Digital measurement of torsional eye movement due to postural change and its effect on reading performance

A torsional eye movement calculation algorithm for low contrast images in video-oculography

Video-oculography (VOG) is a frequently used clinical technique to detect eye movements. In this research, head mounted small video-cameras and IR-illumination are employed to image the eye. Many algorithms have been developed to extract horizontal and vertical eye movements from the video images. Designing a method to determine torsional eye movements is a more complex task. The use of IR-wavelengths required for illumination in certain clinical tests results in a very low image contrast. In such images, iris textures are almost invisible, making them unsuited for direct application of standard matching algorithms, which are used to calculate torsional eye movements. This research presents the design and implementation of a robust torsional eye movement detection algorithm for VOG. This algorithm uses a new approach to measure the torsional eye movement and is suitable for low contrast videos. The algorithm is implemented in a clinical device and its performance is compared to that of alternative techniques.

Effect of instrument rotation on handheld keratometry

PURPOSE

To study the effect of instrument rotation on handheld automated keratometry.

SETTING

Department of Optometry and Radiography, The Hong Kong Polytechnic University, Hong Kong SAR, China.

METHODS

In 33 recruited subjects, corneal curvature in 1 eye (randomly selected) was measured using a Medmont topographic keratometer and a Nidek handheld keratometer. In handheld keratometry, measurements were obtained holding the instrument in the upright position and rotating it anticlockwise 5 degrees, 10 degrees, and 15 degrees and then clockwise 5 degrees, 10 degrees, and 15 degrees. The sequence of measurements was randomly assigned. The steepest and flattest corneal curvatures as well as the axis along the flattest meridian were compared in different conditions. The corneal power was converted to vector representation (M, J0, J45) for a second comparison.

RESULTS

There was a significant difference in the steepest and flattest curvatures in different conditions (repeated-measures analysis of variation, P<.05). However, the mean difference between handheld and topographic keratometry was approximately 0.25 diopter (D) for the steepest curvature and 0.05 D for the flattest curvature regardless of the direction and amount of rotation. The intraclass correlation coefficients were nearly 1, which indicated good clinical reliability. The mean difference in axis determination followed the direction and amount of rotation. With vector representation, the difference between the devices increased with the amount of rotation, especially J0 and J45.

CONCLUSIONS

Handheld keratometry was in agreement with topographic keratometry. However, practitioners should adjust the axis manually according to the direction and amount of rotation. The difference between handheld and topographic keratometry increased with the rotational effect, which was seen with vector representation. Practitioners are advised to use the handheld keratometer in the upright position.