回廊的
心率变异性
动态心电图
心电图
医学
心脏病学
节拍(声学)
心率
内科学
计算机科学
血压
声学
物理
作者
Felke Steijns,Máté I. Tóth,Anthony Demolder,Lars Emil Larsen,Jana Desloovere,Marjolijn Renard,Robrecht Raedt,Patrick Segers,Julie De Backer,Patrick Sips
出处
期刊:Sensors
[Multidisciplinary Digital Publishing Institute]
日期:2020-07-10
卷期号:20 (14): 3867-3867
被引量:9
摘要
Ambulatory electrocardiography (AECG) is a primary diagnostic tool in patients with potential arrhythmic disorders. To study the pathophysiological mechanisms of arrhythmic disorders, mouse models are widely implemented. The use of a technique similar to AECG for mice is thus of great relevance. We have optimized a protocol which allows qualitative, long-term ECG data recording in conscious, freely moving mice. Automated algorithms were developed to efficiently process the large amount of data and calculate the average heart rate (HR), the mean peak-to-peak interval and heart rate variability (HRV) based on peak detection. Ectopic beats are automatically detected based on aberrant peak intervals. As we have incorporated a multiple lead configuration in our ECG set-up, the nature and origin of the suggested ectopic beats can be analyzed in detail. The protocol and analysis tools presented here are promising tools for studies which require detailed, long-term ECG characterization in mouse models with potential arrhythmic disorders.
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