Synthetic multi-line kymographic analysis: A spatiotemporal data reduction technique for high-speed videoendoscopy.

High-speed videoendoscopy (HSV) enables observation of the true vibratory behavior of the vocal folds. To quantify the vocal fold vibration captured by the HSV, lateral movement features (e.g., glottal width and vocal fold edge displacements) have been extracted as functions of time. The most common analysis method is to extract the features on a lateral strip used to form digital kymogram. The weakness of this method is that it can only capture the vibrational behavior local to the strip location. While the multi-line kymographic approach has been utilized to capture the spatial diversity, the observation points are either fixed or manually positioned. Behaviors of pathological vocal folds, especially those with lesions, are expected to be spatially diverse and also diverse among speakers, making fixed observation points ineffective. This paper proposes a technique to synthesize kymographic waveforms from full spatiotemporal HSV feature data to extract distinctive behaviors automatically. Each synthesized waveform represents a non-overlapping section of the glottis, where vocal folds are locally behaving homogeneously. The efficacy of the algorithm is demonstrated with four HSV recordings (three pathological) and discussed, including mitigation of the known drawbacks.