Estimating tremor in Vocal Fold Biomechanics for Neurological Disease characterisation

Neurological Diseases (ND) are affecting larger segments of aging population every year. Treatment is dependent on expensive accurate and frequent monitoring. It is well known that ND leave correlates in speech and phonation. The present work shows a method to detect alterations in vocal fold tension during phonation. These may appear either as hypertension or as cyclical tremor. Estimations of tremor may be produced by auto-regressive modeling of the vocal fold tension series in sustained phonation. The correlates obtained are a set of cyclicality coefficients, the frequency and the root mean square amplitude of the tremor. Statistical distributions of these correlates obtained from a set of male and female subjects are presented. Results from five study cases of female voice are also given

Voice characteristics in smith–magenis syndrome: An acoustic study of laryngeal biomechanics

Smith–Magenis syndrome (SMS) is a rare genetic disease characterized by intellectual disability, serious behavior disorders, neurodevelopment delay, and speech and language disorders. An acoustic and biomechanical analysis of the voice of SMS young adults was carried out due to (a) the close relationship between the laryngeal biomechanics and the clinical and emotional state of a person; (b) the fact that no research on the voice in this syndrome has been conducted previously. The vocal timbre of most people diagnosed with SMS does not seem to be according to the complexion of diagnosed individuals, nor to their gender and age, so it could be interesting to attend the analysis of phonation of people with a rare genetic syndrome such as SMS. We used BioMetPhon, a specific piece of software to analyze the glottal source and biomechanics of vocals folds. Nineteen features related to dysphonia, physiology, and biomechanics of the vocal folds were considered. The adult phonation of 9 individuals with SMS was analyzed and compared to 100 normative male and female adult voices. Results showed that the phonation of the SMS group significantly deviates from the adult normophonic profile in more than one of the 19 features examined, such as stiffness of the thyroarytenoid muscle and dynamic mass of the vocal fold cover, among othersThis research was funded by grant TEC2016-77791-C4-4-R (Plan Nacional de I+D+i, Ministry of Economic Affairs and Competitiveness of Spain

Unveiling the impact of neuromotor disorders on speech: a structured approach combining biomechanical fundamentals and statistical machine learning

Speech has been shown to convey clinically useful information in the study of Neurodegenerative Disorders (NDs), such as Parkinson’s Disease (PD). Traditionally the use of speech as an exploratory tool in People with Parkinson’s (PwP) has focused on the estimation of acoustic characteristics and their study at face value, analysing the physio-acoustical markers and using them as features for the differentiation between Healthy Controls (HC) and PwP. The present work takes a step further, given the intricate interoperation between neuromotor activity, responsible for both planning and driving the system, and the production of the acoustic speech signal; by the study of speech, this relationship may be properly exploited and analysed, providing a non-invasive method for the diagnosis, analysis, and observation of NDs. This work aims to introduce a working model that is capable of linking both domains and serves as a projection tool to provide insights about a speaker’s neuromotor state. This is based on a review of the neurophysiological background of the structure and function of the nervous system, and a review of the main nervous system dysfunctions involved in PD and other related neuromotor disorders. The role of the respiratory, phonatory, and articulatory systems is reviewed in the production of voice and speech under normal and pathological circumstances. This setting might allow for speech to be considered a useful trait within the precision medicine framework, as it provides a personal biometric marker that is innate and easy to elicit, can be recorded remotely with inexpensive equipment, is non-invasive, cost-effective, and easy to process. The problem can be divided into two main categories: firstly, a binary detection task distinguishing between healthy controls and individuals with NDs based on the projection model and phonatory estimates; secondly, a progression and tracking task providing a set of quantitative indices that enable clinically interpretable scores. This study aims to define a set of features and models that help to characterise hypokinetic dysarthria (HD). These incorporate the neuroscientific knowhow semantically and quantitatively to be used in clinical decision support tools that provide mechanistic insight on the processes involved in speech production, incorporating into the algorithmic element neuromotor considerations that add to better interpretability, consequently leading to improved clinical decisions and diagnosis. An overview of the acoustic signal processing algorithms for use in speech articulation and phonation system inversion regarding neuromotor disorder assessment is provided. An algorithmic methodology for model inversion and exploration has been proposed for the functional characterization and system inversion of each subsystem involved under the neuro-biomechanical foundations exposed before. A description of the vocal fold biomechanics using the glottal source, and formant dynamics provides the base for specific mapping to articulation kinematics. The statistical methods used in performance evaluation are based on three-way comparisons and transversal and longitudinal assessment by classical hypothesis testing. Three related experimental studies are shown to empirically illustrate the potential of phonation and articulation analysis: the characterization of PD from glottal biomechanics based on the amplitude distributions of the glottal flow and on the vocal fold body stiffness in assessing the efficiency of transcranial magnetic stimulation, and the description of PD dysarthria through an articulation projection model. The results from the biomechanical analysis of phonation showed that the behaviour of glottal source amplitude distributions from PD and healthy controls using three-way comparisons and hierarchical clustering were essentially distinguishable from those from normative young participants with the best accuracy scores produced by SVM classifiers of 94.8% (males) and 92.2% (females). Nevertheless, PD participants were barely separable from age-matched controls, possibly pointing to confounding factors due to age. The outcomes from using vocal fold stiffness in assessing the efficiency of transcranial magnetic stimulation showed mixed results, as some PD participants reflected clear improvements in phonation stability after stimulation, whereas some others did not. Some cases of sham controls experienced also minor improvements of unknown origin, possibly expressing a placebo effect. The overall results on the efficiency of stimulation showed an accuracy global score of 67% over the 18 cases studied. The results from articulation projection modelling showed the possibility of formulating personalised models for PD and control participants to transform acoustic formant dynamics into articulation kinematics. This might open the possibility of characterising PD dysarthria based on speech audio records. The most remarkable findings of the study include the determination of the glottal source amplitude distribution behaviour of normative and PD participants; the impact of age effects in phonation as a confounding factor in neuromotor disorder characterization; the importance of ensuring that the classification of speech dysarthria is based on principles that can be explained and interpreted; the need of taking into account the effects of medication when framing new classification experiments; the potential of using EEG-band decomposition to analyse vocal fold stiffness correlates, as well as the possibility of using these descriptions in longitudinal monitoring of treatment efficiency; the feasibility of establishing a relationship between acoustic and kinematic variables by projection model inversion; and the potential of these descriptions for estimating neuromotor activities in midbrain related to phonation and articulation activity. The most important outcome to be brought forth from the thesis is that the methodology used throughout the project uses a bottom-up approach based on speech model inversion at the acoustical, biomechanical, and neuromotor levels allowing to estimate glottal signals, biomechanical correlates, and neuromotor activity from speech alone, establishing a common neuromechanical characterisation framework on its own

