Photoplethysmography (PPG) Scheming System Based on Finite Impulse Response (FIR) Filter Design in Biomedical Applications

Abstract

Photoplethysmography (PPG) is a non-invasive technique that measures relative blood volume changes in the blood vessels close to the skin. This research work intends to design a real-time filtering system. There are two main parts in this heart rate detection system: the data-gathering portion and real-time processing. Both processing includes preprocessing and filtering in which PPG signals derive from the pulse sensor in the data-gathering stage. It filters from PPG signal in real-time processing. In the data-gathering stage, the PPG signal is first derived from the pulse sensor, and then it is preprocessed to remove noise and enhance the signal quality to collect the paired-pulse index (PPI). After the signal has been preprocessed, the PPI is extracted from the signal, and this signal with features is collected as a data point to give an input signal for Raspberry Pi to draw the heat rate plot. In this system implementation, the pulse sensor is used to detect the heart-beat information of blood stream. This computer-aided system may also help patients save their time being spent waiting for doctors’ decisions. Biomedical analysis, digital signal processing, image processing, and data analysis become important factors for the automatic diagnosis system.