Exploring the elusive mind: a multimodal wearable sensor solution for measuring mind wandering in university students

Khosravi, S., Li, H., Khan, A. R., Zoha, A. and Ghannam, R. (2024) Exploring the elusive mind: a multimodal wearable sensor solution for measuring mind wandering in university students. Advanced Sensor Research, 3(1), 2300067. (doi: 10.1002/adsr.202300067)

Abstract

Mind-wandering is a typical daily phenomenon during which attention shifts from external stimuli to internal trains of thought. It affect students' learning by impairing comprehension, diminishing academic achievement, impeding critical thinking, and encouraging a lack of attention and engagement in classroom activities. This study aims to introduce a new method of detecting and tracking mind wandering in university students. This approach involves using wearable sensors, including galvanic skin response (GSR), photoplethysmography (PPG), and eye-trackers, along with machine learning techniques. The study provides a proof of concept for this multisensory approach. The association between longer fixation duration and mind wandering, and the influence of an instructor's presence on fixation allocation, and, consequently, the frequency and occurrence of mind wandering is investigated. Furthermore, the feasibility of using eye-trackers in conjunction with GSR and PPG sensors for detecting mind wandering through a wearable multisensory data collection system is assessed. The wearable multisensory device is evaluated by ten participants (university students, males/females aged between 21-30). Two distinct machine learning methods, support vector machine (SVM) and gated recurrent unit (GRU), are used as classification models. With sensor fusion, the SVM and GRU models yielded maximum accuracies of 86.53% and 89.86%, respectively. Moreover, participants are observed to fixate on instructors more often, just before instances of mind wandering.

• Item Type: Articles
• Additional Information: S. K. PhD was supported by the College of Science and Engineering Scholarship at the University of Glasgow.
• Keywords: Multisensory, mind-wandering, sensor-fusion, wearable devices, machine learning, education.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Zoha, Dr Ahmed and Khan, Ahsan Raza and Ghannam, Professor Rami and Li, Haobo and Khosravi, Sara
• Authors: Khosravi, S., Li, H., Khan, A. R., Zoha, A., and Ghannam, R.
• College/School: College of Science and Engineering; College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
• Journal Name: Advanced Sensor Research
• Publisher: Wiley
• ISSN: 2751-1219
• ISSN (Online): 2751-1219
• Published Online: 15 November 2023
• Copyright Holders: Copyright: © 2023 The Authors
• First Published: First published in Advanced Sensor Research 3(1):2300067
• Publisher Policy: Reproduced under a Creative Commons licence