Multimodal heart beat detection using signal quality indices

The electrocardiogram (ECG) is a well studied signal from which many clinically relevant parameters can be derived, such as heart rate. A key component in the estimation of these parameters is the accurate detection of the R peak in the QRS complex. While corruption of the ECG by movement artefact or sensor failure can result in poor delineation of the R peak, use of synchronously measured signals could allow for resolution of the R peak even scenarios with poor quality ECG recordings. Robust estimation of R peak locations from multimodal signals facilitates real time monitoring and is likely to reduce false alarms due to inaccurate derived parameters. We propose a method which fuses R peaks detected on the ECG using an energy detector with those detected on the arterial blood pressure (ABP) waveform using the length transform. A signal quality index (SQI) for the two signals is then derived. The ECG SQI is based upon the agreement between two distinct peak detectors. The ABP SQI estimates the blood pressure at various phases in the cardiac cycle and only accepts the signal as good quality if the values are physiologically plausible. Detections from these two signals were merged by selecting the R peak detections from the signal with a higher SQI. The approach presented in this paper was evaluated on datasets provided for the Physionet/Computing in Cardiology Challenge 2014. The algorithm achieved a sensitivity of 95.1% and positive predictive value of 89.3% on an external evaluation set, and achieved a score of 91.5%. The method here demonstrated excellent performance across a variety of signal morphologies collected during clinical practice. Fusion of R peaks from other signals has the potential to provide informed estimates of the R peak location in situations where the ECG is noisy or completely absent. Source code for the algorithm is made available freely online.