Key result
Advanced digital signal processing methods reduce noise to improve cardiac bioelectrical signal quality.
Why the study?
Advanced signal processing methods are rapidly developing in biomedical engineering with increasing usage in clinical practice, warranting a comprehensive review of cardiac bioelectrical signal processing.
This review provides a comprehensive overview of signal processing techniques essential for reducing noise and extracting diagnostic information from ECG and other cardiac bioelectrical signals.
Advanced signal processing methods are one of the fastest developing scientific and technical areas of biomedical engineering with increasing usage in current clinical practice. This paper presents an extensive literature review of the methods for the digital signal processing of cardiac bioelectrical signals that are commonly applied in today's clinical practice. This work covers the definition of bioelectrical signals. It also covers to the extreme extent of classical and advanced approaches to the alleviation of noise contamination such as digital adaptive and non-adaptive filtering, signal decomposition methods based on blind source separation and wavelet transform.
No takes yet. Share an insight, caveat, or question.
Martínek et al. (2021) reported a review. Advanced bioelectrical signal processing methods was evaluated. Advanced digital signal processing methods, including adaptive filtering and wavelet transforms, are comprehensively reviewed for their role in alleviating noise in cardiac bioelectrical signals.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: