Mu-beta rhythm ERD/ERS quantification for foot motor execution and imagery tasks in BCI applications

Tariq, Madiha; Uhlenberg, Lena; Trivailo, Pavel M.; Munir, Khurram; Simić, Milan

doi:10.1109/coginfocom.2017.8268222

Cited by 20 publications

(22 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…People affected by neurological disorder, stroke, or spinal cord injury (SCI) necessitate a therapeutic goal of motor gait rehabilitation using assistive technologies [1,2]. For lower-limb affectees, to re-gain the dorsiflexion of foot drop is vital [3][4][5]. The lost motor control functions could be emulated by inducing neuroplasticity using a brain-computer interface (BCI) system [6].…”

Section: Introductionmentioning

confidence: 99%

Mu-Beta event-related (de)synchronization and EEG classification of left-right foot dorsiflexion kinaesthetic motor imagery for BCI

2020

Self Cite

View full text Add to dashboard Cite

The left and right foot representation area is located within the interhemispheric fissure of the sensorimotor cortex and share spatial proximity. This makes it difficult to visualize the cortical lateralization of event-related (de)synchronization (ERD/ERS) during left and right foot motor imageries. The aim of this study is to investigate the possibility of using ERD/ERS in the mu, low beta, and high beta bandwidth, during left and right foot dorsiflexion kinaesthetic motor imageries (KMI), as unilateral control commands for a braincomputer interface (BCI). EEG was recorded from nine healthy participants during cuebased left-right foot dorsiflexion KMI tasks. The features were analysed for common average and bipolar references. With each reference, mu and beta band-power features were analysed using time-frequency (TF) maps, scalp topographies, and average time course for ERD/ERS. The cortical lateralization of ERD/ERS, during left and right foot KMI, was confirmed. Statistically significant features were classified using LDA, SVM, and KNN model, and evaluated using the area under ROC curves. An increase in high beta power following the end of KMI for both tasks was recorded, from right and left hemispheres, respectively, at the vertex. The single trial analysis and classification models resulted in high discrimination accuracies, i.e. maximum 83.4% for beta ERS, 79.1% for beta ERD, and 74.0% for mu ERD. With each model the features performed above the statistical chance level of 2-class discrimination for a BCI. Our findings indicate these features can evoke left-right differences in single EEG trials. This suggests that any BCI employing unilateral foot KMI can attain classification accuracy suitable for practical implementation. Given results stipulate the novel utilization of mu and beta as independent control features for discrimination of bilateral foot KMI in a BCI.

show abstract

Section: Introductionmentioning

confidence: 99%

Mu-Beta event-related (de)synchronization and EEG classification of left-right foot dorsiflexion kinaesthetic motor imagery for BCI

2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…computer) operatable commands [1]. The state-of-the art BCI is based on the idea of developing an artificial, muscle-free communication channel that acts as a natural communication channel between the brain and a machine [2,3]. Applications of BCI systems are widespread and vary from the fields of neuroscience, rehabilitation, cognitive infocommunications (CogInfoCom) [4] to entertainment, and defence [5].…”

Section: Introductionmentioning

confidence: 99%

“…BCI-controlled wearable/assistive robots for mobility restoration. Such devices can be useful for direct communication in inter-cognitive CogInfoCom applications [2,9], and necessitates more research in this area.…”

Section: Introductionmentioning

confidence: 99%

“…Successful quantification of left vs. right hand and foot motor imagery have been reported, including studies on the discrimination of different upper limbs [16], but no literature exists on the decoding of different movements within the same 'lower limb'. Investigations on independent lower-limb motor imagery tasks have been reported recently [2,[17][18][19], however, those studies did not cover the same limb tasks. This is because of the well-established fact about 'mesial wall' location of lower-limb representation area on the sensorimotor cortex.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Comparison of Event-related Changes in Oscillatory Activity During Different Cognitive Imaginary Movements Within Same Lower-Limb

