Time bias awareness in ECG-based multiple source data matching
First published in
Number in series
Studies in Health Technology and Informatics 295: 91-94 (2022)
Contribution to Conference
For cardiological datasets acquired via different methodologies, ECG signals that are recorded in parallel allow for relatively accurate matching. Some research issues, e.g., the identification of timings of the cardiac cycle in seismocardiography, require higher temporal resolutions. Therefore, we introduce a method derived from a feasibility study to determine deviations and factors influencing the merging of signals simultaneously recorded with different modalities.