Mechanism of and Threshold Biomechanical Conditions for Falsetto Voice Onset

The sound source of a voice is produced by the self-excited oscillation of the vocal folds. In modal voice production, a drastic increase in transglottal pressure after vocal fold closure works as a driving force that develops self-excitation. Another type of vocal fold oscillation with less pronounced glottal closure observed in falsetto voice production has been accounted for by the mucosal wave theory. The classical theory assumes a quasi-steady flow, and the expected driving force onto the vocal folds under wavelike motion is derived from the Bernoulli effect. However, wavelike motion is not always observed during falsetto voice production. More importantly, the application of the quasi-steady assumption to a falsetto voice with a fundamental frequency of several hundred hertz is unsupported by experiments. These considerations suggested that the mechanism of falsetto voice onset may be essentially different from that explained by the mucosal wave theory. In this paper, an alternative mechanism is submitted that explains how self-excitation reminiscent of the falsetto voice could be produced independent of the glottal closure and wavelike motion. This new explanation is derived through analytical procedures by employing only general unsteady equations of motion for flow and solids. The analysis demonstrated that a convective acceleration of a flow induced by rapid wall movement functions as a negative damping force, leading to the self-excitation of the vocal folds. The critical subglottal pressure and volume flow are expressed as functions of vocal fold biomechanical properties, geometry, and voice fundamental frequency. The analytically derived conditions are qualitatively and quantitatively reasonable in view of reported measurement data of the thresholds required for falsetto voice onset. Understanding of the voice onset mechanism and the explicit mathematical descriptions of thresholds would be beneficial for the diagnosis and treatment of voice diseases and the development of artificial vocal folds

Universal mechanisms of sound production and control in birds and mammals

As animals vocalize, their vocal organ transforms motor commands into vocalizations for social communication. In birds, the physical mechanisms by which vocalizations are produced and controlled remain unresolved because of the extreme difficulty in obtaining in vivo measurements. Here, we introduce an ex vivo preparation of the avian vocal organ that allows simultaneous high-speed imaging, muscle stimulation and kinematic and acoustic analyses to reveal the mechanisms of vocal production in birds across a wide range of taxa. Remarkably, we show that all species tested employ the myoelastic-aerodynamic (MEAD) mechanism, the same mechanism used to produce human speech. Furthermore, we show substantial redundancy in the control of key vocal parameters ex vivo, suggesting that in vivo vocalizations may also not be specified by unique motor commands. We propose that such motor redundancy can aid vocal learning and is common to MEAD sound production across birds and mammals, including humans

Videokymography in voice disorders:What to look for?

Objectives: Kymographic imaging through videokymography has been recognized as a convenient, novel way to display laryngeal behavior, yet little systematic research has been done to map the relevant features displayed in such images. Here we have aimed at specification of these features to enable systematic visual characterization and categorization of vocal fold vibratory patterns in voice disorders. Methods: A cross-sectional, descriptive design was used. We selected 45 subjects and extracted 100 videokymographic images from the archive of more than 7,000 videokymographic examinations of subjects with a wide range of voice disorders. The images showed a large variety of vocal fold vibratory behaviors during sustained phonations. We visually identified the prominent features that distinguished the vibration patterns across the images. Results: We divided the findings into 10 feature categories. They included refined traditional features (eg, mucosal waves), as well as additional features that are obscured in strobolaryngoscopy (eg, different types of irregularities, left-right frequency differences, shapes of lateral and medial peaks, cycle aberrations). Conclusions: The variations in the identified features reveal different behavioral origins of voice disorders. The findings open new possibilities for objective documentation and for monitoring vocal fold behavior in clinical practice through kymographic imaging