In the field of neuropsychology there have been numerous tests primarily designed to detect reaction time of individuals to certain stimuli. These tests have been used to detect brain damage in terms of motor skills and cognitive ability, by measuring an individual's reaction time when having to make a decision.
The questions on which the decision is to be made are oftentimes formulated in terms of displaying certain indicia to which the individual is asked to react. Thus, for instance, an individual may be presented with a red sphere or a green sphere and is asked to make a decision based on whether he perceives this sphere to be red or green. These and related reaction time tests are relatively straightforward and are limited in what they measure. As a result, the tests are given to the patients many times, and then reaction time scores are averaged together, in order to arrive at a single score, or some other metric is applied to compress the scores into a single number.
As mentioned above, cognitive impairment has been measured using reaction time tests. However, there are only a handful of tests that involve reaction time to test either cognitive performance or impairment, or both. Performance and impairment are at two ends of the spectrum. It is the goal of some of today's reaction time tests to allow one to decide when an impaired state exists, what the impaired state is, and what constitutes a higher state of performance in the cognitive sense.
The problem with reaction time tests is that when the individual is taking a stimulant, or a muscle relaxer of any type, this affects muscle response and therefore reaction time. Moreover, one of the major problems with reaction time tests is the variability of test retest accuracy. In reaction time tests one is measuring events at a rate of 200 to 400 milliseconds. However, the error rate is often at or in excess of +/−100 milliseconds from test to test. In order to eliminate the problem of error rate, these tests are performed repeatedly, with averages taken in order to obtain a response baseline. It will be appreciated that obtaining such a baseline is very difficult, and is especially difficult given a sequence of perhaps hundreds of little tests.
Aside from the ability to recognize and respond quickly to the recognition of objects, a recently highly studied measurement of cognitive involves what is known as the blink test in which the subject performs what is known in the field of neuropsychology as an attentional blink. The attentional blink occurs when a human patient or test subject is asked to make choices about what is presented on-screen. When the individual is presented with a choice to be made that he or she is supposed to log or memorize, a so-called blink indicates that the individual understands that there is a decision to be made and is saving this information in memory. The blink is not necessarily a blink in terms of closing one's eyes but is called an attentional blink because the individual can no longer absorb any information while staring at a screen for a short period after being exposed to the information they are supposed to memorize or react to. The attentional blink phenomenon is an example of an artifact of the brain that involves memory, attention, and reaction, and is heavily studied. Despite the large number of research papers and studies examining the attentional blink, few if any of these have produced fruitful results or insight about cognitive performance. Furthermore, the phenomenon is so short in duration, and methods of determining whether a person has expressed the phenomenon are so high level, that there is very little precision. Thus to date very little information is extracted from this form of cognitive testing. In practice today, attentional blink responses are measured by presenting an individual with a series of letters and numbers and then determining which letter or number the individual cannot remember immediately after a special target symbol is displayed.
Aside from reaction times, cognitive function is also measured utilizing technologies and methods that examine the movement of the eyes in relation to a displayed or projected test. Eye tracking cognitive testing is designed specifically to track the eye while it follows a moving dot. The ability of the eye to track the dot as the dot moves yields a measure of cognitive ability. It has been found that a technique called smooth pursuit eye tracking can be used to diagnose cognitive function by measuring small variations in the smooth pursuit data. These variations are quite small and it is only with much calibration and the blocking out of environmental effects that one can see these variations at all. How to reliably measure these small variations is the problem to be solved.
By way of further background, the type of dot moved in neuropsychological testing involves moving dots on a screen in a linear fashion followed by tracking the gaze direction of the eyes. Thus, these dots were moved in an X direction and a Y direction. When the dot was moved from one extreme to the other, the eye begins to flicker because the eye loses track of the dot. A flicker at the extremes of the eye's motion, indicates a loss of tracking the dot, and thus some cognitive limit or change in function, possibly impairment. Although all humans, including non-impaired patients, tend to exhibit some degree of jitter or flicker at the extremities of looking to the left or right, or up or down, the nature of the jitter is thought to express some underlying characteristic of cognitive performance.
