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research-article

Research and Design of Neonatal Jaundice Detector Based on Color Sensor

Authors:

Qingping DengAuthors Info & Claims

DMIP '21: Proceedings of the 2021 4th International Conference on Digital Medicine and Image Processing

Pages 77 - 82

https://doi.org/10.1145/3506651.3506664

Published: 21 February 2022 Publication History

Abstract

Objective: To solve the problem of invasive detection of neonatal jaundice and prone to infection. Methods: A neonatal jaundice detector based on color sensing was proposed. The microprocessor controls the color sensor to read the RGB color components of the skin reflection, and performs a multiple linear regression model fitting with the serum total bilirubin to calculate the corresponding neonatal jaundice index. Results: The paired T test with JM-103 shows that the measurement results have good correlation. The Bland-Altman method was used in neonatal measurement to analyze and verify its consistency. Conclusion: The clinical comparison and verification show that the monitor can measure neonatal jaundice index, and the design has good applicability.

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Cited By

Kumar Pareek PK VN Prasad ADiggi PA D(2023)Classification for Jaundice Symptoms Using Improved Dragonfly with XGBoost Model2023 International Conference on Data Science and Network Security (ICDSNS)10.1109/ICDSNS58469.2023.10245611(1-7)Online publication date: 28-Jul-2023
https://doi.org/10.1109/ICDSNS58469.2023.10245611

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DMIP '21: Proceedings of the 2021 4th International Conference on Digital Medicine and Image Processing

November 2021

87 pages

ISBN:9781450386487

DOI:10.1145/3506651

Copyright © 2021 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 21 February 2022

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Medical Engineering Branch of Guangdong Medical Association

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DMIP '21

DMIP '21: 2021 4th International Conference on Digital Medicine and Image Processing

November 12 - 15, 2021

Kyoto, Japan

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Cited By

Kumar Pareek PK VN Prasad ADiggi PA D(2023)Classification for Jaundice Symptoms Using Improved Dragonfly with XGBoost Model2023 International Conference on Data Science and Network Security (ICDSNS)10.1109/ICDSNS58469.2023.10245611(1-7)Online publication date: 28-Jul-2023
https://doi.org/10.1109/ICDSNS58469.2023.10245611

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