Gotowa bibliografia na temat „Electro-oculograms”

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Artykuły w czasopismach na temat "Electro-oculograms"

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Lubiński, Wojciech, Stanisław Zajączek, Zbigniew Sych, Krzysztof Penkala, Olgierd Palacz i Jan Lubiński. "Supernormal Electro-Oculograms in Patients with Neurofibromatosis Type 1". Hereditary Cancer in Clinical Practice 2, nr 4 (2004): 193. http://dx.doi.org/10.1186/1897-4287-2-4-193.

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Constable, Paul A., John G. Lawrenson i Geoffrey B. Arden. "Light and alcohol evoked electro-oculograms in cystic fibrosis". Documenta Ophthalmologica 113, nr 2 (5.10.2006): 133–43. http://dx.doi.org/10.1007/s10633-006-9023-z.

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David, Hugh, Regis Mollard, Phillipe Gabon i Bruno Farbos. "Point-of-Gaze Evaluation in Simulated ATC". Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44, nr 37 (lipiec 2000): 666–69. http://dx.doi.org/10.1177/154193120004403732.

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Eight Air Traffic Controllers carried out four TRACON II exercises using a graphic and a keyboard interface in low and high traffic. An iView head-mounted eye-tracking device was used. Electroencephalograms, (EEG), Electro-oculograms (EOG) and Electrocardiograms (EKG) were also measured, and on-line observations recorded using the Noldus Observer System. Subjective self-assessments, including the NASA-TLX (Task Load indeX) were employed. Significant events during the exercises were also identified for detailed analysis.
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Türksever, C., S. Orgül i M. Todorova. "Comparing Short-Duration Electro-Oculograms with and without Mydriasis in Healthy Subjects". Klinische Monatsblätter für Augenheilkunde 232, nr 04 (22.04.2015): 471–76. http://dx.doi.org/10.1055/s-0034-1396330.

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Roberti, G., P. Russo i G. Segrè. "Spectral analysis of electro-oculograms in the quantitative evaluation of nystagmus surgery". Medical & Biological Engineering & Computing 25, nr 5 (wrzesień 1987): 573–76. http://dx.doi.org/10.1007/bf02441752.

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McCormick, Steven A., Ronald C. Gentile, J. Vernon Odom i Matthew Farber. "Normal electro-oculograms in two patients with malignant melanoma of the choroid". Documenta Ophthalmologica 92, nr 3 (wrzesień 1996): 167–72. http://dx.doi.org/10.1007/bf02583288.

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Sun, Sheng, Jianyuan Wang, Menglun Zhang, Yuan Ning, Dong Ma, Yi Yuan, Pengfei Niu, Zhicong Rong, Zhuochen Wang i Wei Pang. "MEMS ultrasonic transducers for safe, low-power and portable eye-blinking monitoring". Microsystems & Nanoengineering 8, nr 1 (13.06.2022). http://dx.doi.org/10.1038/s41378-022-00396-w.

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AbstractEye blinking is closely related to human physiology and psychology. It is an effective method of communication among people and can be used in human–machine interactions. Existing blink monitoring methods include video-oculography, electro-oculograms and infrared oculography. However, these methods suffer from uncomfortable use, safety risks, limited reliability in strong light or dark environments, and infringed informational security. In this paper, we propose an ultrasound-based portable approach for eye-blinking activity monitoring. Low-power pulse-echo ultrasound featuring biosafety is transmitted and received by microelectromechanical system (MEMS) ultrasonic transducers seamlessly integrated on glasses. The size, weight and power consumption of the transducers are 2.5 mm by 2.5 mm, 23.3 mg and 71 μW, respectively, which provides better portability than conventional methods using wearable devices. Eye-blinking activities were characterized by open and closed eye states and validated by experiments on different volunteers. Finally, real-time eye-blinking monitoring was successfully demonstrated with a response time less than 1 ms. The proposed solution paves the way for ultrasound-based wearable eye-blinking monitoring and offers miniaturization, light weight, low power consumption, high informational security and biosafety.
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Rozprawy doktorskie na temat "Electro-oculograms"

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Coughlin, Michael J., i n/a. "Calibration of Two Dimensional Saccadic Electro-Oculograms Using Artificial Neural Networks". Griffith University. School of Applied Psychology, 2003. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20030409.110949.

