Can Residual Symptoms During Inter-Episode Period after Partial Remission in Bipolar I Disorder Have Cyclic Patterns with Specific Frequencies?

This case report aimed to describe cyclic patterns of residual mood symptoms in partially remitted bipolar I patient. In a 24-year-old woman with bipolar I disorder, residual mood symptoms measured by self-rated daily mood chart for 18 months were analyzed using wavelet analysis. A 146-day periodicity was prominent for the first 100 days after discharge. Between 100–200 days, 146-day periodicity was progressively diminished and 21- and 8-day periodicity was prominent. Between 200–516 days, 21-day periodicity was diminished and 85-day periodicity became prominent. This case suggest that bipolar patients might have cyclic residual symptoms with specific frequencies.

Early prognostic value of an Algorithm based on spectral Variables of Ventricular fibrillAtion from the EKG of patients with suddEn cardiac death: A multicentre observational study (AWAKE) / Valor pronóstico precoz de un algoritmo basado en variables espectrales de la fibrilación ventricular del ECG de pacientes con muerte súbita cardiaca: estudio observacional multicéntrico (AWAKE)

Abstract Objective: Ventricular fibrillation (VF)-related sudden cardiac death (SCD) is a leading cause of mortality and morbidity. Current biological and imaging parameters show significant limitations on predicting cerebral performance at hospital admission. The AWAKE study (NCT03248557) is a multicentre observational study to validate a model based on spectral ECG analysis to early predict cerebral performance and survival in resuscitated comatose survivors. Methods: Data from VF ECG tracings of patients resuscitated from SCD will be collected using an electronic Case Report Form. Patients can be either comatose (Glasgow Coma Scale GCS --- ≤8) survivors undergoing temperature control after return of spontaneous circulation (RoSC), or those who regain consciousness (GCS = 15) after RoSC; all admitted to Intensive Cardiac Care Units in 4 major university hospitals. VF tracings prior to the first direct current shock will be digitized and analyzed to derive spectral data and feed a predictive model to estimate favorable neurological performance (FNP). The results of the model will be compared to the actual prognosis. Results: The primary clinical outcome is FNP during hospitalization. Patients will be categorized into 4 subsets of neurological prognosis according to the risk score obtained from the predictive model. The secondary clinical outcomes are survival to hospital discharge, and FNP and survival after 6 months of follow-up. The model-derived categorisation will be also compared with clinical variables to assess model sensitivity, specificity, and accuracy. Conclusions: A model based on spectral analysis of VF tracings is a promising tool to obtain early prognostic data after SCD.

Resumen Objetivo: La muerte súbita (MS) por fibrilación ventricular (FV) es una importante causa de morbilidad y mortalidad. Los métodos biológicos y de imagen actuales muestran limitaciones para predecir el pronóstico cerebral al ingreso hospitalario. AWAKE es un estudio observacional, multicéntrico, con el objetivo de validar un modelo basado en el análisis espectral del elec- trocardiograma (ECG), que predice precozmente el pronóstico cerebral y la supervivencia en pacientes resucitados y en estado de coma. Métodos: Se recogerán datos de los ECG con FV de pacientes reanimados de MS. Los pacientes pueden ser tanto supervivientes en estado de coma (Glasgow Coma Scale GCS ≤ 8) sometidos a control de temperatura tras la recuperación de circulación espontánea (RCE), como aquellos que recuperan la consciencia (GCS = 15) tras RCE; todos ellos ingresados en unidades de terapia intensiva cardiológica de 4 hospitales de referencia. Los registros de FV previos al primer choque se digitalizarán y analizarán para obtener datos espectrales que se incluirán en un modelo predictivo que estime el pronóstico neurológico favorable (PNF). El resultado del modelo se comparará con el pronóstico real. Resultados: El objetivo principal es el PNF durante la hospitalización. Los pacientes se categorizarán en 4 subgrupos de pronóstico neurológico según la estimación de riesgo obtenida en el modelo predictivo. Los objetivos secundarios son supervivencia al alta hospitalaria, y PNF y supervivencia a los 6 meses. El resultado de este modelo también se comparará con el pronóstico según variables clínicas. Conclusiones: Un modelo basado en el análisis espectral de registros de FV es una herramienta prometedora para obtener datos pronósticos precoces tras MS por FV.

