Background: Recent studies show that spatial distribution of High Density surface EMG maps (HD-EMG) improves the identification of tasks and their corresponding contraction levels. However, in patients with incomplete spinal cord injury (iSCI), some nerves that control muscles are damaged, leaving some muscle parts without an innervation. Therefore, HD-EMG maps in patients with iSCI are affected by the injury and they can be different for every patient. The objective of this study is to investigate the spatial distribution of intensity in HD-EMG recordings to distinguish co-activation patterns for different tasks and effort levels in patients with iSCI. These patterns are evaluated to be used for extraction of motion intention.; Method: HD-EMG was recorded in patients during four isometric tasks of the forearm at three different effort levels. A linear discriminant classifier based on intensity and spatial features of HD-EMG maps of five upper-limb muscles was used to identify the attempted tasks. Task and force identification were evaluated for each patient individually, and the reliability of the identification was tested with respect to muscle fatigue and time interval between training and identification. Results: Three feature sets were analyzed in the identification: 1) intensity of the HD-EMG map, 2) intensity and center of gravity of HD-EMG maps and 3) intensity of a single differential EMG channel (gold standard).; Results show that the combination of intensity and spatial features in classification identifies tasks and effort levels properly (Acc = 98.8 %; S = 92.5 %; P = 93.2 %; SP = 99.4 %) and outperforms significantly the other two feature sets (p < 0.05).; Conclusion: In spite of the limited motor functionality, a specific co-activation pattern for each patient exists for both intensity, and spatial distribution of myoelectric activity. The spatial distribution is less sensitive than intensity to myoelectric changes that occur due to fatigue, and other time-dependent influences.
Sleep deprivation (SD) has adverse effects on mental and physical health, affecting the cognitive abilities and emotional states. Specifically, cognitive functions and alertness are known to decrease after SD. The aim of this work was to identify the directional information transfer after SD on scalp EEG signals using transfer entropy (TE). Using a robust methodology based on EEG recordings of 18 volunteers deprived from sleep for 36 h, TE and spectral analysis were performed to characterize EEG data acquired every 2 h. Correlation between connectivity measures and subjective somnolence was assessed. In general, TE showed medium-and long-range significant decreases originated at the occipital areas and directed towards different regions, which could be interpreted as the transfer of predictive information from parieto-occipital activity to the rest of the head. Simultaneously, short-range increases were obtained for the frontal areas, following a consistent and robust time course with significant maps after 20 h of sleep deprivation. Changes during sleep deprivation in brain network were measured effectively by TE, which showed increased local connectivity and diminished global integration. TE is an objective measure that could be used as a potential measure of sleep pressure and somnolence with the additional property of directed relationships.
Migliorelli, C.; Alonso, J.F.; Romero, S.; Mañanas, M.A.; Nowak, R.; Russi, A. Journal of neural engineering Vol. 13, num. 2, p. 1-12 DOI: 10.1088/1741-2560/13/2/026029 Data de publicació: 2016-03-02 Article en revista
Objective. Medical intractable epilepsy is a common condition that affects 40% of epileptic patients that generally have to undergo resective surgery. Magnetoencephalography (MEG) has been increasingly used to identify the epileptogenic foci through equivalent current dipole (ECD) modeling, one of the most accepted methods to obtain an accurate localization of interictal epileptiform discharges (IEDs). Modeling requires that MEG signals are adequately preprocessed to reduce interferences, a task that has been greatly improved by the use of blind source separation (BSS) methods. MEG recordings are highly sensitive to metallic interferences originated inside the head by implanted intracranial electrodes, dental prosthesis, etc and also coming from external sources such as pacemakers or vagal stimulators. To reduce these artifacts, a BSS-based fully automatic procedure was recently developed and validated, showing an effective reduction of metallic artifacts in simulated and real signals (Migliorelli et al 2015 J. Neural Eng. 12 046001). The main objective of this study was to evaluate its effects in the detection of IEDs and ECD modeling of patients with focal epilepsy and metallic interference. Approach. A comparison between the resulting positions of ECDs was performed: without removing metallic interference; rejecting only channels with large metallic artifacts; and after BSS-based reduction. Measures of dispersion and distance of ECDs were defined to analyze the results. Main results. The relationship between the artifact-to-signal ratio and ECD fitting showed that higher values of metallic interference produced highly scattered dipoles. Results revealed a significant reduction on dispersion using the BSS-based reduction procedure, yielding feasible locations of ECDs in contrast to the other two approaches. Significance. The automatic BSS-based method can be applied to MEG datasets affected by metallic artifacts as a processing step to improve the localization of epileptic foci.