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The electro-oculogram (EOG) is the most widely used technique for recording eye movements in clinical settings. It is inexpensive, practical, and non-invasive. Use of EOG is usually restricted to horizontal recordings as vertical EOG contains eyelid artefact (Oster & Stern, 1980) and blinks. The ability to analyse two dimensional (2D) eye movements may provide additional diagnostic information on pathologies, and further insights into the nature of brain functioning. Simultaneous recording of both horizontal and vertical EOG also introduces other difficulties into calibration of the eye movements, such as different gains in the two signals, and misalignment of electrodes producing crosstalk. These transformations of the signals create problems in relating the two dimensional EOG to actual rotations of the eyes. The application of an artificial neural network (ANN) that could map 2D recordings into 2D eye positions would overcome this problem and improve the utility of EOG. To determine whether ANNs are capable of correctly calibrating the saccadic eye movement data from 2D EOG (i.e. performing the necessary inverse transformation), the ANNs were first tested on data generated from mathematical models of saccadic eye movements. Multi-layer perceptrons (MLPs) with non-linear activation functions and trained with back propagation proved to be capable of calibrating simulated EOG data to a mean accuracy of 0.33° of visual angle (SE = 0.01). Linear perceptrons (LPs) were only nearly half as accurate. For five subjects performing a saccadic eye movement task in the upper right quadrant of the visual field, the mean accuracy provided by the MLPs was 1.07° of visual angle (SE = 0.01) for EOG data, and 0.95° of visual angle (SE = 0.03) for infrared limbus reflection (IRIS®) data. MLPs enabled calibration of 2D saccadic EOG to an accuracy not significantly different to that obtained with the infrared limbus tracking data.
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Coughlin, Michael J. "Calibration of Two Dimensional Saccadic Electro-Oculograms Using Artificial Neural Networks". Thesis, Griffith University, 2003. http://hdl.handle.net/10072/365854.

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The electro-oculogram (EOG) is the most widely used technique for recording eye movements in clinical settings. It is inexpensive, practical, and non-invasive. Use of EOG is usually restricted to horizontal recordings as vertical EOG contains eyelid artefact (Oster & Stern, 1980) and blinks. The ability to analyse two dimensional (2D) eye movements may provide additional diagnostic information on pathologies, and further insights into the nature of brain functioning. Simultaneous recording of both horizontal and vertical EOG also introduces other difficulties into calibration of the eye movements, such as different gains in the two signals, and misalignment of electrodes producing crosstalk. These transformations of the signals create problems in relating the two dimensional EOG to actual rotations of the eyes. The application of an artificial neural network (ANN) that could map 2D recordings into 2D eye positions would overcome this problem and improve the utility of EOG. To determine whether ANNs are capable of correctly calibrating the saccadic eye movement data from 2D EOG (i.e. performing the necessary inverse transformation), the ANNs were first tested on data generated from mathematical models of saccadic eye movements. Multi-layer perceptrons (MLPs) with non-linear activation functions and trained with back propagation proved to be capable of calibrating simulated EOG data to a mean accuracy of 0.33° of visual angle (SE = 0.01). Linear perceptrons (LPs) were only nearly half as accurate. For five subjects performing a saccadic eye movement task in the upper right quadrant of the visual field, the mean accuracy provided by the MLPs was 1.07° of visual angle (SE = 0.01) for EOG data, and 0.95° of visual angle (SE = 0.03) for infrared limbus reflection (IRIS®) data. MLPs enabled calibration of 2D saccadic EOG to an accuracy not significantly different to that obtained with the infrared limbus tracking data.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Applied Psychology
Griffith Health
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