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1.
Int J Neural Syst ; 32(3): 2250008, 2022 Mar.
Article in English | MEDLINE | ID: mdl-34996341

ABSTRACT

As a neurodevelopmental pathology, Attention Deficit Hyperactivity Disorder (ADHD) mainly arises during childhood. Persistent patterns of generalized inattention, impulsivity, or hyperactivity characterize ADHD that may persist into adulthood. The conventional diagnosis relies on clinical observational processes yielding high rates of overdiagnosis due to varying interpretations among specialists or missing information. Although several studies have designed objective behavioral features to overcome such an issue, they lack significance. Despite electroencephalography (EEG) analyses extracting alternative biomarkers using signal processing techniques, the nonlinearity and nonstationarity of EEG signals restrain performance and generalization of hand-crafted features. This work proposes a methodology to support ADHD diagnosis by characterizing EEG signals from hidden Markov models (HMM), classifying subjects based on similarity measures for probability functions, and spatially interpreting the results using graphic embeddings of stochastic dynamic models. The methodology learns a single HMM for EEG signal from each patient, so favoring the inter-subject variability. Then, the Probability Product Kernel, specifically developed for assessing the similarity between HMMs, fed a support vector machine that classifies subjects according to their stochastic dynamics. Lastly, the kernel variant of Principal Component Analysis provided a means to visualize the EEG transitions in a two-dimensional space, evidencing dynamic differences between ADHD and Healthy Control children. From the electrophysiological perspective, we recorded EEG under the Stop Signal Task modified with reward levels, which considers cognitive features of interest as insufficient motivational circuits recruitment. The methodology compares the supported diagnosis in two EEG channel setups (whole channel set and channels of interest in frontocentral area) and four frequency bands (Theta, Alpha, Beta rhythms, and a wideband). Results evidence an accuracy rate of 97.0% in the Beta band and in the channels where previous works found error-related negativity events. Such accuracy rate strongly supports the dual pathway hypothesis and motivational deficit concerning the pathophysiology of ADHD. It also demonstrates the utility of joining inhibitory and motivational paradigms with dynamic EEG analysis into a noninvasive and affordable diagnostic tool for ADHD patients.


Subject(s)
Attention Deficit Disorder with Hyperactivity , Adult , Attention Deficit Disorder with Hyperactivity/diagnosis , Beta Rhythm/physiology , Child , Electroencephalography/methods , Humans , Signal Processing, Computer-Assisted , Support Vector Machine
2.
J Neural Eng ; 8(3): 036026, 2011 Jun.
Article in English | MEDLINE | ID: mdl-21566273

ABSTRACT

Microelectrode recordings are a valuable tool for assisting localization targets during deep brain stimulation procedures in Parkinson's disease neurosurgery. Attempts to automate and standardize this process have been limited by variability in patient neurophysiology and strong dynamics of microelectrode recordings. In this paper, a methodology for the identification of basal ganglia nuclei is presented that is based on a signal-dependent filter bank method using microelectrode recordings. The method is a customized realization of the discrete wavelet transform via the lifting scheme that is optimally tuned by genetic algorithms. Using this method, unique mother wavelet functions that exhibit an adaptable spectrum to the microelectrode recording dynamic are generated. Additionally, by extracting morphological features from the space-transformed microelectrode recording, it is possible to integrate them into three-dimensional (3D) feature spaces with maximum class separability. Finally, high discriminant feature spaces are fed into basic classifiers to recognize up to four basal nuclei. Comparison with several existing wavelets highlights the characteristics of new mother wavelets. Additionally, classification results show that identification of addressed nuclei in the basal ganglia can be performed with 95% confidence.


Subject(s)
Action Potentials , Algorithms , Basal Ganglia/physiopathology , Diagnosis, Computer-Assisted/methods , Electroencephalography/methods , Parkinson Disease/diagnosis , Parkinson Disease/physiopathology , Humans , Sensitivity and Specificity , Signal Processing, Computer-Assisted
3.
Article in English | MEDLINE | ID: mdl-22254892

ABSTRACT

A methodology for wavelet synthesis based on lifting scheme and genetic algorithms is presented. Often, the wavelet synthesis is addressed to solve the problem of choosing properly a wavelet function from an existing library, but which may be not specially designed to the application in hand. The task under consideration is the identification of epileptic seizures over electroencephalogram recordings. Although basic classifiers are employed, results rendered that the proposed methodology is successful in the considered study achieving similar classification rates that had been reported in literature.


