Pupillography

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Background

Pupillography is a method of recording pupillary movements and study of changes and reactions to light and permits measurements of these movements. It is known that the pupillary pathways follow the optic nerve through the chiasma opticum and the pupil is an important oculomotor system that is affected by a diverse set of stimuli including changes in retinal luminance, sudden changes in stimulus motion, emotional and cognitive factors [1][2][3][4][5].

The measurement of pupil diameter in psychologic disorders provides an estimate of the intensity of mental activity and changes in mental estates. In fact, pupil dilation correlates with arousal so consistently that researchers use pupillometry, to investigate a wide range of psychological phenomena Researches in neuroscience has revealed a tight correlation between the activity of the locus coeruleus and pupillary dilation, so mental activity and pupillary responses have some correlations. Cognitive and emotional events can also dictate pupil constriction and expansion, though such events occur on a smaller scale than the light reflex, causing changes generally less than half a millimeter. By recording subjects’ eyes with infrared cameras and controlling for other factors that might affect pupil size, like brightness, color, and distance, scientists can use pupil movements as a proxy for other processes, like mental strain. It can be a sensitive indicator for Alzheimer's and Parkinson's diseases, Autism or even for opioid and alcohol users [6][7][8][9][10][11][12][13].

Pupil size affects vision with any IOL and pupillography is very important in IOL selection especially in premium IOLs. Accurate pupillography is an essential part of the evaluation, screening, and refractive surgery planning process (14-19).

Scientists have since used pupillography to assess everything from sleepiness to introversion, race bias ,schizophrenia, sexual interest, moral judgment, autism, and depression. And while they haven’t been reading people’s thoughts per se, they’ve come pretty close (20-26).

Most of ophthalmologists take advantage of pupillography because pupil size measurement during a pre-operative evaluation is particularly helpful for optimizing the premium IOL selection for the patient based on the patient's stated preferences about the level of vision he or she values most (e.g., distance, intermediate or near), occupation, lifestyle, and frequency of nighttime driving.

A special designed device that can be used to measure pupils and screen candidates for refractive procedures and other ophthalmic applications such as the fitting of premium IOLs would be useful. It can also work best for diagnostic approaches to mental disorders and addiction.

Pattern Recognition and System Auto-Calibration

In order to track the size of the pupil, a segmentation algorithm can be used. The simplest method to perform this is using the well-known Hugh Transform method, as the pupil is usually in the shape of a circle. Although this method will work in many cases, it will not provide proper accuracy in all different conditions, such as abnormal pupil shapes, and misplaced pupils. As the camera is located exactly in front of the pupil (when the pupils are in the middle of the eye), any movements of the pupil will change its shape from the viewpoint of the camera (it will be more elliptic-shaped rather than a circle). Therefore, Hugh Transform algorithm alone cannot provide the required accuracy.

To enhance the performance of the detection system, a more intelligent pattern recognition system should utilize . Although, these systems need a training set and an experienced user to train the network, it can eventually adapt itself to detect the desired item (such as pupil) with a very high accuracy regardless of its exact shape. Therefore, in the cases of abnormal pupil shape, or misplaced pupil, the algorithm can still accurately detect the pupil and its position.

However, the pupil size scaling is still an issue, which should be pointed out. In other words, if a pupil has a displacement from the center, its measured size may not be accurate enough due to perspective issues. However, when the device frame is symmetric, the scaling factor of both eyes would be the same for each patient. It is worth mentioning that this scaling factor varies from patient to patient, but it will be constant for each patient. Therefore, neglecting this scaling factor (or reporting the normalized outputs rather than the actual values), will not affect the accuracy of the device in the cases of different shapes of patients’ faces (different eye-camera distance).

To compensate for the eye movement, another scaling factor can be utilized to scale the size of the pupil, as it is located in the middle of the eye. This can be done by simple mathematical expressions, since the location of the pupil with respect to the camera can be easily calculated and used to find the variations from the center. This method is a well-known method in image processing algorithms and can be easily implemented in the proposed device.

More Advantages

The most pertinent information will be obtained by measuring a patient's pupils under varying light conditions which simulate real life conditions a patient may experience in daily life such as darkness, a dimly lit room, and driving at night with streetlights. Measurement of the pupil is more difficult than it might seem because of the phenomenon of pupillary hippus or noise. The pupil is never entirely at rest but rather has normal, small continuous oscillations (±0.5mm ). Therefore, when trying to measure the pupil, a single “snapshot” estimate is not a reliable predictor of the true mean size (because the clinician might catch the pupil at the maximum or minimum.) so , a proposed device should record pupillary movements for further processing and analysis so that any technician can perform the test automatically.

