Key result
Advanced biomedical signal and image processing algorithms show promise for extracting physiological information.
Why the study?
Biomedical signal and image processing are widely used for extracting physiological information in clinical procedures, but their interactions and advanced algorithms require systematic review.
Systematic Review
Advanced algorithms in biomedical signal and image processing, particularly those using time-frequency representation, show significant promise for improving clinical procedures across various medical fields including cardiology.
Answers are grounded in this paper and cite their sources.
Supports multimodal ECG/EMG/EEG-image integration in diagnostics; extends time-frequency algorithm research for physiological signal extraction.
Biomedical signal and image processing establish a dynamic area of specialization in both academic as well as research aspects of biomedical engineering. The concepts of signal and image processing have been widely used for extracting the physiological information in implementing many clinical procedures for sophisticated medical practices and applications. In this paper, the relationship between electrophysiological signals, i.e., electrocardiogram (ECG), electromyogram (EMG), electroencephalogram (EEG) and functional image processing and their derived interactions have been discussed. Examples have been investigated in various case studies such as neurosciences, functional imaging, and cardiovascular system, by using different algorithms and methods. The interaction between the extracted information obtained from multiple signals and modalities seems to be very promising. The advanced algorithms and methods in the area of information retrieval based on time-frequency representation have been investigated. Finally, some examples of algorithms have been discussed in which the electrophysiological signals and functional images have been properly extracted and have a significant impact on various biomedical applications.
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Rajeswari et al. (2017) conducted a systematic review in Biomedical signal and image processing. Biomedical signal and image processing algorithms was evaluated. Advanced algorithms and methods in biomedical signal and image processing show promising interactions for extracting physiological information across various clinical applications.
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