Fuzzy-Based Bioengineering System for Predicting and Diagnosing Diseases of the Nervous System Triggered by the Interaction of Industrial Frequency Electromagnetic Fields
Abstract
Overview
This study aims to enhance the standard of medical care for individuals working in the electric power industry who are exposed to industrial frequency electromagnetic fields and associated risk factors. The researchers pursue this goal by integrating fuzzy mathematical models with modern information and intellectual technologies.
Approach
- Developed a methodological framework for synthesizing hybrid fuzzy decision rules, combining clinical expertise with artificial intelligence methodologies.
- Created an original method to evaluate the body's protective capacity, integrating this into decision rules to improve the precision and efficacy of medical decision-making.
Findings
- Industrial frequency electromagnetic fields contribute to illnesses of societal significance, particularly in electric power industry workers.
- These effects are aggravated by additional risk factors, including: adverse microclimates, noise, vibration, chemical exposure, and psychological stress.
- Diseases affecting the neurological, immunological, cardiovascular, genitourinary, respiratory, and digestive systems are linked to these exposures and individual physical traits.
Significance
The developed mathematical models enable early detection and diagnosis of disorders, especially those involving the autonomic nervous system and heart rhythm regulation, in individuals exposed to electromagnetic fields. The models have demonstrated high confidence and accuracy, supporting their use in the clinical treatment of electric power industry personnel.
Conclusion
The link between industrial frequency electromagnetic fields and increased risk for various diseases—particularly those affecting the nervous system and heart—highlights the importance of enhanced health surveillance and predictive technology integration for at-risk occupational groups.