A methodology for monitoring emotional stress in phonation

Stress in phonation is mainly shown in the signature of the fundamental frequency. The proposed methodology is based on the estimation of the vocal fold biomechanics in terms of the distribution of the dynamic mass and the mechanical tension of the vocal fold structure. These parameters are derived from the reconstruction of the glottal source by inverse filtering. The vocal fold mechanical tension correlates (stress and strain), are used as the bases for tremor estimation. The correlates of tension and tremor are used to characterize the spontaneous speech of a database of 40 speakers of both genders (20 male and 20 female). Spontaneous speech consists in short interviews of 20 s of duration where the speakers have to express opinions on hot issues with which they are in agreement (pro) or in disagreement (con) following Arciuli's methodology. The emotional stress is estimated from the biomechanical correlates expressed above (tension and tremor). The null hypothesis formulated as the insensitivity of the speaker to pro and con situations has to be disregarded in view of the results for both genders. Interesting open questions are to be raised regarding the possibility of speakers consciously hiding their true opinion based on political correctness. The discussion will offer different hypotheses to further exploit the objective of detecting self-congruence in spoken messages

Models and Analysis of Vocal Emissions for Biomedical Applications

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies

Models and Analysis of Vocal Emissions for Biomedical Applications

The MAVEBA Workshop proceedings, held on a biannual basis, collect the scientific papers presented both as oral and poster contributions, during the conference. The main subjects are: development of theoretical and mechanical models as an aid to the study of main phonatory dysfunctions, as well as the biomedical engineering methods for the analysis of voice signals and images, as a support to clinical diagnosis and classification of vocal pathologies

LaDIVA: A neurocomputational model providing laryngeal motor control for speech acquisition and production

