Assessment of severe apnoea through voice analysis, automatic speech, and speaker recognition techniques

The electronic version of this article is the complete one and can be found online at: http://asp.eurasipjournals.com/content/2009/1/982531This study is part of an ongoing collaborative effort between the medical and the signal processing communities to promote research on applying standard Automatic Speech Recognition (ASR) techniques for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can receive early treatment. Effective ASR-based detection could dramatically cut medical testing time. Working with a carefully designed speech database of healthy and apnoea subjects, we describe an acoustic search for distinctive apnoea voice characteristics. We also study abnormal nasalization in OSA patients by modelling vowels in nasal and nonnasal phonetic contexts using Gaussian Mixture Model (GMM) pattern recognition on speech spectra. Finally, we present experimental findings regarding the discriminative power of GMMs applied to severe apnoea detection. We have achieved an 81% correct classification rate, which is very promising and underpins the interest in this line of inquiry.The activities described in this paper were funded by the Spanish Ministry of Science and Technology as part of the TEC2006-13170-C02-02 Project

Severe apnoea detection using speaker recognition techniques

Proceedings of the International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS 2009)The aim of this paper is to study new possibilities of using Automatic Speaker Recognition techniques (ASR) for detection of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases can be very useful to give priority to their early treatment optimizing the expensive and timeconsuming tests of current diagnosis methods based on full overnight sleep in a hospital. This work is part of an on-going collaborative project between medical and signal processing communities to promote new research efforts on automatic OSA diagnosis through speech processing technologies applied on a carefully designed speech database of healthy subjects and apnoea patients. So far, in this contribution we present and discuss several approaches of applying generative Gaussian Mixture Models (GMMs), generally used in ASR systems, to model specific acoustic properties of continuous speech signals in different linguistic contexts reflecting discriminative physiological characteristics found in OSA patients. Finally, experimental results on the discriminative power of speaker recognition techniques adapted to severe apnoea detection are presented. These results obtain a correct classification rate of 81.25%, representing a promising result underlining the interest of this research framework and opening further perspectives for improvement using more specific speech recognition technologiesThe activities described in this paper were funded by the Spanish Ministry of Science and Technology as part of the TEC2006-13170-C02-01 project

Psychometric properties of the EPQ-A personality questionnaire in a sample of Spanish-speaking adolescents

Se han estudiado las propiedades psicométricas de la escala de personalidad EPQ-A (Eysenck Personality Questionnaire, forma A) en una muestra de adolescentes de El Salvador, México y España, formada por 1.035 participantes con una edad media de 17 años (en la muestra del EPQ-A). La consistencia interna del EPQ-A se ha calculado mediante el coeficiente de fiabilidad alfa de Cronbach, cuyo valor ha sido de .810 en la dimensión de neuroticismo (N), .678 en la dimensión de extraversión (E) y .702 en la de psicoticismo (P). Con respecto a la validez, la estructura factorial hallada explica un porcentaje elevado de varianza (34.26%). También se estudió la validez convergente, correlacionando el EPQ-A con información sociodemográfica, criminológica y otras escalas de personalidad. Se presentan los baremos elaborados por primera vez en una muestra de adolescentes hispanohablantes correspondientes a tres países. De esta manera, los resultados obtenidos sugieren que el inventario de personalidad EPQ-A es un instrumento válido y fiable en población adolescente hispanohablanteA sample of 1,035 adolescents from El Salvador, Mexico, and Spain, with a mean age of 17 years, participated in the study of the psychometric characteristics of the EPQ-A (Eysenck Personality Questionnaire, form A). EPQ-A internal consistency was calculated through Chronbach’s reliability coefficient, with an alpha = .810 for the neuroticism dimension (N), .678 for the extraversion dimension (E), and .702 for the psychoticism dimension (P). As for validity, the factorial structure found explains a high percentage of variance (34.26%); convergent validity was studied by means of correlations between EPQ-A and sociodemographics, criminological information, and other personality scales. Scales were determined for the first time ever in a sample of Spanish-speaking adolescents from three countries. The results suggest that the EPQ-A is a valid and reliable personality inventory in a Spanish-speaking populatio

