Kornilova L N, Ekimovskiy G A, Habarova E V, Glukhikh D O, Naumov I A, Sagalovitch V N, Solovieva A D, Filatova E G, Fedorova V I
Institute of Biomedical Problems Russian Academy of Science, Moscow.
Sechenov First Moscow State Medical University, Moscow.
Zh Nevrol Psikhiatr Im S S Korsakova. 2015;115(3):54-60. doi: 10.17116/jnevro20151153154-60.
To create a complex computerized method of objectification of dizziness and vertigo, and differentiation of vestibulopathies of various geneses using electrooculography approach that allows to record and analyze spontaneous, vestibular- and visually-induced eye movements, with the following classification (discriminant) analysis of the results obtained.
The study involved 69 patients of different sex and age complained of dizziness, vertigo and disequilibrium, and 64 healthy men. Based on the results of clinical examination, patients were divided into three groups: patients with peripheral vestibulopathy, patients with central vestibulopathy and patients with psychogenic vestibulopathy. Electrooculography was performed using the hardware-software complex (HSC) "OCULOSTIM-CM".
Significant diagnostic parameters based on the recognition and analysis of spontaneous, vestibular- and visually-induced eye movements were coefficients of efficacy and increased frequency of fixation saccades and smooth pursuit with- and without retinal optokinetic stimulation. We developed the algorithm and complex computerized method for differentiation of different types of vestibulopathy.
创建一种复杂的计算机化方法,用于眩晕和头晕的客观化评估,以及使用眼震电图方法区分不同病因的前庭病变,该方法能够记录和分析自发的、前庭诱发和视觉诱发的眼球运动,并对所得结果进行以下分类(判别)分析。
该研究纳入了69例不同性别和年龄、主诉头晕、眩晕和平衡失调的患者,以及64名健康男性。根据临床检查结果,将患者分为三组:外周性前庭病变患者、中枢性前庭病变患者和精神性前庭病变患者。使用硬件 - 软件复合体(HSC)“OCULOSTIM - CM”进行眼震电图检查。
基于对自发的、前庭诱发和视觉诱发的眼球运动的识别和分析,显著的诊断参数包括有效系数以及在有和没有视网膜视动刺激情况下注视性扫视和平稳跟踪的频率增加。我们开发了用于区分不同类型前庭病变的算法和复杂计算机化方法。