Evidence map›Paper›PMID 35009898›Full record

ArticleSensors (Basel, Switzerland)2022

Inattentive Driving Detection Using Body-Worn Sensors: Feasibility Study.

Takuma Akiduki, Jun Nagasawa, Zhong Zhang, Yuto Omae, Toshiya Arakawa, Hirotaka Takahashi

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
3.4field-weighted citation impact, top 8% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
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

6 authors at 5 institutions in 1 country.

Takuma AkidukiGraduate School of Engineering, Toyohashi University of Technology, Toyohashi 441-8580, Japan.ORCID 0000-0002-2064-0633
Jun NagasawaGraduate School of Engineering, Toyohashi University of Technology, Toyohashi 441-8580, Japan.
Zhong ZhangDepartment of Intelligent Mechanical Engineering, Hiroshima Institute of Technology, Saeki-ku, Hiroshima 731-5193, Japan.
Yuto OmaeDepartment of Industrial Engineering and Management, College of Industrial Technology, Nihon University, Narashino 275-8575, Japan.ORCID 0000-0002-5924-6959
Toshiya ArakawaDepartment of Information Technology and Media Design, Nippon Institute of Technology, Miyashiro-machi, Saitama 345-8501, Japan.ORCID 0000-0002-3501-1055
Hirotaka TakahashiResearch Center for Space Science, Advanced Research Laboratories, Tokyo City University, Setagaya-ku, Tokyo 158-0082, Japan.ORCID 0000-0003-0596-4397
Toyohashi University of Technology · JPHiroshima Institute of Technology · JPNihon University · JPNippon Institute of Technology · JPTokyo City University · JP

Funding

Japan Society for the Promotion of Science 19K14924; 20K12090
6 · The paper itself

Abstract

This study aims to build a system for detecting a driver's internal state using body-worn sensors. Our system is intended to detect inattentive driving that occurs during long-term driving on a monotonous road, such as a high-way road. The inattentive state of a driver in this study is an absent-minded state caused by a decrease in driver vigilance levels due to fatigue or drowsiness. However, it is difficult to clearly define these inattentive states because it is difficult for the driver to recognize when they fall into an absent-minded state. To address this problem and achieve our goal, we have proposed a detection algorithm for inattentive driving that not only uses a heart rate sensor, but also uses body-worn inertial sensors, which have the potential to detect driver behavior more accurately and at a much lower cost. The proposed method combines three detection models: body movement, drowsiness, and inattention detection, based on an anomaly detection algorithm. Furthermore, we have verified the accuracy of the algorithm with the experimental data for five participants that were measured in long-term and monotonous driving scenarios by using a driving simulator. The results indicate that our approach can detect both the inattentive and drowsiness states of drivers using signals from both the heart rate sensor and accelerometers placed on wrists.

Indexed as

Automobile DrivingDistracted DrivingWearable Electronic DevicesFeasibility StudiesHumansWakefulnessaccelerometerbody-worn sensordrowsiness drivinginattentive drivingmotion feature

Identifiers

PMID35009898
PMCPMC8749514
OpenAlexW4205502052

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.