Reviewing the connection between speech and obstructive sleep apnea

The electronic version of this article is the complete one and can be found online at: http://link.springer.com/article/10.1186/s12938-016-0138-5Background: Sleep apnea (OSA) is a common sleep disorder characterized by recurring breathing pauses during sleep caused by a blockage of the upper airway (UA). The altered UA structure or function in OSA speakers has led to hypothesize the automatic analysis of speech for OSA assessment. In this paper we critically review several approaches using speech analysis and machine learning techniques for OSA detection, and discuss the limitations that can arise when using machine learning techniques for diagnostic applications. Methods: A large speech database including 426 male Spanish speakers suspected to suffer OSA and derived to a sleep disorders unit was used to study the clinical validity of several proposals using machine learning techniques to predict the apnea–hypopnea index (AHI) or classify individuals according to their OSA severity. AHI describes the severity of patients’ condition. We first evaluate AHI prediction using state-of-theart speaker recognition technologies: speech spectral information is modelled using supervectors or i-vectors techniques, and AHI is predicted through support vector regression (SVR). Using the same database we then critically review several OSA classification approaches previously proposed. The influence and possible interference of other clinical variables or characteristics available for our OSA population: age, height, weight, body mass index, and cervical perimeter, are also studied. Results: The poor results obtained when estimating AHI using supervectors or i-vectors followed by SVR contrast with the positive results reported by previous research. This fact prompted us to a careful review of these approaches, also testing some reported results over our database. Several methodological limitations and deficiencies were detected that may have led to overoptimistic results. Conclusion: The methodological deficiencies observed after critically reviewing previous research can be relevant examples of potential pitfalls when using machine learning techniques for diagnostic applications. We have found two common limitations that can explain the likelihood of false discovery in previous research: (1) the use of prediction models derived from sources, such as speech, which are also correlated with other patient characteristics (age, height, sex,…) that act as confounding factors; and (2) overfitting of feature selection and validation methods when working with a high number of variables compared to the number of cases. We hope this study could not only be a useful example of relevant issues when using machine learning for medical diagnosis, but it will also help in guiding further research on the connection between speech and OSA.Authors thank to Sonia Martinez Diaz for her effort in collecting the OSA database that is used in this study. This research was partly supported by the Ministry of Economy and Competitiveness of Spain and the European Union (FEDER) under project "CMC-V2", TEC2012-37585-C02

Speech Signal and Facial Image Processing for Obstructive Sleep Apnea Assessment

Obstructive sleep apnea (OSA) is a common sleep disorder characterized by recurring breathing pauses during sleep caused by a blockage of the upper airway (UA). OSA is generally diagnosed through a costly procedure requiring an overnight stay of the patient at the hospital. This has led to proposing less costly procedures based on the analysis of patients' facial images and voice recordings to help in OSA detection and severity assessment. In this paper we investigate the use of both image and speech processing to estimate the apnea-hypopnea index, AHI (which describes the severity of the condition), over a population of 285 male Spanish subjects suspected to suffer from OSA and referred to a Sleep Disorders Unit. Photographs and voice recordings were collected in a supervised but not highly controlled way trying to test a scenario close to an OSA assessment application running on a mobile device (i.e., smartphones or tablets). Spectral information in speech utterances is modeled by a state-of-the-art low-dimensional acoustic representation, called i-vector. A set of local craniofacial features related to OSA are extracted from images after detecting facial landmarks using Active Appearance Models (AAMs). Support vector regression (SVR) is applied on facial features and i-vectors to estimate the AHI.The activities in this paper were funded by the Spanish Ministry of Economy and Competitiveness and the European Union (FEDER) as part of the TEC2012-37585-C02 (CMC-V2) project. Authors also thank Sonia Martinez Diaz for her effort in collecting the OSA database that is used in this study

