SIMULATION OF DIGITAL SIGNAL PROCESSING FOR NON-INVASIVE HBA1C MONITORING DEVICE

Diabetes mellitus (DM) is a chronic disease of metabolic disorder due to the pancreas not producing enough insulin or the body can not use insulin produced effectively. (Indonesian Ministry of Health data and information center, 2014). Monitoring the metabolic status of patients with diabetes mel...

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Bibliographic Details
Main Author: Ayu Permatasari, Indah
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/49506
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Institution: Institut Teknologi Bandung
Language: Indonesia
Description
Summary:Diabetes mellitus (DM) is a chronic disease of metabolic disorder due to the pancreas not producing enough insulin or the body can not use insulin produced effectively. (Indonesian Ministry of Health data and information center, 2014). Monitoring the metabolic status of patients with diabetes mellitus is an important part of its management. This monitoring can be done by checking blood glucose or HbA1c. HbA1c levels are tested to show average blood glucose levels for 8-12 weeks. Tests of HbA1c levels is commonly done in an invasive way. This method is done by doing a blood test in the laboratory. Test in the laboratory provides accurate results but requires a long time and must be expensive. Therefore, this final year project focuses on the development of a device that can detect HbA1c levels non-invasively by using the spectroscopy method. On the HbA1c monitoring device there is a digital signal processing sub-system. The sub-system include analog-to-digital conversion and digital filter. IIR (Infinite Impulse Response) and DEMA (Double Exponential Moving Average) is used to reduce noise from PPG signal. Due to limitations caused by the COVID-19 pandemic, the implementation and testing for this final year project is still in the form of circuit simulation. Further work need to be done for physical realization and testing of the design. Simulations are performed to test the filters that have been designed. Synthetic data which is obtained from the modification of the reference dataset is used as an input filter. The performance of the proposed method is evaluated by SNR (Signalto-Noise Ratio). The experimental result shows that the proposed digital filter can increase SNR value of signal around 5-30 dB for noise frequency below 0.5 Hz and above 5 Hz. The evalution show that the proposed digital filter is effective for reducing noise. The maximum value and a minimum value of PPG signal are determined after a clean signal is obtained. The values are sent to an Androidbased smartphone using bluetooth communication.