Certain investigations on VLSI implementation of FIR filtering with secured STBC Alamouti Transmission and Classifiers for FECG Signal

Abstract

The evolution of healthcare technology has enabled innovative approaches to patient care, with remote health monitoring systems emerging as a significant advancement. The importance of remote health monitoring systems has been underscored during the COVID-19 pandemic and other emergencies. These systems enable more effective management of chronic conditions, timely interventions, and a higher quality of life for patients by leveraging technology to provide continuous monitoring and real-time data analysis. Fetal Electrocardiography (FECG) is crucial in prenatal care as it provides detailed information about the fetal heart electrical activity. Continuous and accurate monitoring of FECG can identify early signs of fetal distress and other issues, enabling timely medical intervention. Traditional methods of FECG monitoring often require frequent visits to the clinic, which can be challenging for patients in remote or underserved areas. Moreover, transmitting sensitive medical data over wireless networks raises concerns about data integrity, reliability, and security. This research presents an integrated approach to FECG signal processing and incorporating encryption methods for safety and data integrity. In addition, the research proposes the reliable wireless transmission method to prevent the fading of the signals in the transmission medium and machine learning algorithms for feature extraction and classification to facilitate the automation in analysis of the signal. newlineThe FECG signal is derived from the Non-Invasive Fetal ECG Arrhythmia database in the Physionet database. The FECG signal is contaminated by the powerline noises and baseline wanderer noises due to the electrodes. The powerline and baseline wanderer noises can be filtered by the design of Finite Impulse Response (FIR) bandpass filter by using low power VLSI techniques to eliminate noise and artifacts from the FECG signal. newline