Source: http://www.google.com/patents/US6116736?dq=6778979
Timestamp: 2014-07-29 01:58:11
Document Index: 458278048

Matched Legal Cases: ['art 1', 'art 2', 'art 3', 'art 1', 'art 2', 'art 3']

Patent US6116736 - Pupilometer with pupil irregularity detection capability - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign in<nobr>Advanced Patent Search</nobr>PatentsA pupilometer having a pupil irregularity or non-uniformity detection capability. The pupilometer may comprise an imaging sensor for generating signals representative of a pupil of an eye, a data processor; and a program executable by the data processor for enabling the data processor to process signals...http://www.google.com/patents/US6116736?utm_source=gb-gplus-sharePatent US6116736 - Pupilometer with pupil irregularity detection capabilityAdvanced Patent SearchPublication numberUS6116736 APublication typeGrantApplication numberUS 09/298,670Publication dateSep 12, 2000Filing dateApr 23, 1999Priority dateApr 23, 1999Fee statusPaidAlso published asCA2368232A1, CA2368232C, EP1173089A1, EP1173089A4, US6260968, WO2000064330A1Publication number09298670, 298670, US 6116736 A, US 6116736A, US-A-6116736, US6116736 A, US6116736AInventorsLawrence W. Stark, Claudio M. Privitera, Kamran Siminou, Jeffrey OliverOriginal AssigneeNeuroptics, Inc.Export CitationBiBTeX, EndNote, RefManPatent Citations (26), Non-Patent Citations (49), Referenced by (44), Classifications (5), Legal Events (6) External Links: USPTO, USPTO Assignment, EspacenetPupilometer with pupil irregularity detection capabilityUS 6116736 AAbstract A pupilometer having a pupil irregularity or non-uniformity detection capability. The pupilometer may comprise an imaging sensor for generating signals representative of a pupil of an eye, a data processor; and a program executable by the data processor for enabling the data processor to process signals received from the imaging sensor and to thereby identify one or more regions of non-uniformity within an image of a perimeter of the pupil. The pupilometer may incorporate several innovative calibration and thresholding routines and may provide the basis for an innovative medical diagnostics system, when coupled to a network containing a suitable medical database and data processing hardware.
What is claimed is: 1. A pupilometer comprising:a CMOS sensor for generating image data representative of a pupil of a patient; and deformation detection means coupled to said CMOS sensor for identifying one or more selected regions within an image of a perimeter of said pupil that exhibit a predetermined amount of regional distortion. 2. A pupilometer comprising:a microprocessor; a memory coupled to said microprocessor; an imaging device coupled to said microprocessor; a visible light source coupled to said microprocessor; an IR light source coupled to said microprocessor; and a display coupled to said microprocessor; said memory having stored therein a program for enabling said microprocessor to cause a plurality of visible light stimulus pulses to be generated by said visible light source, to cause said IR light source to generate IR light for illuminating a pupil, to enable said imaging device to acquire a plurality of images of said illuminated pupil, to process data sets representative of said images of said illuminated pupil to obtain information descriptive of a response of said pupil to said visible light stimulus pulses, and to cause said information to be depicted on said display; said information descriptive of a response of said pupil to said visible light stimulus pulses comprising information indicative of a degree of non-uniform deformation of a selected segment of a perimeter of said pupil. 3. A handheld pupilometer comprising:a housing having a display, microprocessor, memory, imaging device, visible light source and IR light source mounted therein; said microprocessor being electronically coupled to said display, said memory, said imaging device, said visible light source and said IR light source; and said memory having stored therein a program for enabling said microprocessor to cause at least one visible light stimulus pulse to be generated by said visible light source, to cause said IR light source to generate IR light for illuminating a pupil, to enable said imaging device to acquire a plurality of images of said illuminated pupil, and to process a plurality of data sets representative of said plurality of images of said illuminated pupil to obtain information descriptive of a response of said pupil to said at least one visible light stimulus pulse, and to cause said information to be depicted on said display; said information descriptive of a response of said pupil to said at least one visible light stimulus pulse comprising information indicative of a degree of deformation of a selected segment of a perimeter of said pupil. 4. The handheld pupilometer of claim 3, wherein said information descriptive of a response of said pupil to said at least one visible light stimulus pulse comprises information descriptive of a dynamic response of said selected segment of said perimeter of said pupil.
5. The pupilometer of claim 3, wherein said imaging device comprises a CMOS N�M sensor.
6. The pupilometer of claim 3, wherein said imaging device comprises a CCD camera.
7. The pupilometer of claim 3 further comprising means coupled to said microprocessor for downloading to a remote storage device said information descriptive of a response of said pupil to said at least one visible light stimulus pulse.
8. The pupilometer of claim 7 wherein said means for downloading comprises at least one of either an IR transmitter circuit or a RF transmitter circuit.
9. The pupilometer of claim 7 wherein said means for downloading comprises at least one of either a data port or a modem for coupling said pupilometer to a computer.
10. The pupilometer of claim 9, wherein said means for acquiring image data comprises a source of infrared light, a source of visible light and an imaging device under microprocessor control.
11. The pupilometer of claim 10, wherein said imaging device is selected from a group consisting of a CCD camera and a N�M CMOS imaging sensor.
12. A handheld pupilometer comprising:a housing having mounted therein means for acquiring image data representative of ocular tissue, means for processing said image data, and means for displaying information derived from said image data, said means for processing said image data comprising a microprocessor and programming for determining a pixel brightness threshold value, programming for locating a pupil within a plurality of image data sets using said pixel brightness threshold value, and programming for identifying one or more regions around a perimeter of said pupil that exhibit a non-uniform change in shape when said pupil is exposed to illumination of a predetermined type. 13. The pupilometer of claim 10, wherein said means for acquiring image data comprises a source of infrared light, a source of visible light and an imaging device under micrprocessor control.