Giménez, S.; Romero, S.; Alonso, J.F.; Mañanas, M.A.; Pujol, A.; Baxarias, P.; Antonijoan, R. M. Journal of clinical monitoring and computing Vol. 31, num. 1, p. 103-110 DOI: 10.1007/s10877-015-9805-5 Data de publicació: 2015-11-14 Article en revista
Las señales corticales del cerebro permiten una visión más clara de la actividad neuronal que el estudio clásico de las señales registradas en el cuero cabelludo y son de gran interés en el estudio de enfermedades neurodegenerativas como la enfermedad de Alzheimer. Con las señales adquiridas sobre el córtex prefrontal y somatosensorial de ratones con la mutación 3xTg-AD, se han estudiado los estados espontáneos UP y DOWN de las oscilaciones lentas del cerebro anestesiado. En primer lugar, se han aplicado técnicas de filtrado para eliminar interferencias y seleccionar la banda de interés entre 0.1 y 200 Hz, en la cual se aplicaron medidas de análisis espectral. Tras un
filtrado adicional entre 30 y 100 Hz para seleccionar la banda gamma asociada a la actividad UP y DOWN, se calcularon variables de conectividad. Entre los resultados obtenidos, se escogieron aquellas variables que presentaban una mayor significación estadística mediante las pruebas T-Student y Wilcoxon. Finalmente, con estas variables se diseñaron dos procedimientos de clasificación por análisis discriminante lineal (Stepwise y Leave-one-out) que consiguen diferenciar entre sujetos enfermos de Alzheimer y sujetos control con un 88% y un 82% de precisión, respectivamente.
Alonso, J.F.; Romero, S.; Mañanas, M.A.; Rojas, M.; Riba, J.; Barbanoj, M.J. Medical and biological engineering and computing Vol. 53, num. 10, p. 1011-1023 DOI: 10.1007/s11517-015-1315-6 Data de publicació: 2015-10-01 Article en revista
The identification of the brain regions involved in the neuropharmacological action is a potential procedure for drug development. These regions are commonly determined by the voxels showing significant statistical differences after comparing placebo-induced effects with drug-elicited effects. LORETA is an electroencephalography (EEG) source imaging technique frequently used to identify brain structures affected by the drug. The aim of the present study was to evaluate different methods for the correction of multiple comparisons in the LORETA maps. These methods which have been commonly used in neuroimaging and also simulated studies have been applied on a real case of pharmaco-EEG study where the effects of increasing benzodiazepine doses on the central nervous system measured by LORETA were investigated. Data consisted of EEG recordings obtained from nine volunteers who received single oral doses of alprazolam 0.25, 0.5, and 1 mg, and placebo in a randomized crossover double-blind design. The identification of active regions was highly dependent on the selected multiple test correction procedure. The combined criteria approach known as cluster mass was useful to reveal that increasing drug doses led to higher intensity and spread of the pharmacologically induced changes in intracerebral current density.
