Using natural head movements to continually calibrate EOG signals
Journal of Eye Movement Research, 2022 Electrooculography (EOG) is the measurement of eye movements using surface electrodes adhered around the eye. EOG systems can be designed to have an unobtrusive form-factor that is ideal for eye tracking in free-living over long durations, but the ...
Jason Nezvadovitz, Hrishikesh Rao
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Proposals and Comparisons from One-Sensor EEG and EOG Human-Machine Interfaces
Sensors, 2021 Human-Machine Interfaces (HMI) allow users to interact with different devices such as computers or home elements. A key part in HMI is the design of simple non-invasive interfaces to capture the signals associated with the user’s intentions. In this work,
Francisco Laport +4 more
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Comparison of head gaze and head and eye gaze within an immersive environment [PDF]
, 2006 For efficient collaboration between participants, eye gaze is seen as being critical for interaction. Teleconferencing systems such as the AcessGrid allow users to meet across geographically disparate rooms but as of now there seems no substitute for ...
Murray, NS, Roberts, DJ
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Recording of Electrooculography in photo phobia patients [PDF]
Biophysical Journal, 2009 AbstractPhotophobia is the condition which in accompanied by lack of color perception in human beings. Color perception is one of the characteristics of visual system in human beings. Retina in visual system is responsible for this characteristic. Electrooculogram(EOG) which is an electrophysiological technique has a contribution from cone cells in ...
N. Laal +3 more
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A Comparison of a Brain-Computer Interface and an Eye Tracker: Is There a More Appropriate Technology for Controlling a Virtual Keyboard in an ALS Patient? [PDF]
, 2017 The ability of people affected by amyotrophic lateral sclerosis (ALS), muscular dystrophy or spinal cord injuries to physically interact with the environment, is usually reduced.
DJ Krusienski +8 more
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Frontiers in Neuroscience, 2021 In recent years, automatic sleep staging methods have achieved competitive performance using electroencephalography (EEG) signals. However, the acquisition of EEG signals is cumbersome and inconvenient.
Jiahao Fan +6 more
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Efficient Implementation and Design of A New Single-Channel Electrooculography-based Human-Machine Interface System [PDF]
, 2015 published_or_final_versio
ANG, MS +8 more
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A Machine Learning Eye Movement Detection Algorithm using Electrooculography.
Sleep, 2022 STUDY OBJECTIVES Eye movement quantification in polysomnograms (PSG) is difficult and resource intensive. Automated eye movement detection would enable further study of eye movement patterns in normal and abnormal sleep, which could be clinically ...
A. Dupre +19 more
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Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms [PDF]
, 2018 We have developed an automatic sleep stage classification algorithm based on deep residual neural networks and raw polysomnogram signals. Briefly, the raw data is passed through 50 convolutional layers before subsequent classification into one of five ...
Jennum, Poul +4 more
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IEEE Access, 2021 Human-Machine Interfaces employing biosignal-based inputs are hard to translate to real-life applications, in part because of the difficulty of developing generalized models to classify physiological events representing a user’s actions.
Joao Perdiz +3 more
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