Haemoglobin measurement from anterior ciliary arteries of human eyes using wavelet deep learning algorithms

Abstract

Smartphone with physiological sensors such as temperature, newlinepressure and SpO2 is used as human health monitoring instrument. newlineSmartphone based human health monitoring instrument is used for accurate newlinediagnosis of various disease/disorder through continous monitoring of newlinephysiological parameters such as blood pressure, SpO2 and glucose. Pregnant newlinewomen, pediatric and pulmonary hypertension patients require continuous newlinehaemoglobin (Hb) measurements for effective treatment. In conventional newlinemethod, haemoglobin measurement is done through the conjunctiva of eye, newlinewhich provides inaccurate result due to various eye disorder and eye diseases newlinesuch as digital eye strain, computer vision syndrome red eye, and increased newlineeye pressure. In conjunctiva of eye, decreased number of density in goblet newlinecells and acinar units in the meibomian glands of the human eye leads to newlineinaccurate measurement of haemoglobin. Moreover, conjunctivitis is an eye newlinedisease caused by inflammation or infection of the conjunctiva. The existing newlinemethod of haemoglobin measurement done in conjunctiva, result in inaccurate newlinevalues due to conjunctivitis eye disease. newlineIn this thesis, Smartphone-Based Haemoglobin (SBH) newlinemeasurement from the anterior ciliary arteries of the eye is proposed using a newlineborescope camera. Smartphone is connected with a high-megapixel borescope newlinecamera for development of SBH instrument. Borescope camera acquires newlineimage of anterior ciliary arteries region of human eye. newline