SISBIO - Biomedical Signals and Systems
Total activity: 1178
Type
Research group
Type of group
UPC research group
Acronym
SISBIO
blanc
http://www.creb.upc.es/Divisions/senyals.htm Open in new window
Objectives
To design and develop advanced biomedical signal processing techniques for the monitoring, diagnosis and therapy of pathologies. The specific objectives are as follows: a) the study of theoretical aspects of signal processing techniques and their applicability to the interpretation of biomedical signals to improve the processing of medical information; b) the development of technological applications to be used in clinical environments, including the use of medical instrumentation; and c) the modelling and simulation of biological systems to improve knowledge of physiological systems and to design new therapeutic procedures. The fields of application are electrocardiography, mobile monitoring equipment, respiratory muscle activity, respiratory sounds, snoring signals, respiratory pattern variability, cardiorespiratory coupling, electroencephalography, polysomnographic signals, etc.
Keywords
Diagnòstic,Interpretació de senyals,Modelització de biosistemes,Monitorització,Processament de senyals,Senyals biomèdics,Sistemes biomèdics,Teràpia

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1 to 50 of 1178 results
  • Data simulation in machine olfaction with the R package chemosensors

     Ziyatdinov, Andrey; Perera Lluna, Alexandre
    PLoS One
    Date of publication: 2014-02
    Journal article

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  • Peak aggregation as an innovative strategy for improving the predictive power of LC-MS metabolomic profiles

     Fernandez Albert, Francesc; Llorach, Rafael; Andres LaCueva, Cristina; Perera Lluna, Alexandre
    Analytical chemistry
    Date of publication: 2014-02-28
    Journal article

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  • Blood pressure variability analysis in supine and sitting position of healthy subjects

     Giraldo Giraldo, Beatriz F.; Calvo, Alejandro; Martínez, Beatriz; Arcentales, Andrés; Jane Campos, Raimon; Benito Vales, Salvador
    Date of publication: 2014
    Book chapter

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    Blood pressure carries a great deal of information about people¿s physical attributes. We analyzed the blood pressure signal in healthy subjects considering two positions, supine and sitting. 44 healthy subjects were studied. Parameters extracted from the blood pressure signal, related to time and frequency domain were used to compare the effect of postural position between supine and sitting. In time domain analysis, the time systolic interval and the time of blood pressure interval were higher in supine than in sitting position (p = 0.001 in both case). Parameters related to frequency peak, interquartile range, in frequency domain presented statistically significant difference (p¿< 0.0005 in both case). The blood pressure variability parameters presented smaller values in supine than in sitting position (p¿< 0.0005). In general, the position change of supine to sitting produces an increment in the pressure gradient inside heart, reflected in the blood pressure variability.

  • Evaluation of Laplacian diaphragm electromyographic recordings in a static inspiratory maneuver

     Estrada, Luis; Torres Cebrian, Abel; Garcia Casado, Javier; Ye-Lin, Y.; Jane Campos, Raimon
    Mediterranean Conference on Medical and Biological Engineering and Computing
    Presentation's date: 2014-09-27
    Presentation of work at congresses

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    Diaphragm electromyography (EMGdi) provides important information on diaphragm activity, to detect neuromuscular disorders of the most important muscle in the breathing inspiratory phase. EMGdi is habitually recorded using needles or esophageal catheters, with the implication of being invasive for patients. Surface electrodes offer an alternative for the non-invasive assessment of diaphragm activity. Ag/AgCl surface disc electrodes are used in monopolar or bipolar configuration to record EMGdi signals. On the other hand, Laplacian surface potential can be estimated by signal recording through active concentric ring electrodes. This kind of recording could reduce physiological interferences, increase the spatial selectivity and reduce orientation problems in the electrode location. The aim of this work is to compare EMGdi signals recorded simultaneously with disc electrodes in bipolar configuration and a Laplacian ring electrode over chest wall. EMGdi signal was recorded in one healthy subject during a breath hold maneuver and a static inspiratory maneuver based on Mueller¿s technique. In order to estimate the covered frequency range and the degree of noise contamination in both bipolar and Laplacian EMGdi signals, the cumulative percentage of the power spectrum and the signal to noise ratio in sub-bands were determined. Furthermore, diaphragm fatigue was evaluated by means of amplitude and frequency parameters. Our findings suggest that Laplacian EMGdi recording covers a broader frequency range although with higher noise contamination compared to bipolar EMGdi recording. Finally, in Laplacian recording fatigue indexes showed a clearer trend for muscle fatigue detection and also a reduced cardiac interference, providing an alternative to bipolar recording for diaphragm fatigue studies.

  • Automatic capacitor bank identification in power distribution systems

     Perera Lluna, Alexandre; Manivannan, Karthick; Xu, Peng; Gutierrez-Osuna, Ricardo; Benner, Carl; Russell, B. Don
    Electric power systems research
    Date of publication: 2014-06
    Journal article

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  • Effect of genetic regions on the correlation between single point mutation variability and morbidity

     Brunel, Helena; Gallardo Chacon, Juan José; Vallverdú Ferrer, Montserrat; Caminal Magrans, Pedro; Perera Lluna, Alexandre
    Computers in biology and medicine
    Date of publication: 2013-06-01
    Journal article

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    Cross-species sequence comparisons have suggested that cross-species sequence variability is correlated with functionality. The goal of this study was to extend this observation at different genetic regions, focusing on the morbidity of Single Nucleotide Polymorphisms (SNPs). A set of deleterious SNPs was compared to a set of neutral SNPs. Both samples were stratified according to the location of the SNPs at different genetic regions. Deleterious SNPs were observed to be less variable across species than neutral SNPs, these differences being significant for missense mutations (p=1.1×10-9p=1.1×10-9), SNPs in introns (p=6.4×10-3p=6.4×10-3), and SNPs in unknown regions (p=8×10-4p=8×10-4).

  • Complexity of the autonomic heart rate control in coronary artery occlusion in patients with and without prior myocardial infarction

     Magrans Nicieza, Rudys; Gomis Román, Pedro; Caminal Magrans, Pedro; Wagner, G.S.
    Medical engineering and physics
    Date of publication: 2013-08-01
    Journal article

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    Autonomic nervous system (ANS) is governed by complex interactions arising from feedback loops of nonlinear systems that operate over a wide range of temporal and spatial scales, enabling the organism to adapt to stress, metabolic changes and diseases. This study is aimed to assess multifractal and nonlinear characteristics of the ANS during ischemic events provoked by a prolonged percutaneous coronary intervention (PCI) procedure. Eighty-seven patients from the STAFF III database were used. Patients were classified into 2 groups: (1) with prior myocardial infarction (MI) and (2) without MI (noMI). R¿R signals during three 3-min stages of the procedures were analyzed using multifractal and surrogate data techniques. Multifractal indices increased significantly from the pre-inflation stage to the post-deflation stage. These variations were more marked for the noMI group. Multifractal changes significantly correlated with both the decreased parasympathetic and the increased sympathetic modulations accounted by classical linear indices. Multifractal measures resulted to be a more powerful indicator than linear HRV indices in quantifying the ischemia-induced changes. Right coronary artery (RCA) occlusions provoke greater multifractal reactions throughout the PCI procedure. Our findings suggest reduced complex multifractal and nonlinear reactions of ANS activity in patients with prior MI in comparison to the noMI group, possibly due to degradation in the complexity of control mechanism of heart rate generation

  • Features extraction method for brain-machine communication based on the empirical mode decomposition

     Diez, Pablo F.; Mut, Vicente A.; Laciar, Eric; Torres Cebrian, Abel; Avila Perona, Enrique M.
    Biomedical Engineering: Applications, Basis and Communications
    Date of publication: 2013-07
    Journal article

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    A brain-machine interface (BMI) is a communication system that translates human brain activity into commands, and then these commands are conveyed to a machine or a computer. It is proposes a technique for features extraction from electroencephalographic (EEG) signals and afterward, their classification on different mental tasks. The empirical mode decomposition (EMD) is a method capable of processing non-stationary and nonlinear signals, as the EEG. The EMD was applied on EEG signals of seven subjects performing five mental tasks. Six features were computed, namely, root mean square (RMS), variance, Shannon entropy, Lempel-Ziv complexity value, and central and maximum frequencies. In order to reduce the dimensionality of the feature vector, the Wilks' lambda (WL) parameter was used for the selection of the most important variables. The classification of mental tasks was performed using linear discriminant analysis (LDA) and neural networks (NN). Using this method, the average classification over all subjects in database is 91 5% and 87 5% using LDA and NN, respectively. Bit rate was ranging from 0.24 bits/trial up to 0.84 bits/trial. The proposed method allows achieving higher performances in the classification of mental tasks than other traditional methods using the same database. This represents an improvement in the brain-machine communication system. 2013 National Taiwan University.

  • Feasibility of noninvasive single-channel automated differentiation of obstructive and central hypopneas with nasal airflow

     Morgenstern de Muller, Christian; Randerath, Winfried J.; Schwaibold, Matthias; Bolz, Armin; Jane Campos, Raimon
    Respiration
    Date of publication: 2013-03
    Journal article

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    Background: The identification of obstructive and central hypopneas is considered challenging in clinical practice. Presently, obstructive and central hypopneas are usually not differentiated or scores lack reliability due to the technical limitations of standard polysomnography. Esophageal pressure measurement is the gold-standard for identifying these events but its invasiveness deters its usage in daily practice. Objectives: To determine the feasibility and efficacy of an automatic noninvasive analysis method for the differentiation of obstructive and central hypopneas based solely on a single-channel nasal airflow signal. The obtained results are compared with gold-standard esophageal pressure scores. Methods: A total of 41 patients underwent full night polysomnography with systematic esophageal pressure recording. Two experts in sleep medicine independently differentiated hypopneas with the gold-standard esophageal pressure signal. Features were automatically extracted from the nasal airflow signal of each annotated hypopnea to train and test the automatic analysis method. Interscorer agreement between automatic and visual scorers was measured with Cohen's kappa statistic (¿). Results: A total of 1,237 hypopneas were visually differentiated. The automatic analysis achieved an interscorer agreement of ¿ = 0.37 and an accuracy of 69% for scorer A, ¿ = 0.40 and 70% for scorer B and ¿ = 0.41 and 71% for the agreed scores of scorers A and B. Conclusions: The promising results obtained in this pilot study demonstrate the feasibility of noninvasive single-channel hypopnea differentiation. Further development of this method may help improving initial diagnosis with home screening devices and offering a means of therapy selection and/or control.

    Background: The identification of obstructive and central hypopneas is considered challenging in clinical practice. Presently, obstructive and central hypopneas are usually not differentiated or scores lack reliability due to the technical limitations of standard polysomnography. Esophageal pressure measurement is the gold-standard for identifying these events but its invasiveness deters its usage in daily practice. Objectives: To determine the feasibility and efficacy of an automatic noninvasive analysis method for the differentiation of obstructive and central hypopneas based solely on a single-channel nasal airflow signal. The obtained results are compared with gold-standard esophageal pressure scores. Methods: A total of 41 patients underwent full night polysomnography with systematic esophageal pressure recording. Two experts in sleep medicine independently differentiated hypopneas with the gold-standard esophageal pressure signal. Features were automatically extracted from the nasal airflow signal of each annotated hypopnea to train and test the automatic analysis method. Interscorer agreement between automatic and visual scorers was measured with Cohen’s kappa statistic (κ). Results: A total of 1,237 hypopneas were visually differentiated. The automatic analysis achieved an interscorer agreement of κ = 0.37 and an accuracy of 69% for scorer A, κ = 0.40 and 70% for scorer B and κ = 0.41 and 71% for the agreed scores of scorers A and B. Conclusions: The promising results obtained in this pilot study demonstrate the feasibility of noninvasive single-channel hypopnea differentiation. Further development of this method may help improving initial diagnosis with home screening devices and offering a means of therapy selection and/or control.

  • Ischemic risk stratification by means of multivariate analysis of the heart rate variability

     Valencia Murillo, Jose Fernando; Vallverdú Ferrer, Montserrat; Voss, Andreas; Porta, Alberto; Vázquez, Rafael; Caminal Magrans, Pedro; Bayes de Luna, Antonio
    Physiological measurement
    Date of publication: 2013
    Journal article

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    In this work, a univariate and multivariate statistical analysis of indexes derived from heart rate variability (HRV) was conducted to stratify patients with ischemic dilated cardiomyopathy (IDC) in cardiac risk groups. Indexes conditional entropy, refined multiscale entropy (RMSE), detrended fluctuation analysis, time and frequency analysis, were applied to the RR interval series (beat-to-beat series), for single and multiscale complexity analysis of the HRV in IDC patients. Also, clinical parameters were considered. Two different end-points after a follow-up of three years were considered: (i) analysis A, with 151 survivor patients as a low risk group and 13 patients that suffered sudden cardiac death as a high risk group; (ii) analysis B, with 192 survivor patients as a low risk group and 30 patients that suffered cardiac mortality as a high risk group. A univariate and multivariate linear discriminant analysis was used as a statistical technique for classifying patients in risk groups. Sensitivity (Sen) and specificity (Spe) were calculated as diagnostic criteria in order to evaluate the performance of the indexes and their linear combinations. Sen and Spe values of 80.0% and 72.9%, respectively, were obtained during daytime by combining one clinical parameter and one index from RMSE, and during nighttime Sen = 80% and Spe = 73.4% were attained by combining one clinical factor and two indexes from RMSE. In particular, relatively long time scales were more relevant for classifying patients into risk groups during nighttime, while during daytime shorter scales performed better. The results suggest that the left atrial size, indexed to body surface and RMSE indexes are those that allow enhanced classification of ischemic patients in their respective risk groups, confirming that a single measurement is not enough to fully characterize ischemic risk patients and the clinical relevance of HRV complexity measures.

  • Heart rate variability analysis in ischemic cardiomyopathy and aortic stenosis patients

     Valencia Murillo, Jose Fernando; Vallverdú Ferrer, Montserrat; Porta, Alberto; Voss, Andreas; Vázquez, Rafael; Caminal Magrans, Pedro
    Date of publication: 2013-06-18
    Book chapter

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  • Biologically inspired large scale chemical sensor arrays and embedded data processing

     Marco Colas, Santiago; Gutierrez-Galvez, Agustin; Lansner, Anders; Martinez, Dominique; Rospars, Jean Piere; Beccherelli, Romeo; Perera Lluna, Alexandre; Pearce, Timmothy Charles; Vershure, Paul; Persaud, Krishna C.
    SPIE Optical Systems Design
    Presentation of work at congresses

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    Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. EU Funded Project NEUROCHEM (Bio-ICT-FET- 216916) has developed novel computing paradigms and biologically motivated artefacts for chemical sensing taking inspiration from the biological olfactory pathway. To demonstrate this approach, a biomimetic demonstrator has been built featuring a large scale sensor array (65K elements) in conducting polymer technology mimicking the olfactory receptor neuron layer, and abstracted biomimetic algorithms have been implemented in an embedded system that interfaces the chemical sensors. The embedded system integrates computational models of the main anatomic building blocks in the olfactory pathway: The olfactory bulb, and olfactory cortex in vertebrates (alternatively, antennal lobe and mushroom bodies in the insect). For implementation in the embedded processor an abstraction phase has been carried out in which their processing capabilities are captured by algorithmic solutions. Finally, the algorithmic models are tested with an odour robot with navigation capabilities in mixed chemical plumes.

  • Cardiac interference reduction in diaphragmatic MMG signals during a maintained inspiratory pressure test

     Sarlabous, Leonardo; Torres Cebrian, Abel; Fiz, José Antonio; Jane Campos, Raimon
    IEEE Engineering in Medicine and Biology Society
    Presentation's date: 2013-07
    Presentation of work at congresses

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    A recursive least square (RLS) adaptive filtering algorithm for reduction of cardiac interference in diaphragmatic mecanomyographic (MMGdi) signals is addressed in this paper. MMGdi signals were acquired with a capacitive accelerometer placed between 7th and 8th intercostal spaces, on the right anterior axillary line, during a maintained inspiratory pressure test. Subjects were asked to maintain a constant inspiratory pressure with a mouthpiece connected to a closed tube (without breathing). This maneuver was repeated at five different contraction efforts: apnea (no effort), 20 cmH2O, 40 cmH2O, 60 cmH2O and maximum voluntary contraction. An adaptive noise canceller (ANC) using the RLS algorithm was applied on the MMGdi signals. To evaluate the behavior of the ANC, the MMGdi signals were analyzed in two segments: with and without cardiac interference (WCI and NCI, respectively). In both segments it was analyzed the power spectral density (PSD), and the ARV and RMS amplitude parameters for each contraction effort. With the proposed ANC algorithm the amplitude parameters of the WCI segments were reduced to a level similar to the one of the NCI segments. The obtained results showed that ANC using the RLS algorithm allows to significantly reduce the cardiac interference in MMGdi signals.

