erratic driving behaviors. Furthermore, our Random Forest models identified the number of night trips, number of trips, and education as the most influential factors in our data evaluation.
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Registered trials
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.