AIMC Topic: Brain-Computer Interfaces

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Super-Resolution for Improving EEG Spatial Resolution using Deep Convolutional Neural Network-Feasibility Study.

Sensors (Basel, Switzerland) Dec 3, 2019
Electroencephalography (EEG) has relatively poor spatial resolution and may yield incorrect brain dynamics and distort topography; thus, high-density EEG systems are necessary for better analysis. Conventional methods have been proposed to solve thes...
Humans Neural Networks, Computer Machine Learning Electroencephalography Signal Processing, Computer-Assisted Feasibility Studies Brain-Computer Interfaces Normal Distribution Algorithms Brain Computer Simulation Adult
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Automatic bad channel detection in implantable brain-computer interfaces using multimodal features based on local field potentials and spike signals.

Computers in biology and medicine Dec 2, 2019
"Bad channels" in implantable multi-channel recordings bring troubles into the precise quantitative description and analysis of neural signals, especially in the current "big data" era. In this paper, we combine multimodal features based on local fie...
Machine Learning Action Potentials Brain-Computer Interfaces
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Evaluating a Semiautonomous Brain-Computer Interface Based on Conformal Geometric Algebra and Artificial Vision.

Computational intelligence and neuroscience Nov 27, 2019
In this paper, we evaluate a semiautonomous brain-computer interface (BCI) for manipulation tasks. In such a system, the user controls a robotic arm through motor imagery commands. In traditional process-control BCI systems, the user has to provide t...
Imagination Proof of Concept Study Event-Related Potentials, P300 Motor Activity Mental Fatigue Biomechanical Phenomena Male Models, Theoretical Robotics Electroencephalography Signal Processing, Computer-Assisted Goals Brain-Computer Interfaces Artificial Intelligence Brain Female Young Adult Humans
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Deep Learning Neural Encoders for Motor Cortex.

IEEE transactions on bio-medical engineering Nov 25, 2019
Intracortical brain-machine interfaces (BMIs) transform neural activity into control signals to drive a prosthesis or communication device, such as a robotic arm or computer cursor. To be clinically viable, BMI decoders must achieve high accuracy and...
Deep Learning Brain-Computer Interfaces Motor Cortex Macaca mulatta Humans Algorithms Animals
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Improved Transductive Support Vector Machine for a Small Labelled Set in Motor Imagery-Based Brain-Computer Interface.

Computational intelligence and neuroscience Nov 25, 2019
Long and tedious calibration time hinders the development of motor imagery- (MI-) based brain-computer interface (BCI). To tackle this problem, we use a limited labelled set and a relatively large unlabelled set from the same subject for training bas...
Foot Motor Activity Imagination Humans Brain Time Factors Hand Tongue Calibration Brain-Computer Interfaces Models, Theoretical Support Vector Machine Electroencephalography Signal Processing, Computer-Assisted
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Electroencephalogram based communication system for locked in state person using mentally spelled tasks with optimized network model.

Artificial intelligence in medicine Nov 19, 2019
Due to growth in population, Individual persons with disabilities are increasing daily. To overcome the disability especially in Locked in State (LIS) due to Spinal Cord Injury (SCI), we planned to design four states moving robot from four imagery ta...
Reproducibility of Results Aged Aged, 80 and over Young Adult Adult Male Middle Aged Electroencephalography Neural Networks, Computer Algorithms Computer Simulation Female Humans Wavelet Analysis Spinal Cord Injuries Communication Devices for People with Disabilities Locked-In Syndrome Electrodes Sex Characteristics Healthy Volunteers Brain-Computer Interfaces
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Subject-Independent Brain-Computer Interfaces Based on Deep Convolutional Neural Networks.

IEEE transactions on neural networks and learning systems Nov 13, 2019
For a brain-computer interface (BCI) system, a calibration procedure is required for each individual user before he/she can use the BCI. This procedure requires approximately 20-30 min to collect enough data to build a reliable decoder. It is, theref...
Information Theory Adult Male Deep Learning Bayes Theorem Electroencephalography Brain-Computer Interfaces Movement Imagination Brain Female Reproducibility of Results Young Adult Humans Neural Networks, Computer Algorithms Databases, Factual
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Optimized artificial neural network based performance analysis of wheelchair movement for ALS patients.

Artificial intelligence in medicine Nov 9, 2019
Individuals with neurodegenerative attacks loose the entire motor neuron movements. These conditions affect the individual actions like walking, speaking impairment and totally make the person in to locked in state (LIS). To overcome the miserable co...
Healthy Volunteers Brain-Computer Interfaces Patients Wheelchairs Middle Aged Robotics Electroencephalography Amyotrophic Lateral Sclerosis Locked-In Syndrome Humans Neural Networks, Computer Algorithms Female Young Adult Adult Male
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Signal identification system for developing rehabilitative device using deep learning algorithms.

Artificial intelligence in medicine Nov 8, 2019
Paralyzed patients were increasing day by day. Some of the neurodegenerative diseases like amyotrophic lateral sclerosis, Brainstem Leison, Stupor and Muscular dystrophy affect the muscle movements in the body. The affected persons were unable to mig...
Rehabilitation Healthy Volunteers Brain-Computer Interfaces Electrooculography Self-Help Devices Eye Movements Equipment Design Signal Processing, Computer-Assisted Electrodes Humans Algorithms Female Reproducibility of Results Male Aging Deep Learning Young Adult Adult
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The Last Mile: Where Artificial Intelligence Meets Reality.

Journal of medical Internet research Nov 8, 2019
Although much effort is focused on improving the technical performance of artificial intelligence, there are compelling reasons to focus more on the implementation of this technology class to solve real-world applications. In this "last mile" of impl...
Brain-Computer Interfaces Artificial Intelligence Algorithms Technology
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