Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Quantitative sleep analysis through the use of polysomnography is a well established standard. Finding new ways to approach this, especially over multiple nights, is becoming more important due to a growing recognition of adverse effects from poor sleep and sleep disorders. The Non-Invasive Analysis of Physiological Signals (NAPS) system is a ballistocardiography-based monitoring system developed to measure heart rate, breathing rate and musculoskeletal movement that shows promise as a general sleep analysis tool. Overnight sleep studies were conducted on 20 healthy subjects during a validation clinical trial which compared the NAPS system to actigraphy, using polysomnography as the gold standard. The NAPS system [kappa=0.478; 95% CI (0.463, 0.494); p-value<0.001] outperformed actigraphy [kappa=0.344; 95% CI (0.324, 0.358); p-value<0.001], largely due to better performance in distinguishing sleep onset times as determined by polysomnography [NAPS mean bias estimate: -2.5 epochs; 95% CI (-16.8, 11.9); p=0.725|Actigraphy mean bias estimate: -33.6 epochs; 95% CI (-57.4, -9.7); p=0.016)].
Download full-text PDF |
Source |
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http://dx.doi.org/10.1109/IEMBS.2009.5333805 | DOI Listing |
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