Open AccessDevelopment of Altera NIOS II Soft-core system to predict total Hemoglobin using Multivariate Analysis
Author(s) -
Caje Pinto,
Jivan S. Parab,
Marlon Sequeira,
Gourish M. Naik
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1921/1/012039
Subject(s) - multivariate statistics , hemoglobin , core (optical fiber) , multivariate analysis , computer science , medicine , mathematics , statistics , telecommunications
In Today’s world, Hemoglobin is measured using an invasive method. This method leads to delayed diagnosis, painful experiences for patients, and a lot of biomedical waste. To overcome these problems, an Altera NIOS II soft-core based system was built to monitor hemoglobin non-invasively. The heart of the system is NIOS II soft-core processor which was configured on the DE0 Nano FPGA board having Cyclone IV EP4CE22F17C6N. This system also has a finger probe which consists of five LED sources (670 nm, 770 nm, 810nm, 850nm and 950nm) and a photodetector (OPT101) to acquire the signal using photoplethysmography (PPG). The incoming real-time PPG signal is recorded at five different wavelengths for fifteen individual subjects. Before applying Multivariate Partial Least Square Regression (PLSR), mathematical empirical formulas was used to predict hemoglobin which gave Root Mean Square Error (RMSE) of 0.442 g/dL and the prediction accuracy of 97.05%. To further improve the system accuracy, the PLSR model was implemented on the NIOS II soft-core system. With this, the hemoglobin was predicted with an accuracy of 98.98% and a RMSE of 0.179 g/dL. The designed system was validated with Bland-Altman analysis which shows good agreement between predicted and reference hemoglobin