Abstract
Assessing vocal fold (VF) vibrations is important for the diagnosis of several diseases, and is made possible through the analysis of videoendoscopy recordings. However, the visual analysis of these recordings is hard due to the high acquisition rate. For this reason, it is commonly used to extract the laryngeal activity information from the recordings and represent it in a way suitable to be visually analyzed. Waveforms, images and playbacks are examples of representations reported in the literature. The main limitation of some of them is the lack of precisely locating the pathology within the VFs. Whereas others require the segmentation of the glottis in all the images of the video which is a complex and hard task given the high amount of images in the video and the necessity for the user intervention. To overcome these problems, the present study proposes a new waveform that maps the local vibrations of the VFs without the need for segmenting all the images of the video. Instead, the segmentation is restricted to only one image per vibratory cycle. Then, a new optical flow based technique is proposed to deduce the cycle-to-cycle dynamics of the VFs. The ability of the proposed approach to provide a reliable visual assessment is experimentally evaluated using different types of phonation and different vocal pathologies.