The video ocular counter-roll (VOCR): a new bedside clinical test of otolith function

Abstract

An ocular counter-roll (OCR) measurement and evaluation system includes a head attachment frame; a head orientation sensing device attached to the head attachment frame; an eye-torsion sensing device attached to the head attachment frame, the eye-torsion sensing device being configured to communicate with the head orientation sensing device; a data processor configured to communicate with the head orientation sensing device and the eye-torsion sensing device while a subject performs test evaluation; and a display device configured to communicate with the data processor to display information received therefrom in real time while the subject performs the test evaluation.

Description

THE VIDEO OCULAR COUNTER-ROLL (VOCR): A NEW BEDSIDE CLINICAL TEST OF OTOLITH FUNCTIONCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] The present patent application claims priority benefit to U.S. Provisional Patent Application No. 63 / 662,163, filed on June 20, 2024, the entire content of which is incorporated herein by reference. All references cited anywhere in this specification, including the Background and Detailed Description sections, are incorporated by reference as if each had been individually incorporated.GOVERNMENT SUPPORT

[0002] This invention was made with government support under grant 1R01DC018815 awarded by the National Institutes of Health / NIH / DHHS. The government has certain rights in the invention.BACKGROUND1. Technical Field

[0003] The currently claimed embodiments of the present invention relate to an ocular counter-roll (OCR) measurement and evaluation system and methods.2. Discussion of Related Art

[0004] The vestibular system functions to detect the position and movement of our head in space. It is located within the inner ear and consists of semicircular canals (the angular sensors) and otolithorgans (the linear sensors). It has a primary role of providing visual stability associated with head movement through the vestibulo-ocular reflex (VOR). Without this essential reflex, head movement would induce visual blurring or dizziness. Video-oculography (VOG) goggles have been integrated into the bedside assessment of patients with vestibular disorders. The emphasis has been mostly on the function of semicircular canals using the video head impulse test (vHIT), but a similar VOG method for the clinical test of otolith function (another important aspect of inner ear balance function) is lacking.

[0005] Ocular counter-roll (OCR) is a VOR characterized by torsional rotations of the eye in response to lateral tilt of the head (ear to shoulder) to maintain visual stability. With a sustained head tilt, the OCR is driven by the otolith organs (mainly the utricles), which results in a static change in torsional eye position in the direction away from the head tilt. Because otolith pathways are commonly affected in vestibular disorders, an easy-to-use, bedside VOG test of otolith function is valuable in the evaluation of these patients. Most VOG goggles are only capable of measuring horizontal or vertical eye movement but are unable to measure torsional eye movement. There thus remains a need for an easy-to-use device and methods for bedside VOG test of otolith function.SUMMARY

[0006] An ocular counter-roll (OCR) measurement and evaluation system according to an embodiment of the current invention includes a head attachment frame; a head orientation sensing device attached to the head attachment frame; an eye-torsion sensing device attached to the head attachment frame, the eye-torsion sensing device being configured to communicate with the head orientation sensing device; a data processor configured to communicate with the head orientation sensing device and the eye-torsion sensing device while a subject performs test evaluation; and a display device configured to communicate with the data processor to display information received therefrom in real time while the subject performs the test evaluation.BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Embodiments of the present invention, as well as the methods of operation and functions of the related elements of structure and the combination of parts and economies of manufacture, will become more apparent upon consideration of the following description and the appended claims with reference to the accompanying drawings, all of which form a part of this specification, wherein like reference numerals designate corresponding parts in the various figures. It is to be expressly understood, however, that the drawings are for the purpose of illustration and description only and are not intended as a definition of the limits of the invention.

[0008] FIG. 1A shows the vOCR test measures otolith-driven VOR by tracking ocular torsion during static lateral head tilt according to an embodiment of the current invention.

[0009] FIG. IB shows that the receiver operating characteristic analysis has similar diagnostic accuracy for vOCR and VEMPs (cervical and ocular).

