Work place: Department of Biomedical Engineering, Khulna University of Engineering and Technology, Khulna-9203, Bangladesh
E-mail: altabhossain68743@gmail.com
Website: https://orcid.org/0000-0003-3720-3883
Research Interests:
Biography
Md. Altab Hossain received his B.Sc. degree in Biomedical Engineering from Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh. His research interests include biomedical instrumentation, biomedical signal and image processing, machine learning in healthcare, clinical engineering, healthcare systems, and the study of brain function using functional near-infrared spectroscopy (fNIRS).
By Md. Altab Hossain Sheikh Md. Rabiul Islam
DOI: https://doi.org/10.5815/ijigsp.2025.06.04, Pub. Date: 8 Dec. 2025
A noninvasive blood hemoglobin monitoring device was designed specifically for monitoring anemia and polycythemia. Invasive techniques, which are painful and expensive, are commonly used to estimate blood hemoglobin concentrations. This paper presents a noninvasive method for monitoring blood hemoglobin values. A photodiode and a near-infrared (NIR) LED with a wavelength of 940 nm were used to construct a finger probe. At 940 nm wavelength shows distinct variation between oxygenated and deoxygenated hemoglobin and single-wavelength systems significantly reduce hardware complexity, cost, power consumption, and size. Use a continuous-wave NIR LED light through the finger to check the sensitivity of different hemoglobin concentrations. A total of 100 patients participated in our proposed device for evaluating noninvasive hemoglobin concentration. These participants collected both invasive and noninvasive hemoglobin concentration values. The correlation coefficient between the predicted (noninvasive) hemoglobin value and the reference (invasive) hemoglobin value was 0.9496, with a normalized root mean squared error (NRMSE) of 0.6504 and a mean absolute percentage error (MAPE) of 0.0505. The noninvasive blood hemoglobin level was classified using the k-nearest neighbour (kNN) classifier, and the proposed device accuracy was calculated at 90%. The Bland-Altman methodology evaluated differences between invasive and noninvasive blood hemoglobin concentrations. The absolute mean difference was 0.1124 (95% confidence interval [CI] -0.01535 to 0.2401), with an upper agreement limit of 1.374 (95% CI [1.153 - 1.595]) and a lower agreement limit of -1.149 (95% CI [-1.371 - 0.9282]).
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