HARNESSING FRACTAL THEORY FOR BIOMEDICAL SIGNAL ANALYSIS: A COMPREHENSIVE REVIEW

Najmeh Pakniyat, Jamaluddin Abdullah, Gaurav Agarwal, Ondrej Krejcar and Hamidreza Namazi
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Najmeh Pakniyat: 30 Shore Breeze Drive, Toronto, ON M8V 0J1, Canada
Jamaluddin Abdullah: ��School of Mechanical Engineering, Universiti Sains Malaysia, Penang, Malaysia
Gaurav Agarwal: ��School of Computer Science & Engineering, Galgotias University, Greater Noida, Uttar Pradesh, India
Ondrej Krejcar: �Faculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove, Czech Republic
Hamidreza Namazi: �Faculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove, Czech Republic¶Biomedical Signal and Image Processing Lab, Galgotias University, Greater Noida, Uttar Pradesh, India

FRACTALS (fractals), 2025, vol. 33, issue 05, 1-11

Abstract: Fractal theory has become an essential tool for analyzing complex biomedical signals, offering novel methods to interpret physiological data that traditional approaches struggle to decipher. This review explores how fractal analysis has transformed clinical diagnostics, disease monitoring, and personalized treatment planning across various biomedical domains, including Electrocardiography (ECG), Electroencephalography (EEG), Electromyography (EMG), Phonocardiogram (PCG), Magnetoencephalography (MEG), and Galvanic Skin Response (GSR). Key advancements, such as early detection of cardiac anomalies, differentiation of neurological disorders, and improved neuromuscular rehabilitation, underscore the clinical relevance of fractal-based methods. By identifying subtle patterns in physiological signals, fractal analysis enhances the precision of diagnosis, and supports real-time monitoring in clinical practice. The review also examines the challenges of implementing fractal techniques in healthcare, including data noise, nonstationarity, and algorithm optimization; Future innovations, particularly the integration of machine learning and real-time monitoring systems, hold significant potential for advancing biomedical research and improving patient outcomes. This work highlights fractal analysis as a vital asset in modern medicine, bridging the gap between complex data interpretation and effective clinical application.

Keywords: Fractal Theory; Biomedical Signal Analysis; Complexity; Clinical Applications (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1142/S0218348X25300016

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