[0010] FIG. 2A is a schematic illustration of a vOCR system according to an embodiment of the current invention.

[0011] FIG. 2B is a schematic corresponding to the embodiment of FIG. 2A.

[0012] FIG. 3 illustrates the general structure of our method to measure torsional eye movements according to some embodiments of the current invention.

[0013] FIG. 4 shows that the vOCR value is measured as the torsional eye position (red(right eye) / blue(left eye) crosses) by tracking the iris pattern and comparing it to a reference frame in the upright position according to an embodiment of the current invention.

[0014] FIG. 5 shows an example of a user interface showing online tracking of OCR (ocular torsion) shown as the red and blue traces for both eyes as well as the head tilt angles in roll and pitch planes (top right) according to an embodiment of the current invention.

[0015] FIG. 6 illustrates that the tilt maneuver during the vOCR test is a passive en bloc tilt of the head and trunk while the subject is sitting on a chair according to another embodiment of the current invention.

[0016] FIG. 7 shows an example of vOCR measurement with right and left head tilts showing a lower value on the left side according to another embodiment of the current invention.DETAILED DESCRIPTION

[0017] Some embodiments of the current invention are discussed in detail below. In describing embodiments, specific terminology is employed for the sake of clarity. However, the invention is not intended to be limited to the specific terminology so selected. A person skilled in the relevant art will recognize that other equivalent components can be employed, and other methods developed, without departing from the broad concepts of the present invention. All references cited anywhere in this specification are incorporated by reference as if each had been individually incorporated.

[0018] Accordingly, our lab has developed a new VOG test that can measure static OCR (vOCR) with a simple maneuver, when tilting a subject’s head to the side to obtain a test of utricle function. In a previous study, we have shown that the vOCR can detect loss of otolith function with an accuracy comparable with the vestibular-evoked myogenic potentials (VEMP), a widely used laboratory test of otolith function. A following study further shows that the vOCR test can be easily applied with a bedside tilt of the head and torso en bloc to detect or track loss of otolith function at various stages of vestibular function loss.

[0019] The test can be easily applied with a simple tilt of the head and torso together while the patient is seated and looking straight ahead. According to an embodiment of the current invention, commercially available, high-speed video goggles can be modified by adding the sensors which can track head motion in real-time. Use of VOG goggles and automated analysis software can provide immediate feedback of vestibular loss during a clinical evaluation of patients with dizziness and balance problems. This test could be used to measure and track recovery from vestibular loss, as well as being able to track a patient’s response to vestibular physical therapy. An embodiment of the current invention has multiple implications to better detect and measure recovery from inner ear disorders, particularly dysfunction of the utricle.

[0020] While video-oculography (VOG) has been widely used for clinical assessment of canal function, a comparable VOG method for measurement of otolith function has been lacking. The otolith organs detect inertial forces on the head and provide the brain with essential and wide rangeneurophysiologic functions including detection of head translation, generation of a torsional VOR, maintenance of postural control during stance / gait, and perception of spatial orientation. Since otolith pathways are commonly affected in vestibular disorders, an easy-to-use, bedside VOG test of otolith function is valuable for clinical evaluation of these patients [1-4], When the head is tilted laterally in the roll plane, the resulting VOR is a torsional rotation of the eyes in the opposite direction of the head tilt, known as the ocular counter-roll (OCR) [5-7], During the movement of the head, the dynamic component of OCR is driven by the activity from both semicircular canals and otolith organs, and it consists of a torsional nystagmus with a slow phase in the opposite direction of the head tilt [8,9], During a sustained head tilt, however, the static OCR that maintains the ocular torsion away from the side of the head tilt is mainly generated by the utricular otolith inputs [3,10-13], Normally, the gain of static OCR during lateral head tilt is about 0.25 [14,5,8], On this basis, we have developed a VOG method of OCR measurement (vOCR) for rapid quantification of otolith function, which utilizes high-speed VOG and automated analysis software [14-16], The vOCR test is applied with a simple head tilt maneuver and has a diagnostic accuracy comparable to the vestibular evoked myogenic potentials (VEMP), the widely used clinical test of otolith function (FIGS. 1A, IB)

