Abstract
Objective: Haemoglobin(Hb) measurement is generally performed by the traditional “fingerstick” test i.e., by invasively drawing blood from the body. Although the conventional laboratory measurement is accurate, it has its own limitations such as time delay, inconvenience of the patient, exposure to biohazards and the lack of real-time monitoring in critical situations. Non-invasive Haemoglobin Measurement (SpHb) has gained enormous attention among researches and can provide an earlier diagnosis to polycythemia, anaemia, various cardiovascular diseases, etc. Currently, Photoplethysmograph signal (PPG) is used for measuring oxygen saturation, to monitor the depth of anesthesia, heart rate and respiration monitoring. But through detailed statistical analysis, PPG signal can provide further information about various blood components. Investigation / Methodology: In this paper, an approach for non-invasive measurement of Hb using PPG, Principal Component Analysis (PCA) and Neural Network is proposed. A transmissive type PPG sensor is developed which is interfaced with Crowduino for the acquisition of PPG. From the obtained PPG signal, Principal Components (PC) are extracted. SpHb is predicted followed by the extraction of features from the PC. The analysis involves the SpHb prediction using a single PC, double PC and finally all the three PC. The predicted SpHb is evaluated with Hblab in terms of R-value, Mean Absolute Error, Mean Squared Error and Root Mean Squared Error. Conclusion: An approach for non-invasive measurement of Hb using Principal Components obtained from the PPG signal is discussed. The SpHb value is compared with the Hblab values. Correlation R-value between SpHb and Hblab is 0.77 when three principal components are used. Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE) between SpHb and Hblab are 0.3, 0.44 and 0.6633 respectively when SpHb is measured with three principal components. It is evident from the result analysis that SpHb shows the promising result when all the three principal components are used. However, one of the limitations of the work is that the population setting chosen for the work does not include paediatric patients, accurately ill patient, pregnant population and surgical patients. With detailed analysis on a wide range of population setting, Hb prediction using PPG is a promising approach for non-invasive measurement.
Highlights
Haemoglobin (Hb) is a complex protein molecule in red blood cells which is responsible for carrying oxygen from the lungs to the body's tissues and to return carbon dioxide from the tissues back to the lungs
An attempt has been made for non-invasive estimation of haemoglobin level by adopting Principal Component Analysis (PCA) [24] in combination with neural networks
The PCA has been performed on the Photoplethysmograph signal (PPG) signal to obtain principal components
Summary
Haemoglobin (Hb) is a complex protein molecule in red blood cells which is responsible for carrying oxygen from the lungs to the body's tissues and to return carbon dioxide from the tissues back to the lungs. To ensure adequate tissue oxygenation, to screen for and help diagnose conditions that affect Red Blood Cells (RBCs), to assess the severity and diagnosis of anaemia/polycythemia, sufficient haemoglobin level must be maintained. Haemoglobin measurement is one of Haemoglobin measurement is generally performed by the traditional “fingerstick” test i.e., by invasively drawing blood. The Open Biomedical Engineering Journal, 2019, Volume 13 115 from the body. The health professional will clean the finger, prick the tip of it with a tiny needle (or lancet) to collect the blood. Collecting a sample of blood is only temporarily uncomfortable and can feel like a quick pinprick. The conventional laboratory measurement is accurate, it has its own limitations such as time delay, inconvenience of the patient, exposure to biohazards and the lack of real-time monitoring in critical situations
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