Lopez, M.; Escartín, J.A.; Martinez, S.; Fernandez, R.; Querol, L.; Romero, S.; Mañanas, M.A.; Riba, J. PLoS one Vol. 10, num. 8 DOI: 10.1371/journal.pone.0136786 Data de publicació: 2015-08-31 Article en revista
Multiple sclerosis (MS) is a chronic central nervous system disorder characterized by white matter inflammation, demyelination and neurodegeneration. Although cognitive dysfunction is a common manifestation, it may go unnoticed in recently-diagnosed patients. Prior studies suggest MS patients develop compensatory mechanisms potentially involving enhanced performance monitoring. Here we assessed the performance monitoring system in early-stage MS patients using the error-related negativity (ERN), an event-related brain potential (ERP) observed following behavioral errors. Twenty-seven early-stage MS patients and 31 controls were neuropsychologically assessed. Electroencephalography recordings were obtained while participants performed: a) a stop task and b) an auditory oddball task. Behavior and ERP measures were assessed. No differences in performance were found between groups in most neuropsychological tests or in behavior or ERP components in the auditory oddball task. However, the amplitude of the ERN associated with stop errors in the stop task was significantly higher in patients. ERN amplitude correlated positively with scores on the Expanded Disability Status Scale and the Multiple Sclerosis Severity Score, and negatively with the time since last relapse. Patients showed higher neuronal recruitment in tasks involving performance monitoring. Results suggest the development of compensatory brain mechanisms in early-stage MS and reflect the sensitivity of the ERN to detect these changes.
Background: Psychedelics induce intense modifications in the sensorium, the sense of "self," and the experience of reality. Despite advances in our understanding of the molecular and cellular level mechanisms of these drugs, knowledge of their actions on global brain dynamics is still incomplete. Recent imaging studies have found changes in functional coupling between frontal and parietal brain structures, suggesting a modification in information flow between brain regions during acute effects.; Methods: Here we assessed the psychedelic-induced changes in directionality of information flow during the acute effects of a psychedelic in humans. We measured modifications in connectivity of brain oscillations using transfer entropy, a nonlinear measure of directed functional connectivity based on information theory. Ten healthy male volunteers with prior experience with psychedelics participated in 2 experimental sessions. They received a placebo or a dose of ayahuasca, a psychedelic preparation containing the serotonergic 5-HT2A agonist N,N-dimethyltryptamine.; Results: The analysis showed significant changes in the coupling of brain oscillations between anterior and posterior recording sites. Transfer entropy analysis showed that frontal sources decreased their influence over central, parietal, and occipital sites. Conversely, sources in posterior locations increased their influence over signals measured at anterior locations. Exploratory correlations found that anterior-to-posterior transfer entropy decreases were correlated with the intensity of subjective effects, while the imbalance between anterior-to-posterior and posterior-to-anterior transfer entropy correlated with the degree of incapacitation experienced.; Conclusions: These results suggest that psychedelics induce a temporary disruption of neural hierarchies by reducing top-down control and increasing bottom-up information transfer in the human brain.
Migliorelli, C.; Alonso, J.F.; Romero, S.; Mañanas, M.A.; Nowak, R.; Russi, A. Journal of neural engineering Vol. 12, p. 046001-1-046001-12 DOI: 10.1088/1741-2560/12/4/046001 Data de publicació: 2015-05-27 Article en revista
Objective. One of the principal drawbacks of magnetoencephalography (MEG) is its high sensitivity to metallic artifacts, which come from implanted intracranial electrodes and dental ferromagnetic prosthesis and produce a high distortion that masks cerebral activity. The aim of this study was to develop an automatic algorithm based on blind source separation (BSS) techniques to remove metallic artifacts from MEG signals. Approach. Three methods were evaluated: AMUSE, a second-order technique; and INFOMAX and FastICA, both based on high-order statistics. Simulated signals consisting of real artifact-free data mixed with real metallic artifacts were generated to objectively evaluate the effectiveness of BSS and the subsequent interference reduction. A completely automatic detection of metallic-related components was proposed, exploiting the known characteristics of the metallic interference: regularity and low frequency content. Main results. The automatic procedure was applied to the simulated datasets and the three methods exhibited different performances. Results indicated that AMUSE preserved and consequently recovered more brain activity than INFOMAX and FastICA. Normalized mean squared error for AMUSE decomposition remained below 2%, allowing an effective removal of artifactual components. Significance. To date, the performance of automatic artifact reduction has not been evaluated in MEG recordings. The proposed methodology is based on an automatic algorithm that provides an effective interference removal. This approach can be applied to any MEG dataset affected by metallic artifacts as a processing step, allowing further analysis of unusable or poor quality data.
