PUPILOMETER WITH PUPIL IRREGULARITY DETECTION, PUPIL TRACKING, AND PUPIL RESPONSE DETECTION CAPABILITY, GLAUCOMA SCREENING CAPABILITY, INTRACRANIAL PRESSURE DETECTION CAPABILITY, AND OCULAR ABERRATION MEASUREMENT CAPABILITY

• US 6,820,979 B1
• Filed: 11/09/2000
• Issued: 11/23/2004
• Est. Priority Date: 04/23/1999
• Status: Expired due to Term

• Current Assignee: Neuroptics Incorporated
• Original Assignee: Neuroptics Incorporated
• Inventors: Oliver, Jeffrey, Siminou, Kamran, Stark, Lawrence W., Privitera, Claudio M.
• Primary Examiner(s): MANUEL, GEORGE C
• Application Number:
  US09/711,675
• Time in Patent Office: 1,475 Days
• Field of Search: 351/204, 351/205, 351/206, 351/209, 351/210, 351/211, 351/212, 351/221, 351/246, 600/398, 600/474, 600/549, 600/399, 600/400, 382/117
• US Class Current: 351/206
• CPC Class Codes: A61B 3/112 for measuring diameter of pupils
• CPC Class Codes: A61B 5/163 by tracking eye movement, gaze, or pupil change
• CPC Class Codes: A61N 1/36046 of the eye
• CPC Class Codes: A61N 2005/0648 the light being directed to the eyes

Abstract

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.

Claims

1. A pupilometer comprising:

a visible light source for generating light to stimulate a retina of an eye;

an IR light source for generating IR light for illuminating a pupil of the eye;

an imaging sensor for generating signals representative of the pupil of the eye;

a microprocessor; and

a program executable by said microprocessor for enabling said microprocessor to process signals received from said imaging sensor and to thereby identify the pupil'"'"'s dynamic response to the visible light generated by the visible light source.

2. The pupilometer of claim 1, wherein the visible light source generates green light.

3. The pupilometer of claim 1, wherein the visible light source generates blue light.

4. The pupilometer of claim 1, wherein the signal received from the imaging sensor represents the amplitude of the pupil'"'"'s response to the light generated from the visible light source.

5. The pupilometer of claim 1, wherein the signal received from the imaging sensor represents the velocity of the pupil'"'"'s response to the light generated from the visible light source.

6. The pupilometer of claim 1, wherein the light generated from the visible light source is projected onto at least one region of the retina of the eye.

7. The pupilometer of claim 6, wherein the light generated from the visible light source is projected onto multiple regions on the retina of the eye in succession.

8. The pupilometer of claim 1, wherein the microprocessor is electrically coupled to the visible light source, and wherein the program enables said microprocessor to cause a plurality of light stimulus pulses to be generated by said visible light source, and enables said imaging device to acquire a plurality of images of said pupil.

9. The pupilometer of claim 1, wherein the signal received from the imaging sensor represents the latency of pupilary response to the light generated from the visible light source.

10. The pupilometer of claim 1, wherein the signal received from the imaging sensor represents the constriction velocity of the pupil in response to the light generated from the visible light source.

11. The pupilometer of claim 1, wherein the signal received from the imaging sensor represents a first dilation velocity of the pupil.

12. The pupilometer of claim 1, wherein the signal received from the imaging sensor represents a second dilation velocity of the pupil.

13. The pupilometer of claim 1, wherein the signal received from the imaging sensor represents a maximum diameter of the pupil.

14. The pupilometer of claim 1, wherein the signal received from the imaging sensor represents a minimum diameter of the pupil.

15. The pupilometer of claim 1, wherein the visible light source generates white light.

16. The pupilometer of claim 1, wherein the visible light source generates yellow diffuse light.

17. A method for detecting glaucoma comprising the steps of:

providing a pupilometer;

obtaining, using the pupilometer, pupilary response data from an eye of a patient, said pupilary response data being representative of one or more pupilary response characteristics of said eye;

storing within a database data representative of a plurality of pupilary response characteristics;

comparing within an automated data analysis system said pupilary response data obtained from said patient with said data representative of a plurality of pupilary response characteristics to determine whether the patient'"'"'s pupilary response data indicates Glaucoma.

