Evaluation of voice pathology based on the estimation of vocal fold biomechanical parameters.

Voice disorders are a source of increasing concern as normal voice quality is a social demand for at least one third of the population in developed countries in cases where voice is an essential resource in professional exercise. In addition, the growing exposure to certain pathogenic factors such as smoking, alcohol abuse, air pollution, and acoustic contamination, and other problems such as gastro-esopharyngeal reflux or allergy as well as aging, aggravate voice disorders. Voice pathologies justify the assignment of larger resources to prevention policies, early detection, and less aggressive treatments. Traditional pathology detection relies on perceptive evaluation methods (GRABS), acoustic analysis, and visual inspection (indirect laryngoscopy, and modern fibro-endo-stroboscopy). This article describes a method for voice pathology detection based on the noninvasive estimation of vocal cord biomechanical parameters derived from voice using specific signal processing methods. Preliminary results using records from patients showing four frequent causes of voice pathology (nodules, polyps, chronic laryngitis, and Reinke's edema) are given. The results show that the alteration (distortion, unbalance, or deviation) of cord biomechanical parameters may serve as an indicator of pathology. Statistical methods based on hierarchical clustering and principal component analysis reveal that combining biomechanical estimates with classic perturbation parameters increases the accuracy of acoustic analysis, improving the detection of voice pathology. This research could open new possibilities for noninvasive screening of vocal fold pathologies and could be used in the implantation of e-health voice care services.