Improving SSVEP-BCI performance using pre-trial normalization methods

Henshaw, James; Liu, Wei; Romano, Daniela M.

doi:10.1109/coginfocom.2017.8268251

Cited by 4 publications

(3 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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%

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

Section: Introductionmentioning

confidence: 99%

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

show abstract

“…CogInfoCom covers several disciplines appearing in applications and research areas also. CogInfoCom is available technology from socio-cognitive ICT [55][56][57][58][59][60][61][62][63][64][65] to cognitive aided engineering [66][67][68][69][70][71][72][73][74][75][76][77] and its related aspects in terms of online collaborative systems and virtual reality solutions [78][79][80], teaching-learning [81][82][83][84][85][86] and human cognitive interfaces such as braincomputer interfaces (BCIs) [87][88][89][90][91][92] and medicals [93][94][95][96].…”

Section: Human-computer Interfaces and Cognitive Infocommunicationmentioning

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

“…These human-machine interface systems have appeared in many applications and research areas, basically called the field of cognitive infocommunications (CogInfoCom). CogInfoCom, involves the speechability, communication, linguistic and behavioural interaction analysis, face and gesture recognition, brain-computer interface (BCI), human cognitive interface -virtual and real avatars dealing with the complex mixture of human and artificial cognitive capabilities in human computer interaction processes [48][49][50][51][52][53][54][55][56][57][58][59][60][61][62][63]. The socio-cognitive ICT field includes collective knowledge, cognitive networks and their intelligent capabilities.…”

Section: Introductionmentioning

confidence: 99%

The Evaluation of BCI and PEBL-based Attention Tests

2018

APH

View full text Add to dashboard Cite

Improving SSVEP-BCI performance using pre-trial normalization methods

Cited by 4 publications

References 34 publications

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

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

The Evaluation of BCI and PEBL-based Attention Tests

Contact Info

Product

Resources

About