[0014] , Patients with acute vestibular loss have vOCR values lower on the side of vestibular loss creating an asymmetry between both labyrinths, but the asymmetry reduces in subacute and chronic vestibular loss [15,16], In contrast, the VEMP values remain reduced in chronic stages of vestibular loss. Thus, while VEMP is limited as a monoaural measure of otolith function, vOCR is a measure of otolith function that can correspond with recovery [14-16], Here we describe the application of vOCR as a novel and easy-to-apply measure of otolith function.

[0021] FIG. 1 A shows the vOCR test measures otolith-driven VOR by tracking ocular torsion during static lateral head tilt. FIG. IB shows the receiver operating characteristic analysis shows similar diagnostic accuracy for vOCR and VEMPs (cervical and ocular), which validates vOCR as a comparable otolith measure

[0014] ,

[0022] The system used for vOCR testing is portable and can be used in any ambulatory setting (FIG. 2A). The system comprises a head attachment frame (or goggles) shown at 200, a head orientation sensing element shown at 201, an eye orientation sensing element shown at 202, and custom software for recording and analysis of the eye and head position data shown at 204 and 207. Both the eye and head sensor elements are mounted on the head frame. The eye sensorshave two video cameras mounted on the head frame, each camera pointing at one eye. The eye sensor captures images of the eye(s) using an infrared light sources and cameras. The images allow for tracking of the reflection of the light source and visible ocular features such as the pupil features and iris pattern. The collected data from the camera can be used to measure the movement of the eye and the eyelid.

[0023] The head orientation sensing element is rigidly mounted to the head-worn frame to allow equal change in the orientation of the head sensing unit with any head movement. The head orientation sensor consists of a 6 DOF IMU (Inertial Measurement Unit) sensor (TDK ICM- 42688-p), which incorporates three axes of angular rate sensors, and three axes of linear acceleration sensors. A head-mounted microcontroller acquires accelerometer data from the IMU chip and sends the accelerometer data via serial link into one of the camera digital inputs, where it is then sent via the camera’s Firewire interface to the host PC and saved along with the video images. Data from the head sensors is processed by the tracking software to detect positional changes within the pitch and roll planes (i.e., head motion in vertical direction and around the line of sight), and is combined with data from the eye sensors to provide online measures of eye and head position during the vOCR test, and to plot the eye and head position traces.

[0024] FIGS. 2A, 2B provide schematic illustrations of the vOCR system. The head attachment frame (200) is used to mount the head orientation sensor (201) and eye sensors (202) connected via wires (203). A host PC receives the data from the sensors via wired connection (206) and runs the software for eye and head tracking and data analysis. The testing software (204) is used for tracking and displaying the eye and head positions during the test. The analysis software (207) is used for plotting the data and calculating the vOCR value. Although the device illustrated in FIG. 2A has hard-wired connections, such as wired connection 206, the general concepts of the current invention are not limited to only hard-wired connections. Wireless radio and / or optical connections can also be used in alternative embodiments.Eye tracking

[0025] For eye tracking we can use a method that takes advantage of (OpenCV) advances in the field of iris recognition for measurement of torsional eye movements or ocular torsion