Análisis exploratorio de ondículas de los patrones de estacionalidad del dengue en Colombia / Exploratory wavelet analysis of dengue seasonal patterns in Colombia

Introducción. El dengue tiene un comportamiento estacional asociado a los cambios climáticos, los ciclos del vector, los serotipos circulantes y las dinámicas poblacionales. El análisis de ondículas permite descomponer una serie de tiempo muy larga en sus componentes de tiempo calendario y periodo. Esta es la primera vez que se utiliza esta técnica para generar un modelo exploratorio del comportamiento del dengue en Colombia. Objetivo. Examinar los patrones de estacionalidad interanual del dengue en Colombia, en particular en los cinco municipios más endémicos, para el periodo 2007 a 2012, y de los ciclos entre años entre 1978 y 2013 a nivel nacional. Materiales y métodos. Se hizo un análisis exploratorio de ondículas con base en los datos de los casos incidentes de dengue reportados por semana epidemiológica en el periodo de 2007 a 2012, y por año, en el periodo de 1978 a 2013. Se utilizó un modelo autorregresivo de primer orden como hipótesis nula. Resultados. Fue evidente el efecto de la epidemia de 2010 sobre la serie de tiempo a nivel nacional y la de los cinco municipios. Se observaron diferencias en los patrones de estacionalidad interanual por municipio. Asimismo, a nivel nacional se hallaron ciclos de dos a cinco años desde el 2004. Conclusiones. El análisis de ondícula permite estudiar una serie de tiempo larga con patrones de estacionalidad variables, como en el caso del dengue en Colombia, e identificar diferencias por regiones. Es necesario explorar estos patrones en niveles de agregación inferiores y evaluar su relación con diversas variables predictoras.

Introduction: Dengue has a seasonal behavior associated with climatic changes, vector cycles, circulating serotypes, and population dynamics. The wavelet analysis makes it possible to separate a very long time series into calendar time and periods. This is the first time this technique is used in an exploratory manner to model the behavior of dengue in Colombia. Objective: To explore the annual seasonal dengue patterns in Colombia and in its five most endemic municipalities for the period 2007 to 2012, and for roughly annual cycles between 1978 and 2013 at the national level. Materials and methods: We made an exploratory wavelet analysis using data from all incident cases of dengue per epidemiological week for the period 2007 to 2012, and per year for 1978 to 2013. We used a first-order autoregressive model as the null hypothesis. Results: The effect of the 2010 epidemic was evident in both the national time series and the series for the five municipalities. Differences in interannual seasonal patterns were observed among municipalities. In addition, we identified roughly annual cycles of 2 to 5 years since 2004 at a national level. Conclusions: Wavelet analysis is useful to study a long time series containing changing seasonal patterns, as is the case of dengue in Colombia, and to identify differences among regions. These patterns need to be explored at smaller aggregate levels, and their relationships with different predictive variables need to be investigated.

Value of wavelet analysis to ultrasonic diagnosis for liver neoplasms / 中国医学装备

Objective:To investigate the Value of Wavelet Analysis to Ultrasonic Diagnosis for liver neoplasms. Methods: The tissue images of Liver Neoplasms by ultrasonic examination experienced color conversion with Photoshop software, and the corresponding relationship among wavelet coefficient, spacial distribution and local image characteristic after conversion were analyzed, i.e.the row details were arrayed in line sequence,the line details in row sequence and the diagonal details in Zsequence. Results: The frequency spectral data and the image texture information were provided via imaging detection and wavelet analysis of, as well as the quantitative data description of the texture of the foci or the normal tissue. Conclusion:Wavelet analysis provided with a reliable basis for the early clinical diagnosis and treatment for liver neoplasms, by which the focal character and degree can be differentiated or analyzed.

Measuring the elasticity of HL-60 cell microvillus by parallel plate flow chamber / 医用生物力学

Objective To filter the noises in the experimental data of parallel plate flow chamber for observing more clearly the events occurring in the process of cell rolling adhesion and develop a new method to measure the elasticity of microvillus on cells based on the flow chamber experiment. Method The experiment of E-selectin regulated HL-60 cell rolling was performed by flow chamber system, and the data were denoised by wavelet analysis so that the high frequency thermal response signals were extracted from the data. Based on the equipartition theorem and equilibrium equations of tethered cell, the relationship between the cell microvillus spring constant and thermal fluctuations was constructed. Results Filtering noises from cell rolling time course by wavelet analysis, the events such as free rolling, slowing down, stopping and speeding up of rolling cell could be observed more easily; almost 80% of fluctuating energy of a rolling cell was involved in its high frequency fluctuation which was regarded as the thermal response of the cell to the Brown movement of water molecules, and the spring constant of microvillus on HL-60 cell was measured to be (13.7±7.4) μN/m at wall shear stress from 0.01～0.06 Pa. Conclusions The wavelet analysis can filter the thermal noises in cell rolling data of flow chamber experiment, and since the rigidity information of cell microvillus is involved in and can be extracted from the high frequency thermal fluctuation of the rolling cell, the parallel plate flow chamber experimental technique can be extended to measure the elasticity of microvillus on cells.

