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10.3390/bios7030040 http://scihub22266oqcxt.onion/10.3390/bios7030040 C5618046!5618046!28930184     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=28930184&cmd=llinks): Failed to open stream: HTTP request failed! 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Use of Wavelet Transform to Detect Compensated and Decompensated Stages in the Congestive Heart Failure Patient |pdf=|usr=}}{{28930184}} gab.com Text Use of Wavelet Transform to Detect Compensated and Decompensated Stages in the Congestive Heart Failure Patient JO: Biosensors (Basel) http://www.kidney.de/pget.php?&tw=1&pmid=28930184 #FOAvip This research work is aimed at improving health care, reducing cost, and the occurrence of emergency hospitalization in patients with Congestive Heart Failure (CHF) by analyzing heart and lung sounds to distinguish between the compensated and decompensated states. Compensated state defines stable state of the patient but with lack of retention of fluids in lungs, whereas decompensated state leads to unstable state of the patient with lots of fluid retention in the lungs, where the patient needs medication. Acoustic signals from the heart and the lung were analyzed using wavelet transforms to measure changes in the CHF patient?s status from the decompensated to compensated and vice versa. Measurements were taken on CHF patients diagnosed to be in compensated and decompensated states by using a digital stethoscope and electrocardiogram (ECG) in order to monitor their progress in the management of their disease. Analysis of acoustic signals of the heart due to the opening and closing of heart valves as well as the acoustic signals of the lungs due to respiration and the ECG signals are presented. Fourier, short-time Fourier, and wavelet transforms are evaluated to determine the best method to detect shifts in the status of a CHF patient. The power spectra obtained through the Fourier transform produced results that differentiate the signals from healthy people and CHF patients, while the short-time Fourier transform (STFT) technique did not provide the desired results. The most promising results were obtained by using wavelet analysis. Wavelet transforms provide better resolution, in time, for higher frequencies, and a better resolution, in frequency, for lower frequencies. Twit Text FOAVip Use of Wavelet Transform to Detect Compensated and Decompensated Stages in the Congestive Heart Failure Patient ????Biosensors (Basel) http://www.kidney.de/pget.php?&tw=1&pmid=28930184 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28930184 #FOAvip English Wikipedia <ref>{{Cite pmid|28930184}}</ref> Use of Wavelet Transform to Detect Compensated and Decompensated Stages in the Congestive Heart Failure Patient #MMPMID28930184 Sharma P; Newman K; Long CS; Gasiewski AJ; Barnes F Biosensors (Basel) 2017[Sep]; 7 (3): ä PMID28930184show ga This research work is aimed at improving health care, reducing cost, and the occurrence of emergency hospitalization in patients with Congestive Heart Failure (CHF) by analyzing heart and lung sounds to distinguish between the compensated and decompensated states. Compensated state defines stable state of the patient but with lack of retention of fluids in lungs, whereas decompensated state leads to unstable state of the patient with lots of fluid retention in the lungs, where the patient needs medication. Acoustic signals from the heart and the lung were analyzed using wavelet transforms to measure changes in the CHF patient?s status from the decompensated to compensated and vice versa. Measurements were taken on CHF patients diagnosed to be in compensated and decompensated states by using a digital stethoscope and electrocardiogram (ECG) in order to monitor their progress in the management of their disease. Analysis of acoustic signals of the heart due to the opening and closing of heart valves as well as the acoustic signals of the lungs due to respiration and the ECG signals are presented. Fourier, short-time Fourier, and wavelet transforms are evaluated to determine the best method to detect shifts in the status of a CHF patient. The power spectra obtained through the Fourier transform produced results that differentiate the signals from healthy people and CHF patients, while the short-time Fourier transform (STFT) technique did not provide the desired results. The most promising results were obtained by using wavelet analysis. Wavelet transforms provide better resolution, in time, for higher frequencies, and a better resolution, in frequency, for lower frequencies. äUse of Wavelet Transform to Detect Compensated and Decompensated Stage(epmc).pdf DeepDyve Pubget Overpricing