Regardless of the type of flicker test, it was thought that predictable brain trauma could be ascertained by eye tracking involving horizontal x axis movement versus y axis movement of a dot. These x, y dot movement tests could be predictive of not only brain trauma, but also some other type of trauma other than traumatic brain injury, or TBI.
The major problem with the translation of a dot either in the x direction or in the y direction is that when one seeks to detect eye motion responsive to following a moving dot, one in fact detects eye movement at the fringes, i.e. at the extreme positions of the eye. Detecting data from the fringes is unreliable because both the data and flickering eye are erratic. Thus, it is necessary to cancel out the effects at the fringes in order to get a continuous sequence of data in the middle that is useful in determining cognitive ability. If one can obtain a continuous sequence of data this permits detection of variations in eye tracking ability using more advanced and yet more reliable mathematical constructs, such as variability, aggregatation, and standard deviation to name a few. If the dot movement is detected not at extremes but between them, this is referred to as smooth eye tracking.
Thus, what is required for sensitive measurement of cognitive ability is continuous sequences of data from smooth eye pursuit in order to sensitively detect cognitive ability due to variations in the ability of the eye to track. To detect cognitive impairment one looks at the variability with which the eyes track an onscreen object. It is only by taking the smooth transition of the eye as it tracks the object that one is able to obtain predictable smooth movement variations.
Once one is able to detect the predictable smooth movement increments, one can measure cognitive impairment based on the measurement of the continuous sequence of data in terms of variability of the eye to track the on-screen image. It is the variability of the smooth eye pursuit that is indicative of cognitive function. How to obtain these variability increments so as to detect minute variabilities is a problem with current techniques, and requires time consuming calibration as will be discussed.
As to measurements of variability there are a number of techniques, for instance measuring the amount by which the eye is ahead of the moving dot, behind a moving dot, or on top of the moving dot. These measurements ascertain the amount ahead, behind or on top throughout the entire test and more importantly the variability of the movement.
As described above, these types of tests are one called smooth pursuit tests and the area of interest is called smooth pursuit eye tracking. The purpose of this type of testing is to provide consistent data in a sequential data set from the start of the test until the end of the test in which the data points considered are not interrupted by the edge effect of the eye going back and forth, and thereby introducing jitter or flickering movements of the eye sometimes referred in the art as saccading, which are both difficult to analyze mathematically, and difficult to replicate with precision from one test to another.
Moreover, a further caveat to any eye tracking test is that the tests is affected by actual eye blinking. It will be appreciated that with one or two eyes blinks, data is dropped during the duration of the blink, and often for some period slightly before and after the blink, as the eyelid obscures the portion of the eye that is being measured by the smooth pursuit eye tracking technology. In order to accommodate blinking when eye blinking is detected, the data is ignored during any analytical stage.
The above describes a dot that moves in a straight line from one end to the other and then reverses itself. It has been found that by moving the dot that the eye is focusing on in a circle, one does not have to artificially carve off the effects of the edges as the eye abruptly changes direction at the end of a linear sweep. As a result, circular movement is a more natural way of aggregating data to variability algorithms.
In order to measure the smooth eye pursuit, various eye tracking methodologies have been used. Researchers have been tempted to use virtual reality head mounted displays because of their availability but the results are not satisfactory. While a number of virtual reality head mounted displays exist, no virtual reality headsets are used for eye tracking primarily because they provide binocular 3D virtual reality viewing that requires calibration of the binocular channels. It also has to take into account intraocular distance so as to calibrate one eye with the other when 3D virtual reality headsets having two separate screens are used, which makes sensitive measurements virtually impossible.
As will be appreciated, these virtual reality headsets provide an individual with a set of screens in front of his eyes that are viewed in binocular fashion. To the extent that virtual reality headsets have been used for neuropsychological testing, these screens are utilized not for eye tracking but rather to present images to the individual and the individual is provided with clickers to measure reaction time. The reason that these head mounted displays are utilized for reaction time testing is that they provide a controlled environment that cancels outside noise and distractions when administering a test. Thus the utilization of virtual reality head mounted displays provide a controlled way of administrating reaction time tests, but to date they have not been utilized for eye tracking.
