BrĂ¼ser, Christoph
Stadlthanner, Kurt
de Waele, Stijn
Leonhardt, Steffen
2011-03-01
A ballistocardiograph records the mechanical activity of the heart. We present a novel algorithm for the detection of individual heart beats and beat-to-beat interval lengths in ballistocardiograms (BCGs) from healthy subjects. An automatic training step based on unsupervised learning techniques is used to extract the shape of a single heart beat from the BCG. Using the learned parameters, the occurrence of individual heart beats in the signal is detected. A final refinement step improves the accuracy of the estimated beat-to-beat interval lengths. Compared to many existing algorithms, the new approach offers heart rate estimates on a beat-to-beat basis. The agreement of the proposed algorithm with an ECG reference has been evaluated. A relative beat-to-beat interval error of 1.79% with a coverage of 95.94% was achieved on recordings from 16 subjects.
https://doi.org/10.1109/titb.2011.2128337
oai:zenodo.org:852414
Zenodo
info:eu-repo/semantics/openAccess
Other (Open)
Adaptive Beat-to-Beat Heart Rate Estimation in Ballistocardiograms
info:eu-repo/semantics/article