This paper explores the integration of computational intelligence techniques in the field of biomedical signal processing. Biomedical signal processing involves the analysis and interpretation of biological signals to aid in the diagnosis, treatment, and monitoring of diseases. The rapid advancements in computational intelligence have provided new avenues for improving the effectiveness and accuracy of biomedical signal processing. This study delves into various computational intelligence methods such as artificial neural networks, evolutionary algorithms, and fuzzy logic systems, and examines their applications in signal acquisition, feature extraction, noise reduction, and classification tasks. The paper further investigates the challenges faced in implementing these methods and proposes potential solutions. Through a comprehensive analysis of the literature, this study highlights the significance of computational intelligence in enhancing the capabilities of biomedical signal processing, thereby contributing to the advancement of healthcare technology.
Harris, E. Computational Intelligence in Biomedical Signal Processing. Transactions on Engineering and Technology, 2020, 2, 13. https://doi.org/10.69610/j.tet.20201021
AMA Style
Harris E. Computational Intelligence in Biomedical Signal Processing. Transactions on Engineering and Technology; 2020, 2(2):13. https://doi.org/10.69610/j.tet.20201021
Chicago/Turabian Style
Harris, Emma 2020. "Computational Intelligence in Biomedical Signal Processing" Transactions on Engineering and Technology 2, no.2:13. https://doi.org/10.69610/j.tet.20201021
APA style
Harris, E. (2020). Computational Intelligence in Biomedical Signal Processing. Transactions on Engineering and Technology, 2(2), 13. https://doi.org/10.69610/j.tet.20201021
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