On Automatic Diagnosis of Alzheimer's Disease based on Spontaneous Speech Analysis and Emotional Temperature

Alzheimer's disease is the most prevalent form of progressive degenerative dementia; it has a high socio-economic impact in Western countries. Therefore it is one of the most active research areas today. Alzheimer's is sometimes diagnosed by excluding other dementias, and definitive confirmation is only obtained through a post-mortem study of the brain tissue of the patient. The work presented here is part of a larger study that aims to identify novel technologies and biomarkers for early Alzheimer's disease detection, and it focuses on evaluating the suitability of a new approach for early diagnosis of Alzheimer’s disease by non-invasive methods. The purpose is to examine, in a pilot study, the potential of applying Machine Learning algorithms to speech features obtained from suspected Alzheimer sufferers in order help diagnose this disease and determine its degree of severity. Two human capabilities relevant in communication have been analyzed for feature selection: Spontaneous Speech and Emotional Response. The experimental results obtained were very satisfactory and promising for the early diagnosis and classification of Alzheimer’s disease patients.

Alzheimer disease diagnosis based on automatic spontaneous speech analysis

Alzheimer’s disease (AD) is the most prevalent form of progressive degenerative dementia and it has a high socio-economic impact in Western countries, therefore is one of the most active research areas today. Its diagnosis is sometimes made by excluding other dementias, and definitive confirmation must be done trough a post-mortem study of the brain tissue of the patient. The purpose of this paper is to contribute to im-provement of early diagnosis of AD and its degree of severity, from an automatic analysis performed by non-invasive intelligent methods. The methods selected in this case are Automatic Spontaneous Speech Analysis (ASSA) and Emotional Temperature (ET), that have the great advantage of being non invasive, low cost and without any side effects.

Alzheimer Disease Diagnosis based on Automatic Spontaneous Speech Analysis

Alzheimer’s disease (AD) is the most prevalent form of progressive degenerative dementia and it has a high socio-economic impact in Western countries, therefore is one of the most active research areas today. Its diagnosis is sometimes made by excluding other dementias, and definitive confirmation must be done trough a post-mortem study of the brain tissue of the patient. The purpose of this paper is to contribute to improvement of early diagnosis of AD and its degree of severity, from an automatic analysis performed by non-invasive intelligent methods. The methods selected in this case are Automatic Spontaneous Speech Analysis (ASSA) and Emotional Temperature (ET), that have the great advantage of being non invasive, low cost and without any side effects.

Spontaneous Speech and Emotional Response modeling based on One-class classifier oriented to Alzheimer Disease diagnosis

The purpose of our project is to contribute to earlier diagnosis of AD and better estimates of its severity by using automatic analysis performed through new biomarkers extracted from non-invasive intelligent methods. The methods selected in this case are speech biomarkers oriented to Sponta-neous Speech and Emotional Response Analysis. Thus the main goal of the present work is feature search in Spontaneous Speech oriented to pre-clinical evaluation for the definition of test for AD diagnosis by One-class classifier. One-class classifi-cation problem differs from multi-class classifier in one essen-tial aspect. In one-class classification it is assumed that only information of one of the classes, the target class, is available. In this work we explore the problem of imbalanced datasets that is particularly crucial in applications where the goal is to maximize recognition of the minority class as in medical diag-nosis. The use of information about outlier and Fractal Dimen-sion features improves the system performance.

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

Feature selection for automatic analysis of emotional response based on nonlinear speech modeling suitable for diagnosis of Alzheimer׳s disease

Alzheimer׳s disease (AD) is the most common type of dementia among the elderly. This work is part of a larger study that aims to identify novel technologies and biomarkers or features for the early detection of AD and its degree of severity. The diagnosis is made by analyzing several biomarkers and conducting a variety of tests (although only a post-mortem examination of the patients’ brain tissue is considered to provide definitive confirmation). Non-invasive intelligent diagnosis techniques would be a very valuable diagnostic aid. This paper concerns the Automatic Analysis of Emotional Response (AAER) in spontaneous speech based on classical and new emotional speech features: Emotional Temperature (ET) and fractal dimension (FD). This is a pre-clinical study aiming to validate tests and biomarkers for future diagnostic use. The method has the great advantage of being non-invasive, low cost, and without any side effects. The AAER shows very promising results for the definition of features useful in the early diagnosis of AD.

Real-Time implementation of a blind authentication method using self-synchronous speech watermarking

A blind speech watermarking scheme that meets hard real-time deadlines is presented and implemented. In addition, one of the key issues in these block-oriented watermarking techniques is to preserve the synchronization. Namely, to recover the exact position of each block in the mark extract process. In fact, the presented scheme can be split up into two distinguished parts, the synchronization and the information mark methods. The former is embedded into the time domain and it is fast enough to be run meeting real-time requirements. The latter contains the authentication information and it is embedded into the wavelet domain. The synchronization and information mark techniques are both tunable in order to allow a con gurable method. Thus, capacity, transparency and robustness can be con gured depending on the needs. It makes the scheme useful for professional applications, such telephony authentication or even sending information throw radio applications.

On the origin and scope of the second language speech production disadvatage

Los hablantes bilingües tienen un acceso al léxico más lento y menos robusto que los monolingües, incluso cuando hablan en su lengua materna y dominante. Este fenómeno, comúnmente llamado “la desventaja bilingüe” también se observa en hablantes de una segunda lengua en comparación con hablantes de una primera lengua. Una causa que posiblemente contribuya a estas desventajas es el uso de control inhibitorio durante la producción del lenguaje: la inhibición de palabras coactivadas de la lengua actualmente no en uso puede prevenir intrusiones de dicha lengua, pero al mismo tiempo ralentizar la producción del lenguaje. El primer objetivo de los estudios descritos en este informe era testear esta hipótesis mediante diferentes predicciones generadas por teorías de control inhibitorio del lenguaje. Un segundo objetivo era investigar la extensión de la desventaja bilingüe dentro y fuera de la producción de palabras aisladas, así como avanzar en el conocimiento de las variables que la modulan. En lo atingente al primer objetivo, la evidencia obtenida es incompatible con un control inhibitorio global, desafiando la idea de mecanismos específicos en el hablante bilingüe utilizados para la selección léxica. Esto implica que una explicación común para el control de lenguaje y la desventaja bilingüe en el acceso al léxico es poco plausible. En cuanto al segundo objetivo, los resultados muestran que (a) la desventaja bilingüe no tiene un impacto al acceso a la memoria; (b) la desventaja bilingüe extiende a la producción del habla conectada; y (c) similitudes entre lenguas a diferentes niveles de representación así como la frecuencia de uso son factores que modulan la desventaja bilingüe.   

Late bloomer or language impaired? Screening the speech of a Spanish-English bilingual toddler for early signs of language impairment

This case study presents corpus data gathered from a Spanish-English bilingual child with expressive language delay. Longitudinal data on the child’s linguistic development was collected from the onset of productive speech at age 1;1 until age 4 over the course of 28 video-taped sessions with the child’s principal caregivers. A literature review focused on the relationship between language delay and persisting disorders—including a discussion of the frequent difficulty in distinguishing between the two at early stages of bilingual development—is followed by an analysis of the child’s productive development in 2 distinct phases. An attempt is made to assess the child’s speech at age 4 for preliminary signs of SLI and to consider techniques for identifying ‘at risk’ bilingual children (that is, those with productive language delay, poor oral fluency, and family history of language problems) based on samples of recorded and transcribed speech.