[0017] , FIG. 3 shows the general structure of our method to measure torsional eye movements accordingto some embodiments of the current invention. This method is based on measuring the rotation of the iris pattern around the pupil center by comparing each video frame with a reference frame. First, we select the area of the image around the center of the pupil that contains the entire iris and then mask the pixels that are covered by the eyelids and corneal reflections with zero values. Then we apply a polar transformation to the image to transform the circular pattern of the iris into a rectangular configuration. This facilitates the torsion calculation because rotations around the pupil center become translations in one dimension. Since the relevant information about the torsion is only in one dimension, we can optimize the image by low pass filtering the radial dimension and band pass filtering the tangential dimension using the Sobel function in OpenCV. The low pass filtering reduces the noise in the image without reducing the information available for calculating torsion and the high pass filtering eliminates the effect of changes in overall luminance in the image and enhances the small but salient iris features. This filtering is comparable to the Gabor filtering typically used in iris recognition. Finally, we replace the masked pixels with random noise to eliminate the interference of eyelids, eyelashes and corneal reflections when calculating the cross-correlation. The iris pattern contains pixels between the edge of the pupil and the outer edge of the iris. Because the pupil size can change, we apply a transformation to compare the iris pattern obtained at different pupil sizes. We simply scale the pattern to a fixed size of 60 pixels regardless of the size of the pupil or iris. Thus, our iris pattern will always be 360 pixels long and 60 pixels wide regardless of the pupil size. This resizing can also be important to ensure that the processing time does not change when the properties of the image change (resolution, iris size, pupil size, etc.) so that real time processing is always possible at 100 frames per second. To calculate torsion, we use a template matching technique based on the FFT (Fast Fourier Transform) as implemented in the OpenCV library (matchTemplate function). The template matching provides a measure of similarity of two images for different overlapping positions. The template matching method is conceptually equivalent to shifting the image one pixel at a time and measuring the correspondence between the reference and the current image. For vOCR measurement, a reference image is set as zero torsion when the head is upright and any changes in the iris pattern as a result of change in torsional eye position is compared to this reference image (FIG. 4).

[0026] In FIG. 3 ocular torsion is measured as rotations of the iris around the center of the pupil. First, we get a rough estimate of the location of the pupil using an image with reducedresolution. This approximation defines the region of interest where the subsequent processing steps occur. Next, we detect the eyelids and use them to identify the parts of the pupil contour and the iris not covered by the eyelids or eyelashes. Then we fit an ellipse to the visible pupil contour to get precise measurement of the horizontal and vertical position of the center of the pupil. Next, we select the iris pattern, apply a polar transformation (including geometric correction for eccentric eye positions), optimize the image to enhance the iris features, and mask the parts covered by the eyelids. To determine the torsion angle, we use the template matching method implemented in OpenCV to compare the current iris pattern with a reference image. Thus, all measurements of torsion are relative to the orientation of the eye when the reference image is obtained. The method produces real time recordings at 100Hz of the horizontal, vertical, and torsional positions of both eyes. Before executing the automatic algorithm, the operator must specify a few parameters: the two thresholds that are used to identify the darkest (pupil) and brightest (corneal reflections) pixels in the image, and the iris radius. All parameters can be selected easily using an interactive user interface by observing them directly overlaid on the images of the eye.

[0027] The eyelids or eyelashes may naturally cover parts of the iris or the pupil. To address occlusion of the iris, we automatically track the position of the eyelids, and ignore the parts of the pupil contour or the iris that are covered. This method is based on the Hough Transform to detect portions of the edges of the eyelids that approximate a small straight line. First, the image is filtered, and lines are enhanced using an edge detection filter. Similar to the method for iris recognition four regions of interest are defined around the pupil, and one line is detected in each region that corresponds with the edge segment of the eyelid. Next, the curvature of the eyelid is outlined by fitting two parabolas (one for the lower lid and one for the upper lid) to the edge segments (FIGS. 3 and 4). We consider the area between the two parabolas as the visible part of the eye and mask or ignore anything falling outside of it.

[0028] In FIG. 4, the vOCR value is measured as the torsional eye position (red(right eye) / blue(left eye) crosses) by tracking the iris pattern and comparing it to a reference frame in the upright position. The eyelid tracking is shown as orange (light) lines.Head tracking

[0029] The IMU sensor provides a reading of the orientation of the head sensor relative to gravity. A rotation matrix is applied to correct for any difference in the physical orientation of the IMU sensor and the head attachment frame. With this method, we can obtain the orientation of the head relative to gravity by measuring Euler angles via standard trigonometry.

