Andrzej Izworski

Recognition of defects in high voltage transmission lines using the acoustic signal of corona effect

The paper deals with the analysis of the possible application of neural networks to the recognition of typical damage of UHV transmission lines. The acoustic signal generated as a result of corona effects is used as a damage symptom, as its intensity is usually increased after damage occurrence or after contamination of the surface of a conductor or an insulator string. The primary problem in the diagnostic process is the distinguishing between signals generated as results of damage and contamination. The problem is not solved by methods based on the RF signal interference or by the classical methods of acoustic signal analysis. The construction and verification of the assumed diagnostic model have been carried out by experimental studies in laboratory conditions, where typical damage and contamination of the transmission line elements have been simulated.

Processing and classification of deformed speech using neural networks

In many problems of medical diagnosis as well as therapy and rehabilitation, evaluation of the deformed speech signal quality is required. In problems of distorted speech diagnosis the regular methods of speech signal preprocessing and classification, used in speech or voice recognition, totally fail. Also the standard speech signal parametrization techniques (e.g. LPC or cepstral coefficients) cannot satisfactorily describe pathological speech because of its dissimilar phonetic and acoustic structure compared with correct speech, and also because the aim of the recognition process is totally different. In the paper a new method for processing and classification of pathologically deformed speech, based on neural networks techniques, is presented and discussed.

Artificial Intelligence Methods in Diagnostics of the Pathological Speech Signals

In the work excerpts of research are presented, concerning the application of modified acoustic signal processing methods in the problem of “understanding” of selected pathologies of vocal tract. The concept of the research scheme is based on the technique of advanced acoustic signal analysis and it refers to the analysis of artificial neural networks functioning in the task of recognition of selected types of vocal tract pathologies. The method is based on utilization of an internal model of the considered signal’s generator and it is directed towards such a structure analysis of the examined sound. The described method allows to achieve more subtle differentiation for signal characterized by small diversification of measurable features, observed for the classes being recognized, what is the case in the problem of identification of selected pathologies considered here.

Nonlinear processing of auditory brainstem response

Auditory brainstem response potentials (ABR) are signals calculated from the EEG signals registered as responses to an acoustic activation of the auditory system. The ABR signals provide an objective, diagnostic method, widely applied in examinations of hearing organs. The shape of the time-dependent signal, and its possible distortion, and particularly the presence or absence of characteristic waves are of great diagnostic importance. In the present work methods of automated identification of wave V are presented, using multilayer perceptron type networks. Classification methods are also proposed, based on cascade architecture of the neural networks used for recognition of the context information.

The utilization of context signals in the analysis of ABR potentials by application of neural networks

The elaboration of head-surface registration techniques for auditory potentials evoked from the brainstem (ABR) enabled the construction of objective research and diagnostic methods, which can utilized in the examinations of auditory organs. The aim of the present work was the construction of a method, making use of the neural network techniques, enabling an automated detection of wave V in the ABR signals. The basic problem encountered in any attempts of automated analysis of the auditory potentials is connected with impossibility of a reliable evaluation of a single response evoked by a weak acoustic signal. It has been assumed that considerably better detection results should be obtained, when additional context information will be provided to the networks input. This assumption has been verified using complex, hybrid neural networks. As a result about 90% of correct recognitions has been achieved.

System for Intelligent Processing and Recognition of Auditory Brainstem Response (ABR ) Signals

The registration of auditory brainstem response signals allows an objective analysis of processes taking place at particular levels of the neural part of the auditory system. The studies on hearing threshold using auditory brainstem response (ABR) comprise registration of a series of responses for stimuli of varying intensities and frequencies and then determination of the wave V detection threshold, which is directly correlated with the hearing threshold. The paper presents the currently realized system for analysis of ABRs registered during screening and diagnostic examinations. Presented are the methods of preliminary processing and analysis of ABR signals, the selected space of distinctive features describing these signals and the constructed techniques for classification and automated recognition of ABR signals. The system will allow collection and distribution of both raw and processed data for conducting the research work in the field of neuroacoustics and social medicine as well as the development and testing of electromedical equipment.

Telemedical system in evaluation of auditory brainsteam responses and support of diagnosis

The paper presents the use of telemedicine in intelligent supporting of otorhinolaryngologist in the diagnosis of auditory brainsteam responses. This test is easy to visualize but difficult to diagnose. The presented software system uses advanced methods of signal processing and an authors algorithm supporting the doctor by setting the characteristic points of the examination and reach the diagnosis. This paper describes the capabilities of the system and underline the benefits which are result of the nature of this application. It also highlights the benefits and opportunities introduced to this field of medicine by the described intelligent software system.

The methods of pathological speech visualization [using Kohonen neural networks]

In tasks related to the analysis and recognition of pathological speech it is often more important to provide the respective person (e.g. physician) with guidelines for a qualitative evaluation of this speech than to achieve a very accurate automated recognition. By ear it is easy to judge whether the speech is regular or deformed, but any attempt of a quantitative evaluation is not satisfactory. If the speech is transformed to a graphic form, by a proper visualization method, it is easier for a person to estimate its deformation degree by comparing the respective graphical patterns. The new visualization method proposed is based on the results obtained by application of Kohonen neural networks.

Inżynieria biomedyczna – partner medycyny w komunikowaniu o innowacjach medycznych

Paper presents opportunities to take advantage of knowledge of higher technical personnel with Biomedical Engineering specialty as a partner of both doctors and medias representatives in the health communication. It was shown that such partnership is necessary when building patient’s trust for the innovations in medicine. It was also proven how underestimated factor in health communication is properly handled documentation and allowing patients to access it remotely. Conclusions was backed by specific examples of innovations in medicine and means to inform patients about them.

IT Systems of Remote Medical Care

Abstract Intensive development of medical sciences and information technology, and their cooperation offers new opportunities and sets course of action for complex healthcare and human life protection. With the development of equipment capabilities, the emergence of new sensors and advancement of information technology, the emergence of applications supporting life and health protection, ensuring both the healthcare and human protection against various threats, can be observed. Especially in an aging society a huge demand for this type of products and services is visible, and that niche in the market is still not filled. In this paper several existing systems of remote medical care are analyzed and a concept of the constructed system of own authorship is presented.