Effect of incubation and rearing temperatures on white muscle growth of the common dentex Dentex dentex (Linnaeus, 1758)

In order to determine the impact of temperature on axial muscle growth of common dentex Dentex dentex (Linnaeus, 1758) eggs from the same spawn were divided into four batches and reared under different temperature combinations. The cross-sectional area of white muscle and the number and average area of the white muscle fibres were quantified at different stages of larval development. Our results show that, in newly hatched larvae, slight changes in incubation temperature (≈ 2 ºC) produced significant differences in the cross-sectional area of white muscle, which was greater in the group incubated at ambient temperature. As the larval development advanced, the muscle growth parameters showed the highest values in larvae maintained in constantly heated water.Se pretende valorar el efecto de la temperatura sobre el crecimiento de la musculatura axial del dentón Dentex dentex (Linnaeus, 1758). Para ello se incubó una puesta distribuida en cuatro lotes que fueron sometidos a combinaciones de temperatura. En distintos momentos del desarrollo larvario se cuantificó el área total del miotomo, el área de las fibras blancas y el número de fibras blancas de la sección transversal. Los resultados han demostrado que modificaciones pequeñas en la temperatura de incubación (≈ 2 ºC) producen diferencias significativas en el área transversal total del músculo blanco de las larvas recién eclosionadas, diferencias que son mayores en los ejemplares incubados a temperatura ambiente. A medida que avanza el desarrollo de las larvas se produce una inversión y pasan a ser mayores los parámetros de crecimiento muscular en las larvas mantenidas siempre en agua que es calentada.Instituto Español de Oceanografí

Building a Gold Standard Dataset to Identify Articles About Geographic Information Science

To know the overall regional or international scientific production is of vital importance to many areas of knowledge. Nevertheless, in interdisciplinary areas such as Geographic Information Science (GISc) it is not enough to just count papers published in specific journals. Most of them, as is the case of the International Journal of Remote Sensing (IJRS), welcome GISc papers but are not exclusive to that area so the production assignable to authors in the region must consider not only affiliation but also whether or not each paper falls into the theme of GISc. IJRS publishes far more papers than any other GISc journal, so it is important to assess quantitatively how many of them are of GISc. In this work, a representative sample of IJRS articles published over a period of almost 30 years was analyzed using a specific GISc definition. With these data, a manual classification methodology through a set of experts was carried out, and a dataset was built, analyzed, and statistically tested. As a result we estimate that between 47 and 76% of the IJRS articles can be considered from GISc, with a confidence level of 95%. Aside from the primary goal, this set could be used as a gold standard for future classification tasks. It constitutes the first GISc dataset of this kind, that may be used to train artificial intelligence systems capable of performing the same classification automatically and in a massive way. A similar procedure could be applied to other interdisciplinary fields of knowledge as well

Clinical Predictors of Hyperperfusion Syndrome Following Carotid Stenting: Results From a National Prospective Multicenter Study

