Haemosync: A synchronisation algorithm for multimodal haemodynamic signals

BACKGROUND: Synchronous acquisition of haemodynamic signals is crucial for their multimodal analysis, such as dynamic cerebral autoregulation (DCA) analysis of arterial blood pressure (ABP) and transcranial Doppler (TCD)-derived cerebral blood velocity (CBv). Several technical problems can, however, lead to (varying) time-shifts between the different signals. These can be difficult to recognise and can strongly influence the multimodal analysis results.

METHODS: We have developed a multistep, cross-correlation-based time-shift detection and synchronisation algorithm for multimodal pulsatile haemodynamic signals. We have developed the algorithm using ABP and CBv measurements from a dataset that contained combinations of several time-shifts. We validated the algorithm on an external dataset with time-shifts. We additionally quantitatively validated the algorithm's performance on a dataset with artificially added time-shifts, consisting of sample clock differences ranging from -0.2 to 0.2 s/min and sudden time-shifts between -4 and 4 s. The influence of superimposed noise and variation in waveform morphology on the time-shift estimation was quantified, and their influence on DCA-indices was determined.

RESULTS: The instantaneous median absolute error (MedAE) between the artificially added time-shifts and the estimated time-shifts was 12 ms (median, IQR 12-12, range 11-14 ms) for drifts between -0.1 and 0.1 s/min and sudden time-shifts between -4 and 4 s. For drifts above 0.1 s/min, MedAE was higher (median 753, IQR 19 - 766, range 13 - 772 ms). When a certainty threshold was included (peak cross-correlation > 0.9), MedAE for all drifts-shift combinations decreased to 12 ms, with smaller variability (IQR 12 - 13, range 8 - 22 ms, p < 0.001). The time-shift estimation is robust to noise, as the MedAE was similar for superimposed white noise with variance equal to the signal variance. After time-shift correction, DCA-indices were similar to the original, non-time-shifted signals. Phase shift differed by 0.17° (median, IQR 0.13-0.2°, range 0.0038-1.1°) and 0.54° (median, IQR 0.23-1.7°, range 0.0088-5.6°) for the very low frequency and low frequency ranges, respectively.

DISCUSSION: This algorithm allows visually interpretable detection and accurate correction of time-shifts between pulsatile haemodynamic signals (ABP and CBv).