Delayed Maturation of P2 Flash Visual Evoked Potential (VEP) Latency in Newborns of Gestational Diabetic Mothers

2021 ◽  
pp. 105503
Author(s):  
Lauren C. Shuffrey ◽  
Cynthia Rodriguez ◽  
Daianna J. Rodriguez ◽  
Hana Mahallati ◽  
Minna Jayaswal ◽  
...  
Keyword(s):  
Visual Evoked Potential ◽  
Evoked Potential ◽  
Flash Visual Evoked Potential ◽  
Delayed Maturation ◽  
Vep Latency ◽  
Diabetic Mothers ◽  
Visual Evoked

Flash Visual Evoked Potential (VEP) in Amblyopia and Optic Nerve Disease

1995 ◽  
Vol 72 (9) ◽  
pp. 612-618 ◽  
Author(s):  
ELIZABETH T. DAVIS ◽  
SHERRY J BASS ◽  
JEROME SHERMAN
Keyword(s):  
Optic Nerve ◽  
Visual Evoked Potential ◽  
Evoked Potential ◽  
Optic Nerve Disease ◽  
Flash Visual Evoked Potential ◽  
Nerve Disease ◽  
Visual Evoked

Age‐associated changes in the equine flash visual evoked potential

2018 ◽  
Vol 22 (4) ◽  
pp. 388-397 ◽  
Author(s):  
Lena Ström ◽  
Måns Michanek ◽  
Björn Ekesten
Keyword(s):  
Visual Evoked Potential ◽  
Evoked Potential ◽  
Flash Visual Evoked Potential ◽  
Visual Evoked

Early Magnocellular Loss in Glaucoma Demonstrated Using the Pseudorandomly Stimulated Flash Visual Evoked Potential

1999 ◽  
Vol 8 (2) ◽  
pp. 140???148 ◽  
Author(s):  
Alexander I. Klistorner ◽  
Stuart L. Graham
Keyword(s):  
Visual Evoked Potential ◽  
Evoked Potential ◽  
Flash Visual Evoked Potential ◽  
Visual Evoked

scholarly journals Flash Visual Evoked Potential under General Anesthesia

2017 ◽  
Vol 37 (2) ◽  
pp. 262-268
Author(s):  
Hironobu HAYASHI ◽  
Masahiko KAWAGUCHI
Keyword(s):  
General Anesthesia ◽  
Visual Evoked Potential ◽  
Evoked Potential ◽  
Flash Visual Evoked Potential ◽  
Visual Evoked

scholarly journals Prediction of Post-operative Visual Deterioration Using Visual-Evoked Potential Latency in Extended Endoscopic Endonasal Resection of Craniopharyngiomas

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiaorong Tao ◽  
Xiaocui Yang ◽  
Xing Fan ◽  
Hao You ◽  
Yanwen Jin ◽  
...  
Keyword(s):  
Visual Evoked Potential ◽  
Evoked Potential ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Threshold Value ◽  
Endoscopic Endonasal ◽  
P100 Latency ◽  
Visual Deterioration ◽  
Vep Latency ◽  
Visual Evoked

Background: The current study aimed to investigate the predictive value of visual-evoked potential (VEP) latency for post-operative visual deterioration in patients undergoing craniopharyngioma resection via extended endoscopic endonasal approach (EEEA).Methods: Data from 90 patients who underwent craniopharyngioma resection via EEEA with intraoperative VEP monitoring were retrospectively reviewed. P100 latency was compared between patients with and without post-operative visual deterioration, and the threshold value of P100 latency for predicting post-operative visual deterioration was calculated by the receiver operating characteristic curve analysis. In addition, other potential prognostic factors regarding post-operative visual outcomes were also analyzed by multivariate analysis.Results: Patients with post-operative visual deterioration showed a significantly longer VEP latency than those without (p < 0.001). An extension over 8.61% in VEP latency was identified as a predictor of post-operative visual deterioration (p < 0.001). By contrast, longer preoperative visual impairment duration and larger tumor volume were not significant predictors for post-operative visual deterioration.Conclusions: The current study revealed that intraoperative VEP monitoring in EEEA is effective for predicting post-operative visual deterioration, and an extension over 8.61% in VEP latency can be used as a critical cut-off value to predict post-operative visual deterioration.

scholarly journals Evaluation of Filtering Techniques applied to simulated Electroencephalogram signals for Visual Evoked Potential Detection

Nova Scientia ◽  
2020 ◽  
Vol 12 (25) ◽  
Author(s):  
Jesús Alejandro Montalvo-Aguilar ◽  
Ivonne Bazán ◽  
Alfredo Ramírez-García
Keyword(s):  
Visual Evoked Potential ◽  
Evoked Potential ◽  
Extraction Methods ◽  
Denoising Method ◽  
Rectangular Window ◽  
Advantages And Disadvantages ◽  
Average Latency ◽  
Vep Latency ◽  
The Impact ◽  
Visual Evoked

Introduction: In this paper, it is presented an assessment of different windowing techniques and denoising methods applied to detect the Visual Evoked Potential (VEP) contained into the electroencephalographic (EEG) signals. The objective is to analyze advantages and disadvantages of each technique performance to identify correctly the VEP waveform and to quantify the latency which is a parameter commonly used as an indicator of ocular diseases.                       Method: Assessment of techniques was performed considering rigorous controlled conditions on the signal set, to assure that obtained results were linked just to the technique performances and avoid any undesirable effect due to the natural interference of acquisition of signals. For this reason, a simulated signals set was created based on a typical VEP waveform commonly registered around 100ms after an external stimulus was applied in the routine clinical study. Additionally, two evaluation stages were considered: fixed latency parameters stage and random latency parameters stage.Results: The best results without filter was with rectangular window and the use of elliptic filter can help to extract the VEP with a rectangular window too. For wavelet denoising the best result is Biorthogonal 2.6 wavelet with a Hamming window.                       Discussion or Conclusion: Five parameters were proposed to assessment the VEP extraction performed: signal noise ratio (SNR) mean square error (MSE), average latency (AL), latency standard deviation (LSD) and latency correlation variance (LCV) as representative factors to be considered on evaluations of VEP extraction methods. SNR and MSE were focused to assess the level of noise that remain in signal after windowing & denoising method was applied. In the other hand AL, LSD and LCV were oriented to evaluate the impact of the method on the VEP latency estimation.

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