PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

The article describes the principles of developing a preprocessing algorithm for electro cardio signals in an in-house wireless automated Holter cardiac activity monitoring system. The system stands out for lower energy consumption due to the compression and processing of transmitted information. The article's authors propose a wireless electro cardio signal transmission method based on energy-saving Wi-Fi technologies for transmitting electro cardio signals. The article also includes a step-by-step electro cardio signal filtering technique, which lies in an algorithm combining wavelet compression and low-frequency filtering and an algorithm for high-frequency and neural network filtering of transmitted electro cardio signals, ensuring high reliability of the transmitted electrocardiographic (ECG) information. The authors developed a Holter monitoring system model, which includes real-time MATLAB system packages, the PhysioBank’s Automated Teller Machine electro cardio signal database, and an external wireless subsystem for transmitting ECG information. The authors also present a real-virtual complex for setting up and implementing the algorithm of the developed system, providing a wide range of software and hardware tools, including specialised MATLAB system packages for setting up, debugging, and optimising operating modes. The analysis of the obtained time diagrammes showed no interferences after the signal reception, transmission, and processing, and the valuable signal increased fourfold. This electro cardio signal processing enhances the quality of ECG identification and interpretation. The developed wavelet-based algorithm provides an ECG data compression ratio of about 8:1, ensuring the preservation of diagnostically important signal features. The proposed methods and algorithms ensure high-quality, multi-day wireless transmission of ECG signals with low energy consumption.