Artificial Intelligence Procedure for the Screening of Genetic Syndromes Based on Voice Characteristics.

Perceptual and statistical evidence has highlighted voice characteristics of individuals affected by genetic syndromes that differ from those of normophonic subjects. In this paper, we propose a procedure for systematically collecting such pathological voices and developing AI-based automated tools to support differential diagnosis. Guidelines on the most appropriate recording devices, vocal tasks, and acoustical parameters are provided to simplify, speed up, and make the whole procedure homogeneous and reproducible.

Machine Learning Assessment of Spasmodic Dysphonia Based on Acoustical and Perceptual Parameters.

Adductor spasmodic dysphonia is a type of adult-onset focal dystonia characterized by involuntary spasms of laryngeal muscles. This paper applied machine learning techniques for the severity assessment of spasmodic dysphonia. To this aim, 7 perceptual indices and 48 acoustical parameters were estimated from the Italian word /a'jwɔle/ emitted by 28 female patients, manually segmented from a standardized sentence and used as features in two classification experiments.

Analysis of Brain-Heart Interactions in newborns with and without seizures using the Convergent Cross Mapping approach.

In the last years, the characterization of brain-heart interactions (BHIs) in epilepsy has gained great interest. For some specific seizures there is still a lack of information about the mechanisms occurring during or close to ictal events between the central nervous system (CNS) and the autonomic nervous system (ANS). This is the case for neonatal seizures, one of the most common neurological emergencies in the first days of life.

Aggregate Channel Features for newborn face detection in Neonatal Intensive Care Units.

An efficient face detector could be very helpful to point out possible neurological dysfunctions such as seizure events in Neonatal Intensive Care Units. However, its development is still challenging because large public datasets of newborns' faces are missing. Over the years several studies introduced semi-automatic approaches.

Heart Rate Variability Analysis for Seizure Detection in Neonatal Intensive Care Units.

In Neonatal Intensive Care Units (NICUs), the early detection of neonatal seizures is of utmost importance for a timely clinical intervention. Over the years, several neonatal seizure detection systems were proposed to detect neonatal seizures automatically and speed up seizure diagnosis, most based on the EEG signal analysis. Recently, research has focused on other possible seizure markers, such as electrocardiography (ECG).

A Generalized Linear Model for an ECG-based Neonatal Seizure Detector.

Seizures represent one of the most challenging issues of the neonatal period's neurological emergency. Due to the heterogeneity of etiologies and clinical characteristics, seizures recognition is tricky and time-consuming. Currently, the gold standard for seizure diagnosis is Electroencephalography (EEG), whose correct interpretation requires a highly specialized team.

Multiscale Entropy Analysis of Heart Rate Variability in Neonatal Patients with and without Seizures.

The complex physiological dynamics of neonatal seizures make their detection challenging. A timely diagnosis and treatment, especially in intensive care units, are essential for a better prognosis and the mitigation of possible adverse effects on the newborn's neurodevelopment. In the literature, several electroencephalographic (EEG) studies have been proposed for a parametric characterization of seizures or their detection by artificial intelligence techniques.

Multiparametric EEG analysis of brain network dynamics during neonatal seizures.

Background: One of the most challenging issues in paediatric neurology is the diagnosis of neonatal seizures, whose delayed treatment may affect the neurodevelopment of the newborn. Formulation of the correct diagnosis is conditioned by the high number of perceptually or automatically detected false positives.

New Method: New methodologies are proposed to assess neonatal seizures trend over time.

Semioccluded Vocal Tract Exercises Improve Self-Perceived Voice Quality in Healthy Actors.

Purpose: Semi-occluded vocal tract exercises (SOVTE) have shown to lead to more effective and efficient vocal production for individuals with voice disorders and for singers. The aim of the present study is to investigate the effects of a 10-minute SOVTE warm-up protocol on the actors' voice.

Methods: Twenty-seven professional theater actors (16 females) without voice complaints were audio-recorded while reading aloud, with their acting voice, a short dramatic passage at four time points.

Automatic detection and sonification of nonmotor generalized onset epileptic seizures: Preliminary results.

Long-term video-EEG monitoring has improved diagnosis and treatment of epilepsy, especially in children. However, the amount of data neurophysiologists must analyze has grown remarkably. The main purpose of this paper is to provide a diagnostic support to speed up and ease EEG interpretation for a specific application concerning absence seizures, a type of non-motor generalized epileptic seizures.

Maximal Ambient Noise Levels and Type of Voice Material Required for Valid Use of Smartphones in Clinical Voice Research.

Purpose: Smartphone technology provides new opportunities for recording standardized voice samples of patients and transmitting the audio files to the voice laboratory. This drastically improves the achievement of baseline designs, used in research on efficiency of voice treatments. However, the basic requirement is the suitability of smartphones for recording and digitizing pathologic voices (mainly characterized by period perturbations and noise) without significant distortion.

Multidimensional Assessment of the Effectiveness of Group Voice Therapy.

Objective: Group voice therapy has been successfully used in patients with dysphonia, but there is little objectively documented evidence of its effects on voice quality and the self-perception of voice fatigue. The aim of this study was to investigate the effectiveness of group therapy in patients with functional dysphonia and minor anatomic vocal fold pathologies linked by appearance and history to voice use in an objective and multidimensional manner.