  • Cancellation of cardiac interference in diaphragm EMG signals using an estimate of ECG reference signal

     Torres Cebrian, Abel; Fiz, José Antonio; Jane Campos, Raimon
    Mediterranean Conference on Medical and Biological Engineering and Computing
    Presentation's date: 2013-09-27
    Presentation of work at congresses

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    The analysis of the electromyographic signal of the diaphragm muscle (EMGdi) can provide important information in order to evaluate the respiratory muscular function. However, EMGdi signals are usually contaminated by the electrocardiographic (ECG) signal. An adaptive noise cancellation (ANC) based on event-synchronous cancellation can be used to reduce the ECG interference in the recorded EMGdi activity. In this paper, it is proposed an ANC scheme for cancelling the ECG interference in EMGdi signals using only the EMGdi signal (without acquiring the ECG signal). In this case the detection of the QRS complex has been performed directly in the EMGdi signal, and the ANC algorithm must be robust to false or missing QRS detections. Furthermore, an automatic criterion to select the adaptive constant of the LMS algorithm has been proposed (µ). The µ constant is selected automatically so that the canceling signal energy equals the energy of the reference signal (which is an estimation of the ECG interference present in the EMGdi signal). This approach optimizes the tradeoff between cancellation of ECG interference and attenuation of EMG component. A number of weights equivalent of a time window that contains several QRS complexes is selected in order to make the algorithm robust to QRS detection errors.

  • Study of the oscillatory breathing pattern in elderly patients

     Giraldo Giraldo, Beatriz F.; Tellez, Joan P.; Herrera, Sergio; Benito Vales, Salvador
    IEEE Engineering in Medicine and Biology Society
    Presentation's date: 2013-06
    Presentation of work at congresses

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    Some of the most common clinical problems in elderly patients are related to diseases of the cardiac and respiratory systems. Elderly patients often have altered breathing patterns, such as periodic breathing (PB) and Cheyne-Stokes respiration (CSR), which may coincide with chronic heart failure. In this study, we used the envelope of the respiratory flow signal to characterize respiratory patterns in elderly patients. To study different breathing patterns in the same patient, the signals were segmented into windows of 5 min. In oscillatory breathing patterns, frequency and time-frequency parameters that characterize the discriminant band were evaluated to identify periodic and non-periodic breathing (PB and nPB). In order to evaluate the accuracy of this characterization, we used a feature selection process, followed by linear discriminant analysis. 22 elderly patients (7 patients with PB and 15 with nPB pattern) were studied. The following classification problems were analyzed: patients with either PB (with and without apnea) or nPB patterns, and patients with CSR versus PB, CSR versus nPB and PB versus nPB patterns. The results showed 81.8% accuracy in the comparisons of nPB and PB patients, using the power of the modulation peak. For the segmented signal, the power of the modulation peak, the frequency variability and the interquartile ranges provided the best results with 84.8% accuracy, for classifying nPB and PB patients.

  • Analysis of epileptic EEG signals in children by symbolic dynamics

     Paternoster, Luca; Vallverdú Ferrer, Montserrat; Melia, Umberto Sergio Pio; Claria, Francisco; Voss, Andreas; Caminal Magrans, Pedro
    International Conference of the IEEE Engineering in Medicine and Biology Society
    Presentation's date: 2013-07-03
    Presentation of work at congresses

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    Epilepsy is one of the most prevalent neurological disorders among children. The study of surface EEG signals in patients with epilepsy by techniques based on symbolic dynamics can provide new insights into the epileptogenic process and may have considerable utility in the diagnosis and treatment of epilepsy. The goal of this work was to find patterns from a methodology based on symbolic dynamics to characterize seizures on surface EEG in pediatric patients with intractable epilepsy. A total of 76 seizures were analyzed by their pre-ictal, ictal and post-ictal phases. An analytic signal envelope algorithm was applied to each EEG segment and its performance was evaluated. Several variables were defined from the distribution of words constructed on the EEG transformed into symbols. The results showed strong evidences of detectable non-linear changes in the EEG dynamics from pre-ictal to ictal phase and from ictal to post-ictal phase, with an accuracy higher than 70%.

  • Auto-mutual information function for predicting pin responses in EEG signals during sedation

     Melia, Umberto Sergio Pio; Vallverdú Ferrer, Montserrat; Jospin, Matieu; Jensen, Erik W.; Valencia, J.F.; Clarià, Francesc; Gambus, Pedro L.; Caminal Magrans, Pedro
    Mediterranean Conference on Medical and Biological Engineering and Computing
    Presentation's date: 2013-09-25
    Presentation of work at congresses

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    The level of sedation in patients undergoing medical procedures evolves continuously, such as the effect of the anesthetic and analgesic agents is counteracted by pain stimuli. The monitors of depth of anesthesia, based on the analysis of the electroencephalogram (EEG), have been progressively introduced into the daily practice to provide additional information about the state of the patient. However, the quantification of analgesia still remains an open problem. The purpose of this work was to analyze the capability of prediction of nociceptive responses based on the auto-mutual information function (AMIF). AMIF measures were calculated on EEG signal in order to predict the presence or absence of the nociceptive responses to endoscopy tube insertion during sedation in endoscopy procedure. Values of prediction probability of Pk above 0.80 and percentages of sensitivity and specificity above 70% and 70% respectively were achieved combining AMIF with power spectral density and concentrations of remifentanil.

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    Methodology for determine the moment of disconnection of patients of the mechanical ventilation using discrete wavelet transform  Open access

     González Acuña, Hernan; Gonzalez Acevedo, Hernando; Arizmendi Pereira, Carlos Julio; Giraldo Giraldo, Beatriz F.
    International Conference on Complex Medical Engineering
    Presentation's date: 2013-05
    Presentation of work at congresses

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    The process of weaning from mechanical ventilation is one of the challenges in intensive care units. 66 patients under extubation process (T-tube test) were studied: 33 patients with successful trials and 33 patients who failed to maintain spontaneous breathing and were reconnected. Each patient was characterized using 7 time series from respiratory signals, and for each serie was evaluated the discrete wavelet transform. It trains a neural network for discriminating between patients from the two groups.

    The process of weaning from mechanical ventilation is one of the challenges in intensive care units. 66 patients under extubation process (T-tube test) were studied: 33 patients with successful trials and 33 patients who failed to maintain spontaneous breathing and were reconnected. Each patient was characterized using 7 time series from respiratory signals, and for each serie was evaluated the discrete wavelet transform. It trains a neural network for discriminating between patients from the two groups.

  • Higuchi¿s fractal complexity of RR and QT interval eeries during transient myocardial ischemia

     Magrans Nicieza, Rudys; Gomis Román, Pedro; Caminal Magrans, Pedro; Voss, Andreas
    Computing in Cardiology
    Presentation's date: 2013-09-24
    Presentation of work at congresses

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    Myocardial ischemia may lead to significant changes in autonomic control of heart rate (HR) affecting its variability and alter beat-to-beat ventricular repolarization periods. We hypothesized that transient myocardial ischemia affects the complex dynamics of the HR and QT. The aim of this study was to assess the RR and QT interval time series complexity using Higuchi¿s fractal dimension (HFD) during prolonged balloon occlusion of one of the major coronary arteries. Eighty-five patients who underwent elective percutaneous coronary intervention procedures were selected. Patients were classified into 2 groups according to the presence of prior healed myocardial infarction (INF) (n = 29) or not (No_INF) (n = 56). RR, QT and QTc (Bazzet¿s formula) time series were obtained from continuous ECG. Three 3-minute stages were chosen: (1) preinflation as baseline (pre), (2) from the start of occlusion (pci), and (3) immediately post deflation (post_pci). HFD was calculated on each 3-minute stage time series to quantify the changing complexity and self-similarity of RR, QT and QTc time series (HFD RR, HFD QT and HFD QTc, respectively). Cohen¿s d statistics were included to measure the effect size of the procedure. HFD values decreased significantly from baseline to pci and post_pci in the three time-series. HFD RR, 1.76 ± 0.13 vs. 1.69 ± 0.15 (p<0.001, Cohen¿s d = -0.64); HFD QT, 1.90 ± 0.11 vs 1.82 ± 0.13 (p<0.001, d = -0.67); HFD QTc, 1.88 ± 0.09 vs. 1.83 ± 0.11 (p<0.01, d= -0.46). The HFD reduction was greater from baseline to post_pci (p<0.001, d = -0.99 (RR), d = -1.02 (QT)). HFD of QT intervals decreases during the procedure predominantly in the No_INF group. The time series studied, related to autonomic control of HR and to the variability of ventricular repolarization, exhibit a reduced complexity provoked by transient myocardial ischemia.