Alonso, J.F.; Romero, S.; Ballester, M. R.; Antonijoan, R. M.; Mañanas, M.A. Physiological measurement Vol. 36, p. 1351-1365 DOI: 10.1088/0967-3334/36/7/1351 Data de publicació: 2015-05-27 Article en revista
The biological response to stress originates in the brain but involves different biochemical and physiological effects. Many common clinical methods to assess stress are based on the presence of specific hormones and on features extracted from different signals, including electrocardiogram, blood pressure, skin temperature, or galvanic skin response. The aim of this paper was to assess stress using EEG-based variables obtained from univariate analysis and functional connectivity evaluation. Two different stressors, the Stroop test and sleep deprivation, were applied to 30 volunteers to find common EEG patterns related to stress effects. Results showed a decrease of the high alpha power (11 to 12 Hz), an increase in the high beta band (23 to 36 Hz, considered a busy brain indicator), and a decrease in the approximate entropy. Moreover, connectivity showed that the high beta coherence and the interhemispheric nonlinear couplings, measured by the cross mutual information function, increased significantly for both stressors, suggesting that useful stress indexes may be obtained from EEG-based features.
Alonso, J.F.; Sabater, A.; Romero, S.; Mañanas, M.A.; Riba, J. A Dialogue with the Cerebral Cortex: Cortical Function and Interfacing p. 1-4 DOI: 10.3389/conf.fnsys.2015.06.00008 Data de presentació: 2015-04-29 Presentació treball a congrés
Electroencephalographic analysis techniques have become a very useful tool to assess brain activity and interactions between cerebral regions, that is, the so-called cerebral connectivity analysis. The effects of some drugs have, so far, been studied using spectral analysis and, to a lesser extent, some linear and nonlinear connectivity techniques. New indexes have recently been designed based on assumptions that make them more robust against volume conduction effects that could yield to spurious connectivity results.
These new indexes such as the imaginary coherence (IC) [Nolte et al., 2004], the phase-lag index (PLI) [Stam et al., 2007] and the weighted phase-lag index (WPLI) [Vinck et al., 2011] have proven very useful in several fields, for example in characterizing electroencephalographic (EEG) and magnetoencephalographic (MEG) activity of Alzheimer’s Disease patients compared to healthy controls.
However, these techniques have not been applied to study the effect of drugs on the brain. The main purpose of the current work was to assess the suitability and effectiveness of these innovative indexes to study the brain connectivity under psychoactive drug treatment, and concretely, the effects of a single dose of alprazolam, a short-acting drug of the benzodiazepine family.
Alprazolam is extensively prescribed for the treatment of anxiety and panic disorders, and peak plasma concentrations are obtained between 0.5 and 2 hours after intake [Greenblat and Wright, 1993]. Being a benzodiazepines, alprazolam induces an enhancement of the inhibitory pathways through their activity on the GABA A receptor complex, favouring the entrance to chloride ions into the neurons [Haefely, 1990]. Due to the enhancement of the inhibitory pathways a weakening or even an impairment of functional connectivity could be hypothesized
En el presente trabajo se estudian los efectos de la privación del sueño sobre las señales electroencefalográficas de voluntarios sanos mediante la transferencia de entropía (TE), una técnica no paramétrica que permite detectar relaciones direccionales entre variables y que no ha sido utilizada antes para el estudio de la vigilia prolongada.
Los resultados obtenidos concuerdan con la potencia en la banda ¿, un marcador reconocido relacionado con la presión de sueño.
