A subjective and objective synchronization assessment method of cognitive load for the lunar exploration

Abstract

The cognitive load of astronauts has a large impact on the efficiency of human-machine co-operation, and the reasonable adjustment of astronauts' cognitive load is crucial to guarantee the success of the mission. However, the current cognitive load prediction and assessment methods have the problems of detaching the evoked task (N-back) from the main task and the high latency of subjective load assessment, which affect the accuracy of the prediction and assessment of cognitive load. Therefore, the study proposes a subjective-objective synchronised cognitive load experimental assessment method for typical tasks on the lunar surface, where a dynamic N-back experimental paradigm is designed according to the operation process to induce different levels of cognitive loads for the astronauts, and at the same time, the astronauts are required to complete corresponding NASA-TLX scale pop-ups for real-time subjective load assessment in different operation processes. In the objective assessment, the multimodal signals of the astronauts were collected based on GSR, ECG and PPG for feature extraction. Finally, this study constructs a comprehensive assessment model of human-machine collaborative effectiveness for lunar surface operations based on behavioural performance and cognitive load state and verifies its validity through typical experimental tasks. The experimental assessment method can comprehensively consider the human-machine cooperative ability of astronauts under the influence of multiple factors in the lunar surface special-cause environment, construct the N-back experimental paradigm of the evoked task and the typical task organically combined experiments, and at the same time reduce the latency of the subjective evaluation, realise the synchronous assessment based on subjective and objective physiological and task data, and effectively enhance the accuracy of the prediction and assessment of the cognitive load.

Keywords: Lunar exploration, Cognitive load assessment, Human-Machine interaction for complex systems, Human-Machine collaboration

DOI: 10.54941/ahfe1006133