RESUMEN
The features of the esophageal contractile activity recorded during swallowing have been investigated using a signal-processing approach. Data of a 10 min recording taken from 10 normal subjects have been examined. The final features of each peristaltic wave are a set of parameters comprising the locations and magnitudes of the local wavelets contributing to the peristaltic. The approach is based on an inverse filtering technique. The inverse filter, designed with a knowledge of an average peristaltic profile formed by coherent averaging of many peristaltic examples aligned to their maxima, is used to refine the process of locating the local wavelets. It is shown that the inferred wavelet structure offers a good basis for modelling the different peristaltics, and that it suggests new parameters for esophageal characterization and classification procedures.
Asunto(s)
Deglución/fisiología , Esófago/fisiología , Procesamiento de Señales Asistido por Computador , Humanos , Modelos Lineales , Modelos Biológicos , Reconocimiento de Normas Patrones Automatizadas , Peristaltismo/fisiología , Presión , Valores de Referencia , Reproducibilidad de los ResultadosRESUMEN
Analysis and classification of esophageal motility records were investigated using signal processing and fuzzy-set pattern recognition techniques. A set of parameters has been extracted from the raw records and has previously been used as characterizing features. Improvements to these procedures were obtained by extracting these features from processed data, and some additional parameters were developed. The new set of features was used in the design of a fuzzy classifier, and classification accuracy was estimated using the leave-one-out technique. To our knowledge, this is the first report of the application of automatic classification to esophageal motility records.
Asunto(s)
Trastornos de la Motilidad Esofágica/clasificación , Trastornos de la Motilidad Esofágica/fisiopatología , Lógica Difusa , Procesamiento de Señales Asistido por Computador , Recolección de Datos/métodos , Interpretación Estadística de Datos , Trastornos de la Motilidad Esofágica/diagnóstico , Estudios de Evaluación como Asunto , Humanos , Manometría/métodos , Registros Médicos , Peristaltismo , Presión , Reproducibilidad de los ResultadosRESUMEN
For the esophageal contractile activity recorded during swallowing, a feature extraction scheme has been developed. It recognizes the time, duration, and amplitudes of local peaks for each peristaltic wave. The method is based on the Tauberian approximation for modeling waveforms as a sum of identically shaped pulses with different time delays and amplitudes. Initial conditions on the pulse properties are set and an optimal solution is sought. The method is completely automated and can be utilized for characterization and classification purposes.