[0030] FIG. 5 shows an example of a user interface showing online tracking of OCR (ocular torsion) shown as the red and blue traces for both eyes as well as the head tilt angles in roll and pitch planes (top right) according to an embodiment of the current invention.Method Overview

[0031] As a clinical test, vOCR measurement can be done with a tilt maneuver during which the head and trunk are tilted en bloc while the subject is sitting upright (FIG. 6). When the head and trunk are tilted together, the static OCR is primarily driven by the otolith inputs, whereas if the head is tilted on the trunk, a change of inputs from the neck proprioceptors in addition to the vestibular inputs may contribute to the static OCR response. A 30° lateral tilt is large enough to produce a measurable OCR, and yet within the comfortable range of positions to maintain during the tilt maneuver. The degree of tilt is measured by an IMU sensor mounted on the VOG goggles and the operator received numerical feedback on the head roll and pitch angles in real time so that a roll angle of 30° and a pitch angle of zero degree could be maintained during the tilt maneuver. Subjects sit upright on a chair, fixing on a small visual target 135 cm away at eye level. In addition to the fixation target straight ahead, the lateral targets are used so that the straight-ahead fixation could be maintained by instructing the subjects to fix on the lateral target during the tilt. All three targets are in line with the lateral targets placed at equal distances from the central target. The distance between the lateral and central targets calculated as the difference between the sitting surface (subject’s hip level) to the lateral canthus of the eyes divided by two (i.e., multiply by the sine of 30°), hence taking into account the height of the trunk for maintaining straight ahead fixation during the tilt. The torsional position of both eyes and the position of the head are recorded simultaneously using the VOG goggles. The recording of ocular torsion and head position starts with the head and trunk in the upright position for 30 seconds, followed by three right and left lateral tilts, each lasting 30 seconds, separated by 30-second periods with the body back in the upright position.

[0032] FIG. 6 illustrates that the tilt maneuver during the vOCR test is a passive en bloc tilt of the head and trunk while the subject is sitting on a chair. Subjects sit upright on a chair, fixing on a small visual target at eye level (e.g., 135 cm). Since the line of sight will change during a lateral en bloc tilt of head and trunk, two additional targets are used on each side so that the straight-ahead fixation could be maintained by instructing the subjects to fix on the lateral target during the tilt on the same side. The distance between the lateral and central targets calculated as the difference between the sitting surface (subject’s hip level) to the lateral canthus of the eyes multiply by the sine of tilt angle (e.g., 30°), hence taking into account the height of the trunk for maintaining straight ahead fixation during the tilt. vOCR measurement

[0033] All aspects of data analysis for vOCR measurement can be done by a custom software. The vOCR value is measured as the difference between the average ocular torsion of both eyes during the static tilt and the preceding reference value in the upright position (FIG. 7). These ocular torsion values are selected along with their corresponding head tilt data within the custom analysis software to calculate the vOCR value. Because the static tilt is maintained manually and there could be a few degrees of difference in the actual tilt position versus the desired tilt position during the test, the vOCR value can be corrected based on the actual amount of static tilt. Accordingly, for a desired head position of 30°, the corrected vOCR = (measured vOCR *30 ) / (measured static roll tilt angle).

[0034] FIG. 7 shows an example of vOCR measurement (blue) with right and left head tilts (red) showing a lower value on the left side. The average values for three trials in each head tilt direction are presented in the bar graph (error bars represent standard error of mean).