  • Analysis of muscle coupling during isokinetic endurance contractions by means of nonlinear prediction

     Rojas Martínez, Mónica; Alonso López, Joan Francesc; Chaler Vilaseca, Joaquim Lluís; Mañanas Villanueva, Miguel Angel
    IEEE Engineering in Medicine and Biology Society
    Presentation's date: 2013-07
    Presentation of work at congresses

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    Isokinetic exercises have been extensively used in order to analyze muscle imbalances and changes associated with fatigue. It is known that such changes are difficult to assess from EMG signals during dynamic contractions, especially, using linear signal processing tools. The aim of this work was to use nonlinear prediction in order to analyze muscle couplings and interactions in this context and to assess the load-sharing of different muscles during fatigue. Results show promising for detecting interaction strategies between muscles and even for the interaction between muscles and the output torque during endurance tests.

  • Prediction of nociceptive responses during sedation by time-frequency representation

     Melia, Umberto Sergio Pio; Vallverdú Ferrer, Montserrat; Jospin, Mathieu; Jensen, Erik W.; Valencia, Jose Fernando; Clarià, Francesc; Gambus, Pedro L.; Caminal Magrans, Pedro
    International Conference of the IEEE Engineering in Medicine and Biology Society
    Presentation's date: 2013-07-03
    Presentation of work at congresses

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    The level of sedation in patients undergoing medical procedures evolves continuously, such as the effect of the anesthetic and analgesic agents is counteracted by pain stimuli. The monitors of depth of anesthesia, based on the analysis of the electroencephalogram (EEG), have been progressively introduced into the daily practice to provide additional information about the state of the patient. However, the quantification of analgesia still remains an open problem. The purpose of this work is to analyze the capability of prediction of nociceptive responses based on the time-frequency representation (TFR) of EEG signal. Functions of spectral entropy, instantaneous power and instantaneous frequency were calculated in order to predict the presence or absence of the nociceptive responses to different stimuli during sedation in endoscopy procedure. Values of prediction probability of Pk above 0.75 and percentages of sensitivity and specificity above 70% and 65% respectively were achieved combining TFR functions with bispectral index (BIS) and with concentrations of propofol (CeProp) and remifentanil (CeRemi).

  • Análisis espectral no lineal del EEG de niños con epilepsia intratable

     Portolés, oscar; Schroeder, Rico; Vallverdú Ferrer, Montserrat; Voss, Andreas; Caminal Magrans, Pedro
    Jornadas de Automàtica
    Presentation's date: 2013-09-04
    Presentation of work at congresses

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  • Refined multiscale entropy analysis of heart period and QT interval variabilities in long QT syndrome type-1 patients

     Bari, V.; Valencia, Jose Fernando; Vallverdú Ferrer, Montserrat; Girardengo, G.; Bassani, T.; Marchi, A.; Calvillo, L.; Caminal Magrans, Pedro; Cerutti, Sergio; Brink, P.A.; Crotti, L.; Schwartz, P.J.; Porta, A.
    International Conference of the IEEE Engineering in Medicine and Biology Society
    Presentation's date: 2013-07-03
    Presentation of work at congresses

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    This study assesses complexity of cardiovascular control in patients affected by type-1 variant of long QT (LQT1) syndrome. Complexity was assessed by refined multiscale entropy of heart period (HP) and QT interval variabilities. HP was taken as the time distance between two consecutive R peaks (RR) and QT interval was approximated as the time distance between the R-peak and T-wave apex (RTa) and between R-peak and T-wave end (RTe). RR, RTa and RTe intervals were automatically extracted from 24h Holter recordings and the daytime period was analyzed (from 02:00 to 06:00 PM). Non mutation carrier (NMC) individuals (n=11), utilized as a control group, were taken from the same family line of the mutation carrier (MC) subjects (n=26). We found that, while NMC and MC groups were indistinguishable based on time domain and complexity analyses of RR dynamics, complexity analysis of RTa and RTe variabilities clearly separates the two populations and suggests an impairment in the cardiac control mechanisms acting on the ventricles.

  • Characterization of patients with different ventricular ejection fractions using blood pressure signal analysis

     Arcentales, Andrés; Voss, Andreas; Caminal Magrans, Pedro; Bayes-Genis, Antoni; Domingo, Mar Teresa; Giraldo Giraldo, Beatriz F.
    Computing in Cardiology
    Presentation's date: 2013-09
    Presentation of work at congresses

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    Ischemic and dilated cardiomyopathy are associated with disorders of myocardium. Using the blood pressure (BP) signal and the values of the ventricular ejection fraction, we obtained parameters for stratifying cardiomyopathy patients as low- and high-risk. We studied 48 cardiomyopathy patients characterized by NYHA =2: 19 patients with dilated cardiomyopathy (DCM) and 29 patients with ischemic cardiomyopathy (ICM). The left ventricular ejection fraction (LVEF) percentage was used to classify patients in low risk (LR: LVEF > 35%, 17 patients) and high risk (HR: LVEF = 35%, 31 patients) groups. From the BP signal, we extracted the upward systolic slope (BP sl), the difference between systolic and diastolic BP (BPA), and systolic time intervals (STI). When we compared the LR and HR groups in the time domain analysis, the best parameters were standard deviation (SD) of 1=STI, kurtosis (K) of BPsl, and K of BPA. In the frequency domain analysis, very low frequency (VLF) and high frequency (HF) bands showed statistically significant differences in comaprisons of LR and HR groups. The area under the curve of power spectral density was the best parameter in all classifications, and particularly in the very-low-and high- frequency bands (p < 0.001). These parameters could help to improve the risk stratification of cardiomyopathy patients.

  • Evaluating spatial characteristics of upper-limb movements from EMG signals

     Urra, Oiane; Casals Gelpi, Alicia; Jane Campos, Raimon
    Mediterranean Conference on Medical and Biological Engineering and Computing
    Presentation's date: 2013-09-27
    Presentation of work at congresses

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    Stroke is a major cause of disability, usually causing hemiplegic damage on the motor abilities of the patient. Stroke rehabilitation seeks restoring normal motion on the affected limb. However, `normality¿ of movements is usually assessed by clinical and functional tests, without considering how the motor system responds to therapy. We hypothesized that electromyographic (EMG) recordings could provide useful information for evaluating the outcome of rehabilitation from a neuromuscular perspective. Four healthy subjects were asked to perform 14 different functional movements simulating the action of reaching over a table. Each movement was defined according to the starting and target positions that the subject had to connect using linear trajectories. Bipolar recordings of EMG signals were taken from biceps and triceps muscles, and spectral and temporal characteristics were extracted for each movement. Using pattern recognition techniques we found that only two EMG channels were sufficient to accurately determine the spatial characteristics of motor activity: movement direction, length and execution zone. Our results suggest that muscles may fire in a patterned way depending on the specific characteristics of the movement and that EMG signals may codify such detailed information. These findings may be of great value to quantitatively assess poststroke rehabilitation and to compare the neuromuscular activity of the affected and unaffected limbs, from a physiological perspective. Furthermore, disturbed movements could be characterized in terms of the muscle function to identify, which is the spatial characteristic that fails, e.g. movement direction, and guide personalized rehabilitation to enhance the training of such characteristic.

  • Characterization of laplacian surface electromyographic signals during isometric contraction in biceps brachii

     Estrada, Luis; Torres Cebrian, Abel; Garcia Casado, Javier; Prats Boluda, Gema; Jane Campos, Raimon
    IEEE Engineering in Medicine and Biology Society
    Presentation's date: 2013-07
    Presentation of work at congresses

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    Surface electromyography (sEMG) is a noninvasive technique for monitoring the electrical activity produced by the muscles. Usually, sEMG is performed by carrying out monopolar or bipolar recordings by means of conventional Ag/AgCl electrodes. In contrast, Laplacian recordings of sEMG could also be obtained by using coaxial ring electrodes. Laplacian recordings increase spatial resolution and attenuate other distant bioelectric interferences. Nevertheless, the spectral characteristics of this kind of recordings have been scarcely studied. The objective of this paper is to characterize the sEMG signals recorded with a Laplacian ring electrode and to compare them with traditional bipolar recordings with disc electrodes. Both kinds of signals were collected simultaneously in two healthy subjects during resting and sustained isometric voluntary contraction activities in biceps brachii. The conducted study computed the cumulative percentage of the power spectrum of sEMG so as to determine the energy bandwidth of the two kinds of recordings and the signal to noise ratio in different bands of the sEMG spectrum. Also, muscle fatigue, a condition when muscle force is reduced, was assessed using indexes from amplitude and frequency domain. The results of this study suggest that Laplacian sEMG has higher spectral bandwidth but a lower signal to noise ratio in comparison to bipolar sEMG. In addition, frequency fatigue indexes showed that Laplacian recording had better response than bipolar recording, which suggests that Laplacian electrode can be useful to study muscular fatigue due to better spatial resolution.