18. The method of claim 17, wherein the pupilometer comprises a visible light source, an IR light source, an imaging sensor, a microprocessor, and a program executable by said microprocessor.

19. The method of claim 18, wherein the step of obtaining the patient'"'"'s pupilary response data comprises the steps of:

illuminating the eye the IR light from the IR light source;

projecting a first image of the eye to the imaging sensor; and

transmitting data representative of the first image of the eye to the microprocessor.

20. The method of claim 19 further comprising the steps of:

projecting light from the visible light source onto a retina of the eye;

projecting a second image of the eye to the imaging sensor; and

transmitting data representative of the second image of the eye to the microprocessor.

21. The method of claim 17, wherein the data representative of a plurality of pupilary response characteristics is associated with Glaucoma.

22. The method of claim 17, wherein the data representative of a plurality of pupilary response characteristics is associated with a healthy eye.

23. The method of claim 17, wherein the pupilary response characteristics of said eye comprise the velocity of pupilary response to retinal stimulation by light.

24. The method of claim 17, wherein the pupilary response characteristics of said eye comprise the amplitude of pupilary response to retinal stimulation by light.

25. The method of claim 17, wherein the database is in electrical communication with the pupilometer.

26. The method of claim 17, wherein the data analysis system is in electrical communication with the pupilometer.

27. A system for use in diagnosing glaucoma, said system comprising:

a pupilometer for obtaining data descriptive of one or more pupilary characteristics from an eye of a patient;

a database for storing data descriptive of a plurality of pupilary characteristics; and

a central processing unit coupled to said pupilometer and said database for comparing said data obtained by said pupilometer to said data stored within said database such that Glaucoma may be diagnosed based upon said comparison.

28. The system of claim 27, wherein the pupilometer comprises a first visible light source, a second visible light source, an IR light source, and an imaging sensor.

29. The system of claim 28, wherein the first visible light source generates white light.

30. The system of claim 28, wherein the first visible light source generates a yellow diffuse light.

31. The system of claim 28, wherein the second visible light source generates green light.

32. The system of claim 28, wherein the second visible light source generates blue light.

33. The system of claim 27 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.

38. The method of claim 31 further comprising the step of providing a second moveable target in the visual field of the subject.

34. A system for use in diagnosing impairment to brain function, said system comprising:

a pupilometer for obtaining data descriptive of one or more pupilary characteristics from a subject;

a movable target;

a database for storing data descriptive of one or more pupilary characteristics associated with a set pattern of target movement; and

a central processing unit coupled to the pupilometer and the database for comparing the data obtained by the pupilometer to the data stored within the database to assess the subject'"'"'s level of brain function.

35. The system of claim 34, wherein the pupilometer comprises a visible light source, and the movable target comprises light generated by said visible light source.

36. The system of claim 35 further comprising a second movable target.

37. A method for diagnosing impairment to brain function comprising the steps of:

providing a pupilometer;

providing a movable target in the visual field of a subject;

moving the target within the visual field of the subject in a set pattern of target movement;

obtaining, using the pupilometer, a first set of data descriptive of one or more pupilary characteristics from an eye of the subject as the subject follows the target;

storing within a database a second set of data descriptive of plurality of pupilary characteristics associated with the set pattern of target movement;

comparing within a data analysis system said first set of data with said second set of data to determine whether the subject'"'"'s brain function is impaired.

39. The method of claim 37, wherein the second set of data is associated with impairment to brain function.

40. The method of claim 37, wherein the second set of data is associated with normal levels of brain function.

41. The method of claim 37, wherein the database is in electrical communication with the pupilometer.

42. The method of claim 37, wherein the data analysis system is in electrical communication with the pupilometer.

43. A system for diagnosing neurological disease or trauma, said system comprising:

a pupilometer for obtaining data descriptive of one or more pupilary characteristics from an eye of a patient;

a stimulus source in communication with the pupilometer; and

a central processing unit coupled to the pupilometer and in communication with the stimulus source, said central processing unit being capable of activating the stimulus source thereby sending a stimulus to an anatomical structure of the patient.

