Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.7150/ijms.9303 http://scihub22266oqcxt.onion/10.7150/ijms.9303 C4057486!4057486 !24936142     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\24936142 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Int+J+Med+Sci 2014 ; 11 (8 ): 796-802 Nephropedia Template TP {{tp|p=24936142 |t=2014. Automated sleep apnea quantification based on respiratory movement |pdf=|usr=}}{{24936142 }} gab.com Text Automated sleep apnea quantification based on respiratory movement JO: Int J Med Sci http://www.kidney.de/pget.php?&tw=1&pmid=24936142 #FOAvip Obstructive sleep apnea (OSA) is a prevalent and treatable disorder of neurological and medical importance that is traditionally diagnosed through multi-channel laboratory polysomnography(PSG). However, OSA testing is increasingly performed with portable home devices using limited physiological channels. We tested the hypothesis that single channel respiratory effort alone could support automated quantification of apnea and hypopnea events. We developed a respiratory event detection algorithm applied to thoracic strain-belt data from patients with variable degrees of sleep apnea. We optimized parameters on a training set (n=57) and then tested performance on a validation set (n=59). The optimized algorithm correlated significantly with manual scoring in the validation set (R2=0.73 for training set, R2=0.55 for validation set; p<0.05). For dichotomous classification, the AUC was >0.92 and >0.85 using apnea-hypopnea index cutoff values of 5 and 15, respectively. Our findings demonstrate that manually scored AHI values can be approximated from thoracic movements alone. This finding has potential applications for automating laboratory PSG analysis as well as improving the performance of limited channel home monitors. Twit Text FOAVip Automated sleep apnea quantification based on respiratory movement ????Int J Med Sci http://www.kidney.de/pget.php?&tw=1&pmid=24936142 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=24936142 #FOAvip English Wikipedia <ref>{{Cite pmid|24936142 }}</ref> Automated sleep apnea quantification based on respiratory movement #MMPMID24936142 Bianchi MT ; Lipoma T ; Darling C ; Alameddine Y ; Westover MB Int J Med Sci 2014[]; 11 (8 ): 796-802 PMID24936142 show ga Obstructive sleep apnea (OSA) is a prevalent and treatable disorder of neurological and medical importance that is traditionally diagnosed through multi-channel laboratory polysomnography(PSG). However, OSA testing is increasingly performed with portable home devices using limited physiological channels. We tested the hypothesis that single channel respiratory effort alone could support automated quantification of apnea and hypopnea events. We developed a respiratory event detection algorithm applied to thoracic strain-belt data from patients with variable degrees of sleep apnea. We optimized parameters on a training set (n=57) and then tested performance on a validation set (n=59). The optimized algorithm correlated significantly with manual scoring in the validation set (R2=0.73 for training set, R2=0.55 for validation set; p<0.05). For dichotomous classification, the AUC was >0.92 and >0.85 using apnea-hypopnea index cutoff values of 5 and 15, respectively. Our findings demonstrate that manually scored AHI values can be approximated from thoracic movements alone. This finding has potential applications for automating laboratory PSG analysis as well as improving the performance of limited channel home monitors. |*Equipment Design [MESH] |*Respiration [MESH] |Adolescent [MESH] |Adult [MESH] |Aged [MESH] |Aged, 80 and over [MESH] |Algorithms [MESH] |Female [MESH] |Humans [MESH] |Male [MESH] |Middle Aged [MESH] |Polysomnography/*instrumentation/methods [MESH] |Sleep Apnea Syndromes/diagnosis/pathology [MESH]Automated sleep apnea quantification based on respiratory movement (epmc).pdf DeepDyve Pubget Overpricing