14. The pupilometer of claim 12, wherein said illumination comprises exposure to ambient light.
15. A method for correlating pupilary responses with pathological indications, said method comprising the steps of:storing within a database data representative of a plurality of pupilary response characteristics associated with one or more pathological indications; using a pupilometer obtaining pupilary response data from a patient, said pupilary response data being representative of one or more pupilary response characteristics of said patient; and comparing within a data analysis system said pupilary response data obtained from said patient with said data representative of a plurality of pupilary response characteristics to identify one or more pathological conditions of said patient. 16. A method for correlating pupilary measurements with pathological indications, said method comprising the steps of:storing within a database data representative of a plurality of pupilary configurations and associated pathological conditions; using a pupilometer obtaining pupilary configuration data from a patient; and comparing within a data analysis system said pupilary configuration data obtained from said patient with said data representative of said plurality of pupilary configurations to identify one or more pathological conditions of said patient. 17. The method of claim 16, wherein said pupilary configuration data comprises data descriptive of a pupilary response to at least one visible light stimulus pulse.
18. The method of claim 16, wherein said pupilary configuration data comprises data descriptive of a pupilary change in shape responsive to at least one light stimulus pulse.
19. The method of claim 16, wherein said pupilary configuration data comprises data descriptive of a pupilary response to ambient light exposure.
20. A method for correlating pupilary responses with pathological indications, said method comprising the steps of:storing within a database data representative of a plurality of pupilary sectional configurations and associated pathological conditions; using a pupilometer obtaining pupilary configuration data from a patient, said pupilary configuration data including data indicative of selected regional non-uniformities of a pupil of said patient if said patient's pupil exhibits such regional non-uniformities; and comparing within a data analysis system said pupilary configuration data obtained from said patient with said data representative of said plurality of pupilary sectional configurations to identify one or more pathological conditions of said patient. 21. A method for correlating pupilary responses with a scalar value indicative of a state of health of an individual or physiological system of said individual, said method comprising the steps of:storing within a database data representative of a plurality of pupilary response characteristics associated with one or more pathological indications; using a pupilometer obtaining pupilary response data from a patient, said pupilary response data being representative of one or more pupilary response characteristics of said patient; and comparing within a data analysis system said pupilary response data obtained from said patient with said data representative of said plurality of pupilary response characteristics to derive said scalar value. 22. A system for use in diagnosing pathological conditions, said system comprising:a pupilometer for obtaining data descriptive of one or more pupilary characteristics from a patient; a database for storing data descriptive of a plurality of pupilary characteristics and associated physical conditions; and a central processing unit coupled to said digital pupilometer and said database for comparing said data obtained by said pupilometer to said data stored within said database such that a pathological condition of said patient may be diagnosed based upon said comparison. 23. The system of claim 22 further comprising a processing subroutine for generating a scalar indicator based upon a result of said step of comparing said data stored within said pupilometer to said data stored within said database.
24. The system of claim 22 further comprising a display coupled to said central processing unit for displaying images of said patient's pupil and for providing an indication of whether or not said pupilary characteristics of said patient correspond to any of said pupilary characteristics represented by said data stored within said database.
25. A method for locating a pupil within an image of ocular tissue, said method comprising the steps of:establishing a pixel brightness threshold value for discriminating between light and dark gray scale data comprising said image, and comparing gray scale image data at a plurality of pixel locations within said image of ocular tissue to said pixel brightness threshold value to identify a region within said image of ocular tissue that represents said pupil, wherein said step of establishing a pixel brightness threshold value comprises the steps of selecting a pixel brightness threshold value, constructing vertical and horizontal histogram data sets from said image of ocular tissue, wherein each histogram data set comprises a plot of sums of pixel locations having a value exceeding said threshold value along respective rows or columns of pixels comprising said image, determining whether curves mapped from said vertical and horizontal histogram data sets comprise at least one maximum value bordered by a pair of null values, and repeating said selecting, constructing and determining steps until a pixel brightness threshold value is identified that satisfies said determining step. 26. The method of claim 25, wherein said step of selecting a pixel brightness threshold value comprises the steps of selecting a maximum pixel brightness threshold value and decreasing said pixel brightness threshold value in increments from said maximum pixel brightness threshold value upon each repetition of said selecting step.
27. The method of claim 25, wherein said step of selecting a pixel brightness threshold value comprises the steps of selecting a minimum pixel brightness threshold value and increasing said pixel brightness threshold value in increments from said minimum pixel brightness threshold value upon each repetition of said selecting step.
28. The method of claim 27, wherein said assigning step comprises the step of deriving a pixel brightness threshold value comprising the sum of the relative minimum pixel brightness threshold value and 2/3 times the difference between the relative maximum and relative minimum pixel brightness threshold values.
29. The method of claim 25, wherein said step of selecting a pixel brightness threshold value comprises the steps ofselecting a maximum pixel brightness threshold value and decreasing said pixel brightness threshold value in increments from said maximum pixel brightness threshold value until a first predetermined histogram plot is achieved and a relative maximum pixel brightness threshold value is identified, selecting a minimum pixel brightness threshold value and increasing said pixel brightness threshold value in increments from said minimum pixel brightness threshold value until a second predetermined histogram plot is achieved and a relative minimum pixel brightness threshold value is identified, and assigning said pixel brightness threshold value a level between said relative maximum pixel brightness threshold value and said relative minimum pixel brightness threshold value. 30. A method of processing data representative of an image of ocular tissue, said method comprising the steps of:generating digital image data representative of said image of said ocular tissue; processing said digital image data representative of said image of said ocular tissue to locate one or more landmarks within said image of said ocular tissue; using said one or more landmarks determine whether a right eye or left eye of a patient is being monitored. 31. A method of calibrating a pupilometer comprising the steps of:acquiring at least one data set representative of an image of an eye including a pupil and an iris, deriving from said at least one data set information descriptive of a shape of an outer perimeter region of said iris, deriving from said at least one data set information descriptive of a shape of a perimeter region of said pupil, and comparing said information descriptive of said shape of said outer perimeter region of said iris to said information descriptive of said perimeter region of said pupil to normalize and establish a frame of reference for said information descriptive of said shape of said pupil. 32. A method for calibrating a pupilometer comprising the steps of:acquiring at least one data set representative of an image of an eye including a pupil and an iris, deriving from said at least one data set an indication of a diameter of an outer perimeter of said iris, comparing said indication of said diameter of said outer perimeter of said iris to an assumed diameter of said iris, and utilizing a difference between said indication of said diameter of said outer perimeter of said iris and said assumed diameter to calibrate said pupilometer. 33. The method of claim 32, wherein said assumed diameter of said iris is a horizontal diameter and is approximately 11.75 mm.