Study Design: This is a prospective longitudinal study.

Analysis of facial expressions in parkinson's disease through video-based automatic methods.

Background: The automatic analysis of facial expressions is an evolving field that finds several clinical applications. One of these applications is the study of facial bradykinesia in Parkinson's disease (PD), which is a major motor sign of this neurodegenerative illness. Facial bradykinesia consists in the reduction/loss of facial movements and emotional facial expressions called hypomimia.

Physiology and Acoustics of Inspiratory Phonation.

Introduction: Inspiratory phonation (IP) means phonating with inspiratory airflow. Some vocalists remarkably master this technique, to such an extent that it offers new dramatic, aesthetic, and functional possibilities in singing specific contemporary music. The present study aims to a better understanding of the physiological backgrounds of IP.

Application of Pattern Recognition Techniques to the Classification of Full-Term and Preterm Infant Cry.

Objectives: Scientific and clinical advances in perinatology and neonatology have enhanced the chances of survival of preterm and very low weight neonates. Infant cry analysis is a suitable noninvasive complementary tool to assess the neurologic state of infants particularly important in the case of preterm neonates. This article aims at exploiting differences between full-term and preterm infant cry with robust automatic acoustical analysis and data mining techniques.

Automatic Assessment of Acoustic Parameters of the Singing Voice: Application to Professional Western Operatic and Jazz Singers.

Introduction: The obvious perceptual differences between various singing styles like Western operatic and jazz rely on specific dissimilarities in vocal technique. The present study focuses on differences in vibrato acoustics and in singer's formant as analyzed by a novel software tool, named BioVoice, based on robust high-resolution and adaptive techniques that have proven its validity on synthetic voice signals.

Material And Methods: A total of 48 professional singers were investigated (29 females; 19 males; 29 Western operatic; and 19 jazz).

Voice dosimetry and monitoring, with emphasis on professional voice diseases: Critical review and framework for future research.

Professional voice has become an important issue in the field of occupational health. Similarly, voice diseases related to occupations gain interest in insurance medicine, particularly within the frame of specific insurance systems for occupational diseases. Technological developments have made possible dosimetry of voice loading in the work-place, as well as long-term monitoring of relevant voice parameters during professional activities.

Automated tracking of quantitative parameters from single line scanning of vocal folds: a case study of the 'messa di voce' exercise.

This article presents a novel application of the 'single line scanning' of the vocal fold vibrations (kymography) in singing pedagogy, particularly in a specific technical voice exercise: the 'messa di voce'. It aims at giving the singer relevant and valid short-term feedback. A user-friendly automatic analysis program makes possible a precise, immediate quantification of the essential physiological parameters characterizing the changes in glottal impedance, concomitant with the progressive increase and decrease of the lung pressure.

Ambulatory phonation monitoring in a sample of 92 call center operators.

Objectives: The voice is a primary work tool for call center operators, but the main risk factors for voice disorders in this category have not yet been clarified. This study aimed to analyze the vocal behavior in call center operators and search for correlations between the daily voice dose and the self-perceived voice-related handicap.

Study Design: Prospective.

Modelling of thermal hyperemia in the skin of type 2 diabetic patients.

The microcirculatory response to thermal stimulation involves both an axon reflex and NO-mediated activation. The analysis of the microcirculatory flow following thermal stimulation may therefore enhance the detection of any impairment of the small unmyelinated fibres that are involved in the axon reflex. The aim of this work is to establish a method of non-invasive measurement of small fibre impairment.

Quantitative analysis of videokymography in normal and pathological vocal folds: a preliminary study.

Videokymography (VKG) captures high-speed images of the vocal folds independently of the periodicity of the acoustic signal. The aim of this study was to preliminarily assess a software package that can objectively measure specific parameters of vocal fold vibration. From August 2009 until December 2010, we prospectively evaluated 40 subjects (Group A, 18 normal subjects; Group B, 14 patients with benign lesions of the middle third of the vocal fold, such as polyps and cysts; Group C, 8 patients treated by endoscopic excision of vocal fold benign lesions) by videoendoscopy, videolaryngostroboscopy, and VKG.

Validity of jitter measures in non-quasi-periodic voices. Part I: perceptual and computer performances in cycle pattern recognition.

The limit of about 5% for reliable quantification of jitter in sustained vowels of dysphonic voices-a widely accepted guideline-deserves critical analysis. The present study pertains to the effect of experience and training on the perceptual (visual) capability of correctly identifying periods in (highly) perturbed signals, and to a comparison of the performance of several programs for voice analysis. Synthesized realistic vowels (/a:/) with exactly known jitter (2.

Validity of jitter measures in non-quasi-periodic voices. Part II: the effect of noise.

In this paper the effect of noise on both perceptual and automatic evaluation of the glottal cycle length in irregular voice signals (sustained vowels) is studied. The reliability of four tools for voice analysis (MDVP, Praat, AMPEX, and BioVoice) is compared to visual inspection made by trained clinicians using two measures of voice signal irregularity: the jitter (J) and the coefficient of variation of the fundamental frequency (F0CV). The purpose is also to test to what extent of irregularity trained raters are capable of determining visually the glottal cycle length as compared to dedicated software tools.