  • Estimation of instantaneous frequency from empirical mode decomposition on respiratory sounds analysis

     Lozano, Manuel; Fiz, José Antonio; Jane Campos, Raimon
    IEEE Engineering in Medicine and Biology Society
    Presentation's date: 2013-06
    Presentation of work at congresses

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    Instantaneous frequency (IF) calculated by empirical mode decomposition (EMD) provides a novel approach to analyze respiratory sounds (RS). Traditionally, RS have been analyzed using classical time-frequency distributions, such as short-time Fourier transform (STFT) or wavelet transform (WT). However, EMD has become a powerful tool for nonlinear and non-stationary data analysis. IF estimated by EMD has two major advantages: its high temporal resolution and the fact that a priori knowledge of the signal characteristics is not required. In this study, we have estimated IF by EMD on real RS signals in order to identify continuous adventitious sounds (CAS), such as wheezes, within inspiratory sounds cycles. We show that there are differences in IF distribution among frequency scales of RS signal when CAS are within RS. Therefore, a new method for RS analysis and classification may be developed by combining both EMD and IF.

  • Characterization of the respiratory pattern variability of patients with different pressure support levels

     Giraldo Giraldo, Beatriz F.; Chaparro Preciado, Javier; Caminal Magrans, Pedro; Benito Vales, Salvador
    IEEE Engineering in Medicine and Biology Society
    Presentation's date: 2013-07-03
    Presentation of work at congresses

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    One of the most challenging problems in intensive care is still the process of discontinuing mechanical ventilation, called weaning process. Both an unnecessary delay in the discontinuation process and a weaning trial that is undertaken too early are undesirable. In this study, we analyzed respiratory pattern variability using the respiratory volume signal of patients submitted to two different levels of pressure support ventilation (PSV), prior to withdrawal of the mechanical ventilation. In order to characterize the respiratory pattern, we analyzed the following time series: inspiratory time, expiratory time, breath duration, tidal volume, fractional inspiratory time, mean inspiratory flow and rapid shallow breathing. Several autoregressive modeling techniques were considered: autoregressive models (AR), autoregressive moving average models (ARMA), and autoregressive models with exogenous input (ARX). The following classification methods were used: logistic regression (LR), linear discriminant analysis (LDA) and support vector machines (SVM). 20 patients on weaning trials from mechanical ventilation were analyzed. The patients, submitted to two different levels of PSV, were classified as low PSV and high PSV. The variability of the respiratory patterns of these patients were analyzed. The most relevant parameters were extracted using the classifiers methods. The best results were obtained with the interquartile range and the final prediction errors of AR, ARMA and ARX models. An accuracy of 95% (93% sensitivity and 90% specificity) was obtained when the interquartile range of the expiratory time and the breath duration time series were used a LDA model. All classifiers showed a good compromise between sensitivity and specificity. © 2013 IEEE.

  • Obstructive sleep apnea in a rat model: effects of anesthesia on autonomic evaluation from heart rate variability measures

     Jane Campos, Raimon; Lázaro, Jesús; Ruiz, Puy; Gil, Eduardo; Navajas, Daniel; Farré, Ramon; Laguna, Pablo
    Computing in Cardiology
    Presentation's date: 2013-09-25
    Presentation of work at congresses

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    Rat model of Obstructive Sleep Apnea (OSA) is a realistic approach for studying physiological mechanisms involved in sleep. Rats are usually anesthetized and autonomic nervous system (ANS) could be blocked. This study aimed to assess the effect of anesthesia on ANS activity during OSA episodes. Seven male SpragueDawley rats were anesthetized intraperitoneally with urethane (1 g/kg). The experiments were conducted applying airway obstructions, simulating 15s-apnea episodes for 15 minutes. Five signals were acquired: respiratory pressure and flow, Sa02, ECG and photoplethysmography (PPG). In total, 210 apnea episodes were studied. Normalized power spectrum of Pulse Rate Variability (PRV) was analyzed in the Low Frequency (LF) and High Frequency (HF) bands, for each episode in consecutive 15s intervals (before, during and after the apnea). All episodes showed changes in respiratory flow and Sa02 signal. Conversely, decreases in the amplitude fluctuations of PPG (DAP) were not observed. Normalized LF presented extremely low values during breathing (median=7,67%), suggesting inhibition of sympathetic system due to anesthetic effect. Subtle increases of LF were observed during apnea. HRV and PPG analysis during apnea could be an indirect tool to assess the effect and deep of anesthesia.

  • Analysis of heart rate variability in elderly patients with chronic heart failure and periodic breathing

     Giraldo Giraldo, Beatriz F.; Tellez, Juan Pablo; Herrera, Sergio; Benito Vales, Salvador
    Computing in Cardiology
    Presentation's date: 2013-09
    Presentation of work at congresses

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  • Characterization of blood pressure signal considering low and high risk stratification in cardiomyopathy patients

     Arcentales, Andrés; Voss, Andreas; Caminal Magrans, Pedro; Bayes-Genis, Antoni; Domingo, Maite; Giraldo Giraldo, Beatriz F.
    Computing in Cardiology
    Presentation's date: 2013-09
    Presentation of work at congresses

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    Ischemic and dilated cardiomyopathy are associated with disorders of myocardium. Using the blood pressure (BP) signal and the values of the ventricular ejection fraction, we obtained parameters for stratifying cardiomyopathy patients as low- and high-risk. We studied 48 cardiomyopathy patients characterized by NYHA '22: 19 patients with dilated cardiomyopathy (DCM) and 29 patients with ischemic cardiomyopathy (lCM). The left ventricular ejection fraction (LVEF) percentage was used to classify patients in low risk (LR: LVEF > 35%, 17 patients) and high risk (HR: LVEF::; 35%, 31 patients) groups. From the BP signal, we extracted the upward systolic slope (BPsl), the difference between systolic and diastolic BP (B P A), and systolic time intervals (ST I). When we compared the LR and HR groups in the time domain analysis, the best parameters were standard deviation (SD) of 1/ ST I, kurtosis (K) of B Psl, and K of B P A. In the frequency domain analysis, very low frequency (VLF) and high frequency (HF) bands showed statistically significant differences in comaprisons of LR and HR groups. The area under the curve of power spectral density was the best parameter in all classifications, and particularly in the very low- and high- frequency bands (p < 0.001). These parameters could help to improve the risk stratification of cardiomyopathy patients.

  • Influence of respiration in the very low frequency modulation of QRS slopes and heart rate variability in cardiomyopathy patients

     Hernando, David; Alcaine, A; Pueyo, Esther; Laguna, Pablo; Arcentales, Andrés; Giraldo Giraldo, Beatriz F.; Voss, Andreas; Bayes-Genis, Antoni; Bailón, Raquel
    Computing in Cardiology
    Presentation's date: 2013-09
    Presentation of work at congresses

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    This work investigates the very low frequency (VLF) modulation of QRS slopes and heart rate variability (HRV). Electrocardiogram (ECG) and respiratory flow signal were acquired from patients with dilated cardiomyopathy and ischemic cardiomyopathy. HRV as well as the upward QRS slope (IUS) and downward QRS slope (IDS) were extracted from the ECG. The relation between HRV and QRS slopes in the VLF band was measured using ordinary coherence in 5-minute segments. Partial coherence was then used to remove the influence that respiration simultaneously exerts on HRV and QRS slopes. A statistical threshold was determined, below which coherence values were considered not to represent a linear relation.