34. A method for calibrating a pupilometer comprising the steps of:illuminating a portion of an eye including an iris and a pupil with low intensity blue light, using an imaging sensor, obtaining data descriptive of an image of said portion of said eye illuminated by said low intensity blue light, analyzing said data to identify an outer perimeter of said iris of said eye within said image, and using said identified outer perimeter of said iris of said eye to calibrate said pupilometer. 35. A method for acquiring pupilometry data, said method comprising the steps of:exposing an eye of a patient to blue light pulses and IR pulses in a predetermined sequence, obtaining data descriptive of a shape of an iris of said eye when said eye is exposed to said blue light pulses, and obtaining data descriptive of a shape of a pupil of said eye when said eye is exposed to said IR pulses. 36. The method of claim 35, wherein said light pulses and IR pulses, and said respective data obtaining steps, are multiplexed.
37. A method of calibrating a pupilometer, said method comprising the steps of:exposing an eye to a plurality of light stimulus pulses, using said pupilometer obtaining a plurality of image data sets representative of respective pupilary responses of said eye to said light stimulus pulses, using said plurality of obtained image data sets deriving response curves representative of said respective pupilary responses, and using said response curves to evaluate a degree of adaptation of said eye to said stimulus pulses. 38. The method of claim 37 further comprising the step of using an estimate of said degree of accommodation of said eye to said stimulus pulses to normalize one or more image data sets representing a pupilary response to a selected stimulus pulse.
39. A pupilometry system comprising:a display, microprocessor, memory, imaging device, first and second visible light sources and an IR light source; said microprocessor being electronically coupled to said display, said memory, said imaging device, said visible light sources and said IR light source; and said memory having stored therein a program including stimulus control code for enabling said microprocessor to cause said first visible light source to generate a first visible light stimulus pulse for illuminating a first eye, to cause said second visible light source to generate a second visible light stimulus pulse for illuminating a second eye at a predetermined time following termination of said first visible light stimulus pulse, and to cause said first visible light source to generate a third visible light stimulus pulse for illuminating said first eye at a predetermined time following termination of said second visual light stimulus pulse; including illumination control code for enabling said microprocessor to cause said IR light source to generate IR light for illuminating a pupil of said first eye during a duration of said first, second and third visible light stimulus pulses; including image acquisition code for enabling said microprocessor to cause said imaging device to acquire a plurality of images of said IR illuminated pupil; including image analysis code for enabling said microprocessor to process data sets representative of said images of said IR illuminated pupil to obtain information descriptive of a response of said pupil to said visible light illumination of said first eye and said second eye; and display code for enabling said microprocessor to cause said information to be depicted on said display. 40. The pupilometer of claim 39 further comprising an armature that extends from a main body of said pupilometer for supporting said second visible light source.
41. The pupilometer of claim 40, wherein said armature detachably engages said main body of said pupilometer.
FIELD OF THE INVENTION The present invention relates generally to pupilometry systems and, more particularly, to pupilometry systems having a pupil irregularity detection capability. In one particularly innovative aspect, the present invention relates to hand-held pupilometry systems having a pupil irregularity detection capability, to methods and processing sequences used within such systems, and to methods of using such systems.
BACKGROUND OF THE INVENTION Systems for monitoring pupil size and pupil responsiveness characteristics are well known in the art and are generally referred to as pupilometry systems or, simply, pupilometers. One early pupilometer is described in U.S. Pat. No. 3,533,683, which issued to Stark et al. on Oct. 13, 1970 and is entitled "Dynamic Pupilometers Using Television Camera System." The Stark et al. system employed a television camera system, a digital computer system, an infrared light source, and a visual light stimulator for determining the instantaneous size of a pupil as an eye (or neurologic pupilary control system) of a patient was exposed to various stimuli. Like the early Stark et al. system, conventional pupilometers measure, for example, the diameter of a pupil before and after the pupil is exposed to a light stimulus pulse and also measure the rates at which the pupil may constrict and dilate in response to the initiation and termination of the light stimulus pulse. Pupilometers may comprise hand-held units or, alternatively, may comprise desk or table-mounted, stand-alone units. Pupilometers also generally include some mechanism for ensuring that an imager within the pupilometer is properly positioned in relation to a pupil to be imaged. For example, U.S. Pat. No. 5,646,709, issued to Elbert P. Carter, describes an electronic centering system for ensuring that a pupilometer is properly positioned in relation to a pupil to be imaged. Similarly, U.S. Pat. No. 5,187,506, issued to Elbert P. Carter, describes an eye orbit housing for ensuring proper positioning between a pupilometer and an eye of a subject prior to the initiation of a pupilary scanning procedure.
Similarly, those skilled in the art will appreciate that a need exists for pupilometers that are capable of evaluating more than a mere pupilary response to light stimulus pulses. For example, it is believed that a substantial need exists for a pupilometer that is capable not only of measuring changes in pupilary diameter in response one or more light stimulus pulses, but also of evaluating pupil shape and/or segmental responses to a visual stimulus. Stated somewhat differently, it is believed that a substantial need exists for a pupilometer having a pupilary shape irregularity or non-uniformity detection capability.
