Classification of ischaemic episodes with ST/HR diagrams

Area of Science:

• Cardiology
• Biomedical Engineering
• Medical Diagnostics

Background:

• Coronary artery disease is a leading cause of mortality and myocardial ischemia.
• Electrocardiogram (ECG) ST segment deviation is a key indicator, but ambulatory ECG analysis is complicated by non-ischemic, heart rate-related episodes.
• Distinguishing between ischemic and non-ischemic ST deviations is crucial for accurate diagnosis.

Purpose of the Study:

• To adapt features from exercise ECG for heart rate adjustment of ST segment depression.
• To apply these features to ambulatory ECG for improved detection of ischemic events.
• To differentiate between true ischemic ST segment deviations and non-ischemic, heart rate-related variations.

Main Methods:

• Utilized annotations from the Long-Term ST Database for ST/HR (heart rate) diagram plotting.
• Estimated overall and maximal slopes of ST/HR diagrams during exercise and recovery phases.
• Calculated the angle at the extrema of the ST/HR diagrams for each ST segment deviation episode.

Main Results:

• Ischemic ST segment deviation episodes exhibited significantly steeper overall and maximal slopes compared to heart rate-related episodes.
• The explored features demonstrated utility in statistically differentiating between ischemic and non-ischemic ST deviations.
• The proposed features showed promise for enhancing automated ECG analysis.

Conclusions:

• Transformed exercise ECG features are effective for analyzing ST segment deviations in ambulatory ECG.
• The ST/HR diagram slopes provide a valuable metric for distinguishing ischemic from non-ischemic events.
• These findings support the use of proposed features in automated ECG interpretation for improved coronary artery disease detection.