ArticleProceedings. International Conference on Computational Science and Computational Intelligence2022
Methods and Tools for Monitoring Driver's Behavior.
Article in Proceedings. International Conference on Computational Science and Computational Intelligence, 2022. 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
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.
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.
Who cites it
9 citing papers in PubMed.
- Pattern Mining of Older Drivers' Driving Behavior Through Telematics-data-driven Unsupervised Learning.IEEE sensors journal · 2025Article
- Enhancing road safety: In-vehicle sensor analysis of cognitive impairment in older drivers.Multimedia tools and applications · 2025Article
- Advances in Cardiovascular Wearable Devices.Biosensors · 2024Review
- Objective estimation of m-CTSIB balance test scores using wearable sensors and machine learning.Frontiers in digital health · 2024Article
- Curve Walking Reveals More Gait Impairments in Older Adults with Mild Cognitive Impairment than Straight Walking: A Kinect Camera-Based Study.Journal of Alzheimer's disease reports · 2024Article
- Detection of mild cognitive impairment using various types of gait tests and machine learning.Frontiers in neurology · 2024Article
- Anomalous Behavior Detection in Trajectory Data of Older Drivers.2023 IEEE 20th International Conference on Smart Communities: Improving Quality of Life using AI, Robotics and IoT (HONET) · 2023Article
- In-vehicle Sensing and Data Analysis for Older Drivers with Mild Cognitive Impairment.2023 IEEE 20th International Conference on Smart Communities: Improving Quality of Life using AI, Robotics and IoT (HONET) · 2023Article
- Deep Learning Technology to Recognize American Sign Language Alphabet.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
In-vehicle sensing technology has gained tremendous attention due to its ability to support major technological developments, such as connected vehicles and self-driving cars. In-vehicle sensing data are invaluable and important data sources for traffic management systems. In this paper we propose an innovative architecture of unobtrusive in-vehicle sensors and present methods and tools that are used to measure the behavior of drivers. The proposed architecture including methods and tools are used in our NIH project to monitor and identify older drivers with early dementia.
Indexed as
Identifiers
What OpenQuestion holds
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.