2023年8月23日 · We conducted an exploratory investigation using uncontaminated EEG data and ensemble learning algorithms to characterize the pilot’s mental states (i.e., channelized attention, diverted attention, startle/surprise, and normal).

2023年2月13日 · Pilot cognitive workload has been studied across many operational environments, including simulated flight with fighter pilots 7, in simulated flight using dry-electrode EEG 8, and in live flight...

2025年1月28日 · The central innovation of PilotCareTrans Net lies in its Adaptive Temporal Encoder Network (ATEN), a specialized module designed to enhance the Transformer's capacity to handle the unique characteristics of EEG data. EEG signals are known for their temporal complexity and high variability across different individuals and conditions.

2022年2月22日 · In this paper, we propose a convolutional neural network to classify EEG features across different mental workloads in a continuous performance task test that partly measures working memory and working memory capacity.

2023年8月23日 · This study presents a reliable and efficient solution for detecting mental states in pilots and highlights the potential of EEG signals and ensemble learning algorithms in developing cognitive cockpit systems.

In this paper we have focused on studying the pilot's cortical potentials in simulated flight environment in order to classify his mental state into three categories i.e. rest mode, navigation flying mode, and dogfight mode. 14 channel Emotiv EEG headset was used by the subjects while playing a fighter aircraft game which could simulate all the ...

2005年2月1日 · The electroencephalogram (EEG) is used to screen pilot candidates for professional licensure irrespective of medical history in many European countries; applicants with paroxysmal abnormalities are excluded.

Based on the EEG characteristics, the pilots’ psychological workload was classified through the use of a support vector machine (SVM). The study results showed significant changes in the energy ratio of beta waves and Shannon entropy during left and right turns compared to …

2023年7月10日 · This study presents a real-time pilot mental workload (MWL) detection system utilizing a consumer-grade wireless electroencephalogram headset (WEEGH) with EEG features. The optimal model, KNN with all power spectral density (PSD) features, was determined by comparing and training the performance of various algorithms and selecting features ...

We conducted an exploratory investigation using uncontaminated EEG data and ensemble learning algorithms to characterize the pilot’s mental states (i.e., channelized attention, diverted attention, startle/surprise, and normal).