44. The system of claim 43, wherein the stimulus source is a noxious stimulus source.

45. The system of claim 44, wherein the stimulus source is a container of a liquid substance.

46. The system of claim 45, wherein the stimulus source is a container of compressed liquid substance.

47. The system of claim 43, further comprising:

a database for storing a second set of data descriptive of a plurality of pupilary characteristics, said central processing unit in communication with the database;

and a data analysis system, said data analysis system capable of comparing the first set of data and second set of data such that neurological disease or trauma may be diagnosed based on such comparison.

48. The system of claim 43, wherein the stimulus source is configured to provide an electrical current.

49. The system of claim 43, wherein the stimulus source is a light source.

50. The system of claim 43, wherein the central processing unit is capable of synchronizing the activation of the stimulus source with the pupilometer.

51. The system of claim 43, wherein the data comprises pupilary latency indicia.

52. The system of claim 43, wherein the data comprises pupilary constriction velocity indicia.

53. The system of claim 43, wherein the data comprises pupilary first and second dilation velocity indicia.

54. The system of claim 43, wherein the data comprises pupilary amplitude indicia.

55. The system of claim 43, wherein the data comprises pupilary diameter indicia.

56. The system of claim 43, wherein the data comprises segmental dynamic analysis indicia.

57. The system of claim 43, wherein the data comprises segmental static analysis indicia.

58. The system of claim 43, wherein the central processing unit comprises an algorithm configured to convert said data to one or more scalar values.

59. A method for diagnosing neurological disease or trauma, said method comprising the steps of:

providing a pupilometer comprising a central processing unit and a memory;

providing a stimulus source, said stimulus source in communication with the pupilometer;

activating the stimulus source with the pupilometer thereby causing the stimulus source to send a stimulus to an anatomical structure of a patient;

obtaining, using the pupilometer, temporal data with respect to the activation of the stimulus source; and

obtaining, using the pupilometer, a first set of data descriptive of one or more pupilary characteristics from an eye of the patient.

60. The method of claim 59, wherein the pupilometer comprises a light source.

61. The method of claim 59, wherein the pupilary response characteristics of the eye comprise pupilary constriction velocity indicia.

62. The method of claim 59, wherein the pupilary response characteristics of the eye comprise pupilary amplitude indicia.

63. The method of claim 59, wherein the anatomical structure that is stimulated with the stimulus comprises the cornea.

64. The method of claim 59, wherein the anatomical structure that is stimulated with the stimulus comprises the ear.

65. The method of claim 59, wherein the anatomical structure that is stimulated comprises dermatopic areas.

66. The method of claim 59, wherein the database is in electrical communication with the pupilometer.

67. The method of claim 59, wherein the data analysis system is in electrical communication with the pupilometer.

68. The method of claim 59, further comprising the steps of:

storing within a database a second set of data descriptive of a plurality of pupilary characteristics associated with pupilary response to a stimulus; and

comparing within a data analysis system said first set of data with said second set of data to determine whether neurological disease or trauma in the patient is indicated.

69. The method of claim 59, wherein the stimulus source is a noxious stimulus source.

70. The method of claim 59, wherein the stimulus source is a light source.

71. The method of claim 59, wherein the step of activating the stimulus source is controlled and synchronized by the central processing unit.

72. The method of claim 59, wherein the stimulus source is configured to provide an electrical current.

73. The method of claim 59, further comprising the step of obtaining, using the pupilometer, a second set of data descriptive of one or more pupilary characteristics from a second eye of the patient.

74. The method of claim 73, further comprising the step of comparing within a data analysis system said first set of data with said second set of data.

75. The method of claim 73, further comprising the step of converting, using an algorithm, said second set of data to one or more scalar values.

76. The method of claim 73, further comprising the step of converting, using an algorithm, said first and said second sets of data to one or more scalar values.

77. The method of claim 59, wherein the first set of data comprises pupilary latency indicia.

78. The method of claim 59, wherein the first set of data comprises pupilary constriction velocity indicia.

79. The method of claim 59, wherein the first set of data comprises pupilary first and second dilation velocity indicia.

80. The method of claim 59, wherein the first set of data comprises pupilary amplitude indicia.

81. The method of claim 59, wherein the first set of data comprises pupilary diameter indicia.

82. The method of claim 59, wherein the first set of data comprises segmental dynamic analysis indicia.

83. The method of claim 59, wherein the first set of data comprises segmental static analysis indicia.

84. The method of claim 59, further comprising the step of converting, using an algorithm, said first set of data to one or more scalar values.