Subject(s)
Electroencephalography/methods , Seizures/physiopathology , Humans , Seizures/diagnosis
4.
Article in English | MEDLINE | ID: mdl-21097286

ABSTRACT

Two new surrogate methods, the Small Shuffle Surrogate (SSS) and the Truncated Fourier Transform Surrogate (TFTS), have been proposed to study whether there are some kind of dynamics in irregular fluctuations and if so whether these dynamics are linear or not, even if this fluctuations are modulated by long term trends. This situation is theoretically incompatible with the assumption underlying previously proposed surrogate methods. We apply the SSS and TFTS methods to microelectrode recording (MER) signals from different brain areas, in order to acquire a deeper understanding of them. Through our methodology we conclude that the irregular fluctuations in MER signals possess some determinism.


Subject(s)
Microelectrodes , Algorithms , Fourier Analysis
5.
Article in English | MEDLINE | ID: mdl-19163233

ABSTRACT

In this work, the acoustic and spectral characteristics and the automatic recognition of human emotional states through speech analysis have been studied. Acoustic features have been evaluated and features from time-frequency representation are proposed. The method is based in the representation of speech signal through energy distributions (Gabor transform and WVD) and discrete coefficients (DWT and linear prediction analysis). Recognition accuracy of 94.6% for emotion detection are obtained from SES database of emotional speech in spanish language.


Subject(s)
Emotions , Signal Processing, Computer-Assisted , Speech Acoustics , Speech , Fourier Analysis , Humans , Language , Models, Statistical , Models, Theoretical , Reproducibility of Results , Speech Intelligibility , Speech Perception , Speech Production Measurement , Verbal Behavior
9.
Bol. méd. Hosp. Infant. Méx ; 41(2): 90-4, 1984.
Article in Spanish | LILACS | ID: lil-21200

ABSTRACT

Se muestra el analisis de 43 ninos que ingresaron al Servicio de Urgencias de un hospital de pediatria, con el diagnostico de intoxicacion en el periodo de seis meses comprendido de abril a noviembro de 1982. Se reviso la frecuencia de edad, la substancia causante de la intoxicacion, el mecanismo de intoxicacion, asi como las repercusiones socioeconomicas. Los ninos mas afectados fueron los menores de un ano de edad; la mayor parte procedian del area urbana y de una distancia mayor de 4 km, del hospital. El agente causal mas frecuente fue la atropina que se presento en casi la mitad de los pacientes. La yatrogenia fue el mecanismo mas comun de la intoxicacion. Se revisa la literatura medica sin encontrar diferencia a lo observado en 1958 en el hospital y se hace enfasis en la necesidad de mejorar la educacion medica a todos los niveles


Subject(s)
Infant, Newborn , Infant , Child, Preschool , Child , Humans , Atropine , Poisoning , Socioeconomic Factors
12.
Bol. méd. Hosp. Infant. Méx ; 40(5): 265-7, 1983.
Article in Spanish | LILACS | ID: lil-14627

ABSTRACT

Se presenta el caso de una nina de tres anos de edad con antecedente epidemiologico franco de contacto con plomo, la cual desarrollo sintomatologia de intoxicacion plumbica que fue manejada sintomaticamente en forma extrahospitalaria e ingreso al hospital por un cuadro de intoxicacion por fenotiacinas. Se menciona el cuadro clinico de la intoxicacion por este metal e el manejo quelante; se hace enfasis en la necesidad de diagnostico temprano para evitar secuelas neurologicas graves


Subject(s)
Child, Preschool , Humans , Female , Lead Poisoning , Phenothiazines , Poisoning
14.
Bol. méd. Hosp. Infant. Méx ; 39(8): 563-5, 1982.
Article in Spanish | LILACS | ID: lil-10235

ABSTRACT

Se presenta el caso de un recien nacido a termino con apendicitis aguda en una hernia escrotal, cuya sintomatologia inicial condujo a descartar problema neurologico.Por signos inflamatorios localizados a escroto, se intervino quirurgicamente con resultados satisfactorios. Se analizan las causas de la morbiletalidad, cuadro clinico y radiologico de la apendicitis en la etapa neonatal


Subject(s)
Infant, Newborn , Humans , Male , Appendicitis , Hernia, Inguinal , Infant, Newborn, Diseases
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