Real-Time Signal Processing for Biomedical Applications Using MATLAB (Comprehensive Journal of Science, 2025)
Artificial Intelligence (AI) and advanced computational tools such as MATLAB have becomeessential in biomedical research and clinical practice. Real-time biomedical signal processingplays a critical role in improving patient monitoring, early diagnosis, and therapeutic interventions.Biomedical signals such as electrocardiograms (ECG), electroencephalograms (EEG), andelectromyograms (EMG) contain rich diagnostic information, but they are often contaminated byvarious sources of noise including power line interference, muscle artifacts, and baseline wander.Real-time signal processing ensures that physicians and automated systems can interpret thesesignals accurately and without delay, enabling prompt medical decisionsThis paper presents an overview of assisted real-time biomedical signal processing, wherein thestress is particular on ECG analysis. MATLAB offers an integrated environment with specialtytoolboxes such as Signal Processing Toolbox and DSP System Toolbox, where a researcher candesign, simulate, and implement algorithms in a real-time setting. MATLAB supports fastprototyping and testing of biomedical systems by the use of heavy filtering techniques and anactive real-time visualization tool. With this case study, the ECG signals are filtered through afourth-order Butterworth bandpass filter within the range of 0.5–40 Hz. With baseline drift andhigh-frequency noise being filtered out, the focus is so much on the clarity of the QRS complexand other important features of the ECG waveform. MATLAB allows for the continuous acquisitionof signals, instantaneous signal processing, and coordination with clinical monitoring systems fordisplaying both raw and filtered signals. Hence, the results show that good filtering could reducefalse alarms and ensure early detection of arrhythmias, thereby largely improving diagnosticaccuracy and patient safety
Keywords: Artificial Intelligence, MATLAB, Biomedical Signals, Real-Time Processing, ECG, EEG, Signal Filtering