Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Jain, Divya; Tiwari, Vibha; Tiwari, Akshra; Khare, Suyash Title A name given to the resource Time-Frequency Analysis of ECG Signal Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Time-Frequency Analysis in Biomedical Engineering: Contemporary Methods and Applications;pp.37-58 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1201/9781003611448-4" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003611448-4</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105037895207?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105037895207?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Jain D., Oriental College of Technology, Madhya Pradesh, Bhopal, India; Tiwari V., Centre for Artificial Intelligence, Madhav Institute of Technology and Science, Deemed University Gwalior, Madhya Pradesh, India; Tiwari A., School of Sciences, Christ University, Delhi, India; Khare S., Centre for Artificial Intelligence, Madhav Institute of Technology and Science, Deemed University, Gwalior, India Description An account of the resource Time-frequency analysis (TFA), especially well suited for biomedical applications, is a potent method for deciphering non-stationary signals, where frequency characteristics vary with time. These dynamic signals are too complex for conventional frequency analysis approaches, which calls for sophisticated techniques like the discrete wavelet transform, continuous wavelet transform, and short-time Fourier transform. This research focuses on the uses of TFA techniques in biomedical signal processing and how well they expose transitory phenomena and temporal patterns that are missed by conventional methods. In particular, we look at how TFA is applied to the analysis of electrocardiogram (ECG) signals. The chapter discusses baseline wander, notch filtering, and low-pass filtering as crucial pre-processing techniques for clean ECG readings. Furthermore, we present the symbolic aggregate approximation paradigm for effective data retrieval and storage. 2026 selection and editorial matter, Ganesh R. Naik. Publisher An entity responsible for making the resource available CRC Press Relation A related resource ISBN: 978-104056627-5; 978-104100745-6; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online