FIG. 8 is a flow chart illustrating a basic operating protocol for a pupilometer in accordance with the present invention.
DESCRIPTION OF PREFERRED EMBODIMENTS A. Hardware Components of a Pupilometer in Accordance with the Present Invention
Thus, as shown in FIGS. 1 and 3, the beam splitter 18 functions to direct blue and/or IR light generated by the blue and IR LEDs 28 and 24, respectively, toward the eye 38 of a patient and to provide a return path to the imaging sensor 14 for blue and/or IR light that is reflected from the eye 38 ofthe patient.
Turning now to FIGS. 5-7, a pupilometer 10 in accordance with the present invention is a microprocessor based system and, therefore, preferably includes several software components or modules for controlling its operation. As is well know in the art, an operating system provides fundamental machine level interfaces between the hardware elements comprising the pupilometer 10. More specifically, various device drivers are used to provide an interface between the microprocessor (not shown) and the imaging sensor 14, IR LEDs 24, yellow LEDs 26, blue LED 28, keypad 39 and liquid crystal display 36.
During a typical stimulus/illumination sequence, the LEDs 24, 26 and 28 may be operated as shown in FIG. 6. For example, during a typical measurement sequence, the yellow LEDs 26 may be activated and deactivated for successive 1 second intervals (i.e., "on" for 1 second and "off" for 1 second) for a period of 10 seconds total. Simultaneously, the IR LEDs 24 may be activated for all periods when the yellow LEDs 26 are "off," and may be deactivated, activated and deactivated (i.e., turned "off," "on" and "off") for respective 0.04, 0.92 and 0.04 second intervals, while the yellow LEDs 26 are turned "on." Similarly, the blue LED 28 may be activated, deactivated and activated for respective 0.04, 0.92 and 0.04 second intervals, while the yellow LEDs 26 are turned "on," and may be deactivated during all periods when the yellow LEDs are turned "off." This allows for the operation of the IR LEDs 24 and blue LED 28 to be multiplexed. In such an embodiment, the image frame transfer rate preferably would be set, for example, to 50 frames per second.
3. The CMOS Camera Obiect
The feature extraction object 106 employs a flying spot processing algorithm to identify the center of the pupil, a fitted circumference and/or radius of the pupil and, preferably, 48 radii representing the distance between the center and perimeter of the pupil at 48 separate angles in an R,θ coordinate system, where θ defines an angular orientation about the center of the pupil, and R represents the radius of the pupil at that orientation. The fitted radius of the pupil is determined by selecting a circumference that best fits a contour of the pupil and by solving the equation 2πr to obtain the radius value (r).
Frame=eye image frame generated by the CMOS imaging sensor 14
Threshold=gray level threshold value; any pixel having a gray scale value greater than the threshold value is considered to be part of the pupil.
It is believed that the use of flying spot algorithms are well known in the art and, therefore, that the flying spot algorithm need not be described in detail herein. Nonetheless, the basic flying spot procedure may be described as follows. The flying spot procedure starts with a large circumference centered on the image of an eye and iteratively reduces the size of the circumference. In reducing the size of the circumference and adjusting the center location of the circumference, for each iteration the following momentums will be computed: ##EQU1## where N represents the number of pixels having coordinates x,y in the circumference contour; gray-- level-- sign(x,y) is +1, if the gray level value of the pixel (x,y) is greater than the threshold value; gray-- level-- sign(x,y) is -1, if the gray level value of the pixel (x,y) is less than the threshold value; and x0,y0 are the center coordinates of the circumference.
x0=x0+&#956;x* Gain-- x
y0=y0+&#956;y* Gain-- y
radius=radius+&#956;r* Gain-- r.
Turning now in particular to FIGS. 7(a) and 7(b) the hypothetical maximum and hypothetical minimum threshold values are determined by iteratively altering a hypothetical threshold value until a prescribed histogram profile is achieved. An acceptable profile is illustrated in FIG. 7(a) and is one in which a null-high-null pattern is achieved for both a row histogram (y Hist) and column histogram (x Hist). More specifically, an acceptable profile preferably comprises a single "high" bordered by a pair of "nulls." Unacceptable profiles are illustrated, for example, in FIG. 7(b).
The hypothetical maximum threshold value is determined by selecting an absolute maximum value and iteratively decreasing that value and deriving corresponding histogram data sets until acceptable row and column histogram profiles are achieved. Similarly, the hypothetical minimum threshold value is determined by selecting an absolute minimum value and iteratively increasing that value and deriving corresponding histogram data sets until acceptable row and column histogram profiles are achieved. Once the hypothetical maximum and minimum threshold values are determined, those values are averaged to determine the defined threshold value that will be used by the feature extraction object 106. Those skilled in the art will appreciate that the defined threshold value may correspond to the maximum hypothetical threshold value, the minimum hypothetical threshold value, or any value that is between those values. Thus, in alternative embodiments, the defined threshold value could be determined, for example, based on a weighted average of the maximum and minimum hypothetical threshold values. In such an embodiment, the defined threshold value may comprise a value corresponding to the sum of the minimum hypothetical threshold value and 2/3 of the difference between the maximum and minimum hypothetical threshold values.
A typical image acquisition and analysis procedure may proceed as follows. If the pupilometer 10 has been idle for a predetermined period of time (e.g., 120 seconds), the pupilometer 10 is automatically placed in a battery-conserving sleep mode (step 202). By depressing the "scan" button 45 (shown in FIG. 2), the user causes the pupilometer 10 to enter a "ready" mode (step 200). At this time, the user is prompted to enter an alphanumeric subject or patient identification number via the keypad 39 or to download any necessary patient information from a network computer via an infrared data interface, such as an IrDA interface that is provided on numerous conventional personal computer products (step 204). Once any requisite patient identification data has been entered into the system, the user is prompted via the liquid crystal display 36 or an audio prompt to hold down the "scan" button 45 and to position the pupilometer 10 in front of the eye 38 of a subject (step 210).
