Neurocognitive factors of new drone Pilots: Identifying candidates with expert potential

The increasing use of drones in both military and civilian applications underscores the critical need for the proper selection and training of pilots. Identifying the neurocognitive variables that influence the performance of these pilots can optimize selection and training processes. This study aimed to evaluate the relationship between neuropsychological variables and performance on drone flight tasks. The sample consisted of 36 participants: 31 with no prior flight experience and five experienced drone pilots. Participants completed the WinSCAT, which assessed neurocognitive functions such as visuospatial working memory, attention, and processing speed. These cognitive variables were then correlated with performance in two different flight tests: a simulated flight task and a real flight test in which participants had to execute specific maneuvers using a drone. The results revealed that participants who performed better in areas such as working memory, spatial processing, and concentration not only completed the simulated flight tasks in less time, but their performance in the real flight test was comparable to that of expert pilots. Visuospatial working memory and processing speed were identified as the strongest predictors of performance across both flight tasks. These findings suggest that neurocognitive assessment prior to training can help identify individuals who will likely complete drone training more efficiently, optimizing both time and resources. • Comprehensive analysis. Computerized neurocognitive tests assessed cognitive skills and their effect on drone piloting. • Experienced vs. novice pilots. Cognitive and flight performance were compared between expert and novice drone pilots. • Key cognitive factors. Faster reaction times were identified as a key predictor of successful drone piloting. • Performance enhancement. Insights on how cognitive training could improve drone piloting skills were provided.

Authors

Institutions

Publication Details

Journal
Computers in Human Behavior Reports
Published
2025-06-07
DOI
https://doi.org/10.1016/j.chbr.2025.100705
Citations
1
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
2.44

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Neurocognitive factors of new drone Pilots: Identifying candidates with expert potential

Sara González-Torre, Miguel A. Ramallo, Álvaro Rodríguez-Mora, Gabriel G. De la Torre
1 citations
Computers in Human Behavior Reports
Human-Automation Interaction and Safety
2.44
article

Neurocognitive factors of new drone Pilots: Identifying candidates with expert potential

Sara González-Torre, Miguel A. Ramallo, Álvaro Rodríguez-Mora, Gabriel G. De la Torre
article en
1 citations

Abstract

The increasing use of drones in both military and civilian applications underscores the critical need for the proper selection and training of pilots. Identifying the neurocognitive variables that influence the performance of these pilots can optimize selection and training processes. This study aimed to evaluate the relationship between neuropsychological variables and performance on drone flight tasks. The sample consisted of 36 participants: 31 with no prior flight experience and five experienced drone pilots. Participants completed the WinSCAT, which assessed neurocognitive functions such as visuospatial working memory, attention, and processing speed. These cognitive variables were then correlated with performance in two different flight tests: a simulated flight task and a real flight test in which participants had to execute specific maneuvers using a drone. The results revealed that participants who performed better in areas such as working memory, spatial processing, and concentration not only completed the simulated flight tasks in less time, but their performance in the real flight test was comparable to that of expert pilots. Visuospatial working memory and processing speed were identified as the strongest predictors of performance across both flight tasks. These findings suggest that neurocognitive assessment prior to training can help identify individuals who will likely complete drone training more efficiently, optimizing both time and resources. • Comprehensive analysis. Computerized neurocognitive tests assessed cognitive skills and their effect on drone piloting. • Experienced vs. novice pilots. Cognitive and flight performance were compared between expert and novice drone pilots. • Key cognitive factors. Faster reaction times were identified as a key predictor of successful drone piloting. • Performance enhancement. Insights on how cognitive training could improve drone piloting skills were provided.

Computers in Human Behavior ReportsVol. 19
Universidad de Cádiz (ES)
Ministerio de Ciencia, Innovación y Universidades
Openalex Percentile: Top 12%
Human-Automation Interaction and Safety
2.44
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.