Open Access

ARTICLE

Haemoglobin Measurement from Eye Anterior Ciliary Arteries through Borescope Camera

Mohamed Abbas Ahamed Farook^1,*, S. Rukmanidevi², N. R. Shanker³

1 Department of Electronics and Communication Engineering, Vel Tech Multi Tech Dr Rangarajan Dr Sakunthala Engineering College, Chennai, 600062, India
2 Department of Electronics and Communication Engineering, R.M.D Engineering College, Chennai, 601206, India
3 Department of Computer Science and Engineering, Aalim Muhammed Salegh College of Engineering, Chennai, 600055, India

* Corresponding Author: Mohamed Abbas Ahamed Farook. Email:

Computer Systems Science and Engineering 2023, 44(2), 1763-1774. https://doi.org/10.32604/csse.2023.026260

Received 20 December 2021; Accepted 02 March 2022; Issue published 15 June 2022

Abstract

Nowadays, smartphones are used as self-health monitoring devices for humans. Self-health monitoring devices help clinicians with big data for accurate diagnosis and guidance for treatment through repetitive measurement. Repetitive measurement of haemoglobin requires for pregnant women, pediatric, pulmonary hypertension and obstetric patients. Noninvasive haemoglobin measurement through conjunctiva leads to inaccurate measurement. The inaccuracy is due to a decrease in the density of goblet cells and acinar units in Meibomian glands in the human eye as age increases. Furthermore, conjunctivitis is a disease in the eye due to inflammation or infection at the conjunctiva. Conjunctivitis is in the form of lines in the eyelid and covers the white part of the eyeball. Moreover, small blood vessels in eye regions of conjunctiva inflammations are not visible to the human eye or standard camera. This paper proposes smartphone-based haemoglobin (SBH) measurement through a borescope camera from anterior ciliary arteries of the eye for the above problem. The proposed SBH method acquires images from the anterior ciliary arteries region of the eye through a smartphone attached with a high megapixel borescope camera. The anterior ciliary arteries are projected through transverse dyadic wavelet transform (TDyWT) and applied with delta segmentation to obtain blood cells from the ciliary arteries of the eye. Furthermore, the Gaussian regression algorithm measures haemoglobin (Hb) with more accuracy based on the person, eye arteries, red pixel statistical parameters obtained from the left and right eye, age, and weight. Furthermore, the experimental result of the proposed SBH method has an accuracy of 96% in haemoglobin measurement.

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Keywords

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