Los efectos máximos de la privación del sueño se producen a partir de las 24 horas sin dormir. Durante este periodo, se producen incrementos de TE localizados en la zona anterior mientras que los decrementos principalmente se originan en la zona occipital y afectan globalmente al resto del cerebro. El promedio de estos decrementos muestra una fuerte correlación con la potencia ¿, por lo que se podría considerar como otro marcador fiable de la presión de sueño que, además, proporciona información sobre la localización de los cambios producidos, indicando una disminución de la transferencia de información entre las regiones cerebrales.
En el presente trabajo se estudian los efectos de la privación del sueño sobre las señales electroencefalográficas de voluntarios sanos mediante la transferencia de entropía (TE), una técnica no paramétrica que permite detectar relaciones direccionales entre variables y que no ha sido utilizada antes para el estudio de la vigilia prolongada.
Los resultados obtenidos concuerdan con la potencia en la banda ϴ, un marcador reconocido relacionado con la presión de sueño.
Los efectos máximos de la privación del sueño se producen a partir de las 24 horas sin dormir. Durante este periodo, se producen incrementos de TE localizados en la zona anterior mientras que los decrementos principalmente se originan en la zona occipital y afectan globalmente al resto del cerebro. El promedio de estos decrementos muestra una fuerte correlación con la potencia ϴ, por lo que se podría considerar como otro marcador fiable de la presión de sueño que, además, proporciona información sobre la localización de los cambios producidos, indicando una disminución de la transferencia de información entre las regiones cerebrales.
Carme, U.; Chaler, J.; Rojas, M.; Pujol, E.; Bertram, M.; Garreta, R.; Mañanas, M.A. European Journal of Physical and Rehabilitation Medicine Vol. 49, num. 4, p. 507-515 Data de publicació: 2013-08 Article en revista
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. […]
sEMG signal has been widely used in different applications in kinesiology and rehabilitation as well as in the control of human-machine interfaces. In general, the signals are recorded with bipolar electrodes located in different muscles. However, such configuration may disregard some aspects of the spatial distribution of the potentials like location of innervation zones and the manifestation of inhomogineties in the control of the muscular fibers. On the other hand, the spatial distribution of motor unit action potentials has recently been assessed with activation maps obtained from High Density EMG signals (HD-EMG), these lasts recorded with arrays of closely spaced electrodes. The main objective of this work is to analyze patterns in the activation maps, associating them with four movement directions at the elbow joint and with different strengths of those tasks. Although the activation pattern can be assessed with bipolar electrodes, HD-EMG maps could enable the extraction of features that depend on the spatial distribution of the potentials and on the load-sharing between muscles, in order to have a better differentiation between tasks and effort levels.
sEMG signal has been widely used in different applications in kinesiology and rehabilitation
as well as in the control of human-machine interfaces. In general, the signals are recorded
with bipolar electrodes located in different muscles. However, such configuration may
disregard some aspects of the spatial distribution of the potentials like location of innervation
zones and the manifestation of inhomogineties in the control of the muscular fibers. On the
other hand, the spatial distribution of motor unit action potentials has recently been assessed
with activation maps obtained from High Density EMG signals (HD-EMG), these lasts
recorded with arrays of closely spaced electrodes. The main objective of this work is to
analyze patterns in the activation maps, associating them with four movement directions at
the elbow joint and with different strengths of those tasks. Although the activation pattern can
be assessed with bipolar electrodes, HD-EMG maps could enable the extraction of features
that depend on the spatial distribution of the potentials and on the load-sharing between
muscles, in order to have a better differentiation between tasks and effort levels.
An experimental protocol consisting of isometric contractions at three levels of effort during
flexion, extension, supination and pronation at the elbow joint was designed and HD-EMG signals were recorded with 2D electrode arrays on different upper-limb muscles. Techniques
for the identification and interpolation of artifacts are explained, as well as a method for the
segmentation of the activation areas. In addition, variables related to the intensity and spatial
distribution of the maps were obtained, as well as variables associated to signal power of
traditional single bipolar recordings. Finally, statistical tests were applied in order to assess
differences between information extracted from single bipolar signals or from HD-EMG
maps and to analyze differences due to type of task and effort level.