Pressure-dependent scaling scenarios in experiments of spontaneous imbibition

The scaling properties of the rough liquid-air interface formed in the spontaneous imbibition of a viscous liquid by a model porous medium are found to be very sensitive to the magnitude of the pressure difference applied at the liquid inlet. Interface fluctuations change from obeying intrinsic anomalous scaling at large negative pressure differences, to being super-rough with the same dynamic exponent z¿3 at less negative pressure differences, to finally obeying ordinary Family-Vicsek scaling with z¿2 at large positive pressure differences. This rich scenario reflects the relative importance on different length scales of capillary and permeability disorder, and the role of surface tension and viscous pressure in damping interface fluctuations.

Parity violation in Aharonov-Bohm systems: The spontaneous Hall effect

We show how macroscopic manifestations of P (and T) symmetry breaking can arise in a simple system subject to Aharonov-Bohm interactions. Specifically, we study the conductivity of a gas of charged particles moving through a dilute array of flux tubes. The interaction of the electrons with the flux tubes is taken to be of a purely Aharonov-Bohm type. We find that the system exhibits a nonzero transverse conductivity, i.e., a spontaneous Hall effect. This is in contrast to the fact that the cross sections for both scattering and bremsstrahlung (soft-photon emission) of a single electron from a flux tube are invariant under reflections. We argue that the asymmetry in the conductivity coefficients arises from many-body effects. On the other hand, the transverse conductivity has the same dependence on universal constants that appears in the quantum Hall effect, a result that we relate to the validity of the mean-field approximation.

Bacterial translocation in cirrhotic rats. Its role in the development of spontaneous bacterial peritonitis

Bacterial translocation occurs in ascitic cirrhotic rats, but its association with ascites infection is unknown. The aim of this study was to assess the relation between bacterial translocation and ascites infection in cirrhotic rats. Male Sprague-Dawley rats were induced to cirrhosis with intragastric CCl4. Ascitic fluid, portal and peripheral blood, mesenteric lymph nodes, liver and spleen samples were cultured before death in those cirrhotic rats with less (group A) or more (group B) than 250 polymorphonuclear neutrophils/mm3 in ascitic fluid, as well as in healthy control rats. Histological examination of jejunum, ileum, and caecum was also performed. Bacterial translocation occurred in 45% of ascitic rats (without differences between groups A and B), but in 0% controls (p = 0.01). Bacterial translocation was associated with positive ascitic fluid culture in 60% of the cases. In all of them the same bacterial species was isolated in both mesenteric lymph node and ascitic fluid. Submucosal caecal oedema (100%), ileal lymphangiectasia (41%), and caecal inflammatory infiltrate (41%) occurred in ascitic rats, the last being associated with ascitic fluid positive culture (p = 0.04). These results suggests that bacterial translocation occurs frequently in ascitic cirrhotic rats, and may play a permissive, but not unique, part in a number of ascites infections. Whether histological changes seen in cirrhotic ascitic rats favour bacterial translocation remains to be elucidated.

Spontaneous mirror symmetry breaking in the limited enantioselective autocatalysis model: abyssal hydrotermal vents as scenario for the emergence of chirality in prebiotic chemistry

The emergence of chirality in enantioselective autocatalysis for compounds unable to transform according to the Frank-like reaction network is discussed with respect to the controversial limited enantioselectivity (LES) model composed of coupled enantioselective and non-enantioselective autocatalyses. The LES model cannot lead to spontaneous mirror symmetry breaking (SMSB) either in closed systems with a homogeneous temperature distribution or in closed systems with a stationary non-uniform temperature distribution. However, simulations of chemical kinetics in a two-compartment model demonstrate that SMSB may occur if both autocatalytic reactions are spatially separated at different temperatures in different compartments but coupled under the action of a continuous internal flow. In such conditions, the system can evolve, for certain reaction and system parameters, toward a chiral stationary state; that is, the system is able to reach a bifurcation point leading to SMSB. Numerical simulations in which reasonable chemical parameters have been used suggest that an ade- quate scenario for such a SMSB would be that of abyssal hydrothermal vents, by virtue of the typical temper- ature gradients found there and the role of inorganic solids mediating chemical reactions in an enzyme-like role. Key Words: Homochirality Prebiotic chemistry.