Evidence map›Paper›PMID 38097931›Full record

ArticleBMC geriatrics2023

Study protocol for "In-vehicle sensors to detect changes in cognition of older drivers".

Ruth Tappen, David Newman, Monica Rosselli, Jinwoo Jang, Borko Furht, KwangSoo Yang, Seyedeh Gol Ara Ghoreishi, Jiannan Zhai, Joshua Conniff, Muhammad Tanveer Jan and 4 more

Abstract read
In one paragraph

Article in BMC geriatrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Spatial Deep Learning Approach to Older Driver Classification.IEEE access : practical innovations, open solutions · 2024
    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

14 authors.

Ruth TappenChristine E. Lynn College of Nursing, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA. rtappen@health.fau.edu.
David NewmanChristine E. Lynn College of Nursing, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA.
Monica RosselliDepartment of Psychology, Florida Atlantic University, 3200 College Ave, Davie, FL, 33314, USA.
Jinwoo JangDepartment of Civil, Environmental, and Geomatics Engineering, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA.
Borko FurhtDepartment of Electrical Engineering and Computer Science, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA.
KwangSoo YangDepartment of Electrical Engineering and Computer Science, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA.
Seyedeh Gol Ara GhoreishiDepartment of Electrical Engineering and Computer Science, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA.
Jiannan ZhaiI-SENSE, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA.
Joshua ConniffNeuropsychology Lab, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA.
Muhammad Tanveer JanDepartment of Electrical Engineering and Computer Science, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA.
Sonia MoshfeghiDepartment of Civil, Environmental, and Geomatics Engineering, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA.
Somi PandayChristine E. Lynn College of Nursing, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA.
Kelley JacksonChristine E. Lynn College of Nursing, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA.
Marie Adonis-RizzoChristine E. Lynn College of Nursing, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA.

Funding

In-Vehicle Sensors to Detect Cognitive Change in Older DriversR01AG068472 · NIA · FLORIDA ATLANTIC UNIVERSITY · PI NEWMAN, DAVID, TAPPEN, RUTH M · 2020 to 2024
$5.5M
NIA NIH HHS R01 AG068472
6 · The paper itself

Abstract

backgroundDriving is a complex behavior that may be affected by early changes in the cognition of older individuals. Early changes in driving behavior may include driving more slowly, making fewer and shorter trips, and errors related to inadequate anticipation of situations. Sensor systems installed in older drivers' vehicles may detect these changes and may generate early warnings of possible changes in cognition.

methodA naturalistic longitudinal design is employed to obtain continuous information on driving behavior that will be compared with the results of extensive cognitive testing conducted every 3 months for 3 years. A driver facing camera, forward facing camera, and telematics unit are installed in the vehicle and data downloaded every 3 months when the cognitive tests are administered.

resultsData processing and analysis will proceed through a series of steps including data normalization, adding information on external factors (weather, traffic conditions), and identifying critical features (variables). Traditional prediction modeling results will be compared with Recurring Neural Network (RNN) approach to produce Driver Behavior Indices (DBIs), and algorithms to classify drivers within age, gender, ethnic group membership, and other potential group characteristics.

conclusionIt is well established that individuals with progressive dementias are eventually unable to drive safely, yet many remain unaware of their cognitive decrements. Current screening and evaluation services can test only a small number of individuals with cognitive concerns, missing many who need to know if they require treatment. Given the increasing number of sensors being installed in passenger vehicles and pick-up trucks and their increasing acceptability, reconfigured in-vehicle sensing systems could provide widespread, low-cost early warnings of cognitive decline to the large number of older drivers on the road in the U.S. The proposed testing and evaluation of a readily and rapidly available, unobtrusive in-vehicle sensing system could provide the first step toward future widespread, low-cost early warnings of cognitive change for this large number of older drivers in the U.S. and elsewhere.

Indexed as

Automobile DrivingCognitive DysfunctionAccidents, TrafficAgedCognitionHumansCognitive changeDrivingMild cognitive impairmentOlder driverSensorsTelematicsVideo

Identifiers

PMID38097931
PMCPMC10720160

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.