Significant differences were observed between EMG signal power obtained from single
bipolar configuration and HD-EMG and better results regarding the identification of tasks
and effort levels were obtained with the latter. Additionally, average maps for a population of
12 subjects were obtained and differences in the co-activation pattern of muscles were found
not only from variables related to the intensity of the maps but also to their spatial
Intensity and spatial distribution of HD-EMG maps could be useful in applications where the
identification of movement intention and its strength is needed, for example in robotic-aided
therapies or for devices like powered- prostheses or orthoses. Finally, additional data
transformations or other features are necessary in order to improve the performance of tasks identification.
La señal EMG de superficie permite analizar cuantitativamente los cambios fisiológicos ocasionados por diferentes patologías ya sea sobre la Médula espinal, las Motoneuronas, la unión neuromuscular o los músculos propiamente dichos. Por tratarse de una técnica no invasiva, facilita el proceso de diagnóstico y monitorización de dichas enfermedades. Por otra parte, la EMG multicanal permite estudiar directamente
los determinantes fisiológicos de la fatiga muscular, relacionados con cambios a nivel celular que ocasionan variaciones en la conducción de los potenciales de acción sobre las fibras musculares. En este estudio se introducen los mecanismos de la contracción muscular, su relación con la señal EMG y se presentan dos ejemplos de aplicación en el estudio de patologías de la extremidad superior.
The application of engineering system analysis is a very important field in
biomedical engineering (BME) studies: modeling, simulation and control
of the most important physiological systems. A virtual laboratory for the
analysis and the study of human circulatory system is presented in this paper.
This laboratory is based on the compilation of several mathematical models
described in the literature. In addition, some model parameters have been tuned
by means of experimental data under caffeine stimulus. The computational
tool has been built using MATLAB/SIMULINK and EJS, so it combines
good computation capabilities with interactivity. The virtual laboratory has
been designed in order to understand the operation of the circulatory system
under normal conditions, and to predict circulatory variables at different
types and levels of stimuli and conditions.
Ceres, R.; Mañanas, M.A.; Azorín, J. Revista iberoamericana de automática e informática industrial Vol. 8, num. 2, p. 5-15 DOI: 10.4995/RIAI.2011.02.03 Data de publicació: 2011-04-01 Article en revista
La Bioingeniería constituye un área de trabajo e investigación multidisciplinar entre las ingenierías y la medicina que resulta de un interés humano, social y económico creciente. La automática en particular, en sus aspectos de percepción, modelado, control, monitorización, actuación e interacción, entre otros, ofrece importantes conocimientos y herramientas para abordar los problemas relacionados con el diagnóstico y el seguimiento de patologías, con las necesidades funcionales especiales e igualmente con las diferentes terapias a aplicar. Este tutorial presenta aspectos relacionados con el estado del arte y últimos avances en los siguientes campos: Interfaces para la interacción y comunicación de personas con discapacidad, robótica para la rehabilitación y compensación funcional, y sistemas para la mejora de la terapia clínica
La posición y el movimiento del cuerpo están controlados por señales eléctricas que viajan desde y hacia el Sistema Nervioso Central, produciendo la contracción de los músculos voluntarios.
Cuando se presenta una patología ya sea sobre la Médula espinal, las Motoneuronas, la unión neuromuscular o los músculos propiamente dichos, se generan ciertas variaciones sobre la propagación eléctrica y la morfología de dichas señales. Estas variaciones pueden ser observadas y cuantificadas por medio de señales de electromiografía. Más aún, si se utilizan técnicas no invasivas de detección en la superficie de la piel, se facilita el proceso diagnóstico y monitorización de este tipo de enfermedades. La EMG multicanal permite estudiar los determinantes fisiológicos de la fatiga muscular y el análisis de la actividad de unidades motoras aisladas. Dicha información resulta de gran ayuda para la valoración y mejora de los procesos de rehabilitación motora.
