ECG quality measures in telecare monitoring.
We analyze the use of unsupervised ECG acquisition in the home environment. An algorithm for automatically marking ECG recordings for sections of obvious artifact is described. The algorithm was validated against a set of 150 records randomly chosen from a database of ECGs and manually annotated to identify sections of artifact. Using this algorithm 4751 single lead-I ECG recordings from 24 home-dwelling patients were examined. The ECGs were collected using a remote home monitoring system. The participant ages (N=24) ranged from 54-92 years and were suffering either chronic obstructive pulmonary disease and/or congestive heart failure. Percentages of amplifier saturation, high frequency artifact, low signal power and the maximum continuous section of useable ECG are quoted. 1344 records were found to contain no artifact, while 3506 records contained 10 seconds or more of uninterrupted ECG (including the 1344 with no artifact). The results show that in the majority of cases, the capture of ECG in an unsupervised home environment is achievable.
Redmond
Stephen J
SJ
Graduate School of Biomedical Engineering, University of New South Wales, Sydney NSW, Australia.
Lovell
Nigel H
NH
Basilakis
Jim
J
Celler
Branko G
BG
D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation* / Q000379:methods*; D004562:Electrocardiography / Q000295:instrumentation* / Q000379:methods*; D004867:Equipment Design; D006333:Heart Failure / Q000503:physiopathology*; D006801:Humans; D008875:Middle Aged; D011237:Predictive Value of Tests; D029424:Pulmonary Disease, Chronic Obstructive / Q000503:physiopathology*; D011786:Quality Control; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D017216:Telemedicine / Q000295:instrumentation* / Q000379:methods