Key result
Various feature extraction techniques from photoplethysmogram waveforms, such as peak analysis and derivatives, show potential for non-invasive disease detection and cardiovascular monitoring.
Why the study?
Various feature extraction techniques from photoplethysmogram waveforms have been implemented for improved disease detection accuracy, warranting a comparative survey and reference.
This review synthesizes current techniques for extracting diagnostic features from PPG waveforms, providing a reference for future non-invasive healthcare applications.
May enable non-invasive cardiovascular monitoring; leaves open need for prospective validation before clinical use.
This paper presents a bibliographical survey of recently-published research on different techniques to extract feature from photoplethysmogram (PPG). These techniques and approaches have been implemented for better accuracy in detecting diseases. Moreover, several aspects in analyzing PPG waveform are discussed on the techniques in feature extraction, parameters involved and performance comparisons. This review will serve as a comparative study and reference for researches working on PPG waveform in health care applications.
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Hafifah et al. (2020) conducted a review in Cardiovascular and other diseases (via PPG analysis). Photoplethysmogram (PPG) feature extraction techniques was evaluated. Various feature extraction techniques from photoplethysmogram waveforms, such as peak analysis and derivatives, show potential for non-invasive disease detection and cardiovascular monitoring.
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