Exploring Fatigue Effects on Performance Variation of Intensive Brain–Computer Interface Practice

Songwei Li; Junyi Duan; Yu Sun; Xinjun Sheng; Xiangyang Zhu; Jianjun Meng

doi:10.3389/fnins.2021.773790

Frontiers in Neuroscience (Dec 2021)

Exploring Fatigue Effects on Performance Variation of Intensive Brain–Computer Interface Practice

Songwei Li,
Junyi Duan,
Yu Sun,
Xinjun Sheng,
Xiangyang Zhu,
Jianjun Meng

Affiliations

Songwei Li: State Key Laboratory of Mechanical Systems and Vibrations, Institute of Robotics, Shanghai Jiao Tong University, Shanghai, China
Junyi Duan: State Key Laboratory of Mechanical Systems and Vibrations, Institute of Robotics, Shanghai Jiao Tong University, Shanghai, China
Yu Sun: Key Laboratory for Biomedical Engineering of Ministry of Education of China, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
Xinjun Sheng: State Key Laboratory of Mechanical Systems and Vibrations, Institute of Robotics, Shanghai Jiao Tong University, Shanghai, China
Xiangyang Zhu: State Key Laboratory of Mechanical Systems and Vibrations, Institute of Robotics, Shanghai Jiao Tong University, Shanghai, China
Jianjun Meng: State Key Laboratory of Mechanical Systems and Vibrations, Institute of Robotics, Shanghai Jiao Tong University, Shanghai, China

DOI: https://doi.org/10.3389/fnins.2021.773790
Journal volume & issue: Vol. 15

Abstract

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Motor imagery (MI) is an endogenous mental process and is commonly used as an electroencephalogram (EEG)-based brain–computer interface (BCI) strategy. Previous studies of P300 and MI-based (without online feedback) BCI have shown that mental states like fatigue can negatively affect participants’ EEG signatures. However, exogenous stimuli cause visual fatigue, which might have a different mechanism than endogenous tasks do. Furthermore, subjects could adjust themselves if online feedback is provided. In this sense, it is still unclear how fatigue affects online MI-based BCI performance. With this question, 12 healthy subjects are recruited to investigate this issue, and an MI-based online BCI experiment is performed for four sessions on different days. The first session is for training, and the other three sessions differ in rest condition and duration—no rest, 16-min eyes-open rest, and 16-min eyes-closed rest—arranged in a pseudo-random order. Multidimensional fatigue inventory (MFI) and short stress state questionnaire (SSSQ) reveal that general fatigue, mental fatigue, and distress have increased, while engagement has decreased significantly within certain sessions. However, the BCI performances, including percent valid correct (PVC) and information transfer rate (ITR), show no significant change across 400 trials. The results suggest that although the repetitive MI task has affected subjects’ mental states, their BCI performances and feature separability within a session are not affected by the task significantly. Further electrophysiological analysis reveals that the alpha-band power in the sensorimotor area has an increasing tendency, while event-related desynchronization (ERD) modulation level has a decreasing trend. During the rest time, no physiological difference has been found in the eyes-open rest condition; on the contrary, the alpha-band power increase and subsequent decrease appear in the eyes-closed rest condition. In summary, this experiment shows evidence that mental states can change dramatically in the intensive MI-BCI practice, but BCI performances could be maintained.

Published in Frontiers in Neuroscience

ISSN: 1662-4548 (Print); 1662-453X (Online)
Publisher: Frontiers Media S.A.
Country of publisher: Switzerland
LCC subjects: Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry
Website: http://www.frontiersin.org/neuroscience

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