AIMC Topic: Electroencephalography

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A brain-controlled lower-limb exoskeleton for human gait training.

The Review of scientific instruments Oct 1, 2017
Brain-computer interfaces have been a novel approach to translate human intentions into movement commands in robotic systems. This paper describes an electroencephalogram-based brain-controlled lower-limb exoskeleton for gait training, as a proof of ...
Humans Brain Gait Brain-Computer Interfaces Exoskeleton Device Feedback Robotics Electroencephalography
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Automated EEG artifact elimination by applying machine learning algorithms to ICA-based features.

Journal of neural engineering Aug 1, 2017
OBJECTIVE: Biological and non-biological artifacts cause severe problems when dealing with electroencephalogram (EEG) recordings. Independent component analysis (ICA) is a widely used method for eliminating various artifacts from recordings. However,...
Artifacts Middle Aged Electroencephalography Machine Learning Signal Processing, Computer-Assisted Algorithms Brain Humans Female Adult Male
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Epileptic seizure detection based on the kernel extreme learning machine.

Technology and health care : official journal of the European Society for Engineering and Medicine Jul 20, 2017
This paper presents a pattern recognition model using multiple features and the kernel extreme learning machine (ELM), improving the accuracy of automatic epilepsy diagnosis. After simple preprocessing, temporal- and wavelet-based features are extrac...
Humans Machine Learning Brain Epilepsy Seizures Reproducibility of Results Models, Statistical Electroencephalography
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Real-time analysis on ensemble SVM scores to reduce P300-Speller intensification time.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2017
In most Brain-Computer Interface systems, especially the P300-Speller, there must be a harmonized balance between the accuracy and the spelling time. One major drawback of the classical 36-choice P300-Speller is the slow rate of character elicitation...
Algorithms User-Computer Interface Signal Processing, Computer-Assisted Support Vector Machine Brain-Computer Interfaces Electroencephalography Event-Related Potentials, P300
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A separated feature learning based DBN structure for classification of SSMVEP signals.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2017
Signal processing is one of the key points in brain computer interface (BCI) application. The common methods in BCI signal classification include canonical correlation analysis (CCA), support vector machine (SVM) and so on. However, because BCI signa...
Humans Neural Networks, Computer Machine Learning Algorithms Electroencephalography Brain-Computer Interfaces Evoked Potentials, Visual
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Soft brain-machine interfaces for assistive robotics: A novel control approach.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Jul 1, 2017
Robotic systems offer the possibility of improving the life quality of people with severe motor disabilities, enhancing the individual's degree of independence and interaction with the external environment. In this direction, the operator's residual ...
Electroencephalography Equipment Design Adult Brain-Computer Interfaces Task Performance and Analysis User-Computer Interface Humans Self-Help Devices Robotics Young Adult Fixation, Ocular
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Utilization of kinematical redundancy of a rehabilitation robot to produce compliant motions under limitation on actuator performance.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Jul 1, 2017
This paper addresses the mechanical structure and control method of a redundant drive robot (RDR) to produce compliant motions, and show how the design parameters of the RDR can effect the produced motions and the mechanical and performance limitatio...
Stroke Rehabilitation Robotics Electroencephalography Equipment Design Humans Biomechanical Phenomena
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Improving robotic stroke rehabilitation by incorporating neural intent detection: Preliminary results from a clinical trial.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Jul 1, 2017
This paper presents the preliminary findings of a multi-year clinical study evaluating the effectiveness of adding a brain-machine interface (BMI) to the MAHI-Exo II, a robotic upper limb exoskeleton, for elbow flexion/extension rehabilitation in chr...
Electroencephalography Signal Processing, Computer-Assisted Intention Middle Aged Robotics Elbow Brain-Computer Interfaces Upper Extremity Stroke Rehabilitation Humans Brain Female Aged Male
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A cross-sectional evaluation of meditation experience on electroencephalography data by artificial neural network and support vector machine classifiers.

Medicine Apr 1, 2017
To quantitate the meditation experience is a subjective and complex issue because it is confounded by many factors such as emotional state, method of meditation, and personal physical condition. In this study, we propose a strategy with a cross-secti...
Aged Middle Aged Humans Support Vector Machine Adult Image Interpretation, Computer-Assisted Electroencephalography Artificial Intelligence Meditation Cross-Sectional Studies
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Unity is Strength: Improving biomedical classification performance based on ensemble learning approaches.

Computer methods and programs in biomedicine Apr 1, 2017
Decision Support Systems, Clinical Autistic Disorder Electroencephalography Supervised Machine Learning Image Interpretation, Computer-Assisted Algorithms Tomography, X-Ray Computed Diagnosis, Computer-Assisted Humans Lung Neoplasms Computational Biology
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