Toward Neuroergonomic Evaluation of Human-Computer Interaction: A Cognitive Segmented Dual-Task Approach

Traditional ERP paradigms lack ecological validity in dynamic human-computer interaction (HCI) evaluation, emphasizing the need for neuroergonomic designs reflecting real-world cognitive demands. This study introduces a novel Cognitive Segmented Dual-Task (CSDT) ERP paradigm, integrating stimulus recognition with simulated flight operations while temporally separating task phases to reduce interference. Sixteen participants performed tasks under baseline, direct dual-task (DDT), and CSDT conditions, with difficulty manipulated by different icon quantity and time pressure. Results showed that four icons with a 5-second interval represented optimal difficulty, with higher loads yielding larger ERP amplitudes but reduced sensitivity. The CSDT paradigm successfully preserved both ERP sensitivity and ideal task performance. Machine learning classification further confirmed clearer cognitive load distinctions under CSDT, supporting its value for neuroergonomic evaluation and adaptive human-computer interface design in avionics.