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Article type: Other
Authors: Muthalagu, Rajaa; * | Bai, Vijayan Thulasib | Gracias, Doreenc | John, Sheilad
Affiliations: [a] Department of Electronics and Communication Engineering, Dhanalakshmi College of Engineering, Anna University, Chennai, India | [b] Department of Electronics and Communication Engineering, KCG College of Technology, Chennai, India | [c] NABL, Clinical Haematology and Clinical Pathology, Sankara Nethralaya, Chennai, India | [d] Department of Teleophthalmology, Sankara Nethralaya, Chennai, India
Correspondence: [*] Corresponding author: Raja Muthalagu, Department of Electronics and Communication Engineering, Dhanalakshmi College of Engineering, Anna University, Chennai, India. E-mail: [email protected].
Abstract: Anaemia is predicted as one of the serious communal health issue in the world. The deficiency exists most common among children and women. A substantial issue prevails in providing quality healthcare services to rural communities, which remains a challenge to health service providers throughout the world. Traditionally physician and health workers recognized anaemia from certain clinical findings, such as pallor of the conjunctivae, nail beds, lips, tongue, and oral mucosa. Confirmation of anaemic condition through physical examination of Dorsum of a tongue or lower bulbar conjunctiva is a subjective analysis. Invasive methods have a possibility to spread infection through the needle. The existing non-invasive techniques need costly equipment and qualified technicians. Growing developments in science and technologies play an important role in medicine. This proposal introduces a new non-invasive diagnostic tool correlating the hemoglobin with conjunctiva pallor colour scores and classification using neural networks. In this study, the eye images were obtained using a mobile camera were processed using the HSI model, which estimates different colour scores of the selected region. These scores were correlated with laboratory haemoglobin value. Feedforward neural network and Elman neural network were used for classifying anaemic and non-anaemic cases. This proposed tool will be useful for the health workers to identify the mass screening of anaemia in rural areas.
Keywords: Anaemia, haemoglobin conjunctiva pallor, neural network, HSI model, screening tool
DOI: 10.3233/THC-181291
Journal: Technology and Health Care, vol. 26, no. 4, pp. 723-727, 2018
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