Analysis of pupil fluctuations after a light stimulus by image processing and neural network
In this paper the analysis of pupil fluctuations after a light stimulus is considered; it is useful for non-invasive diagnosis of many different diseases. When a light stimulus is presented to a subject, the pupil response is not instantaneous because of the action of the sphincter muscle. A sequenc...
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| Published in | Computers & mathematics with applications (1987) Vol. 53; no. 8; pp. 1260 - 1270 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.04.2007
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| Abstract | In this paper the analysis of pupil fluctuations after a light stimulus is considered; it is useful for non-invasive diagnosis of many different diseases. When a light stimulus is presented to a subject, the pupil response is not instantaneous because of the action of the sphincter muscle. A sequence of images will be caught by a pupillometer and each image of the sequence will be binarized; for each segmented image, a useful parameter will be considered, the major diameter that is the length (in pixels) of the major axis of the ellipse that has the same second moments of the pupil. The aim is the identification of the response time after a light stimulus, from the sequence of the major diameters. The considered signal is degraded because of the presence of the measurement noise, the natural fluctuation of the pupil (usually called “pupil noise”), and the general health state of the subject. To enhance the significant part of this noisy signal a neural network is suitable trained. From the clean signal the identification of the response time of the pupil will be easier and a simple method will be proposed. |
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| AbstractList | In this paper the analysis of pupil fluctuations after a light stimulus is considered; it is useful for non-invasive diagnosis of many different diseases. When a light stimulus is presented to a subject, the pupil response is not instantaneous because of the action of the sphincter muscle. A sequence of images will be caught by a pupillometer and each image of the sequence will be binarized; for each segmented image, a useful parameter will be considered, the major diameter that is the length (in pixels) of the major axis of the ellipse that has the same second moments of the pupil. The aim is the identification of the response time after a light stimulus, from the sequence of the major diameters. The considered signal is degraded because of the presence of the measurement noise, the natural fluctuation of the pupil (usually called “pupil noise”), and the general health state of the subject. To enhance the significant part of this noisy signal a neural network is suitable trained. From the clean signal the identification of the response time of the pupil will be easier and a simple method will be proposed. |
| Author | Iacoviello, Daniela |
| Author_xml | – sequence: 1 givenname: Daniela surname: Iacoviello fullname: Iacoviello, Daniela email: iacoviel@dis.uniroma1.it organization: Department of Computer and Systems Science “Antonio Ruberti”, University of Rome “La Sapienza”, Via Eudossiana 18, 00184 Rome, Italy |
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| CitedBy_id | crossref_primary_10_1016_j_cegh_2020_01_010 crossref_primary_10_1002_mma_10677 crossref_primary_10_1002_col_22546 |
| Cites_doi | 10.1007/s002130000398 10.1016/j.ijpsycho.2003.12.007 10.2337/diacare.25.9.1545 10.1152/japplphysiol.00616.2002 10.1109/TBME.2005.851512 10.1016/S0167-8760(02)00122-8 10.1109/NEBC.1996.503246 10.1109/ICOSP.1998.770949 10.1167/iovs.02-0468 10.1016/0042-6989(94)00268-Q 10.1016/j.cmpb.2004.09.001 10.1109/10.942585 10.1136/bjo.85.10.1225 10.1016/j.ijpsycho.2003.12.004 10.1109/IEMBS.1997.756905 10.1109/10.376153 10.1016/S1071-5819(03)00122-8 10.1126/science.143.3611.1190 10.1002/ana.10556 10.1016/S0169-2607(98)00105-9 10.1109/TPAMI.2005.4 10.1016/j.ijfatigue.2004.01.004 10.1016/S0167-8760(98)00046-4 10.1016/j.jcrs.2004.09.057 10.1016/S0167-8760(00)00099-4 10.1016/j.physbeh.2004.02.008 10.1007/BF00688956 10.1016/j.jcrs.2003.09.060 10.1016/j.ijpsycho.2003.12.010 10.1016/j.biopsycho.2003.10.001 10.1055/s-0038-1634286 10.1016/S0886-3350(03)00619-9 10.1109/TELSKS.1999.806263 10.1016/0005-1098(92)90053-I |
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| Keywords | Artificial neural network Image binarization Pupil dynamic Latency |
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| Snippet | In this paper the analysis of pupil fluctuations after a light stimulus is considered; it is useful for non-invasive diagnosis of many different diseases. When... |
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| SubjectTerms | Artificial neural network Fluctuation Image binarization Latency Mathematical analysis Muscles Neural networks Noise Pupil dynamic Pupils Response time |
| Title | Analysis of pupil fluctuations after a light stimulus by image processing and neural network |
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