References

  1. Hakerem G., Sutton S. Pupillary response at visual threshold. Nature. 1966; 212:485–486.
  2. Kardon K. Pupillary light reflex. Curr Opin Ophthalmol. 1995; 6:20–26.
  3. Sahraie A., Barbur J.L. Pupil response triggered by the onset of coherent motion. Graefes Arch Clin Exp Ophthalmol. 1997; 235:494–500.
  4. Goldwater B.C. Psychological significance of pupillary movements. Psychol Bull. 1972; 77:340–355.
  5. Beatty J. Task-evoked pupillary responses, processing load, and the structure of processing resources.Psychol Bull. 1982; 91:276–292.
  6. Fotiou DF, Stergiou V, Tsiptsios D, Lithari C, Nakou M, Karlovasitou A. Cholinergic deficiency in Alzheimer's and Parkinson's disease: evaluation with pupillometry. Int J Psychophysiol. 2009;73(2):143-9.
  7. Stergiou V, Fotiou D, Tsiptsios D, Haidich B, Nakou M, Giantselidis C, Karlovasitou A. Pupillometric findings in patients with Parkinson's disease and cognitive disorder. Int J Psychophysiol. 2009;72(2):97-101.
  8. Fotiou DF, Brozou CG, Haidich AB, Tsiptsios D, Nakou M, Kabitsi A, Giantselidis C, Fotiou F. Pupil reaction to light in Alzheimer's disease: evaluation of pupil size changes and mobility. Aging Clin Exp Res. 2007;19(5):364-71.
  9. Fotiou F, Fountoulakis KN, Tsolaki M, Goulas A, Palikaras A. Changes in pupil reaction to light in Alzheimer's disease patients: a preliminary report. Int J Psychophysiol. 2000;37(1):111-20.
  10. Ghodse H, Taylor DR, Greaves JL, Britten AJ, Lynch D. The opiate addiction test: a clinical evaluation of a quick test for physical dependence on opiate drugs. Br J Clin Pharmacol. 1995;39(3):257-9.
  11. Krach S, Kamp-Becker I, Einhäuser W, Sommer J, Frässle S, Jansen A, Rademacher L, Müller-Pinzler L, Gazzola V, Paulus FM. Evidence from pupillometry and fMRI indicates reduced neural response during vicarious social pain but not physical pain in autism. Hum Brain Mapp. 2015;36(11):4730-44.
  12. Nuske HJ, Vivanti G, Hudry K, Dissanayake C. Pupillometry reveals reduced unconscious emotional reactivity in autism. Biol Psychol. 2014;101:24-35.
  13. Blaser E, Eglington L, Carter AS, Kaldy Z. Pupillometry reveals a mechanism for the Autism Spectrum Disorder (ASD) advantage in visual tasks. Sci Rep. 2014 7;4:4301.

14. Wang M, Corpuz CC, Huseynova T, Tomita M. Pupil Influence on the Visual Outcomes of a New-Generation Multifocal Toric Intraocular Lens With a Surface-Embedded Near Segment. J Refract Surg. 2016;32(2):90-5.

15. Kim MJ, Yoo YS, Joo CK, Yoon G. Evaluation of optical performance of 4 aspheric toric intraocular lenses using an optical bench system: Influence of pupil size, decentration, and rotation. J Cataract Refract Surg. 2015;41(10):2274-82.

16. Vega F, Alba-Bueno F, Millán MS, Varón C, Gil MA, Buil JA. Halo and Through-Focus Performance of Four Diffractive Multifocal Intraocular Lenses. Invest Ophthalmol Vis Sci. 2015;56(6):3967-75.

17. García-Domene MC, Felipe A, Peris-Martínez C, Navea A, Artigas JM, Pons ÁM. Image quality comparison of two multifocal IOLs: influence of the pupil. J Refract Surg. 2015;31(4):230-5.

18. Fliedner J1, Heine C, Bretthauer G, Wilhelm H. The pupil can control an artificial lens intuitively. Invest Ophthalmol Vis Sci. 2014;55(2):759-66.

19. Watanabe K, Negishi K, Dogru M, Yamaguchi T, Torii H, Tsubota K. Effect of pupil size on uncorrected visual acuity in pseudophakic eyes with astigmatism. J Refract Surg. 2013;29(1):25-9.

20. Merritt SL , Schnyders HC, Patel M, Basner RC, O'Neill W. Pupil staging and EEG measurement of sleepiness. Int J Psychophysiol. 2004 Mar;52(1):97-112.

21. Robert M. Stelmack* and Nathan Mandelzys. Psychophysiology Volume 12, Issue 5, pages 536–540, September 1975.

22. Wu EX , Laeng B, Magnussen S. Through the eyes of the own-race bias: eye-tracking and pupillometry during face recognition. Soc Neurosci. 2012;7(2):202-16.

23. Eric Granholm , Steven P. Verney. Pupillary responses and attentional allocation problems on the backward masking task in schizophrenia. International Journal of Psychophysiology Volume 52, Issue 1, March 2004, Pages 37–51.

24. Laeng B , Falkenberg L. Women's pupillary responses to sexually significant others during the hormonal cycle. Horm Behav. 2007 Nov;52(4):520-30. Epub 2007 Aug .

25. Jean Decety , Kalina J. Michalska and Katherine D. Kinzler. The Contribution of Emotion and Cognition to Moral Sensitivity: A Neurodevelopmental Study. Cerebral Cortex Advance Access published May 26, 2011.

26. Leigh Sepeta1 , Naotsugu Tsuchiya , Mari S Davies , Marian Sigman , Susan Y Bookheimer and Mirella Dapretto. Abnormal social reward processing in autism as indexed by pupillary responses to happy faces. Journal of Neurodevelopmental Disorders 2012, 4:17.

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