An Assistive Robotic System for Cognitive State Assessment in Individuals with Spinal Cord Injury

摘要

We introduce an innovative assistive robotic setup tailored for assessing the cognitive state of individuals with spinal cord injuries (SCI) during their daily activities. Utilizing physiological sensors such as ECG, EEG, and EDA, along with cameras for facial expression, our system is designed to detect and evaluate cognitive fatigue in participants as they engage with a collaborative robot. Specifically, two tasks, Cooking Pasta Sauce and Getting Ready for Work–have been crafted to gather data on cognitive states. Participants interact with the robot using natural language (English) to perform tasks, while their physiological responses, facial expressions, and activities are recorded. The study comprises three phases of cognitive fatigue: baseline, moderate, and severe. Cognitive fatigue is induced through the N-back task paradigm, and its severity is assessed using the Visual Analogue Scale for Fatigue (VAS-F) questionnaire. Our system is designed to intervenes during the tasks based on the detected cognitive fatigue levels. In this paper, we concentrate on validating the cognitive fatigue detection system using only physiological sensors during task performance, achieving an accuracy of 85.7% and a recall of 0.87. We provide detailed insights into the system design and present a preliminary analysis of the gathered data.