[0035] References1. Curthoys IS, Manzari L. Otolithic disease: clinical features and the role of vestibular evoked myogenic po-tentials. Semin Neurol. 2013;33:231-237.2. Kim H-A, Hong J-H, Lee H, et al. Otolith dysfunction in vestibular neuritis: recovery pattern and a predictor of symptom recovery. Neurology. 2008;70:449-453.3. Curthoys IS. A critical review of the neurophysiological evidence underlying clinical vestibular testing using sound, vibration and galvanic stimuli. Clin Neurophysiol. 2010;121 : 132-144.4. Halmagyi GM, Curthoys IS, Brandt T, Dieterich M. Ocular tilt reaction: clinical sign of vestibular lesion. Ac-ta Otolaryngol Suppl. 1991;481 :47-50.5. Collewijn H, Van der Steen J, Ferman L, Jansen TC. Human ocular counterroll: assessment of static and dynamic properties from electromagnetic scleral coil recordings. Exp Brain Res. 1985;59: 185-196.6. Otero-Millan J, Kheradmand A. Upright Perception and Ocular Torsion Change Independently during Head Tilt. Front Hum Neurosci [online serial], 2016; 10. Accessed at: https: / / www.ncbi.nlm.nih.gov / pmc / articles / PMC5112230 / . Accessed December 26, 2019.7. Otero-Millan J, Roberts DC, Lasker A, Zee DS, Kheradmand A. Knowing what the brain is seeing in three dimensions: A novel, noninvasive, sensitive, accurate, and low-noise technique for measuring ocular tor-sion. J Vis [online serial], 2015; 15. Accessed at: https: / / www.ncbi.nlm.nih.gov / pmc / articles / PMC4633118 / . Accessed December 26, 2019.8. Markham CH, Diamond SG. Ocular counterrolling in response to static and dynamic tilting: implications for human otolith function. J Vestib Res. 2002;12: 127-134.9. Schmid-Priscoveanu A, Straumann D, Kori AA. Torsional vestibulo-ocular reflex during whole-body oscilla-tion in the upright and the supine position. Exp Brain Res. 2000;134:212-219.10. Diamond SG, Markham CH. Ocular counterrolling as an indicator of vestibular otolith function. Neurology. 1983;33: 1460-1469.11. Uchino Y, Kushiro K. Differences between otolith- and semicircular canal- activated neural circuitry in the vestibular system. Neurosci Res. 2011 ;71 :315-327.12. Pansell T, Ygge J, Schworm HD. Conjugacy of torsional eye movements in response to a head tilt para-digm. Invest Ophthalmol Vis Sci. 2003;44:2557-2564.13. Uchino Y, Kushiro K. Differences between otolith- and semicircular canal- activated neural circuitry in the vestibular system. Neurosci Res. 2011 ;71 :315-327.14. Otero-Millan J, Trevino C, Winnick A, Zee DS, Carey JP, Kheradmand A. The video ocular counter-roll (vOCR): a clinical test to detect loss of otolith-ocular function. Acta Otolaryngol. 2017;137:593-597.15. Sadeghpour S, Fornasari F, Otero-Millan J, Carey JP, Zee DS, Kheradmand A. Evaluation of the Video Ocular Counter-Roll (vOCR) as a New Clinical Test of Otolith Function in Peripheral Vestibulopathy. JAMA Otolaryngology-Head & Neck Surgery [online serial]. Epub 2021 Mar 25. Accessed at: https: / / doi.org / 10.1001 / jamaoto.2021.0176. Accessed April 29, 2021.16. Yang Y, Tian J, Otero-Millan J, Kheradmand A. Video ocular counter roll: A bedside test of otolith-ocular function. Annals of Clinical and Translational Neurology [online serial], n / a. Accessed at: https: / / onlinelibrary.wiley.com / doi / abs / 10.1002 / acn3.51921. Accessed October 16, 2023.17. Otero-Millan J, Roberts DC, Lasker A, Zee DS, Kheradmand A. Knowing what the brain is seeing in three dimensions: A novel, noninvasive, sensitive, accurate, and low-noise technique for measuring ocular tor- si on. J Vis. 2015; 15: 11.