  • Methodology for determine the moment of disconnection of patients of the mechanical ventilation using neural network

     Arizmendi Pereira, Carlos Julio; Giraldo Giraldo, Beatriz F.; Gonzalez Acevedo, Hernando; Acevedo, Holmann Erick
    Latin American and Caribbean Conference for Engineering and Technology
    Presentation's date: 2013-08
    Presentation of work at congresses

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  • A software tool for large-scale synthetic experiments based on polymeric sensor arrays

     Ziyatdinov, Andrey; Fernandez Diaz, Eduard; Chaudry, A.; Marco Colas, Santiago; Persaud, Krishna C.; Perera Lluna, Alexandre
    Sensors and actuators B. Chemical
    Date of publication: 2013-02-01
    Journal article

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  • Access to the full text
    Predictability of gene ontology slim-terms from primary structure information in Embryophyta plant proteins  Open access

     Jaramillo-Garzón, Jorge Alberto; Gallardo Chacon, Juan José; Castellanos Domínguez, Germán; Perera Lluna, Alexandre
    BMC bioinformatics
    Date of publication: 2013-02-26
    Journal article

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  • SVM-based feature selection to optimize sensitivity¿specificity balance applied to weaning

     Garde Martinez, Ainara; Voss, Andreas; Caminal Magrans, Pedro; Benito Vales, Salvador; Giraldo Giraldo, Beatriz F.
    Computers in biology and medicine
    Date of publication: 2013
    Journal article

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    Classification algorithms with unbalanced datasets tend to produce high predictive accuracy over the majority class, but poor predictive accuracy over the minority class. This problem is very common in biomedical datamining. This paper introduces a Support Vector Machine (SVM)- based optimized feature selection method, to select the most relevant features and maintain an accurate and well- balanced sensitivity¿specificity result between unbalanced groups. A new metric called the balance index (B) is defined to implement this optimization. The balance index measures the difference between the misclassified data within each class. The proposed optimized feature selection is applied to the classification of patients¿ weaning trials from mechanical ventilation: patients with successful trials who were able to maintain spontaneous breathing after 48h and patients who failed to maintain spontaneous breathing and were reconnected to mechanical ventilation after 30min.

    Classification algorithms with unbalanced data sets tend to produce high predictive accuracy over the majority class, but poor predictive accuracy over the minority class. This problem is very common in biomedical data mining. This paper introduces a Support Vector Machine(SVM)-based optimized features election method, to select the most relevant features and maintain an accurate and well-balanced sensitivity–specificity result between unbalanced groups. A new metric called the balance index(B) is defined to implement this optimization. The balance index measures the difference between the misclassified data within each class. The proposed optimized feature selection is applied to the classification of patients’ weaning trials from mechanical ventilation: patients with successful trials who were able to maintain spontaneous breathing after 48 h and patients who failed to maintain spontaneous breathing and were reconnected to mechanical ventilation after 30min. Patients are characterized through cardiac and respiratory signals, applying joint symbolic dynamic (JSD) analys is to cardiac interbeat and breath durations. First, the most suitable parameters (C þ ,C ,s)are selected to define the appropriate SVM. Then, the features election process is carried out with this SVM, to maintain B lower than 40%. The best result is obtained using 6 features with an accuracy of 80%, a B of 18.64%, a sensitivity of 74.36% and a specificity of 82.42%.

  • Index for estimation of muscle force from mechanomyogrpahy based on the Lempel-Ziv algorithm

     Sarlabous, Leonardo; Torres Cebrian, Abel; Fiz, José Antonio; Morera, Josep; Jane Campos, Raimon
    Journal of electromyography and kinesiology
    Date of publication: 2013-02-19
    Journal article

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    The study of the amplitude of respiratory muscle mechanomyographic (MMG) signals could be useful in clinical practice as an alternative non-invasive technique to assess respiratory muscle strength. The MMG signal is stochastic in nature, and its amplitude is usually estimated by means of the average rectified value (ARV) or the root mean square (RMS) of the signal. Both parameters can be used to estimate MMG activity, as they correlate well with muscle force. These estimations are, however, greatly affected by the presence of structured impulsive noise that overlaps in frequency with the MMG signal. In this paper, we present a method for assessing muscle activity based on the Lempel-Ziv algorithm: the Multistate Lempel-Ziv (MLZ) index. The behaviour of the MLZ index was tested with synthesized signals, with various amplitude distributions and degrees of complexity, and with recorded diaphragm MMG signals. We found that this index, like the ARV and RMS parameters, is positively correlated with changes in amplitude of the diaphragm MMG components, but is less affected by components that have non-random behaviour (like structured impulsive noise). Therefore, the MLZ index could provide more information to assess the MMG-force relationship.

  • A cross-sectional study comparing strength profile of dorsal and palmar flexor muscles of the wrist in epicondylitis and healthy men

     Carme, Unyó; Chaler Vilaseca, Joaquim Lluís; Rojas Martínez, Mónica; Pujol Medina, Eduard; Müller, Bertram; Garreta, Roser; Mañanas Villanueva, Miguel Angel
    European Journal of Physical and Rehabilitation Medicine
    Date of publication: 2013-08
    Journal article

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    Background: Strength training has been proposed by several authors to treat Lateral Epicondylitis. However, there is still a lack of information concerning muscle weakness and its relationship to imbalances and fatigability of forearm muscles during dynamic conditions in subjects after epicondylitis recovery. Aim: To analyze the relationship between lateral humeral epicondylitis, and forearm muscle strength and fatigue. Setting: Rehabilitation specialized center Population: Cross-sectional study in eight former epicondylitis men free of symptoms and actively working at the moment of the evaluation and eight healthy men volunteers. Methods: Isokinetic tests were performed at different velocities in order to assess strength in concentric and eccentric contractions. Additionally, a long-term concentric test was carried out in order to analyze strength during endurance. The following variables were analyzed: Average torque of dorsal and palmar flexors of the wrist and ratio of agonist/antagonist for non-endurance contractions; length of initial and final plateaus and the slope of average torque decay during the endurance test. Results: In both groups, average torque produced by palmar flexor muscles was higher than that produced by dorsal flexor muscles. Patients showed higher strength in palmar flexor muscles, whereas dorsal flexor strength was similar for both populations. Palmar flexor vs. dorsal flexor ratio was significantly higher in patients for eccentric contractions. Regarding fatigue, results showed that torque decreased earlier in patients. Conclusions and clinical rehabilitation impact: Both palmar flexor force and palmar/dorsal ratio in eccentric exercise were significantly higher in patients. This finding indicates a muscular imbalance in patients underlying the epicondylitis condition. Additionally, former patients fatigued earlier. Findings indicate that muscle imbalances and fatigability might be related to lateral epicondylitis. [¿]

  • A biomimetic approach to machine olfaction, featuring a very large-scale chemical sensor array and embedded neuro-bio-inspired computation

     Marco Colas, Santiago; Gutierrez Galvez, Agustín; Lansner, Anders; Martinez, Dominique; Rospars, Jean Piere; Beccherelli, Romeo; Perera Lluna, Alexandre; Pearce, Timmothy Charles; Verschure, Paulus Franciscus Maria Joseph; Persaud, Krishna C.
    Microsystem technologies-Micro-and nanosystems-Information storage and processing
    Date of publication: 2013-12-21
    Journal article

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  • Short-term vs.long-term heart rate variability in ischemic cardiomyopathy risk stratification

     Voss, Andreas; Schroeder, Rico; Vallverdú Ferrer, Montserrat; Schulz, S; Cygankiewicz, Iwona; Vázquez, Rafael; Bayes de Luna, Antonio; Caminal Magrans, Pedro
    Frontiers in Physiology
    Date of publication: 2013-12-13
    Journal article

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    In industrialized countries with aging populations, heart failure affects 0.3-2% of the general population. The investigation of 24 h-ECG recordings revealed the potential of nonlinear indices of heart rate variability (HRV) for enhanced risk stratification in patients with ischemic heart failure (IHF). However, long-term analyses are time-consuming, expensive, and delay the initial diagnosis. The objective of this study was to investigate whether 30 min short-term HRV analysis is sufficient for comparable risk stratification in IHF in comparison to 24 h-HRV analysis. From 256 IHF patients [221 at low risk (IHFLR) and 35 at high risk (IHFHR)] (a) 24 h beat-to-beat time series (b) the first 30 min segment (c) the 30 min most stationary day segment and (d) the 30 min most stationary night segment were investigated. We calculated linear (time and frequency domain) and nonlinear HRV analysis indices. Optimal parameter sets for risk stratification in IHF were determined for 24 h and for each 30 min segment by applying discriminant analysis on significant clinical and non-clinical indices. Long- and short-term HRV indices from frequency domain and particularly from nonlinear dynamics revealed high univariate significances (p < 0.01) discriminating between IHFLR and IHFHR. For multivariate risk stratification, optimal mixed parameter sets consisting of 5 indices (clinical and nonlinear) achieved 80.4% AUC (area under the curve of receiver operating characteristics) from 24 h HRV analysis, 84.3% AUC from first 30 min, 82.2 % AUC from daytime 30 min and 81.7% AUC from nighttime 30 min. The optimal parameter set obtained from the first 30 min showed nearly the same classification power when compared to the optimal 24 h-parameter set. As results from stationary daytime and nighttime, 30 min segments indicate that short-term analyses of 30 min may provide at least a comparable risk stratification power in IHF in comparison to a 24 h analysis period.

