Ao-I Interval Calculation Algorithm Based on Multifeature Recognition and Waveform Correlation

Seismocardiography (SCG) and Ballistocardiography (BCG) signals represent cardiac vibration patterns acquired at the proximal and distal cardiovascular sites, respectively. Within the physiological interpretation of these signals, the AO (aortic valve opening) and I peaks serve as temporal markers corresponding to aortic valve activation events. The AO-I interval characterizes the hemodynamic propagation process initiated by aortic valve opening and subsequent blood ejection into systemic circulation, holding significant implications for cardiovascular dynamics research. This study proposes an AOI interval detection algorithm based on multi-feature recognition and waveform correlation methodologies. The algorithm initially identifies the most prominent J-peak through analysis of multiwavegroup characteristics in cardiac impulse signals. Subsequently, it locates the preceding I-peak within a search window constrained by the average cardiac cycle duration. Successful I-peak detection enables the definition of a synchronous AO-peak detection range. Through iterative J-peak localization and waveform correlation processes, the AO-peak position is determined, thereby enabling AO-I interval quantification. Experimental validation across an open-access repository demonstrates 97.63% detection accuracy of BCG-I fiducial points. Experimental validation across a proprietary clinical dataset demonstrates 96.47% detection accuracy with 0.2 ms resolution, achieving 91.3% theoretical efficiency relative to Cramér-Rao lower bounds.