Document Type

Article

Source Publication Title

The PErvasive Technologies Related to Assistive Environments Conference

DOI

https://dl.acm.org/doi/10.1145/3652037.3652068

Abstract

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.

Publication Date

6-26-2024

Language

English

License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.