Many voice disorders are the result of intricate neural and/or biomechanical impairments that are poorly understood. The limited knowledge of their etiological and pathophysiological mechanisms hampers effective clinical management. Behavioral studies have been used concurrently with computational models to better understand typical and pathological laryngeal motor control. Thus far, however, a unified computational framework that quantitatively integrates physiologically relevant models of phonation with the neural control of speech has not been developed. Here, we introduce LaDIVA, a novel neurocomputational model with physiologically based laryngeal motor control. We combined the DIVA model (an established neural network model of speech motor control) with the extended body-cover model (a physics-based vocal fold model). The resulting integrated model, LaDIVA, was validated by comparing its model simulations with behavioral responses to perturbations of auditory vocal fundamental frequency (fo) feedback in adults with typical speech. LaDIVA demonstrated capability to simulate different modes of laryngeal motor control, ranging from short-term (i.e., reflexive) and long-term (i.e., adaptive) auditory feedback paradigms, to generating prosodic contours in speech. Simulations showed that LaDIVA’s laryngeal motor control displays properties of motor equivalence, i.e., LaDIVA could robustly generate compensatory responses to reflexive vocal fo perturbations with varying initial laryngeal muscle activation levels leading to the same output. The model can also generate prosodic contours for studying laryngeal motor control in running speech. LaDIVA can expand the understanding of the physiology of human phonation to enable, for the first time, the investigation of causal effects of neural motor control in the fine structure of the vocal signal.Fil: Weerathunge, Hasini R.. Boston University; Estados UnidosFil: Alzamendi, Gabriel Alejandro. Universidad Nacional de Entre Ríos. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación y Desarrollo en Bioingeniería y Bioinformática; ArgentinaFil: Cler, Gabriel J.. University of Washington; Estados UnidosFil: Guenther, Frank H.. Boston University; Estados UnidosFil: Stepp, Cara E.. Boston University; Estados UnidosFil: Zañartu, Matías. Universidad Técnica Federico Santa María; Chil

Models and Analysis of Vocal Emissions for Biomedical Applications

The International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA) came into being in 1999 from the particularly felt need of sharing know-how, objectives and results between areas that until then seemed quite distinct such as bioengineering, medicine and singing. MAVEBA deals with all aspects concerning the study of the human voice with applications ranging from the newborn to the adult and elderly. Over the years the initial issues have grown and spread also in other fields of research such as occupational voice disorders, neurology, rehabilitation, image and video analysis. MAVEBA takes place every two years in Firenze, Italy. This edition celebrates twenty-two years of uninterrupted and successful research in the field of voice analysis

PERIORAL BIOMECHANICS, KINEMATICS, AND ELECTROPHYSIOLOGY IN PARKINSON'S DISEASE

This investigation quantitatively characterized the orofacial biomechanics, labial kinematics, and associated electromyography (EMG) patterns in individuals with Parkinson's disease (PD) as a function of anti-PD medication state. Passive perioral stiffness, a clinical correlate of rigidity, was sampled using a face-referenced OroSTIFF system in 10 mildly diagnosed PD and 10 age/sex-matched control elderly. Labial movement amplitudes and velocities were evaluated using a 4-dimensional computerized motion capture system. Associated perioral EMG patterns were sampled to examine the characteristics of perioral muscles and compensatory muscular activation patterns during repetitive syllable productions. This study identified several trends that reflect various characteristics of perioral system differences between PD and control subjects: 1. The presence of high tonic EMG patterns after administration of dopaminergic treatment indicated an up-regulation of the central mechanism, which may serve to regulate orofacial postural control. 2. Multilevel regression modeling showed greater perioral stiffness in PD subjects, confirming the clinical correlate of rigidity in these patients. 3. Similar to the clinical symptoms in the upper and lower limb, a reduction of range of motion (hypokinesia) and velocity (bradykinesia) was evident in the PD orofacial system. Administration of dopaminergic treatment improved hypokinesia and bradykinesia. 4. A significant correlation was found between perioral stiffness and the range of labial movement, indicating these two symptoms may result in part from a common neural substrate. 5. As speech rate increased, PD speakers down-scaled movement amplitude and velocity compared to the control subjects, reflecting a compensatory mechanism to maintain target speech rates. 6. EMG from orbicularis oris inferior (OOIm) and depressor labii inferioris (DLIm) muscles revealed a limited range of muscle activation level in PD speakers, reflecting the underlying changes in motor unit firing behavior due to basal ganglia dysfunction. The results of this investigation provided a quantitative description of the perioral stiffness, labial kinematics, and EMG patterns in PD speakers. These findings indicate that perioral stiffness may provide clinicians a quantitative biomechanical correlate to medication response, movement aberrations, and EMG compensatory patterns in PD. The utilization of these objective assessments will be helpful in diagnosing, assessing, and monitoring the progression of PD to examine the efficacy of pharmacological, neurosurgical, and behavioral interventions

Models and Analysis of Vocal Emissions for Biomedical Applications

The International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA) came into being in 1999 from the particularly felt need of sharing know-how, objectives and results between areas that until then seemed quite distinct such as bioengineering, medicine and singing. MAVEBA deals with all aspects concerning the study of the human voice with applications ranging from the neonate to the adult and elderly. Over the years the initial issues have grown and spread also in other aspects of research such as occupational voice disorders, neurology, rehabilitation, image and video analysis. MAVEBA takes place every two years always in Firenze, Italy. This edition celebrates twenty years of uninterrupted and succesfully research in the field of voice analysis