[0036] While various embodiments of the present invention have been described above, they have been presented by way of example only, and not limitation. Thus, the breadth and scope of the present invention should not be limited by any of the above-described illustrative embodiments but should instead be defined only in accordance with the following claims and their equivalents.

[0037] The embodiments illustrated and discussed in this specification are intended only to teach those skilled in the art how to make and use the invention. In describing embodiments of the disclosure, specific terminology is employed for the sake of clarity. However, the disclosure is not intended to be limited to the specific terminology so selected. The above-described embodiments of the disclosure may be modified or varied, without departing from the invention, as appreciated by those skilled in the art considering the above insights. It is therefore to beunderstood that, within the scope of the claims and their equivalents, the invention may be practiced otherwise than as specifically described. For example, it is to be understood that the present disclosure contemplates that, to the extent possible, one or more features of any embodiment can be combined with one or more features of any other embodiment.

Claims

WE CLAIM:

1. An ocular counter-roll (OCR) measurement and evaluation system, comprising: a head attachment frame; a head orientation sensing device attached to said head attachment frame; an eye-torsion sensing device attached to said head attachment frame, said eye-torsion sensing device being configured to communicate with said head orientation sensing device; a data processor configured to communicate with said head orientation sensing device and said eye-torsion sensing device while a subject performs test evaluation; and a display device configured to communicate with said data processor to display information received therefrom in real time while said subject performs said test evaluation.

2. The OCR measurement and evaluation system according to claim 1, wherein said eyetorsion sensing device comprises a first light source and a first imaging optical detector arranged to illuminate and detect images of a first eye of said subject, and wherein said eye-torsion sensing device comprises a second light source and a second imaging optical detector arranged to illuminate and detect images of a second eye of said subject.

3. The OCR measurement and evaluation system according to claim 2, wherein said first light source and said second light source are both infrared light sources.

4. The OCR measurement and evaluation system according to any one of claims 1-3, wherein said head orientation sensing device comprises a six-degree of freedom sensor that senses three orthogonal rotational accelerations and three orthogonal linear accelerations.

5. The OCR measurement and evaluation system according to any one of claims 1-4, wherein said data processor is configured to detect iris patterns and to determine an amount of rotation for each eye based said iris patterns.

6. The OCR measurement and evaluation system according to claim 2, wherein said data processor is further configured to: determine regions of said images of said first eye corresponding to eyelids of said first eye, determine locations in said images of said first eye corresponding to a pupil of said first eye, determine first-eye iris patterns in said images of said first eye, compare said first-eye iris patterns to first-eye template iris patterns, and determine an amount of rotation of said first-eye iris pattern relative to said template to provide a measure of first-eye ocular torsion.

7. The OCR measurement and evaluation system according to claim 2, wherein said data processor is further configured to: determine regions of said images of said second eye corresponding to eyelids of said second eye,determine locations in said images of said second eye corresponding to a pupil of said second eye, determine second-eye iris patterns in said images of said second eye, compare said second-eye iris patterns to second-eye template iris patterns, and determine an amount of rotation of said second-eye iris pattern relative to said template to provide a measure of second-eye ocular torsion.

8. The OCR measurement and evaluation system according to any one of claims 1-7, wherein said data processor is further configured to calculate vOCR values.

9. The OCR measurement and evaluation system according to claim 2, wherein said data processor is further configured for measuring ocular torsion, comprising: capturing an image from a camera of an eye; processing said image to determine regions of said image corresponding to eyelids; processing said image to determine a location corresponding to a pupil of said eye; determining an iris pattern of said eye in said image; comparing said iris pattern to a template iris pattern; and determining an amount of rotation of said iris pattern relative to said template to provide a measure of ocular torsion.

10. The OCR measurement and evaluation system according to claim 9, further comprising polar transforming said iris pattern prior to comparing to said template.

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