Automatic nystagmus detection and quantification in long-term continuous eye-movement data
Automatic nystagmus detection and quantification in long-term continuous eye-movement data
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DOI：
10.1016/j.compbiomed.2019.103448
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发表时间：
2019-11-01
影响因子：
7.7
通讯作者：
Bath, Andrew
中科院分区：
文献类型：
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作者：
Newman, Jacob L.;Phillips, John S.;Bath, Andrew
头晕或不平衡的症状经常被65岁以上的人报告。头晕通常是偶发性的，可能有许多原因，使诊断成为问题。当它是由于内耳功能障碍，它通常伴随着异常的眼球运动称为眼球震颤。CAVA（持续动态前庭评估）设备已开发用于提供眼球运动的持续监测，以深入了解头晕发作期间存在的生理参数。在本文中，我们描述了新的算法，用于检测短期的人工诱导眼震的CAVA设备收集的长期眼动数据。在一项涉及17名健康受试者的盲法试验中，每位参与者通过观看VR耳机上的短视频，人工诱导眼球震颤多达8次。我们的算法以98.77%的准确率检测到这些短周期。此外，收集、分析与前庭诱发性眼球震颤相关的数据，然后与用于在冷热试验期间评估眼球震颤的常规技术进行比较。结果表明，可以使用应用于CAVA设备捕获的长期眼动数据的计算方法来识别和量化眼球震颤的范围。
Symptoms of dizziness or imbalance are frequently reported by people over 65. Dizziness is usually episodic and can have many causes, making diagnosis problematic. When it is due to inner-ear malfunctions, it is usually accompanied by abnormal eye-movements called nystagmus. The CAVA (Continuous Ambulatory Vestibular Assessment) device has been developed to provide continuous monitoring of eye-movements to gain insight into the physiological parameters present during a dizziness attack. In this paper, we describe novel algorithms for detecting short periods of artificially induced nystagmus from the long-term eye movement data collected by the CAVA device. In a blinded trial involving 17 healthy subjects, each participant induced nystagmus artificially on up to eight occasions by watching a short video on a VR headset. Our algorithms detected these short periods with an accuracy of 98.77%. Additionally, data relating to vestibular induced nystagmus was collected, analysed and then compared to a conventional technique for assessing nystagmus during caloric testing. The results show that a range of nystagmus can be identified and quantified using computational methods applied to long-term eye-movement data captured by the CAVA device.