85. The method of claims 84, 75, or 76 further comprising the step of applying said scalar values to a scale indicative of a state of neurological health.

86. The method of claim 59, wherein the anatomical structure that is stimulated with the stimulus comprises one or more from the following group:

skin, muscle, or peripheral nerve.

87. A system for testing the functional integrity of a patient'"'"'s auditory pathways, said system comprising:

a pupilometer for obtaining data descriptive of one or more pupilary characteristics of the patient;

a sound generating transducer; and

a central processing unit in communication with the pupilometer and sound generating transducer, said central processing unit capable of activating and controlling the sound generating transducer and synchronizing the pupilometer with the sound generating transducer.

88. The system of claim 87, wherein the sound generating transducer is capable of generating sound in more than one amplitude and more than one frequency.

89. The system of claim 87, wherein the central,processing unit is capable of storing temporal data relating to the activation of the sound generating transducer.

90. The system of claim 87, wherein the central processing unit is capable of controlling temporal data relating to the activation of the sound generating transducer.

91. The system of claim 87, further comprising a database for storing data descriptive of one or more pupilary characteristics associated with a set pattern of sound stimuli, wherein the central processing unit is further capable of comparing the data obtained by the pupilometer to the data stored with the database to asses the functional integrity of the patient'"'"'s auditory pathways based on said comparison.

92. The system of claim 87, further comprising one or more ear-pieces in communication with the sound generating transducer.

93. The system of claim 87, wherein the data comprises pupilary latency indicia.

94. The system of claim 87, wherein the data comprises pupilary constriction velocity indicia.

95. The system of claim 87, wherein the data comprises pupilary first and second dilation velocity indicia.

96. The system of claim 87, wherein the data comprises pupilary amplitude indicia.

97. The system of claim 87, wherein the data comprises pupilary diameter indicia.

98. The system of claim 87, wherein the data comprises segmental dynamic analysis indicia.

99. The system of claim 87, wherein the data comprises segmental static analysis indicia.

100. The system of claim 87, wherein the central processing unit comprises an algorithm configured to convert said data to one or more scalar values.

101. A method for testing the functional integrity of a patient'"'"'s auditory pathways, said method comprising the steps of:

providing a pupilometer;

providing a central processing unit in communication with the pupilometer;

providing a sound generating transducer capable of transmitting an auditory stimulus, said sound generating transducer in communication with the central processing unit, wherein the central processing unit is capable of activating and controlling the sound generating transducer;

using the pupilometer, activating the transducer to produce a sound; and

obtaining, using the pupilometer, a first set of data descriptive of one or more pupilary characteristics from an eye of the patient.

102. The method of claim 101, wherein the pupilometer comprises a light source.

103. The method of claim 101, wherein the pupilometer is in electrical communication with the sound generating transducer.

104. The method of claim 101, wherein the transducer is capable of generating sound in more than one amplitude and more than one frequency.

105. The method of claim 101, wherein the transducer and pupilometer are synchronized.

106. The method of claim 101, wherein the response characteristics of the eye comprises the velocity of pupilary response to auditory stimulus generated by the transducer.

107. The method of claim 101, wherein the response characteristics of the eye comprises the amplitude of pupilary response to auditory stimulus generated by the transducer.

108. The method of claim 101, further comprising the steps of:

storing within a database a second set of data descriptive of one or more pupilary characteristics associated with a set pattern of sound stimuli; and

comparing within a data analysis system said first set of data with said second set of data to assess the functional integrity of the patient'"'"'s auditory pathways based upon said comparison.

109. The method of claim 108, wherein the database is in electrical communication with the pupilometer.

110. The method of claim 108, wherein the data analysis system is in electrical communication with the pupilometer.

111. The method of claim 101, further comprising the steps of:

providing one or more ear-pieces in electrical communication with the transducer; and

inserting the one or more ear-pieces into one or both ears of the patient.