2019

APH

View full text Add to dashboard Cite

The lower-limb representation area in the human sensorimotor cortex has all joints very closely located to each other. This makes the discrimination of cognitive states during different motor imagery tasks within the same limb, very challenging; particularly when using electroencephalography (EEG) signals, as they share close spatial representations. Following that more research is needed in this area, as successfully discriminating different imaginary movements within the same limb, in form of a single cognitive entity, could potentially increase the dimensionality of control signals in a braincomputer interface (BCI) system. This report presents our research outcomes in the discrimination of left foot-knee vs. right foot-knee movement imagery signals extracted from EEG. Each cognitive state task outcome was evaluated by the analysis of eventrelated desynchronization (ERD) and event-related synchronization (ERS). Results reflecting prominent ERD/ERS, to draw the difference between each cognitive task, are presented in the form of topographical scalp plots and average time course of percentage power ERD/ERS. Possibility of any contralateral dominance during each task was also investigated. We have compared the topographical distributions and based on the results we were able to distinguish between the activation of different cortical areas during foot and knee movement imagery tasks. Currently, there are no reports in the literature on discrimination of different tasks within the same lower-limb. Hence, an attempt towards getting a step closer to this has been done. Presented results could be the basis for control signals used in a cognitive infocommunication (CogInfoCom) system to restore locomotion function in a wearable lower-limb rehabilitation system, which can assist patients with spinal cord injury (SCI).

show abstract

“…The aim of the first BCI researchers was to create a direct communicational channel for those in need to help their quality of life, particularly of those suffering from devastating conditions, such as amyotrophic lateral sclerosis (ALS), spinal cord injury, stroke and cerebral palsy. [6][7][8][9][10][11][12][13] BCI is a direct functional interface between the brain and the computer or another device that can observe and decode the electromagnetic signals of brain activities and transfers the received information towards an external device [6,7,50]. Noninvasive BCIs have been an active research area; they include EEG, Near-infrared Spectroscopy (NIRS), functional-MRI (fMRI), among others [22][23][24].…”

Section: The Brain-computer Interfacementioning

confidence: 99%

Examining the Learning Efficiency by a Brain-Computer Interface System

2018

APH

View full text Add to dashboard Cite

Brain research is one of the most significant research areas of the last decades, in which many developments and modern engineering technologies are applied. The electroencephalogram (EEG)-based brain activity observation processes are very promising and have been used in several engineering research fields. Objective: The main goal of this research was to develop a Brain-Computer Interface (BCI) system to observe the level of vigilance calculated by Think Gear-ASIC Module (TGAM1) technology and to evaluate the output with learning efficiency tests applied in cognitive neuroscience. Methods: The performance of the BCI system is evaluated in a comparative study. The BCI system was tested by thirty-two test subjects and the attention level output was compared by the Psychology Experiment Building Language's (PEBL's) Corsi block test (P CORSI) and PEBL's Ebbinghaus procedure (P EBBINGHAUS) tasks. Results: Using the BCI, we have shown statistically significant results between the BCI and the conventional cognitive neuroscience tests. The correlation between the tests and the average attention of the BCI was slightly strong for P CORSI Total Score (r=.63, p<.01 (2-tailed) and slightly strong for P EBBINGHAUS Total Correct (r=-.71, p<.01 (2-tailed). The average level of attention measured by the BCI system during the P CORSI test was 49.00%, while in case of the P EBBINGHAUS test it was 52.41% on all samples. Conclusion: The developed BCI system has a significant correlation with P CORSI and P EBBINGHAUS cognitive neuroscience tests. The BCI system is capable of observing attentional vigilance continuously. Significance: The developed BCI system is applicable to observe vigilance level in realtime while the level of attention depends on activities.

show abstract

Mu-beta rhythm ERD/ERS quantification for foot motor execution and imagery tasks in BCI applications

Cited by 20 publications

References 13 publications

Mu-Beta event-related (de)synchronization and EEG classification of left-right foot dorsiflexion kinaesthetic motor imagery for BCI

Mu-Beta event-related (de)synchronization and EEG classification of left-right foot dorsiflexion kinaesthetic motor imagery for BCI

Comparison of Event-related Changes in Oscillatory Activity During Different Cognitive Imaginary Movements Within Same Lower-Limb

Examining the Learning Efficiency by a Brain-Computer Interface System

Contact Info

Product

Resources

About