AIMC Topic: Electrooculography

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Danger, high voltage! Using EEG and EOG measurements for cognitive overload detection in a simulated industrial context.

Applied ergonomics Apr 8, 2022
Industrial settings will be characterized by far-reaching production automation brought about by advancements in robotics and artificial intelligence. As a consequence, human assembly workers will need to adapt quickly to new and more complex assembl...
Eye Movements Cognition Electroencephalography Electrooculography Humans Artificial Intelligence
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A Human-Machine Interface Based on an EOG and a Gyroscope for Humanoid Robot Control and Its Application to Home Services.

Journal of healthcare engineering Mar 19, 2022
The human-machine interface (HMI) has been studied for robot teleoperation with the aim of empowering people who experience motor disabilities to increase their interaction with the physical environment. The challenge of an HMI for robot control is t...
Humans Robotics Motion Electrooculography
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Human-Machine Interface: Multiclass Classification by Machine Learning on 1D EOG Signals for the Control of an Omnidirectional Robot.

Sensors (Basel, Switzerland) Aug 31, 2021
People with severe disabilities require assistance to perform their routine activities; a Human-Machine Interface (HMI) will allow them to activate devices that respond according to their needs. In this work, an HMI based on electrooculography (EOG) ...
Eye Movements Robotics Machine Learning Electrooculography Algorithms Humans
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Eye-Movement-Controlled Wheelchair Based on Flexible Hydrogel Biosensor and WT-SVM.

Biosensors Jun 16, 2021
To assist patients with restricted mobility to control wheelchair freely, this paper presents an eye-movement-controlled wheelchair prototype based on a flexible hydrogel biosensor and Wavelet Transform-Support Vector Machine (WT-SVM) algorithm. Cons...
Humans Algorithms Hydrogels Wavelet Analysis Electroencephalography Eye Movements Electrooculography Wheelchairs Signal Processing, Computer-Assisted Biosensing Techniques Electrodes Support Vector Machine
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A hybrid unsupervised-Deep learning tandem for electrooculography time series analysis.

PloS one Jul 21, 2020
Medical data are often tricky to get mined for patterns even by the generally demonstrated successful modern methodologies of deep learning. This paper puts forward such a medical classification task, where patient registers of two of the categories ...
Saccades Databases as Topic Photic Stimulation Electrooculography Neural Networks, Computer Algorithms Deep Learning Time Factors Cluster Analysis Unsupervised Machine Learning Humans
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Automated Detection of Presymptomatic Conditions in Spinocerebellar Ataxia Type 2 Using Monte Carlo Dropout and Deep Neural Network Techniques with Electrooculogram Signals.

Sensors (Basel, Switzerland) May 27, 2020
Application of deep learning (DL) to the field of healthcare is aiding clinicians to make an accurate diagnosis. DL provides reliable results for image processing and sensor interpretation problems most of the time. However, model uncertainty should ...
Humans Neural Networks, Computer Spinocerebellar Ataxias Electrooculography Image Processing, Computer-Assisted Decision Trees Monte Carlo Method
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DESIGN AND DEVELOPMENT OF HUMAN COMPUTER INTERFACE USING ELECTROOCULOGRAM WITH DEEP LEARNING.

Artificial intelligence in medicine Nov 21, 2019
Today's life assistive devices were playing significant role in our life to communicate with others. In that modality Human Computer Interface (HCI) based Electrooculogram (EOG) playing vital part. By using this method we can able to overcome the con...
Eye Movements User-Computer Interface Electrodes Pattern Recognition, Automated Electrooculography Sex Characteristics Artifacts Male Aging Deep Learning Female Reproducibility of Results Adult Humans Neural Networks, Computer Algorithms
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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...
Self-Help Devices Rehabilitation Healthy Volunteers Brain-Computer Interfaces Electrooculography Male Aging Deep Learning Signal Processing, Computer-Assisted Electrodes Eye Movements Equipment Design Humans Reproducibility of Results Algorithms Young Adult Adult Female
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A hierarchical sequential neural network with feature fusion for sleep staging based on EOG and RR signals.

Journal of neural engineering Oct 29, 2019
OBJECTIVE: Currently, the automatic sleep staging methods mainly face two problems: the first problem is that although the algorithms which use electroencephalogram (EEG) signals perform well, acquiring EEG signals is complicated and uncomfortable; t...
Female Adult Male Humans Neural Networks, Computer Sleep Stages Databases, Factual Electroencephalography Sleep Apnea Syndromes Electrooculography
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Machine-Learning-Based Detection of Craving for Gaming Using Multimodal Physiological Signals: Validation of Test-Retest Reliability for Practical Use.

Sensors (Basel, Switzerland) Aug 9, 2019
Internet gaming disorder in adolescents and young adults has become an increasing public concern because of its high prevalence rate and potential risk of alteration of brain functions and organizations. Cue exposure therapy is designed for reducing ...
Respiratory Rate Male Craving Humans Self Report Behavior, Addictive Electrooculography Machine Learning Heart Rate Saccades Video Games Young Adult
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