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Continuous heart rate monitoring for automatic detection of atrial fibrillation with novel bio-sensing technology.
Journal of Electrocardiology 2019 January
BACKGROUND: Asymptomatic atrial fibrillation [AF] is an important cause of fatal or disabling stroke. A continuous heart-rate monitoring device, comfortable enough to be worn continuously and reliable enough to detect AF, would allow for prompt initiation of anticoagulation therapy to prevent stroke.
METHODS: We studied a new custom-made wearable photo-plethysmograph [PPG] wrist-watch sensor, specifically designed for continuous heart rate monitoring and incorporating contact and motion noise-filters. We tested its ability to automatically detect AF in patients undergoing elective cardioversion of AF, using simultaneously recorded electrocardiogram [ECG] as gold standard.
RESULTS: A total of 18,608 consecutive R-R-interval measurements were recorded simultaneously with PPG and ECG in 20 patients, including 12,521 [67.3%] R-R-intervals during AF and 6087 [32.7%] R-R intervals during sinus rhythm. Scatter plots and Bland-Altman plots demonstrated that the PPG signals were highly correlated to the simultaneously recorded ECG [R = 0.980, p < 0.001], both during AF and during sinus rhythm. The automatic algorithm distinguished AF from sinus rhythm with a sensitivity of 100% and specificity of 93.1%.
CONCLUSIONS: This PPG-based wrist-watch sensor reliably detected AF in non-ambulatory patients.
METHODS: We studied a new custom-made wearable photo-plethysmograph [PPG] wrist-watch sensor, specifically designed for continuous heart rate monitoring and incorporating contact and motion noise-filters. We tested its ability to automatically detect AF in patients undergoing elective cardioversion of AF, using simultaneously recorded electrocardiogram [ECG] as gold standard.
RESULTS: A total of 18,608 consecutive R-R-interval measurements were recorded simultaneously with PPG and ECG in 20 patients, including 12,521 [67.3%] R-R-intervals during AF and 6087 [32.7%] R-R intervals during sinus rhythm. Scatter plots and Bland-Altman plots demonstrated that the PPG signals were highly correlated to the simultaneously recorded ECG [R = 0.980, p < 0.001], both during AF and during sinus rhythm. The automatic algorithm distinguished AF from sinus rhythm with a sensitivity of 100% and specificity of 93.1%.
CONCLUSIONS: This PPG-based wrist-watch sensor reliably detected AF in non-ambulatory patients.
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