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Literature DB >> 30488148

Motor imagery and mental fatigue: inter-relationship and EEG based estimation.

Upasana Talukdar¹, Shyamanta M Hazarika², John Q Gan³.

Abstract

Even though it has long been felt that psychological state influences the performance of brain-computer interfaces (BCI), formal analysis to support this hypothesis has been scant. This study investigates the inter-relationship between motor imagery (MI) and mental fatigue using EEG: a. whether prolonged sequences of MI produce mental fatigue and b. whether mental fatigue affects MI EEG class separability. Eleven participants participated in the MI experiment, 5 of which quit in the middle because of experiencing high fatigue. The growth of fatigue was monitored using the Kernel Partial Least Square (KPLS) algorithm on the remaining 6 participants which shows that MI induces substantial mental fatigue. Statistical analysis of the effect of fatigue on motor imagery performance shows that high fatigue level significantly decreases MI EEG separability. Collectively, these results portray an MI-fatigue inter-connection, emphasizing the necessity of developing adaptive MI BCI by tracking mental fatigue.

Entities: Disease Species

Keywords: Brain Computer Interface; EEG; Mental fatigue; Motor imagery

Year: 2018 PMID： 30488148 DOI： 10.1007/s10827-018-0701-0

Source DB: PubMed Journal: J Comput Neurosci ISSN： 0929-5313 Impact factor: 1.621

21 in total

1. Optimal spatial filtering of single trial EEG during imagined hand movement.

Authors: H Ramoser; J Müller-Gerking; G Pfurtscheller
Journal: IEEE Trans Rehabil Eng Date: 2000-12

2. Driver Fatigue Classification With Independent Component by Entropy Rate Bound Minimization Analysis in an EEG-Based System.

Authors: Rifai Chai; Ganesh R Naik; Tuan Nghia Nguyen; Sai Ho Ling; Yvonne Tran; Ashley Craig; Hung T Nguyen
Journal: IEEE J Biomed Health Inform Date: 2016-02-19 Impact factor: 5.772

Review 3. Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness.

Authors: Gianluca Borghini; Laura Astolfi; Giovanni Vecchiato; Donatella Mattia; Fabio Babiloni
Journal: Neurosci Biobehav Rev Date: 2012-10-30 Impact factor: 8.989

4. Assessment of mental fatigue during car driving by using high resolution EEG activity and neurophysiologic indices.

Authors: G Borghini; G Vecchiato; J Toppi; L Astolfi; A Maglione; R Isabella; C Caltagirone; W Kong; D Wei; Z Zhou; L Polidori; S Vitiello; F Babiloni
Journal: Conf Proc IEEE Eng Med Biol Soc Date: 2012

5. A prolonged motor imagery session alter imagined and actual movement durations: Potential implications for neurorehabilitation.

Authors: Vianney Rozand; Florent Lebon; Paul J Stapley; Charalambos Papaxanthis; Romuald Lepers
Journal: Behav Brain Res Date: 2015-09-30 Impact factor: 3.332

6. Validity and reliability of a scale to assess fatigue.

Authors: K A Lee; G Hicks; G Nino-Murcia
Journal: Psychiatry Res Date: 1991-03 Impact factor: 3.222

7. Measuring fatigue in clinical and community settings.

Authors: Matteo Cella; Trudie Chalder
Journal: J Psychosom Res Date: 2009-12-11 Impact factor: 3.006

8. Effects of user mental state on EEG-BCI performance.

Authors: Andrew Myrden; Tom Chau
Journal: Front Hum Neurosci Date: 2015-06-02 Impact factor: 3.169

9. Classification of four-class motor imagery employing single-channel electroencephalography.

Authors: Sheng Ge; Ruimin Wang; Dongchuan Yu
Journal: PLoS One Date: 2014-06-20 Impact factor: 3.240

10. Improving EEG-Based Driver Fatigue Classification Using Sparse-Deep Belief Networks.

Authors: Rifai Chai; Sai Ho Ling; Phyo Phyo San; Ganesh R Naik; Tuan N Nguyen; Yvonne Tran; Ashley Craig; Hung T Nguyen
Journal: Front Neurosci Date: 2017-03-07 Impact factor: 4.677

11 in total

1. Emerging techniques in statistical analysis of neural data.

Authors: Sridevi V Sarma
Journal: J Comput Neurosci Date: 2019-02 Impact factor: 1.621

2. Embodiment Comfort Levels During Motor Imagery Training Combined With Immersive Virtual Reality in a Spinal Cord Injury Patient.

Authors: Carla Pais-Vieira; Pedro Gaspar; Demétrio Matos; Leonor Palminha Alves; Bárbara Moreira da Cruz; Maria João Azevedo; Miguel Gago; Tânia Poleri; André Perrotta; Miguel Pais-Vieira
Journal: Front Hum Neurosci Date: 2022-05-20 Impact factor: 3.473

3. Evaluating person-centered factors associated with brain-computer interface access to a commercial augmentative and alternative communication paradigm.

Authors: Kevin M Pitt; Jonathan S Brumberg
Journal: Assist Technol Date: 2021-03-05

Motor imagery and mental fatigue: inter-relationship and EEG based estimation.

1. Optimal spatial filtering of single trial EEG during imagined hand movement.

2. Driver Fatigue Classification With Independent Component by Entropy Rate Bound Minimization Analysis in an EEG-Based System.

Review 3. Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness.

4. Assessment of mental fatigue during car driving by using high resolution EEG activity and neurophysiologic indices.

5. A prolonged motor imagery session alter imagined and actual movement durations: Potential implications for neurorehabilitation.

6. Validity and reliability of a scale to assess fatigue.

7. Measuring fatigue in clinical and community settings.

8. Effects of user mental state on EEG-BCI performance.

9. Classification of four-class motor imagery employing single-channel electroencephalography.

10. Improving EEG-Based Driver Fatigue Classification Using Sparse-Deep Belief Networks.

1. Emerging techniques in statistical analysis of neural data.

2. Embodiment Comfort Levels During Motor Imagery Training Combined With Immersive Virtual Reality in a Spinal Cord Injury Patient.

3. Evaluating person-centered factors associated with brain-computer interface access to a commercial augmentative and alternative communication paradigm.

4. Progressive Training for Motor Imagery Brain-Computer Interfaces Using Gamification and Virtual Reality Embodiment.

5. Developing a Motor Imagery-Based Real-Time Asynchronous Hybrid BCI Controller for a Lower-Limb Exoskeleton.

6. Multiclass Classification Based on Combined Motor Imageries.

7. Spatial constraints and cognitive fatigue affect motor imagery of walking in people with multiple sclerosis.

8. Multi-Parameter Physiological State Monitoring in Target Detection Under Real-World Settings.

9. Exploring Fatigue Effects on Performance Variation of Intensive Brain-Computer Interface Practice.

10. Analysis of the Relationship Between Motor Imagery and Age-Related Fatigue for CNN Classification of the EEG Data.