112. The method of claim 101, further comprising the step of obtaining, using the pupilometer, a second set of data descriptive of one or more pupilary characteristics from a second eye of the patient.

113. The method of claim 112, further comprising the step of comparing within a data analysis system said first set of data with said second set of data.

114. The method of claim 112, further comprising the step of converting, using an algorithm, said second set of data to one or more scalar values.

115. The method of claim 112, further comprising the step of converting, using an algorithm, said first and said second sets of data to one or more scalar values.

116. The method of claim 101, wherein the first set of data comprises pupilary latency indicia.

117. The method of claim 101, wherein the first set of data comprises pupilary constriction velocity indicia.

118. The method of claim 101, wherein the first set of data comprises pupilary first and second dilation velocity indicia.

119. The method of claim 101, wherein the first set of data comprises pupilary amplitude indicia.

120. The method of claim 101, wherein the first set of data comprises pupilary diameter indicia.

121. The method of claim 101, wherein the first set of data comprises segmental dynamic analysis indicia.

122. The method of claim 101, wherein the first set of data comprises segmental static analysis indicia.

123. The method of claim 101, further comprising the step of converting, using an algorithm, said first set of data to one or more scalar values.

124. The method of claims 123, 114 or 115, further comprising the step of applying said scalar values to a scale indicative of a state of auditory pathway health.

125. A method for diagnosing a medical condition, said method comprising the steps of:

providing a pupilometer;

providing a central processing unit in communication with the pupilometer;

providing an amplitude modulated light source for generating light, said light source in communication with the central processing unit, wherein the central processing unit is capable of activating and controlling the amplitude modulated light source;

continuously projecting the light for a given length of time onto the eye of a patient in a predetermined pattern of amplitude modulation; and

obtaining, using the pupilometer, a first set of data representative of a pupil'"'"'s response to the modulated light.

126. The method of claim 125, further comprising the steps of:

storing within a database a second set of data representing pupilary response to light stimulus received in said predetermined pattern of amplitude modulation; and

comparing within a data analysis system said first set of data with said second set of data in order to detect neurological deterioration.

127. The method of claim 126, wherein the database is in electrical communication with the pupilometer.

128. The method of claim 126, wherein the data analysis system is in electrical communication with the pupilometer.

129. The method of claim 126, wherein the second set of data represents data taken from one or more healthy individuals.

130. The method of claim 126, wherein the second set of data represents data taken from one or more individuals with neurological deterioration.

131. The method of claim 126, wherein the first and second sets of data are both taken from the same individual.

132. The method of claim 125, wherein the pupilometer is in electrical communication with the light source.

133. The method of claim 125, further comprising the step of obtaining, using the pupilometer, a second set of data descriptive of one or more pupilary characteristics from a second eye of the patient.

134. The method of claim 133, further comprising the step of comparing within a data analysis system said first set of data with said second set of data.

135. The method of claim 133, further comprising the step of converting, using an algorithm, said second set of data to one or more scalar values.

136. The method of claim 133, further comprising the step of converting, using an algorithm, said first and said second sets of data to one or more scalar values.

137. The method of claim 125, wherein the first set of data comprises pupilary latency indicia.

138. The method of claim 125, wherein the first set of data comprises pupilary constriction velocity indicia.

139. The method of claim 125, wherein the first set of data comprises pupilary first and second dilation velocity indicia.

140. The method of claim 125, wherein the first of data comprises pupilary amplitude indicia.

141. The method of claim 125, wherein the first set of data comprises pupilary diameter indicia.

142. The method of claim 125, wherein the first set of data comprises segmental dynamic analysis indicia.

143. The method of claim 125, wherein the first set of data comprises segmental static analysis indicia.

144. The method of claim 125, further comprising the step of converting, using an algorithm, said first set of data to one or more scalar values.

145. The method of claims 144, 135, and 136, further comprising the step of applying said scalar values to a scale indicative of a medical condition.

146. A method for correlating a pupilary response 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;

providing a data analysis system comprising a microprocessor, said microprocessor in communication with the database and the pupilometer; and

comparing within said 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 indications of said patient.

