Biosimulation of Vocal Fold Inflammation and Healing

Personalized, pre-emptive and predictive medicine is the capstone of contemporary medical care. The central aim of this dissertation is to address clinical challenges in prescribing personalized therapy to patients with acute phonotrauma. Inflammation and healing, which are innate tissue responses to mechanical stress/ trauma, are regulated by a complex dynamic system. A systems biology approach, which combines empirical, mathematical and computational tools, was taken to study the biological complexity of this dynamic system in vocal fold injury.Computational agent-based models (ABMs) were developed to quantitatively characterize multiple cellular and molecular interactions around inflammation and healing. The models allowed for tests of various hypothetical effects of motion-based treatments in individuals with acute phonotrauma. A phonotrauma ABM was calibrated and verified with empirical data of a panel of inflammatory mediators, obtained from laryngeal secretions in individuals following experimentally induced phonotrauma and a randomly assigned motion-based treatment. A supplementary ABM of surgically induced vocal fold trauma was developed and subsequently calibrated and verified with empirical data of inflammatory mediators and extracellular matrix substances from rat studies, for the purpose of gaining insight into the &ldquo net effect &rdquo of cellular and molecular responses at the tissue level.ABM simulations reproduced and predicted trajectories of inflammatory mediators and extracellular matrix as seen in empirical data of phonotrauma and surgical vocal fold trauma. The simulation results illustrated a spectrum of inflammatory responses to phonotrauma, surgical trauma and motion-based treatments. The results suggested that resonant voice exercise may optimize the combination of para- and anti-inflammatory responses to accelerate healing. Moreover, the ABMs suggested that hyaluronan fragments might be an early molecular index of tissue damage that is sensitive to varying stress levels - from relatively low phonatory stress to high surgical stress.We propose that this translational application of biosimulation can be used to quantitatively chart individual healing trajectories, test the effects of different treatment options and most importantly provide new understanding of laryngeal health and healing. By placing biology on a firm mathematical foundation, this line of research has potential to influence the contour of scientific thinking and clinical care of vocal fold injury

Acoustic and perceptual analysis of modal and falsetto registers in females with dysphonia

published_or_final_versionabstracttocEducationMasterMaster of Philosoph

Physiological characteristies of different types of voice production

"A dissertation submitted in partial fulfilment of the requirements for the Bachelor of Science (Speech and Hearing Sciences), The University of Hong Kong, May 10, 2000."Also available in print.Thesis (B.Sc)--University of Hong Kong, 2000published_or_final_versionSpeech and Hearing SciencesBachelorBachelor of Science in Speech and Hearing Science

Discrimination between Modal, Breathy and Pressed Voice for Single Vowels Using Neck-Surface Vibration Signals

The purpose of this study was to investigate the feasibility of using neck-surface acceleration signals to discriminate between modal, breathy and pressed voice. Voice data for five English single vowels were collected from 31 female native Canadian English speakers using a portable Neck Surface Accelerometer (NSA) and a condenser microphone. Firstly, auditory-perceptual ratings were conducted by five clinically-certificated Speech Language Pathologists (SLPs) to categorize voice type using the audio recordings. Intra- and inter-rater analyses were used to determine the SLPs’ reliability for the perceptual categorization task. Mixed-type samples were screened out, and congruent samples were kept for the subsequent classification task. Secondly, features such as spectral harmonics, jitter, shimmer and spectral entropy were extracted from the NSA data. Supervised learning algorithms were used to map feature vectors to voice type categories. A feature wrapper strategy was used to evaluate the contribution of each feature or feature combinations to the classification between different voice types. The results showed that the highest classification accuracy on a full set was 82.5%. The breathy voice classification accuracy was notably greater (approximately 12%) than those of the other two voice types. Shimmer and spectral entropy were the best correlated metrics for the classification accuracy

Investigation of Vocal Fatigue Using a Dose-Based Vocal Loading Task

Vocal loading tasks are often used to investigate the relationship between voice use and vocal fatigue in laboratory settings. The present study investigated the concept of a novel quantitative dose-based vocal loading task for vocal fatigue evaluation. Ten female subjects participated in the study. Voice use was monitored and quantified using an online vocal distance dose calculator during six consecutive 30-min long sessions. Voice quality was evaluated subjectively using the CAPE-V and SAVRa before, between, and after each vocal loading task session. Fatigue-indicative symptoms, such as cough, swallowing, and voice clearance, were recorded. Statistical analysis of the results showed that the overall severity, the roughness, and the strain ratings obtained from CAPE-V obeyed similar trends as the three ratings from the SAVRa. These metrics increased over the first two thirds of the sessions to reach a maximum, and then decreased slightly near the session end. Quantitative metrics obtained from surface neck accelerometer signals were found to obey similar trends. The results consistently showed that an initial adjustment of voice quality was followed by vocal saturation, supporting the effectiveness of the proposed loading task