Journal of Clinical and Diagnostic Research. 2019 Apr, Vol-13(4): CM01-CM03 1 1 DOI: 10.7860/JCDR/2019/41051.12805 Short Communication Physiology Section An Innovative Technique to Evaluate Quantitative Pupillary Light Reﬂex by Dynamic Pupillometry using Infrared Videography INTRODUCTION The pupil is the central aperture of the iris that controls intensity of the light falling on the retina [1]. The pupil is controlled by sphincter pupillae and dilator pupillae [2]. The bright light and accommodation declines pupil size mediated by parasympathetic nerves [3]. The other stimulants like cognitive load and dark light cause dilation of pupil [4-6]. So the pupil size provides potential information in the diagnosis of the patient [7]. The measurement of the pupil’s reaction to light serves as a non-invasive tool in the ﬁeld of neuroscience [8]. The initial pupillometers were time consuming, low precision due to the low frame rate [9]. But, recently the automated pupillometers were evolved with high precision, reliability. However, these pupillometers are very expensive. The accuracy of the pupillary measurements increased over the years due to availability of cameras with good resolution and frame rate. With the advancement of optics, capturing good quality images has become easy. These cameras can also be used to capture pupil. The present study was aimed establish novel methodology to quantify pupillary light reﬂex. MATERIALS AND METHODS Instrument Design The PC based infra-red pupillometer was developed from a web camera (Technotech ZB V90 WEBCAM-640×380). The camera was dissected to remove the infra-red ﬁlter to capture pupil in darkness under infrared illumination. The camera was ﬁxed to a virtual reality box to create darkness. It is the easiest way to eliminate confounding factors related to illumination. Later the camera was surrounded with two 5 mm infra-red light emitting diodes 850 nm (5 milliwatt- for continuous illumination) to provide infra-red illumination in darkness for which pupil does not respond. A white LED (5 milli watt for 2000 milli second ﬂash) was also ﬁxed near the camera to produce a ﬂash of white light stimulus. The camera was ﬁxed at a spatial distance of seven centimetres from the anterior curvature of the eye which does not initiate accommodation reﬂex. The frame rate of the camera is 30 frames/sec with a resolution of 33.3 milli sec/frame. The system was connected to a microcontroller based electronic circuitry to control the intensity of Infra-red LED for continuous illumination and to provide two seconds white light ﬂash. The electronic circuitry was powered through the USB port of the computer. As the system works with 5 volt DC and its electronic circuit does not come in contact with the body surface and it is very safe to use. Methodology The modiﬁed ﬂexible virtual reality box ﬁts for everyone and also creates darkness. The recordings cannot be inﬂuenced by illumination of the surroundings due to the closed box. The real-time pupil examination can be seen on a large computer screen which is not possible in portable pupillometers. The video recording was done using Debut software (version 5.09, NCH software). It is free software for non- commercial use and was used in the current study for recording of the real-time pupillometry. It is user-friendly and easy to navigate with a logical layout. This software can modify the quality and resolution of the recording video ofﬂine. However, it does not change the dimensions of pupil throughout video frames. These video recordings were split into jpeg images using video splitter software (Video to jpeg converter Ver.5.0.101.201). Further, these images were subjected to image analysis software (ImageJ ver.1.43u National Institute of Health, USA). Image J: It is a Java-based image processing software developed at the National Institutes of Health (NIH) and the Laboratory for Optical and Computational Instrumentation. Image J was developed with an open source layout that can be customise with recordable macro java plugins for image processing and analysis. Image J built-in development environment has made it a popular platform for processing of images. The video frames obtained from recording pupil response were analysed in a batch using Image J software by customising java based macro plugin [10]. Steps of Image Processing Images can be analysed either individually or as a batch of images. These pictures for pupil can be measured either in pixels or in physical units with known distances as ﬁxing the scale which provides the area and diameter of the pupil. The following steps can be followed in order to identify and measure pupil dimensions [Table/Fig-1]. AV SIVA KUMAR 1 , R PADMAVATHI 2 , KN MARUTHY 3 , B SOWJANYA 4 , K MAHESH KUMAR 5 Keywords: Autonomic nervous system, Baseline pupil diameter, Image J, Light-emitting diode, Maximum constriction velocity ABSTRACT Introduction: An innovative approach was designed to quantify the pupillary light reﬂex using infrared and white light illumination. This method is convenient to detect pupil edges, area and the diameter of pupil contour recorded in different ambient light conditions. Aim: To establish newer methodology, to quantify pupillary light reﬂex using image analysis. Materials and Methods: A standard web camera was modiﬁed as an Infrared camera to capture the real time pupil response to various intensities of illuminations. Pupillary response to a ﬂash of light was video graphed and split into video frames. These images of the pupil thus obtained were subjected to an image analysing software. This methodology also provides a solution to exclude infra-red LED reﬂection within the pupil circle. The orientation of pupil within iris can be appreciated with this protocol. Results: The steps were tailored to measure various parameters of pupillary light reﬂex like minimum, maximum and mean pupil diameters. It also facilitates to calculate constriction and dilation velocities. The capture, cleavage and ofﬂine analysis of these video frames were done using all open source softwares. Conclusion: This simple, user-friendly, innovative technology can be used for quantifying the pupil response which can be used as an indicator for autonomic dysfunction.