Juan L. Navarro-Mesa

Universidad de Las Palmas de Gran Canaria | ULPGC · Instituto Universitario para el Desarrollo Tecnológico y la Innovación en Comunicaciones (IDeTIC)

In this paper, we thoroughly analyze the detection of sleep apnea events in the context of Obstructive Sleep Apnea (OSA), which is considered a public health problem because of its high prevalence and serious health implications. We especially evaluate patients who do not always show desaturations during apneic episodes (non-desaturating patients)....

We present a computational study whose objective is to show the capacity of the Nitric Oxide (NO) diffusion for information recovery and indexing related to the classical neural architecture Sparse Distributed Memory (SDM). The study is carried out by introducing NO diffusion dynamics by means of a Multi-compartment based NO Diffusion Model in the...

Nowadays there is a world pandemic of a challenging respiratory illness, COVID-19. A large part of COVID-19 patients evolves to severe or fatal complications and require an ICU admission. COVID-19 mortality rate approaches 30% due to complications such as obstruction of the trachea and bronchi of patients during the ICU stay.

Nowadays, there is a population ageing which leads to an increasing of geriatric and non-communicable diseases. One of the major socio-sanitary challenges our society is facing is dementia, with Alzheimer’s disease (AD) as the most prevalent one. AD is a progressive neurodegenerative disorder over years, with several stages. One of them is the prod...

Due to COVID-19 related complications, many of the diagnosed patients end up needing intensive care. Complications are often severe, to such an extent that mortality rates in these patients may be high. Among the wide variety of complications, we find necrotizing tracheobronchitis, which appears suddenly with the obstruction of the endotracheal tub...

We address the problem of estimating the path loss factor and its integration in RSS-based localization algorithms with wireless sensor networks. We propose an algorithm that relies on a stochastic characterization of the uncertainties in the propagation model. Due to that the path loss factor is unknown and the localization is only based on RSS me...

The Canary Islands are a well known tourist destination with generally stable and clement weather conditions. However, occasionally extreme weather conditions occur, which although very unusual, may cause severe damage to the local economy. The ViMetRi-MAC EU funded project has among its goals, managing climate-change-associated risks. The Spanish...

Rain fall detection has been an important factor under study in a multitude of applications: estimation of floods in order to minimize damage before an environmental risk situation, rain removal from images, agriculture field, etc. Actually, there are numerous methods implemented in order to try to solve this issue. For example, some of them are ba...

The detection and quantification of rainfall is of paramount importance in many application contexts. The research work we present here is devoted to design a system to detect meteorological phenomena in situations of risk. Particularly, we extend the usage of systems designed for other specific purposes incorporating them weather observation as a...

Obstructive sleep apnea is a highly prevalent sleep related breathing disorder and polysomnography is the gold standard exam for diagnosis. Despite providing results with high accuracy this multi-parametric test is expensive, time consuming and does not fit with the new tendency in health care that is changing the focus to prevention and wellness....

Our contribution focuses on the characterization of sleep apnea from a cardiac rate point of view, using Recurrence Quantification Analysis (RQA), based on a Heart Rate Variability (HRV) feature selection process. Three parameters are crucial in RQA: those related to the embedding process (dimension and delay) and the threshold distance. There are...

We introduce a sleep apnea characterization and classification approach based on a Heart Rate Variability (HRV) feature selection process, thus focusing on the characterization of the underlying process from a cardiac rate point of view. Therefore, we introduce linear and nonlinear variables, namely Cepstrum Coefficients (CC), Filterbanks (Fbank) a...

Health care is changing the focus from primary and specialty care to prevention and wellness. Therefore, home health care is seen as one of the most relevant wellness services due to high accessibility and low cost of diagnosis. The growth relevance given to the sleep related disorders, due to the high importance of sleep in our lives, is specifica...

The methods for measuring the exposure to high noise levels are mainly oriented to the working environment; however, listening to music in personal music players is a source of exposure whose analysis requires other tools. We hereby present the design of a system able to analyze and evaluate this exposure using various methods: the personal headpho...

A diagnostic system for sleep apnea based on oxygen saturation and RR intervals obtained from the EKG (electrocardiogram) is proposed with the goal to detect and quantify minute long segments of sleep with breathing pauses. We measured the discriminative capacity of combinations of features obtained from RR series and oximetry to evaluate improveme...

In this paper the permutation entropy (PE) obtained from heart rate variability (HRV) is analyzed in a statistical model. In this model we also integrate other feature extraction techniques, the cepstrum coefficients derived from the same HRV and a set of band powers obtained from the electrocardiogram derived respiratory (EDR) signal. The aim of t...

The Spanish Thematic Network on Speech Technology (RTTH) and the ISCA-Special Interest Group on Iberian Languages (SIG-IL) present the selected papers of IberSpeech 2014, Joint VIII Jornadas en Tecnologías del Habla and IV Iberian SLTech Workshop, held in Las Palmas de Gran Canaria, Spain, November 19-21. The articles are organized into four differ...

Permutation entropy obtained from heart rate variability (HRV) is analyzed in a statistical model integrating electrocardiogram derived respiratory (EDR) features and cepstrum coefficients in order to detect obstructive sleep apnea (OSA) events. 70 ECG recordings from Physionet database are divided into a learning set and a test set of equal size....

Many sleep centres try to perform a reduced portable test in order to decrease the number of overnight polysomnographies that are expensive, time-consuming, and disturbing. With some limitations, heart rate variability (HRV) has been useful in this task. The aim of this investigation was to evaluate if inclusion of symbolic dynamics variables to a...

