Frank J. Owens

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BACKGROUND The first stage in computerised processing of the electrocardiogram is beat detection. This involves identifying all cardiac cycles and locating the position of the beginning and end of each of the identifiable waveform components. The accuracy at which beat detection is performed has significant impact on the overall classification performance,(More)
A system was developed which allowed the simultaneous communication of digitized, full duplex speech and electrocardiography (ECG) signals in realtime. A single band-limited channel was used over a standard telephone line providing 3 kHz bandwidth. The full duplex speech was compressed to 2400 bit/s using linear predictive coding, while multiple ECG signals(More)
The present study discusses two different training techniques for electrocardiogram (ECG) beat detection algorithms. The first technique is a patient specific training method which uses data from the patient's ECG signal to train the beat detector. The second technique is more generic as opposed to patient specific and uses ECG information from a database(More)
This paper describes a study of the use of four different neural network techniques for automatic speech recognition (ASR) using two common, real-world application databases. The neural network techniques investigated were the Multi-Layer Perceptron (MLP), the Multi-Output-Layer Perceptron (MOLP), which is an improved version of the MLP , the Time-Delay(More)
Diarrhea may present as an acute transient condition that is hardly more than an inconvenience or as an acute devastating condition that decimates whole armies and cities. In places in which it is endemic, chronic diarrhea may be equally devastating; however, chronic diarrhea is usually the problem of an individual patient. A clinician may require the most(More)