When the user depresses the "scan" button 45, the microprocessor (not shown) initiates an imaging test sequence. The yellow LEDs 26 preferably are not activated during the test sequence. During the test sequence the images that are acquired by the imaging sensor 14 may be displayed on the liquid crystal display (LCD) 36. Preferably, the P-program analyzes the image data frames that are acquired during the test sequence, determines whether or not the pupilometer 10 is properly positioned for obtaining measurements, and determines if all necessary parameters are met to ensure high-quality data recovery. If the test criteria are not met, the user is prompted to reposition the pupilometer 10. After any requisite test criteria are met, the P-program will continue to run the test sequence until the "scan" button 45 is released.
Finally, after an initial set of measurement are obtained, the user may be prompted for a decision to measure the pupilary characteristics of the other eye of the subject/patient, or the user may be prompted for a decision to make a consensual response measurement (steps 238, 242). The consensual response measurement may take the form of a "swinging flashlight" measurement discussed more fully below. If a consensual measurement is to be performed, the user may be prompted to couple a consensual measurement attachment (shown in FIG. 9) to the pupilometer and to position a yellow LED 52 mounted on the attachment in front of the appropriate eye of the subject/patient. If the consensual measurement attachment is permanently affixed to the pupilometer 10, the user may only need to deploy and/or properly position the attachment.
One test for analyzing consensual pupilary responses is commonly referred to within the medical community as a "swinging flashlight test." During a typical swinging flashlight test one eye of a subject is monitored, and a visible light stimulus is applied first to the eye of the patient that is being monitored, then to the eye of the patient that is not monitored and, finally, again to the eye that is monitored. If the eyes of the patient are normal, the pupil of the monitored eye should constrict in response to all of the light stimulus pulses (regardless of which eye the stimulus pulse is applied to). Following application of the first light stimulus, the pupil of the monitored eye should begin to dilate, and upon application of the second light stimulus (i.e., upon application of stimulus to the non-monitored eye), the pupil of the monitored eye should again constrict. If the monitored pupil does not respond adequately to the second stimulus pulse, it may be inferred that the retina of the non-monitored eye somehow may be impaired. If the monitored pupil does not respond adequately to the third stimulus pulse, it may be inferred that the retina of the monitored eye somehow may be impaired.
By using a consensual measurement attachment 50 in accordance with the present invention, it is possible to perform a "swinging flashlight" test using the pupilometer 10. For example, the when performing a "swinging flashlight" test, the P-program may first cause the yellow LEDs 26 within the pupilometer 10 to be activated for a period of, for example, 1 second. The P-program then may deactivate the yellow LEDs 26, and 0.5 second following deactivation of the yellow LEDs 26 may activate for 0.5 second the yellow LED 52 located at the distal end 54 of the consensual attachment. Finally, after deactivating the yellow LED 52 and waiting for a period of, for example, 0.5 second, the P-program may again activate the yellow LEDs 26 for a period of 1 second. Image frames may be obtained by the imaging sensor 14 at a rate of, for example, 10 frames per second and for a total period of 5.0 or more seconds to evaluate the consensual response of the imaged eye. If desired, the process may be repeated a predetermined number of times.
Patent CitationsCited PatentFiling datePublication dateApplicantTitleUS28873 *Jun 26, 1860 Oar and steamboat gasUS3533683 *Jun 13, 1967Oct 13, 1970Whittaker CorpDynamic pupillometers using television camera systemUS3533684 *Jun 26, 1967Oct 13, 1970Troelstra AnneDisplay of measurement adequacy marker system for pupillometersUS3638640 *Nov 1, 1967Feb 1, 1972Robert F ShawOximeter and method for in vivo determination of oxygen saturation in blood using three or more different wavelengthsUS4157864 *Feb 28, 1977Jun 12, 1979Friedrich KilbContact lens eyeball centering support of soft material for use in conjunction with hard contact lensUS4194815 *Jun 28, 1978Mar 25, 1980Dow Corning CorporationSemi-scleral contact lensUS4410245 *Apr 14, 1980Oct 18, 1983Koester Charles JImage stabilization method, and apparatusUS4485820 *May 10, 1982Dec 4, 1984The Johns Hopkins UniversityMethod and apparatus for the continuous monitoring of hemoglobin saturation in the blood of premature infantsUS4649908 *Mar 1, 1985Mar 17, 1987Ghaly Maurice SEye shieldUS4652099 *May 30, 1984Mar 24, 1987Lichtman William MScleral ringUS4664490 *May 2, 1985May 12, 1987Lasag AgContact lens for ophthalmoscopy and ophthalmotherapy by means of laser beamUS4755043 *Nov 14, 1985Jul 5, 1988Somec, Inc.Portable scanning digital pupillometer