In this paper, Detrended Fluctuation Analysis (DFA) of Heart Rate Variability (HRV) is applied in order to study the performance of a classification system of Obstructive Sleep Apnea (OSA), that integrates other variables as cepstrum coefficients and filter banks (FBANK) obtained from HR V The database contains 70 records, divided into two equal-si...

This book constitutes the refereed proceedings of the IberSPEECH 2014 Conference, held in Las Palmas de Gran Canaria, Spain, in November 19-21, 2014. The 29 papers presented were carefully reviewed and selected from 60 submissions. The papers are organized in topical sections on speech production, analysis, coding and synthesis; speaker and languag...

Cepstrum Coe f ficients are analyzed in order to study its peiformance in Sleep Apnea Hypopnea Syndrome (SAHS) screening. A forward feature selection technique is applied in order to know for one thing, what cepstrum parameters can extract better information about the influence of breath sleep disorder on the heart rhythm, and on the other hand, tr...

Two automatic statistical methods for the classification of the obstructive sleep apnoea syndrome based on the cepstrum coefficients of the RR series obtained from the Electrocardiogram (ECG) are presented. We study the effect of working with Linear Discriminant Analysis (LDA) and compare its performance with a reference detector based on Support V...

We present a new method for DOA estimation that relies on the assumption that the sources can be modelled as ARMA. A matrix formulation is introduced in the frequency domain so that the available information from the sources can be incorporated thus allowing the DOA estimation with a few sensors and achieve good estimates with acceptable computatio...

We address the problem of estimating the path loss factor and its integration in RSS-based localization algorithms with wireless sensor networks. We propose an algorithm that relies on a stochastic characterization of the uncertainties in the propagation model. Due to that the path loss factor is unknown and the localization is only based on RSS me...

This paper presents sleep quality differences between good and bad sleepers measured with a statistical continuous sleep model according to the Self-Rating Questionnaire for Sleep and Awakening Quality (SSA). Our main goal is to describe sleep continuous traces that take into account the sleep stage probability with a temporal resolution of 3 s, in...

In a previous paper [8] we have proposed a method to improve the classification between two classes in a new transformed space using the Chernoff similarity measure. The key idea is to estimate a transformation matrix such that the overlap between the pdf associated to the competing classes is minimum thus leading to a minimization of the classific...

Cetaceans are prone to collisions with fast vessels, and in areas of high cetacean and vessel density such as in the Canary Islands, the sperm whale (Physeter macrocephalus) is of great concern. Sperm whales are highly vocal and can be localized with passive sonar, but, when at or near the surface, they tend to stop vocalizing, i.e. when they are m...

This paper presents a sleep stage scoring method based on a Hidden Markov Model (HMM) with the goal of obtaining differences between good and bad sleepers according to the Self Rating Questionnaire for Sleep and Awakening Quality (SSA). For the design of the model, we study several parameterization techniques, the model topology and the training st...

The objective of this paper is to propose the use of a speech model with psychoacoustical information to distinguish between the open and closed phases of the vocal folds, in order to monitor formants as phonetic speech characteristics. Taking a frequency warped ARMA model for each one of the phases, the aim is to integrate the information of vario...

In this paper we propose a classification method in the context of Boosting called Transformed Space Boosting (TSB). Our aim is to develop the idea of using a combination of Gaussian Mixture Models and transformation matrices to design 'non-weak' base learners in Boosting strategies. The use of transformation matrices makes it possible to do a line...

We present a new method for improving the classification score in the problem of binary hypothesis testing where the classes are modeled by a Gaussian mixture. We define a cost function which is based on the Chernoff distance and from it a transformation matrix is estimated that maximizes the separation between the classes. Once defined the cost fu...

In this paper we present the performances of two automatic statistical methods for the classification of the obstructive sleep apnoea syndrome based on the RR series obtained from the Electrocardiogram (ECG). We study the effect of working with Support Vector Machines (SVM) and compare its performance with a reference detector based on Gaussian Mix...

This paper proposes a marine mammal classification method that relies in the assumption that the sources are autoregressive (AR). By incorporating the AR coefficients of each source the author make explicit their contribution to the signals at array sensors. A logarithmic likelihood function is introduced in the frequency domain so that all availab...

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In this paper we present a method for the automatic detection of sleep apnoedHypopnoea syndrome. This method comprises five steps. These are, signals segmentation, RR series generarion, feature extraction, model truining and classijication. We explore the usage of the RR series and oxygen saturation (oximetry) signals both independently and jointly...

In this paper we propose a wide-band direction-of-arrival estimation method that relies in the assumption that the sources are autoregressive. A matrix formulation is introduced in the frequency domain so that all available information from the sources can be incorporated thus allowing a new insight in the estimation process. We show that it is pos...

This paper presents a new method for detecting the instants of glottal closure (IGC), or epochs, in noisy environments based on the Cohen's class time-frequency representations (TFR). We define a detection function inspired in a time-frequency formulation for optimum detection and apply a morphologic closing over it to determine the epochs. It comp...

We exploit the properties of the third-order spectra in two proposals to obtain speech detection functions. One is obtained from the principal domain of the bispectrum and the other one from the integrated bispectrum. We have developed a threshold-based system in which the detection functions can be easily integrated. Experiments show the improveme...

The objective of this paper is to propose the use of a speech model to distinguish between the open and closed phases of the vocal folds, in order to monitor formants as phonetic speech characteristics. Taking a parametric ARMA model for each one of the phases, the aim is to integrate the information of various consecutive periods in which the pole...