ArticleData in brief2026
DriveNet: A comprehensive dataset for driver posture recognition to enhance ergonomics and safety.
Article in Data in brief, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Poorly aligned driving posture in the occupational environment increases the risk of musculoskeletal disorders. Asymmetric pressure distribution on the neck and shoulder areas during driving can lead to severe pain and soreness. Although occupational drivers are extremely focused on safe driving, they are less aware of their seating posture. Although several automated systems have been developed for monitoring driver behavior and detecting driver drowsiness, an alert system with the capability of recognizing the driver posture can assist drivers in maintaining an optimal seating posture and minimizing ergonomic risks. To develop an efficient machine learning-based driver posture recognition system, a dataset that efficiently represents improper seating postures is required. To fulfill this requirement, this paper proposes the DriveNet dataset, a comprehensive dataset developed for the purpose of driver posture recognition. This dataset comprises 11,160 high-resolution RGB images of four posture classes, which are captured using a high-resolution RGB camera installed on the Android smartphone camera. This dataset is intended to facilitate further research on driver posture classification and recognition using advanced machine learning and deep learning techniques.
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.