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If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
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Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
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Driving Under the Influence: How Music Listening Affects Driving Behaviors
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Naturalistic Driving: A Framework and Advances in Using Big Data.

Frank Knoefel1,2,3,4,5, Bruce Wallace6,7,8, Rafik Goubran9,10,11

  • 1Bruyère Continuing Care, Ottawa, ON K1N 5C8, Canada. Fknoefel@bruyere.org.

Geriatrics (Basel, Switzerland)
|April 24, 2019
PubMed
Summary
This summary is machine-generated.

This study proposes a framework for assessing older adult driving ability using in-vehicle sensors and naturalistic driving data. It highlights key driving behaviors and conditions to monitor for safe mobility in aging drivers.

Keywords:
big data analysisdriving assessmentframeworknaturalistic driving study

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Area of Science:

  • Gerontology
  • Transportation Safety
  • Human Factors Engineering

Background:

  • Aging is linked to declines in vision, physical, and cognitive health, potentially impacting driving ability.
  • Driving offers crucial physical, cognitive, and social stimulation for older adults, promoting overall well-being.
  • Assessing driving ability in older adults is vital for maintaining independence and public safety.

Purpose of the Study:

  • To present a comprehensive framework for assessing driving ability in older adults.
  • To explore the utility of naturalistic driving studies (NDS) in evaluating driving performance.
  • To identify key driving characteristics, actions, destinations, and conditions relevant to older adult driving.

Main Methods:

  • Development of a driving assessment framework incorporating driving characteristics, actions, destinations, and conditions.
  • Utilization of naturalistic driving data from a subset of older drivers in the Ottawa region (Candrive study).
  • Analysis of driving patterns and behaviors using in-vehicle sensor technology.

Main Results:

  • The proposed framework categorizes essential driving metrics for comprehensive assessment.
  • Naturalistic driving data provides rich insights into real-world driving behaviors of older adults.
  • The study illustrates the application of this framework using real-world driving data.

Conclusions:

  • Naturalistic driving studies offer a valuable tool for assessing and understanding older adult driving.
  • The framework provides a structured approach to evaluating driving safety and performance in aging populations.
  • Addressing challenges in big data analysis and evolving vehicle technology is crucial for future research.