One of the career areas included in the field of Biomedical Engineering is the
application of engineering system analysis: physiological modelling, simulation and control.
This paper describes a Virtual Laboratory for the analysis and the study of Human circulatory
system. The Virtual Laboratory is based on the compilation of several mathematical models
described in the literature. Presented application has been build using MATLAB/Simulink
and EJS, so it combines good computation capabilities and it is completely interactive. The
Virtual Laboratory is designed in order to understand the operation of the circulatory system
under normal conditions, and to predict circulatory variables at different levels of stimuli and
Hernandez, A.; Pierfranco, G.; Mañanas, M.A.; Costa-Castelló, R. IEEE International Conference on Emerging Technologies and Factory Automation DOI: 10.1109/ETFA.2009.5347145 Data de presentació: 2009-09-23 Presentació treball a congrés
One of the career areas included in the field of Biomedical
Engineering is the application of engineering system
analysis: physiological modelling, simulation and
control. This paper describes a Virtual Laboratory for
the analysis and the study of Human circulatory system.
The Virtual Laboratory is based on the compilation
of several mathematical models described in the literature.
Presented application has been build using MATLAB/
Simulink and EJS, so it combines good computation
capabilities and it is completely interactive. The Virtual
Laboratory is designed in order to understand the operation
of the circulatory system under normal conditions,
and to predict circulatory variables at different levels of
stimuli and conditions.
Quantitative electroencephalographic (EEG) analysis
is very useful for diagnosing dysfunctional neural states
and for evaluating drug effects on the brain, among others.
However, the bidirectional contamination between electrooculographic
(EOG) and cerebral activities can mislead and
induce wrong conclusions from EEG recordings. Different
methods for ocular reduction have been developed but only
few studies have shown an objective evaluation of their
performance. For this purpose, the following approaches
were evaluated with simulated data: regression analysis,
adaptive filtering, and blind source separation (BSS). In the
first two, filtered versions were also taken into account by
filtering EOG references in order to reduce the cancellation
of cerebral high frequency components in EEG data.
Performance of these methods was quantitatively evaluated
by level of similarity, agreement and errors in spectral
variables both between sources and corrected EEG recordings.
Topographic distributions showed that errors were
located at anterior sites and especially in frontopolar and
lateral–frontal regions. In addition, these errors were higher
in theta and especially delta band. In general, filtered versions
of time-domain regression and of adaptive filtering with RLS
algorithm provided a very effective ocular reduction. However,
BSS based on second order statistics showed the highest
similarity indexes and the lowest errors in spectral variables.
Eye movement artifacts represent a critical issue for quantitative electroencephalography (EEG) analysis and a number of mathematical
approaches have been proposed to reduce their contribution in EEG recordings. The aim of this paper was to objectively and quantitatively
evaluate the performance of ocular filtering methods with respect to spectral target variables widely used in clinical and functional EEG studies.
In particular the following methods were applied: regression analysis and some blind source separation (BSS) techniques based on second-order
statistics (PCA, AMUSE and SOBI) and on higher-order statistics (JADE, INFOMAX and FASTICA). Considering blind source decomposition
methods, a completely automatic procedure of BSS based on logical rules related to spectral and topographical information was proposed in
order to identify the components related to ocular interference. The automatic procedure was applied in different montages of simulated EEG
and electrooculography (EOG) recordings: a full montage with 19 EEG and 2 EOG channels, a reduced one with only 6 EEG leads and a third
one where EOG channels were not available. Time and frequency results in all of them indicated that AMUSE and SOBI algorithms preserved
and recovered more brain activity than the other methods mainly at anterior regions. In the case of full montage: (i) errors were lower than
5% for all spectral variables at anterior sites; and (ii) the highest improvement in the signal-to-artifact (SAR) ratio was obtained up to 40 dB
at these anterior sites. Finally, we concluded that second-order BSS-based algorithms (AMUSE and SOBI)