A PHP Error was encountered

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: 1034
Function: getPubMedXML

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016

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

Amplitude based beat detection for atrial fibrillation in pacemaker. | LitMetric

Bradycardia is defined as a sinus rhythm of less than 60 beats per minute and atrial tachyarrhythmia including atrial fibrillation (AF) is frequently associated with bradycardia. Pacemaker is the only effective treatment for symptomatic bradycardia and automatic mode switching (AMS) function is built in pacemaker to switch mode in the presence of atrial tachyarrhythmia. AMS algorithms consider appropriate mode switching in case of undersensing or oversensing and this consideration makes their onset time and resynchronization time late. Current pacemakers have onset time from 2.5 seconds to 26 seconds and resynchronization time from 3.4 seconds to 143 seconds according to manufacturers. In this work, we proposed beat detection algorithm based on amplitude difference between peak and trough for accurate extraction of atrial rate achieving faster mode switching. Evaluation of beat detection algorithm was conducted with six canine AF electrogram (EGM) data. Result showed 96.64% sensitivity, 95.5% positive predictive value in average. With this, transition from AF to normal sinus rhythm could be detected faster than existing AMS algorithms. In conclusion, proposed algorithm can efficiently detect beats in EGM during AF and from this, we can implement faster AMS algorithm.

Download full-text PDF

Source
http://dx.doi.org/10.1109/EMBC.2016.7591301DOI Listing

Publication Analysis

Top Keywords

beat detection
12
mode switching
12
atrial fibrillation
8
sinus rhythm
8
atrial tachyarrhythmia
8
ams algorithms
8
onset time
8
resynchronization time
8
time seconds
8
detection algorithm
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!