  • Evaluación no invasiva de la función muscular respiratoria mediante el análisis de la señal mecanomiográfica en pacientes con enfermedad pulmonar obstructiva crónica  Open access

     Sarlabous Uranga, Leonardo
    Defense's date: 2013-10-22
    Universitat Politècnica de Catalunya
    Theses

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    El estudio y evaluación de la función muscular respiratoria en enfermedades respiratorias a través de técnicas no invasivas representa un tema de gran interés, dado que hasta la fecha no existen métodos satisfactorios aplicables en situaciones clínicas. En la enfermedad pulmonar obstructiva crónica (EPOC), el trabajo mecánico de los músculos respiratorios aumenta dando lugar a la fatiga, disminución de los movimientos de la caja torácica, y por tanto una disminución de la eficiencia muscular respiratoria. Es conocido que el músculo diafragma, principal responsable de la actividad mecánica respiratoria, al igual que otros músculos esqueléticos vibra lateralmente durante su contracción. De ahí, que estas vibraciones puedan ser registradas mediante micrófonos, sensores piezoeléctricos o acelerómetros posicionados encima de la pared inferior del pecho en la zona de aposición del diafragma con la caja torácica. El registro de estas vibraciones da lugar a la señal mecanomiográfica del diafragma (MMGdi). El principal objetivo de esta tesis ha sido el estudio y caracterización no invasiva de la función muscular respiratoria en pacientes con EPOC a través de la señal MMGdi registrada mediante acelerómetros posicionados entre el séptimo y octavo espacios intercostales, en la línea axilar izquierda y derecha del cuerpo durante la realización de los protocolos respiratorios de carga incremental progresiva y de flujo incremental progresivo. Para mejorar la estimación de la amplitud de la señal MMGdi se han propuesto tres nuevos índices, que tienen en cuenta la naturaleza aleatoria y el ruido asociado en las señales MMGdi, y están basados en: el algoritmo de Lempel-Ziv (LZM), la entropía aproximada (fApEn), y la entropía muestral (fSampEn). Todos ellos son calculados con intervalos de cuantificación fijos y empleando ventanas móviles. Los resultados obtenidos con éstos índices han permitido estimar con mayor fiabilidad y robustez la amplitud de las señales MMGdi, en relación a los métodos clásicos utilizados en el estudio de señales miográficas. El estudio del valor medio de los parámetros analizados ha mostrado, que existe una tendencia incremental de éste en los parámetros de amplitud, y una tendencia decreciente en los parámetros frecuenciales (frecuencias media y máxima), con el incremento de la carga y/o flujo. En este sentido, se ha observado que el valor medio es mayor cuanto mayor es la severidad del paciente con EPOC. Por otra parte, se ha observado que existe una fuerte correlación entre los parámetros de amplitud y la presión inspiratoria máxima en el protocolo de flujo incremental progresivo, con una tendencia decreciente con la severidad. Del mismo modo la eficiencia muscular respiratoria, evaluada como la relación entre la fuerza que producen los músculos respiratorios (la presión inspiratoria en boca) y lo que gastan o necesitan para producir esta presión (la vibración de los músculos respiratorios evaluada mediante las señales MMGdi), ha mostrado en general una tendencia decreciente con el aumento de la severidad. Finalmente, los resultados que se desprenden de esta tesis indican que el estudio de la señal MMGdi representa una herramienta útil con un gran potencial para evaluar el grado de la severidad presente en sujetos con EPOC y su relación con la debilidad de la musculatura respiratoria, y por tanto su aplicación en estudios clínicos podría ser de gran ayuda para evaluar el desarrollo de la EPOC.

    The study and evaluation of the respiratory muscles function in people who suffer from respiratory diseases can be evaluated through the use of noninvasive techniques. This is a topic of great interest considering there are currently no existing methods that can be successfully applied in clinical situations. In chronic obstructive pulmonary disease (COPD), the mechanical work of the respiratory muscles increases, which could lead to muscular fatigue, decreased movement of the ribcage, and, therefore, a decrease in the respiratory muscle efficiency. The diaphragm muscle is the principal muscle of inspiration and the main mechanical responsible for the ventilation. Similar to other skeletal muscles the diaphragm laterally vibrates during its contraction. These vibrations can be recorded by microphones, piezoelectric sensors or accelerometers, which are placed above the lower chest wall in the area of apposition of the diaphragm to the ribcage. The record of these vibrations is known as mechanomyographic signal of the diaphragm muscle (MMGdi). The main objective of this thesis has been the study and noninvasive characterization of the respiratory muscles function in patients with COPD. This characterization has been made possible through the use of MMGdi signals recorded by accelerometers placed between the seventh and eighth intercostals spaces on the left and right anterior axillary lines of the body during two respiratory protocols. The first protocol is called progressive incremental load protocol and the second one progressive incremental flow protocol. In this thesis three new indices have been proposed to improve the MMGdi amplitude estimation. These indices take into account the random nature and the associated noise in the MMGdi signals, and are based on the: Lempel-Ziv algorithm (MLZ), approximate entropy (fApEn), and sample entropy (fSampEn). All of them are calculated with fixed quantization intervals and using moving windows. The obtained results with these new indices have shown improved reliability and robustness in the MMGdi amplitude estimation in comparison with classic methods used to study myographic signals. The study of the mean value of the analyzed parameters has shown an increasing trend of the amplitude parameters and a decreasing trend of the frequency parameters (mean and maximum frequencies) with increasing load and/or flow. Furthermore, we found that there was a direct relationship between these mean values and the severity of COPD; hence, the greater the mean value, the greater the severity of COPD. Moreover, we have seen that there is a strong correlation between the amplitude parameters and the maximum inspiratory pressure in the progressive incremental flow protocol with a decreasing trend as the severity of the patients increases. Likewise, the respiratory muscle efficiency, evaluated as the ratio between the force produced by the respiratory muscles (mouth inspiratory pressure) and what they need to produce this pressure (the vibration of respiratory muscles assessed by MMGdi signals), has also shown a generally decreasing trend as the severity of patients increases. Finally, the results of this thesis suggest that the study of the MMGdi signal is a useful tool with great potential to assess the relationship between respiratory muscle weakness and the degree of severity in patients with COPD. Therefore, the application of this innovative tool in clinical studies may be helpful to assess the development of COPD.

  • Genetic association analysis of complex diseases through information theoretic metrics and linear pleiotropy

     Brunel Montaner, Helena
    Defense's date: 2013-11-14
    Universitat Politècnica de Catalunya
    Theses

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  • Electrical stimulation of the dorsal genital nerve to treat neurogenic detrusor overactivity

     Opisso Salleras, Eloy
    Defense's date: 2013-10-23
    Universitat Politècnica de Catalunya
    Theses

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  • Estudio de las Fuerzas de Interacción para la Minimización de Esfuerzos en Rehabilitación Robotizada

     Amigo Vásquez, Luis Ernesto
    Defense's date: 2013-10-17
    Universitat Politècnica de Catalunya
    Theses

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  • On the Intelligent Management of Sepsis in the Intensive Care Unit  Open access

     Ribas Ripoll, Vicente Jorge
    Defense's date: 2013-01-29
    Department of Software, Universitat Politècnica de Catalunya
    Theses