One of the reasons that they have not been adopted for eye tracking is the aforementioned binocular affect, which must be compensated for if one is utilizing the two screens to present an image to be tracked. Using the two screens requires a large amount of calibration because each of the eyes is focused on a different screen, measurements must be calibrated for interocular distance, and the present virtual reality headsets do not have a wide enough field of view for certain types of neuropsychological tests, such as circular smooth pursuit. Thus, virtual reality systems are not in general applicable to eye tracking.
As a result eye tracking usually involves a desktop-mounted system. This can involve the use of an infrared light source arranged on the desktop or nearby surface; or some sort of an optical infrared camera as used that sits on the desk and looks back up at the eyes as the individual's eyes track an image. Aside from calibration, head movement during the test and the effect of outside stimuli and environmentally induced artifacts affect test results.
Another classic system is one in which a tracking device is mounted directly on the eye itself and the eye looks through a translucent piece of semi transparent material. Infrared light is then directed towards the eye, with reflections captured on a camera that looks through the transparent material at the pupil. In this type of system there is no screen associated with the eye tracker. Instead, the screen is placed externally for instance on a monitor on a desk that a subject must look at.
A third type of system places dots on a screen and monitors eye movement of an individual viewing the screen. However, head movement is a very large problem. It is a false assumption that those taking the test can keep their heads still. This is especially true with individuals with cognitive impairment who are often times trying to move their head around. As the individual moves his head around and the individual is staring at a screen, if they move their head to the right the eye tracker data drifts because it does not account for head location. Thus, the eye tracker cannot track where the individual is looking because the individual's eyes can still follow the test dot over the screen even though the head is moving. Therefore, one of the major problems is that one has to fix the location of the screen with respect to the head or one has to exactly track the position of the head in real time.
The fourth category for eye tracking involves fixing the head to a mount and placing dots, stickers, or similar types of markers on the face, head, or body to decide where the head is looking. These systems then place an eye tracker close to the eye and ask a patient to look at a screen. Systems like this are used when head direction and eye detection must be determined in environments that might be inaccessible to traditional mechanical solutions. For example, this technology is currently used inside CAT scan machines, fMRI machines, EEG machines and MEG machines. In order to measure brain damage these systems use functional magnetic resonance imaging, or fMRI, that looks inside the brain to see the activity of the brain and what parts of the brain are illuminating responsive to the test stimuli. As an fMRI test is performed, the technician is asking the patient to track on certain images, all of which leads to a fairly complicated system for pinpointing the reaction of the brain to the eye tracking of an on-screen image. A further problem in EEG imaging is the ability to accommodate blinking. When a patient blinks he creates a massive electrical disturbance inside the brain that oftentimes overruns the EEG imaging machine so that all of a sudden the signal data that is being accumulated does not effectively track what one is thinking because what one is thinking is completely perturbed by the blink. This introduces an artifact which disrupts the entire signal obtained during eye tracking. Therefore, one of the problems involved with these types of eye movement detection systems is the requirement to fix the screen with respect to the eye and to provide a controlled environment.
In order to do this, those involved in the industry attempt to detect head direction by placing beacons on the head, which in one embodiment involves a cap of dots or set of dots that are detectable. Alternatively, infrared reflectors are placed on the head with their location detected by infrared cameras. These head position detectors are then utilized to cancel out the affect of drift as one's head is looking left and right or up and down toward the screen. More recently, the advancement of infrared based 3D positioning technologies has led some to hypothesize the feasibility of using infrared and/or other optical technologies to detect the surface of the head, and thereby induce the direction the head is pointing. Today, the precision of these head direction detection technologies is insufficient to provide the precision required by cognitive testing via analysis of the position of the eyes. In practice, the errors introduced in detecting the head's x, y, z position and direction overwhelm and greatly exceed the eye-based and optical measurement precision, so they typically do more harm than good. The problem with all of these systems is that they do not work because the error in detecting which way the head is facing ends up vastly overwhelming the measurement of the eyes. Thus if one is attempting to measure smooth pursuit eye motion variability, this small variability is lost.