Conference Proceeding
Refine
Year of publication
Institute
- Fachbereich Elektrotechnik und Informationstechnik (302)
- Fachbereich Energietechnik (259)
- Fachbereich Medizintechnik und Technomathematik (241)
- Fachbereich Luft- und Raumfahrttechnik (208)
- Fachbereich Maschinenbau und Mechatronik (207)
- Solar-Institut Jülich (167)
- IfB - Institut für Bioengineering (152)
- Fachbereich Bauingenieurwesen (139)
- Fachbereich Wirtschaftswissenschaften (69)
- ECSM European Center for Sustainable Mobility (59)
Language
- English (1162)
- German (475)
- Multiple languages (1)
- Spanish (1)
Document Type
- Conference Proceeding (1639) (remove)
Keywords
- Biosensor (25)
- Blitzschutz (15)
- CAD (11)
- Finite-Elemente-Methode (11)
- civil engineering (11)
- Bauingenieurwesen (10)
- Lightning protection (9)
- Einspielen <Werkstoff> (6)
- Telekommunikationsmarkt (6)
- shakedown analysis (6)
Clinical assessment of newly developed sensors is important for ensuring their validity. Comparing recordings of emerging electrocardiography (ECG) systems to a reference ECG system requires accurate synchronization of data from both devices. Current methods can be inefficient and prone to errors. To address this issue, three algorithms are presented to synchronize two ECG time series from different recording systems: Binned R-peak Correlation, R-R Interval Correlation, and Average R-peak Distance. These algorithms reduce ECG data to their cyclic features, mitigating inefficiencies and minimizing discrepancies between different recording systems. We evaluate the performance of these algorithms using high-quality data and then assess their robustness after manipulating the R-peaks. Our results show that R-R Interval Correlation was the most efficient, whereas the Average R-peak Distance and Binned R-peak Correlation were more robust against noisy data.