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    The management of the Intensive Care Unit (ICU) in a hospital has its own, very specific requirements that involve, amongst others, issues of risk-adjusted mortality and average length of stay; nurse turnover and communication with physicians; technical quality of care; the ability to meet patient's family needs; and avoid medical error due rapidly changing circumstances and work overload. In the end, good ICU management should lead to an improvement in patient outcomes. Decision making at the ICU environment is a real-time challenge that works according to very tight guidelines, which relate to often complex and sensitive research ethics issues. Clinicians in this context must act upon as much available information as possible, and could therefore, in general, benefit from at least partially automated computer-based decision support based on qualitative and quantitative information. Those taking executive decisions at ICUs will require methods that are not only reliable, but also, and this is a key issue, readily interpretable. Otherwise, any decision tool, regardless its sophistication and accuracy, risks being rendered useless. This thesis addresses this through the design and development of computer based decision making tools to assist clinicians at the ICU. It focuses on one of the main problems that they must face: the management of the Sepsis pathology. Sepsis is one of the main causes of death for non-coronary ICU patients. Its mortality rate can reach almost up to one out of two patients for septic shock, its most acute manifestation. It is a transversal condition affecting people of all ages. Surprisingly, its definition has only been standardized two decades ago as a systemic inflammatory response syndrome with confirmed infection. The research reported in this document deals with the problem of Sepsis data analysis in general and, more specifically, with the problem of survival prediction for patients affected with Severe Sepsis. The tools at the core of the investigated data analysis procedures stem from the fields of multivariate and algebraic statistics, algebraic geometry, machine learning and computational intelligence. Beyond data analysis itself, the current thesis makes contributions from a clinical point of view, as it provides substantial evidence to the debate about the impact of the preadmission use of statin drugs in the ICU outcome. It also sheds light into the dependence between Septic Shock and Multi Organic Dysfunction Syndrome. Moreover, it defines a latent set of Sepsis descriptors to be used as prognostic factors for the prediction of mortality and achieves an improvement on predictive capability over indicators currently in use.

    La gestió d'una Unitat de Cures Intensives (UCI) hospitalària presenta uns requisits força específics incloent, entre altres, la disminució de la taxa de mortalitat, la durada de l'ingrès, la rotació d'infermeres i la comunicació entre metges amb al finalitad de donar una atenció de qualitat atenent als requisits tant dels malalts com dels familiars. També és força important controlar i minimitzar els error mèdics deguts a canvis sobtats i a la presa ràpida de deicisions assistencials. Al cap i a la fi, la bona gestió de la UCI hauria de resultar en una reducció de la mortalitat i durada d'estada. La presa de decisions en un entorn de crítics suposa un repte de presa de decisions en temps real d'acord a unes guies clíniques molt restrictives i que, pel que fa a la recerca, poden resultar en problemes ètics força sensibles i complexos. Per tant, el personal sanitari que ha de prendre decisions sobre la gestió de malalts crítics no només requereix eines de suport a la decisió que siguin fiables sinó que, a més a més, han de ser interpretables. Altrament qualsevol eina de decisió que no presenti aquests trets no és considerarà d'utilitat clínica. Aquesta tesi doctoral adreça aquests requisits mitjançant el desenvolupament d'eines de suport a la decisió per als intensivistes i es focalitza en un dels principals problemes als que s'han denfrontar: el maneig del malalt sèptic. La Sèpsia és una de les principals causes de mortalitats a les UCIS no-coronàries i la seva taxa de mortalitat pot arribar fins a la meitat dels malalts amb xoc sèptic, la seva manifestació més severa. La Sèpsia és un síndrome transversal, que afecta a persones de totes les edats. Sorprenentment, la seva definició ha estat estandaritzada, fa només vint anys, com a la resposta inflamatòria sistèmica a una infecció corfimada. La recerca presentada en aquest document fa referència a l'anàlisi de dades de la Sèpsia en general i, de forma més específica, al problema de la predicció de la supervivència de malalts afectats amb Sèpsia Greu. Les eines i mètodes que formen la clau de bòveda d'aquest treball provenen de diversos camps com l'estadística multivariant i algebràica, geometria algebraica, aprenentatge automàtic i inteligència computacional. Més enllà de l'anàlisi per-se, aquesta tesi també presenta una contribució des de el punt de vista clínic atès que presenta evidència substancial en el debat sobre l'impacte de l'administració d'estatines previ a l'ingrès a la UCI en els malalts sèptics. També s'aclareix la forta dependència entre el xoc sèptic i el Síndrome de Disfunció Multiorgànica. Finalment, també es defineix un conjunt de descriptors latents de la Sèpsia com a factors de pronòstic per a la predicció de la mortalitat, que millora sobre els mètodes actualment més utilitzats en la UCI.

  • Snoring and Arousals in full-night polysomnographic studies from Sleep Apnea-Hypopnea Syndrome patients  Open access

     Gil De Mesquita, Joana Margarida
    Defense's date: 2013-02-22
    Department of Automatic Control, Universitat Politècnica de Catalunya
    Theses

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    SAHS (Sleep Apnea-Hypopnea Syndrome) is recognized to be a serious disorder with high prevalence in the population. The main clinical triad for SAHS is made up of 3 symptoms: apneas and hypopneas, chronic snoring and excessive daytime sleepiness (EDS). The gold standard for diagnosing SAHS is an overnight polysomnographic study performed at the hospital, a laborious, expensive and time-consuming procedure in which multiple biosignals are recorded. In this thesis we offer improvements to the current approaches to diagnosis and assessment of patients with SAHS. We demonstrate that snoring and arousals, while recognized key markers of SAHS, should be fully appreciated as essential tools for SAHS diagnosis. With respect to snoring analysis (applied to a 34 subjects¿ database with a total of 74439 snores), as an alternative to acoustic analysis, we have used less complex approaches mostly based on time domain parameters. We concluded that key information on SAHS severity can be extracted from the analysis of the time interval between successive snores. For that, we built a new methodology which consists on applying an adaptive threshold to the whole night sequence of time intervals between successive snores. This threshold enables to identify regular and non-regular snores. Finally, we were able to correlate the variability of time interval between successive snores in short 15 minute segments and throughout the whole night with the subject¿s SAHS severity. Severe SAHS subjects show a shorter time interval between regular snores (p=0.0036, AHI cp(cut-point): 30h-1) and less dispersion on the time interval features during all sleep. Conversely, lower intra-segment variability (p=0.006, AHI cp: 30h-1) is seen for less severe SAHS subjects. Also, we have shown successful in classifying the subjects according to their SAHS severity using the features derived from the time interval between regular snores. Classification accuracy values of 88.2% (with 90% sensitivity, 75% specificity) and 94.1% (with 94.4% sensitivity, 93.8% specificity) for AHI cut-points of severity of 5 and 30h-1, respectively. In what concerns the arousal study, our work is focused on respiratory and spontaneous arousals (45 subjects with a total of 2018 respiratory and 2001 spontaneous arousals). Current beliefs suggest that the former are the main cause for sleep fragmentation. Accordingly, sleep clinicians assign an important role to respiratory arousals when providing a final diagnosis on SAHS. Provided that the two types of arousals are triggered by different mechanisms we hypothesized that there might exist differences between their EEG content. After characterizing our arousal database through spectral analysis, results showed that the content of respiratory arousals on a mild SAHS subject is similar to that of a severe one (p>>0.05). Similar results were obtained for spontaneous arousals. Our findings also revealed that no differences are observed between the features of these two kinds of arousals on a same subject (r=0.8, p<0.01 and concordance with Bland-Altman analysis). As a result, we verified that each subject has almost like a fingerprint or signature for his arousals¿ content and is similar for both types of arousals. In addition, this signature has no correlation with SAHS severity and this is confirmed for the three EEG tracings (C3A2, C4A1 and O1A2). Although the trigger mechanisms of the two arousals are known to be different, our results showed that the brain response is fairly the same for both of them. The impact that respiratory arousals have in the sleep of SAHS patients is unquestionable but our findings suggest that the impact of spontaneous arousals should not be underestimated.

  • 2o Concurso de planes de negocio de comercialización de una patente/tecnologia

     Mañanas Villanueva, Miguel Angel; Ramos Castro, Juan Jose
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  • Higuchi's fractal complexity of RR and QT interval series during transient myocardial ischemia

     Magrans Nicieza, Rudys; Gomis Román, Pedro; Caminal Magrans, Pedro; Voss, Andreas
    Computing in Cardiology
    Presentation's date: 2013-09
    Presentation of work at congresses

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    Myocardial ischemia may lead to significant changes in autonomic control of heart rate (HR) affecting its variability and alter beat-to-beat ventricular repolarization periods. We hypothesized that transient myocardial ischemia affects the complex dynamics of the HR and QT. The aim of this study was to assess the RR and QT interval time series complexity using Higuchi's fractal dimension (HFD) during prolonged balloon occlusion of one of the major coronary arteries.