Journal article
ADHD Prediction via Time Series Ensemble fed Driving Simulator Data
The International FLAIRS Conference Proceedings, v 34(1)
18 Apr 2021
Abstract
In this paper, we identify the on-road scenarios within a simulated driving environment where a group of clinical trial participants (n= 30) with and without Attention Deficit Hyper-activity Disorder (ADHD) drive perceivably different fromone another. We partition the simulated routes into smaller non-overlapping sections in order to determine which sections elicit behaviors that are predictive of ADHD. Then, we develop section-specific classifiers, which are used as voters in bagging ensemble classifiers. Our results show gains in classifying ADHD (increase in 5-fold average evaluation accuracy) over our previous efforts, as well as providing explainable evidence that driving behaviors indicative of ADHD tend to be exhibited in turns and curves.
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Details
- Title
- ADHD Prediction via Time Series Ensemble fed Driving Simulator Data
- Creators
- David Grethlein - Drexel UniversityAleksanteri Sladek - California University of PennsylvaniaSantiago Ontañón - Drexel University
- Publication Details
- The International FLAIRS Conference Proceedings, v 34(1)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Computer Science
- Scopus ID
- 2-s2.0-85131128465
- Other Identifier
- 991021869112704721