and method of use thereofUS4863260 *Dec 27, 1988Sep 5, 1989Computed Anatomy Inc.System for topographical modeling of anatomical surfacesUS4871247 *Feb 29, 1988Oct 3, 1989Haynes John BCornea-borne image and light display deviceUS4907597 *Oct 9, 1987Mar 13, 1990Biometrak CorporationCerebral biopotential analysis system and methodUS4907872 *Jun 3, 1988Mar 13, 1990G. Rodenstock Instrumente GmbhContact lens for enabling treatment of the eye by laserUS4966452 *Apr 27, 1989Oct 30, 1990Ocular Instruments, Inc.Contact lens for laser surgeryUS5010891 *Apr 12, 1989Apr 30, 1991Biometrak CorporationCerebral biopotential analysis system and methodUS5117835 *Aug 30, 1991Jun 2, 1992Mick Edwin CMethod and apparatus for the measurement of intracranial pressureUS5179953 *Aug 27, 1991Jan 19, 1993Jermik Systems, Ltd.Portable diurnal intraocular pressure recording systemUS5187506 *Sep 28, 1990Feb 16, 1993Fairville Medical Optics Inc.Method and apparatus for determining physiological parameters based on pupil responseUS5214456 *Oct 9, 1991May 25, 1993Computed Anatomy IncorporatedMapping of corneal topography with display of pupil perimeterUS5336215 *Jan 22, 1993Aug 9, 1994Intelligent Surgical LasersEye stabilizing mechanism for use in ophthalmic laser surgeryUS5408998 *Mar 10, 1994Apr 25, 1995Ethicon Endo-SurgeryVideo based tissue oximetryUS5543865 *Jan 17, 1995Aug 6, 1996Nidek Co., Ltd.Fundus camera with partially common coaxial observation and photographing optical systemsUS5646709 *Apr 18, 1995Jul 8, 1997Fairville Medical Optics, Inc.Portable hand-held pupillometer with dynamic electronic image centering aid and method of use thereof* Cited by examinerNon-Patent CitationsReference1 *A. Yarbus, Eye Movements and Vision , Plenum Press, N.Y., pp. 28 41, 1967.2A. Yarbus, Eye Movements and Vision, Plenum Press, N.Y., pp. 28-41, 1967.3 *AMTech GmbH, Introducing CIP: Compact Integrated Pupillograph and Nystagmograph , 18 pages, Sep. 1997.4AMTech GmbH, Introducing CIP: Compact Integrated Pupillograph and Nystagmograph, 18 pages, Sep. 1997.5 *ASL Applied Science Laboratories, Pupilscreen, Pupilscreen Automatic Self Measurement Pupillometry , 5 pages.6ASL Applied Science Laboratories, Pupilscreen, Pupilscreen Automatic Self Measurement Pupillometry, 5 pages.7 *ASL, Model 1050, Pupilscan & Pupilscreen , 5 pages, 1997.8ASL, Model 1050, Pupilscan & Pupilscreen, 5 pages, 1997.9 *Bishop, Pathologic Pupillary Signs: Self Learning Module, Part 1, Critical Care Nurse , vol. 11, No. 6, pp. 58 63.10 *Bishop, Pathologic Pupillary Signs: Self Learning Module, Part 2, Critical Care Nurse , vol. 11, No. 7, pp. 58 67.11 *Bishop, Pathologic Pupillary Signs: Self Learning Module, Part 3, Critical Care Nurse , vol. 11, No. 8, pp. 30 32.12Bishop, Pathologic Pupillary Signs: Self-Learning Module, Part 1, Critical Care Nurse, vol. 11, No. 6, pp. 58-63.13Bishop, Pathologic Pupillary Signs: Self-Learning Module, Part 2, Critical Care Nurse, vol. 11, No. 7, pp. 58-67.14Bishop, Pathologic Pupillary Signs: Self-Learning Module, Part 3, Critical Care Nurse, vol. 11, No. 8, pp. 30-32.15 *C.A. Finnila, A Convenient Eye Position and Pupil Size Meter (partial), 4 pages, 1960.16 *Chestnut, et al., The Localizing Value Of Assymetry In Pupillary Size In Severe Head Injury: Relation To Lesion Type And Location, Neurosurgery vol. 34, No. 5, pp. 840 846, May 1994.17Chestnut, et al., The Localizing Value Of Assymetry In Pupillary Size In Severe Head Injury: Relation To Lesion Type And Location, Neurosurgeryvol. 34, No. 5, pp. 840-846, May 1994.18 *Fairville Medical Options, Inc., Pupilscan II, Hand Held, Cordless Pupillometer , 4 pages, Feb. 12, 1997.19 *Fairville Medical Options, Inc., Pupilscan II, Hand Held, Electronic Pupillometer , 3 pages.20Fairville Medical Options, Inc., Pupilscan II, Hand-Held, Cordless Pupillometer, 4 pages, Feb. 12, 1997.21Fairville Medical Options, Inc., Pupilscan II, Hand-Held, Electronic Pupillometer, 3 pages.22 *Krenz, et al., Neurophysiological Model Of The Normal And Abnormal Human Pupil, IEEE Transactions On Biomedical Engineering , vol. BME 32, No. 10, pp. 817 825, Oct. 1985.23Krenz, et al., Neurophysiological Model Of The Normal And Abnormal Human Pupil, IEEE Transactions On Biomedical Engineering, vol. BME-32, No. 10, pp. 817-825, Oct. 1985.24 *Krieger, et al., Prognostic And Clinical Relevance Of Pupillary Reponses, Intracranial Pressure Monitoring, And Brainstem Auditory Evoked Potentials In Comatose Patients With Acute Supratentorial Mass Lesions, Critical Care Medicine , vol. 21, No. 12, pp. 1944 1950, Dec. 1993.25Krieger, et al., Prognostic And Clinical Relevance Of Pupillary Reponses, Intracranial Pressure Monitoring, And Brainstem Auditory Evoked Potentials In Comatose Patients With Acute Supratentorial Mass Lesions, Critical Care Medicine, vol. 21, No. 12, pp. 1944-1950, Dec. 1993.26 *L. Stark, et al., Pupil Unrest: An Example of Noise in a Biological Servomechanism, Nature , 4639, pp. 857 858, Sep. 27, 1958.27L. Stark, et al., Pupil Unrest: An Example of Noise in a Biological Servomechanism, Nature, 4639, pp. 857-858, Sep. 27, 1958.28 *L. Stark, Stability, Oscillations, and Noise in the Human Pupil Servomechanism, Proceedings of the IRE , pp. 1925 1939, 