Abstract

The authors present an algorithm based on the Karhunen-Loeave transform (KLT) for robust automated detection of ischemic ST segment episodes and measurement of the duration of ischemia in two-channel ambulatory electrocardiographic data. The algorithm operates as a postprocessor to an existing arrhythmia detector. The episode detector incorporates a single-scan trajectory recognition technique in the KLT feature space. The algorithm differentiates between true ischemic ST segment changes and non-ischemic ST deviations caused by axis shifts. In evaluations using the European Society of Cardiology ST-T database, the algorithm achieved a gross ST episode sensitivity of 85.2%, with a positive predictivity of 86.2%. The gross ischemic ST duration sensitivity was 75.8%, with a positive predictivity of 78.0%. >

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.