Analysis of functional MRI data based on lifting wavelet transform / 中国医学影像技术

Objective To design a fast method based on wavelet analysis for fMRI data. Methods Lifting wavelet decomposition instead of stationary wavelet decomposition was utilized to separate paradigm responsive signal and confound ones in fMRI data, while frequency analysis was used to find out the wavelet scales in which paradigm responsive signal existed, then reconstructed signal from these scales was subjected to correlation analysis for actived pixels. Results Analyzing visual fMRI data revealed that when the significant level was α＜10-6, the proposed method gave more sensitive results than correlation analysis, but process time decreased on a large scale compared with the one based on the stationary wavelet transform. At the mean time, the proposed method only used 24 timepoints of data for wavelet reconstruction while one based on stationary wavelet transform used 256 timepoints of data. Conclusion The proposed method is the fast one based on wavelet transform for analyzing fMRI data, which also gives an effective technique for compressing fMRI data.

Clinical application of wavelet analysis in ultrasonic diagnosis / 医疗卫生装备

Objecive To observe the characteristic appearance of veins spatial distribution of lump's tissue by using Photoshop so as to improve the ability of ultrasonic diagnosis.Methods The images of lump's tissue gotten from ultrasonic were converted by using Photoshop.Then the corresponding relations between small wave coefficient and local characteristics were analyzed.Result Image determination and wavelet analysis for lump tissue not only provided frequency spectrum and veins analysis for images,but also acquired quantitative data received from focus and normal tissue.Conclusion Wavelet analysis provides reliable basis for distinguishing and analyzing characteristics of focus in clinical lump diagnosis.

Research on intelligent non-destructive diagnostic instrument for coronary artery disease(CAD) / 医疗卫生装备

Based on the domestic and international research in the past few decades,we present an intelligent non-destructive diagnostic instrument for coronary artery disease(CAD).This instrument analyses the multi-channel heart sounds of patients who have coronary artery disease and combines other information about CAD,then wavelet analysis,artificial neural network and pattern recognition technology are also used.The result of clinic application indicates that this instrument has certain reference value to the diagnosis of CAD and provides potential possibility of general examination.

2D multi-resolution Wavelet analysis of PET signals / 医疗卫生装备

By theory analysis,a good method named 2D multi-resolution Wavelet analysis is obtained.This method can effectively eliminate noises and swell signals.Consequently,the reconstruction of PET image is accelerated and the quality of PET image is improved.

Research on automatic diagnosis system of electrocardiogram / 中国医学物理学杂志

The duration of QRS wave,P wave and T wave of ECG can be computerized auto-detected with digital signal process and waveform recognition technology. It can diagnose 15 kinds of abnormal ECG such as ventricular presystole automatically and print out corresponding diagnosis reports. In order to verify the systems stability and creditability, we used American MIT-BIH database to test our algorithms and got a good result.

Research on insomnia therapeutic instrument with brain electricity stimulation / 医疗卫生装备

Processed by the MATLAB-based wavelet analysis,normal EEG signal is used as stimulating source to stimulate brain at proper points for insomnia treatment.This paper explains the design principle of the instrument as well as the hardware structure and the software implementation.

Image Pre-processing of Gene Chips Based on MATLAB / 医疗卫生装备

Objective To design an image pre-processing system of low-density gene chips based on MATLAB, which can process the colored images by cy3 and cy5 fluorescence staining of low-density chips obtained by the array scanning system. It can filter out noise, enhance the contrast gradient of image, improve the quality of image, and implement the functions of image segmentation, edge detection and region identification. Methods The median filter method of the wavelet was used to implement the function of image denoising and improve the image quality. Edge detection was accomplished by wavelet, combining with edge operators. Image segmentation was developed by genetic algorithms. Results It could reduce the effect of spot, noise and other factors, improve the quality of image, and detect the periphery of image better and the region of sampling point more precisely. It can also effectively separate the valuable weak signal points and background or noise with the system. Conclusion The system can accomplish the functions of image pre-processing of low-density gene chips, and the adopted methods are feasible. It can provide relative accurate data information for future analysis.

Research of predictive model of drinking water quality based on wavelet neural network / 重庆医科大学学报

Objective:To provide the methodology reference for the drinking water quality prediction.Methods:A predictive model of drinking water quality was established by wavelet neural network.The monthly average concentration of potassium permanganate in Chongqing,one drinking water quality parameter,was predicted by the model,and the predictive results were compared with BP neural network.Results:RMSE and MAPE were applied to evaluate the predictive results.The research indicated that the precision of WNN model was superior to that of BP neural network model.Conclusion:The WNN model has better precision for drinking water quality prediction.