1959.29L. Stark, Stability, Oscillations, and Noise in the Human Pupil Servomechanism, Proceedings of the IRE, pp. 1925-1939, 1959.30 *Marshall, et al., Pupillary Abnormalities, Elevated Intracranial Pressure And Mass Lesion Location, Intracranial Pressure VI , Springer Verlag Berlin Heidelberg, pp. 656 660, 1986.31Marshall, et al., Pupillary Abnormalities, Elevated Intracranial Pressure And Mass Lesion Location, Intracranial Pressure VI, Springer-Verlag Berlin Heidelberg, pp. 656-660, 1986.32 *Marshall, et al., The Oval Pupil: Clinical Significance and Relationship To Intracranial Hypertension, J. Neurosurg , vol. 58, pp. 566 568, Apr. 1983.33Marshall, et al., The Oval Pupil: Clinical Significance and Relationship To Intracranial Hypertension, J. Neurosurg, vol. 58, pp. 566-568, Apr. 1983.34 *Myers, et al., Level Dependent Signal Flow In The Light Pupil Reflex, Biological Cybernetics , 68, 229 234, 1993.35Myers, et al., Level Dependent Signal Flow In The Light Pupil Reflex, Biological Cybernetics, 68, 229-234, 1993.36 *S. Asano, et al., Pupillometry, Quarterly Progress Report No. 66, Mass. Inst. of Technology , pp. 404 412, Jul. 15, 1962.37S. Asano, et al., Pupillometry, Quarterly Progress Report No. 66, Mass. Inst. of Technology, pp. 404-412, Jul. 15, 1962.38 *Stark, et al., Instrumentation And Robotic Image Processing Using Top Down Model Control, Robotics and Manufacturing , ASME Press, 675 682, 1988.39Stark, et al., Instrumentation And Robotic Image Processing Using Top-Down Model Control, Robotics and Manufacturing, ASME Press, 675-682, 1988.40 *Stark, et al., Top Down And Bottom Up Image Processing, Proceedings of IEEE 1997 International Conference On Neural Networks , 6 pages, Jun. 1997.41Stark, et al., Top-Down And Bottom-Up Image Processing, Proceedings of IEEE 1997 International Conference On Neural Networks, 6 pages, Jun. 1997.42 *Stark, The Pupil As A Paradigm Example A Neurological Control System: Mathematical Approaches in Biology, The Pupil: Anatomy, Physiology, and Clinical Applications , vol. I, Iowa State University Press, pp. 630 647, 1993.43Stark, The Pupil As A Paradigm Example A Neurological Control System: Mathematical Approaches in Biology, The Pupil: Anatomy, Physiology, and Clinical Applications, vol. I, Iowa State University Press, pp. 630-647, 1993.44 *Stark, The Pupil As A Paradigm For Neurological Control Systems, IEEE Transactions On Biomedical Engineering , vol. BME 31, No. 12, pp. 919 923, Dec. 1984.45Stark, The Pupil As A Paradigm For Neurological Control Systems, IEEE Transactions On Biomedical Engineering, vol. BME-31, No. 12, pp. 919-923, Dec. 1984.46 *Sun, et al., Pupillary Escape Intensified By Large Pupillary Size, Vision Res. , vol. 23, No. 6, pp. 611 615, 1983.47Sun, et al., Pupillary Escape Intensified By Large Pupillary Size, Vision Res., vol. 23, No. 6, pp. 611-615, 1983.48 *Usui, et al., Sensory and Motor Mechanisms Interact To Control Amplitude of Pupil Noise, Vision Res. , vol. 18, pp. 505 507, 1978.49Usui, et al., Sensory and Motor Mechanisms Interact To Control Amplitude of Pupil Noise, Vision Res., vol. 18, pp. 505-507, 1978.* Cited by examinerReferenced byCiting PatentFiling datePublication dateApplicantTitleUS6375325 *Apr 26, 2000Apr 23, 2002Eric German SchellhasPortable digital vertical pupil meterUS6685336 *Mar 29, 2002Feb 3, 2004Gabe NeiserLight emitting diode (LED) flashlightUS7147327 *Oct 30, 2003Dec 12, 2006Neuroptics, Inc.Pupilometer with pupil irregularity detection, pupil tracking, and pupil response detection capability, glaucoma screening capability, intracranial pressure detection capability, and ocular aberration measurement capabilityUS7311401 *May 22, 2001Dec 25, 2007Welch Allyn, Inc.Eye viewing device comprising eyepiece and video capture opticsUS7314164Jul 1, 2004Jan 1, 2008American Express Travel Related Services Company, Inc.System for biometric security using a smartcardUS7314165Jul 1, 2004Jan 1, 2008American Express Travel Related Services Company, Inc.Method and system for smellprint recognition biometrics on a smartcardUS7318550Jul 1, 2004Jan 15, 2008American Express Travel Related Services Company, Inc.Biometric safeguard method for use with a smartcardUS7325724Jul 1, 2004Feb 5, 2008American Express Travel Related Services Company, Inc.Method for registering a biometric for use with a smartcardUS7341181Jul 1, 2004Mar 11, 2008American Express Travel Related Services Company, Inc.Method for biometric security using a smartcardUS7363504Jul 1, 2004Apr 22, 2008American Express Travel Related Services Company, Inc.Method and system for keystroke scan recognition biometrics on a smartcardUS7438234Sep 25, 2007Oct 21, 2008American Express Travel Related Services Company, Inc.System for biometric security using a smartcardUS7445149Sep 25, 2007Nov 4, 2008American Express Travel Related Services Company, Inc.System for biometric security using a smartcardUS7451924Sep 21, 2007Nov 18, 2008American Express Travel Related Services Company, Inc.System for biometric security using a smartcardUS7451925Sep 21, 2007Nov 18, 2008American Express Travel Related Services Company, Inc.System for biometric security using a smartcardUS7488074May 5, 2007Feb 10, 2009Neuroptics, Inc.Intelligent