147. The method of claim 146, wherein the database and data analysis system are integrated into the pupilometer.

148. The method of claim 146, wherein the pupilary response data comprises pupilary latency indicia.

149. The method of claim 146, wherein the pupilary response data comprises pupilary constriction velocity indicia.

150. The method of claim 146, wherein the pupilary response data comprises pupilary first and second dilation velocity indicia.

151. The method of claim 146, wherein the pupilary response data comprises pupilary amplitude indicia.

152. The method claim 146, wherein the pupilary response data comprises pupilary diameter indicia.

153. The method of claim 146, wherein the pupilary response data comprises segmental dynamic analysis indicia.

154. The method of claim 146, wherein the first set of data comprises segmental static analysis indicia.

155. 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 data and associated pathological indications;

using a pupilometer, obtaining pupilary data from a patient;

providing a data analysis system comprising a microprocessor, said microprocessor in communication with the database and the pupilometer; and

comparing with said data analysis system said pupilary data obtained from said patient with said data from said database to identify one or more pathological indications of said patient.

156. The method of claim 155, wherein both the data from the database and the data obtained from the patient represent pupilary shape or pupilary dynamics data.

157. The method of claim 156, wherein both the data from the database and the data obtained from the patient comprise data descriptive of a pupilary response to at least one visible light stimulus pulse.

158. The method of claim 156, wherein both the data from the database and the data obtained from the patient comprise data descriptive of a pupilary change in shape responsive to at least one light stimulus pulse.

159. The method of claim 156, wherein both the data from the database and the data obtained from the patient comprise data descriptive of a pupilary response to ambient light exposure.

160. The method of claim 156, wherein both the data from the database and the data obtained from the patient comprise pupilary latency indicia.

161. The method of claim 156, wherein both the data from the database and the data obtained from the patient comprise pupilary constriction velocity indicia.

162. The method of claim 156, wherein both the data from the database and the data obtained from the patient comprise pupilary first and second dilation velocity indicia.

163. The method of claim 156, wherein both the data from the database and the data obtained from the patient comprise pupilary amplitude indicia.

164. The method of claim 156, wherein both the data from the database and the data obtained from the patient comprise pupilary diameter indicia.

165. The method of claim 156, wherein both the data from the database and the data obtained form the patient comprise segmental dynamic analysis indicia.

166. The method of claim 156, wherein both the data from the database and the data obtained from the patient comprise segmental static analysis indicia.

167. The method of claim 155, wherein the database and data analysis system are integrated into the pupilometer.

168. A method for assessing a state of health of an individual or physiological system of said individual, said method comprising the steps of:

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;

providing a data analysis system comprising a microprocessor, said microprocessor in communication with the pupilometer; and

using the data analysis system to derive a scalar value based on the pupilary response data from the patient.

169. The method of claim 168, further comprising the step of applying the scalar value to a scale indicative of a state of health of an individual or a physiological system of an individual.

170. The method of claim 168, wherein the step of applying the scalar value to a scale is performed by the data analysis system.

171. The method of claim 168, wherein the database and data analysis system are integrated into the pupilometer.

172. A system for use in diagnosing pathological conditions, said system comprising:

a pupilometer for obtaining a first set of data descriptive of one or more pupilary characteristics from a patient;

a database for storing a second set of data descriptive of a plurality of pupilary characteristics and associated physical conditions; and

a central processing unit in communication with said pupilometer and said database for comparing said first set of data with said second set of data such that a pathological condition of said patient may be diagnosed based on said comparison.

173. The system of claim 172, wherein the first and second sets of data comprise image data.

174. The system of claim 172, wherein the first and second sets of data comprise alphanumeric values.

175. The system of claim 172 further comprising a processing subroutine for generating a scalar indicator based upon a result of said comparison of the first and second sets of data by the central processing unit.

176. The system of claim 172 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 second set of data.

177. The system of claim 172, wherein the database and central processing unit are integrated into the pupilometer.

178. A pupilometer comprising:

a display, an imaging device and a microprocessor, said microprocessor being coupled to said display, and said imaging device, said microprocessor comprising a memory, wherein said memory has stored therein a program comprising;

image acquisition code for enabling said microprocessor to cause said imaging device to acquire a plurality of images of a first pupil of an individual'"'"'s eye;

image analysis code for enabling said microprocessor to process data sets representative of said images of said pupil to obtain information descriptive of said pupil; and

display code for enabling said microprocessor to cause said information to be depicted on said display.

