HARNESSING FRACTAL THEORY FOR BIOMEDICAL SIGNAL ANALYSIS: A COMPREHENSIVE REVIEW
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F25%3A50022383" target="_blank" >RIV/62690094:18450/25:50022383 - isvavai.cz</a>
Result on the web
<a href="https://www.worldscientific.com/doi/10.1142/S0218348X25300016" target="_blank" >https://www.worldscientific.com/doi/10.1142/S0218348X25300016</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1142/S0218348X25300016" target="_blank" >10.1142/S0218348X25300016</a>
Alternative languages
Result language
angličtina
Original language name
HARNESSING FRACTAL THEORY FOR BIOMEDICAL SIGNAL ANALYSIS: A COMPREHENSIVE REVIEW
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Fractals
ISSN
0218-348X
e-ISSN
1793-6543
Volume of the periodical
33
Issue of the periodical within the volume
5
Country of publishing house
SG - SINGAPORE
Number of pages
11
Pages from-to
"Article number: 2530001"
UT code for WoS article
001477404600001
EID of the result in the Scopus database
2-s2.0-105003891184