patient interface for ophthalmic instrumentsUS7497375Sep 26, 2007Mar 3, 2009American Express Travel Related Services Company, Inc.Smartcard transaction method and system using smellprint recognitionUS7505941May 11, 2005Mar 17, 2009American Express Travel Related Services Company, Inc.Methods and apparatus for conducting electronic transactions using biometricsUS7506806Sep 26, 2007Mar 24, 2009American Express Travel Related Services Company, Inc.Smartcard transaction method and system using fingerprint recognitionUS7510115Sep 26, 2007Mar 31, 2009American Express Travel Related Services Company, Inc.Smartcard transaction method and system using auditory scan recognitionUS7515054 *Apr 1, 2005Apr 7, 2009Torch William CBiosensors, communicators, and controllers monitoring eye movement and methods for using themUS7523860Sep 26, 2007Apr 28, 2009American Express Travel Related Services Company, Inc.Smartcard transaction method and system using facial scan recognitionUS7530493Sep 26, 2007May 12, 2009American Express Travel Related Services Company, Inc.Smartcard transaction method and system using iris scan recognitionUS7533827Sep 26, 2007May 19, 2009American Express Travel Related Services Company, Inc.Smartcard transaction method and system using signature recognitionUS7594612Sep 27, 2007Sep 29, 2009American Express Travel Related Services Company, Inc.Smartcard transaction method and system using retinal scan recognitionUS7597265Sep 27, 2007Oct 6, 2009American Express Travel Related Services Company, Inc.Method and system for vascular scan recognition with a smartcardUS7618143Dec 23, 2003Nov 17, 2009Newcastle-Upon-Tyne Hospitals Nhs TrustPupilometerUS7670002Apr 4, 2006Mar 2, 2010Neuroptics, Inc.Pupilometer with pupil irregularity detection, pupil tracking, and pupil response detection capability, glaucoma screening capability, intracranial pressure detection capability, and ocular aberration measurement capabilityUS7901079Jun 23, 2010Mar 8, 2011Neuroptics, Inc.Intelligent patient interface for ophthalmic instrumentsUS7909463 *Oct 25, 2007Mar 22, 2011Carl Zeiss Meditec AgMethod for determining vision defects and for collecting data for correcting vision defects of the eye by interaction of a patient with an examiner and apparatus thereforUS7938785 *Jan 23, 2009May 10, 2011Teledyne Scientific & Imaging, LlcFusion-based spatio-temporal feature detection for robust classification of instantaneous changes in pupil response as a correlate of cognitive responseUS7967442Nov 25, 2009Jun 28, 2011Neuroptics, Inc.Methods, systems, and devices for monitoring anisocoria and asymmetry of pupillary reaction to stimulusUS8214299Aug 18, 2010Jul 3, 2012American Express Travel Related Services Company, Inc.Methods and apparatus for conducting electronic transactionsUS8235526Feb 12, 2010Aug 7, 2012Neuroptics, Inc.Pupilometer with pupil irregularity detection, pupil tracking, and pupil response detection capability, glaucoma screening capability, intracranial pressure detection capability, and ocular aberration measurement capabilityUS8393734Sep 13, 2008Mar 12, 2013Neuroptics, Inc.Pupilary screening method and systemUS8403862 *Dec 22, 2008Mar 26, 2013Yeda Research And Development Co. Ltd.Time-based imagingUS8423476Apr 13, 2011Apr 16, 2013American Express Travel Related Services Company, Inc.Methods and apparatus for conducting electronic transactionsUS8433658Apr 13, 2011Apr 30, 2013American Express Travel Related Services Company, Inc.Methods and apparatus for conducting electronic transactionsUS8489513Apr 13, 2011Jul 16, 2013American Express Travel Related Services Company, Inc.Methods and apparatus for conducting electronic transactionsUS8534840Jun 1, 2011Sep 17, 2013Neuroptics, Inc.Methods, systems, and devices for monitoring anisocoria and asymmetry of pupillary reaction to stimulusUS8702236Mar 4, 2009Apr 22, 2014Procyon Instruments LimitedBinocular pupillometersUSRE41376Apr 3, 2007Jun 15, 2010Torch William CSystem and method for monitoring eye movementUSRE42471Aug 27, 2008Jun 21, 2011Torch William CSystem and method for monitoring eye movementWO2005086929A2 *Mar 9, 2005Sep 22, 2005Univ New York State Res FoundApparatus and method for assessing retinal damageWO2009109750A1 *Mar 4, 2009Sep 11, 2009Procyon Instruments LimitedBinocular pupillometers* Cited by examinerClassifications U.S. Classification351/206International ClassificationA61B3/11, A61B10/00Cooperative ClassificationA61B3/112European ClassificationA61B3/11DLegal EventsDateCodeEventDescriptionMay 24, 2013ASAssignmentOwner name: NEUROPTICS, INC., CALIFORNIAFree format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:STARK, LAWRENCE W., DR.;PRIVITERA, CLAUDIO M.;SIMINOU, KAMRAN;AND OTHERS;SIGNING DATES FROM 19990708 TO 19990709;REEL/FRAME:030485/0435Mar 10, 2012FPAYFee paymentYear of fee payment: 12Mar 17, 2008SULPSurcharge for late paymentYear of fee payment: 7Mar 17, 2008FPAYFee paymentYear of fee payment: 8Mar 10, 2004FPAYFee paymentYear of fee payment: 4May 28, 2002CCCertificate of correctionRotateOriginal ImageGoogle Home - Sitemap - USPTO Bulk Downloads - Privacy Policy - Terms of Service - About Google Patents - Send FeedbackData provided by IFI CLAIMS Patent Services©2012 Google