当前位置： SCI文献检索 > JOURNAL OF ELECTROCARDIOLOGY期刊下所有文献 > Automatic detection of ECG cable interchange by analyzing both morphology and interlead relations.

Automatic detection of ECG cable interchange by analyzing both morphology and interlead relations.

Abstract：

BACKGROUND:ECG cable interchange can generate erroneous diagnoses. For algorithms detecting ECG cable interchange, high specificity is required to maintain a low total false positive rate because the prevalence of interchange is low. In this study, we propose and evaluate an improved algorithm for automatic detection and classification of ECG cable interchange. METHOD:The algorithm was developed by using both ECG morphology information and redundancy information. ECG morphology features included QRS-T and P-wave amplitude, frontal axis and clockwise vector loop rotation. The redundancy features were derived based on the EASI™ lead system transformation. The classification was implemented using linear support vector machine. The development database came from multiple sources including both normal subjects and cardiac patients. An independent database was used to test the algorithm performance. Common cable interchanges were simulated by swapping either limb cables or precordial cables. RESULTS:For the whole validation database, the overall sensitivity and specificity for detecting precordial cable interchange were 56.5% and 99.9%, and the sensitivity and specificity for detecting limb cable interchange (excluding left arm-left leg interchange) were 93.8% and 99.9%. Defining precordial cable interchange or limb cable interchange as a single positive event, the total false positive rate was 0.7%. When the algorithm was designed for higher sensitivity, the sensitivity for detecting precordial cable interchange increased to 74.6% and the total false positive rate increased to 2.7%, while the sensitivity for detecting limb cable interchange was maintained at 93.8%. The low total false positive rate was maintained at 0.6% for the more abnormal subset of the validation database including only hypertrophy and infarction patients. CONCLUSION:The proposed algorithm can detect and classify ECG cable interchanges with high specificity and low total false positive rate, at the cost of decreased sensitivity for certain precordial cable interchanges. The algorithm could also be configured for higher sensitivity for different applications where a lower specificity can be tolerated.

journal_name

J Electrocardiol

journal_title

Journal of electrocardiology

authors

Han C,Gregg RE,Feild DQ,Babaeizadeh S

doi

10.1016/j.jelectrocard.2014.08.006

subject

Has Abstract

pub_date

2014-11-01 00:00:00

pages

781-7

issue

eissn

0022-0736

issn

1532-8430

pii

S0022-0736(14)00312-4

journal_volume

pub_type

杂志文章

在线工具

Automatic detection of ECG cable interchange by analyzing both morphology and interlead relations.