[Objectives] The aim of the HISPANIAS (HyperperfusIon Syndrome Post-carotid ANgIoplasty And Stenting) study was to define CHS rates and develop a clinical predictive model for cerebral hyperperfusion syndrome (CHS) after carotid artery stenting (CAS).[Background] CHS is a severe complication following CAS. The presence of clinical manifestations is estimated on the basis of retrospective reviews and is still uncertain.[Methods] The HISPANIAS study was a national prospective multicenter study with 14 recruiting hospitals. CHS was classified as mild (headache only) and moderate-severe (seizure, impaired level of consciousness, or development of focal neurological signs).[Results] A total of 757 CAS procedures were performed. CHS occurred in 22 (2.9%) patients, in which 16 (2.1%) had moderate-severe CHS and 6 (0.8%) had mild CHS (only headache). The rate of hemorrhages was 0.7% and was associated with high mortality (20%). Pre-operative predictors of moderate-severe CHS in multivariate analysis were female sex (odds ratio [OR]: 3.24; 95% confidence interval [CI]: 1.11 to 9.47; p = 0.03), older patients (OR: 1.09; 95% CI: 1.01 to 1.17; p = 0.02), left carotid artery treated (OR: 4.13; 95% CI: 1.11 to 15.40; p = 0.03), and chronic renal failure (OR: 6.29; 95% CI: 1.75 to 22.57; p = 0.005). The area under the curve of this clinical and radiological model was 0.86 (95% CI: 0.81 to 0.92; p = 0.001).[Conclusions] The rate of CHS in the HISPANIAS study was 2.9%, with moderate-severe CHS of 2.1%. CHS was independently associated with female sex, older age, history of chronic kidney disease, and a treated left carotid artery. Although further investigations are needed, the authors propose a model to identify high-risk patients and develop strategies to decrease CHS morbidity and mortality in the future.This study was supported by a Spanish grant from the Instituto de Salud Carlos III (ISCIII-FIS IP14/00971, 2014–2017). The ITRIBIS project has the registration number REGPOT-2013-1. Cooperative Cerebrovascular Disease Research Network (INVICTUS+) (RD16/0019/0015). Dr. Mancha is supported by a Río Hortega contract (CM16/00015). Abbott and Grifols have partial financial supported the conduction of the HISPANIAS project but had no role in the design of the study, interpretation of the data, or manuscript approval.Peer reviewe

Apego y violencia de pareja en una muestra de adolescentes

Different perspectives have analyze the phenomenon of partner violence from different associated factors, arguing that not only is a factor involved in violence but different variables, such as attachment. Therefore, this research analyzes the importance of the attachment with parents and peers and its association with the presence of violent behavior in dating relationships in adolescents. A quantitative approach was used, with a non-experimental and ex post facto design, the scope was descriptive and correlational. The sample consisted of 586 Mexican adolescents, aged between 14 and 19 years. Among other results, it is emphasized that the attachment to the father is related to at least some type of violence in relationships, in addition to the fact that both sexes are victims and perpetrators of violent behavior in their courtship relationships.Diversas perspectivas han indagado el fenómeno de la violencia de pareja desde distintos factores asociados, argumentado que no solo es un factor que interviene en la violencia sino distintas variables, como el apego. Por ello en esta investigación se analiza la importancia de la relación afectiva que se tiene con los padres y los pares con la presencia de conductas violentas en las relaciones de noviazgo en adolescentes. Se empleó un enfoque cuantitativo, con un diseño no experimental y ex post facto, con alcances descriptivos y correlacionales. La muestra fue constituida por 586 adolescentes mexicanos, con edades comprendidas entre 14 y 19 años. Entre otros resultados, se destaca que el apego hacia el padre guarda relación con al menos algún tipo de violencia en las relaciones de pareja, además de que ambos sexos son víctimas y perpetradores de conductas violentas en sus relaciones de noviazgo

Apego y violencia de pareja en una muestra de adolescentes

Diversas perspectivas han indagado el fenómeno de la violencia de pareja desde distintos factores asociados, argumentado que no solo es un factor que interviene en la violencia sino distintas variables, como el apego. Por ello en esta investigación se analiza la importancia de la relación afectiva que se tiene con los padres y los pares con la presencia de conductas violentas en las relaciones de noviazgo en adolescentes. Se empleó un enfoque cuantitativo, con un diseño no experimental y ex post facto, con alcances descriptivos y correlacionales. La muestra fue constituida por 586 adolescentes mexicanos, con edades comprendidas entre 14 y 19 años. Entre otros resultados, se destaca que el apego hacia el padre guarda relación con al menos algún tipo de violencia en las relaciones de pareja, además de que ambos sexos son víctimas y perpetradores de conductas violentas en sus relaciones de noviazgo