179. The pupilometer of claim 178, further comprising a first visible light source, and an IR light source, wherein said microprocessor is in communication with said first visible light source and said IR light source, and said program further comprises:

stimulus control code for enabling said microprocessor to cause said visible light source to generate a first visible light stimulus pulse for illuminating a first eye; and

illumination control code for enabling said microprocessor cause said IR light source to generate IR light for illuminating a pupil of said first eye during a duration of said first visible light stimulus pulse.

180. The pupilometer of claim 179, further comprising an armature extending laterally from a main body of the pupilometer, said armature comprising a second visible light source, said microprocessor in communication with said second visible light source, wherein the stimulus control code is capable of enabling the microprocessor to cause said second visible light source to generate a second visible light stimulus pulse for illuminating a second eye of the individual 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 visible light stimulus pulse.

181. The pupilometer of claim 180, wherein the microprocessor is capable of storing and controlling the times at which the microprocessor activates the first visible light source and a time at which the microprocessor activates the second visible light source.

182. The pupilometer of claim 181, wherein the microprocessor is capable of synchronizing the activation of the first and second visible light sources.

183. A medical diagnosis system comprising:

a pupilometer for obtaining data descriptive of one or more eye movement characteristics from a subject;

a movable target;

a database for storing data descriptive of one or more eye movement characteristics associated with a set pattern of target movement; and

a central processing unit coupled to the pupilometer and the database for comparing the data obtained by the pupilometer to the data stored with the database to assess the subject'"'"'s level of brain function.

184. The system of claim 183, wherein the pupilometer comprises a visible light source, and the movable target comprises light generated by said visible light source.

185. The system of claim 184 further comprising a second movable target.

186. A method for diagnosing a medical condition, said method comprising the steps of:

providing a pupilometer;

providing a movable target in the visual field of a subject;

moving the target with the visual field of the subject in a set pattern of target movement;

obtaining, using the pupilometer, a first set of data descriptive of one or more eye movement characteristics from an eye of the subject as the subject follows the target;

storing within a database a second set of data descriptive of a plurality of eye movement characteristics associated with the set pattern of target movement;

comparing within a data analysis system said first set of data with said second set of data to determine whether the subject'"'"'s brain function is impaired.

187. The method of claim 186 further comprising the step of providing a second moveable target in the visual field of the subject.

188. The method of claim 186, wherein the second set of data is associated with impairment to brain function.

189. The method of claim 186, wherein the second set of data is associated with normal levels of brain function.

190. The method of claim 186, wherein the database is in electrical communication with the pupilometer.

191. The method of claim 186, wherein the data analysis system is in electrical communication with the pupilometer.

192. A method for examining an individual comprising the steps of:

providing a pupilometer comprising an imaging sensor, a data processor, and a program executable by said data processor for analyzing pupilary response to stimuli;

using the pupilometer to acquire a first set of data representative of a response of a first eye of the patient to a first stimulus;

using the pupilometer to acquire of second set of data representative of a response of a second eye of the patient to a second stimulus, the second stimulus being applied at a predetermined time following termination of the first stimulus; and

using the pupilometer to correlate the first set of data with the second set of data to derive a value.

193. The method of claim 192, further comprising the step of comparing the value with a value corresponding with a set of normal responses to the stimulus.

194. The method of claim 192, further comprising the step of comparing the value with a value corresponding with a set of abnormal responses to the stimulus.

195. The method of claim 192, wherein the value derived is a scalar value, said method further comprising the step of applying the scalar value to scale.

196. The method of claim 192, wherein the pupilometer comprises a stimulus source, and the first and second stimuli are delivered by the pupilometer.

197. The method of claim 196, wherein the pupilometer comprises an armature that extends from a main body of the pupilometer for supporting a second stimulus source, and the first stimulus is delivered by the first stimulus source, and the second stimulus is delivered by the second stimulus source.