Analysis of Temporal Patterns of Physiological Parameters

Analysis of Temporal Patterns of Physiological Parameters

Balázs Benyo (Szechnyi Istvan University and Budapest University of Technology and Economics, Hungary)
Copyright: © 2006 |Pages: 33
DOI: 10.4018/978-1-59140-848-2.ch013
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This chapter deals with the analysis of spontaneous changes occurring in two physiological parameters: the cerebral blood flow and respiration. Oscillation of the cerebral blood flow is a common feature in several physiological or pathophysiological states and may significantly influence the metabolic state of the brain. Our goal was to characterize the temporal blood flow pattern before, during, and after the development of CBF oscillations. Investigation of this phenomenon may not only clarify the underlying regulatory mechanisms and their alterations under certain conditions but also lead to the development of novel clinical diagnostic tools for early identification of developing cerebrovascular dysfunction in pathophysiological states such as brain trauma or stroke. A disturbance in normal breathing may occur in several nervous and physical diseases. In the present study, we introduce a reliable online method which is able to recognize abnormal sections of respiration, that is, the most common breathing disorder, the sleep apnea syndrome, based on a single time signal, the nasal air flow. There are several common features of the above problems and signals under investigation that imply similar solutions. The chapter introduces the systematic way of selecting proper feature extraction method and optimal classification procedure. The introduced approach can be generalized for the analysis of similar time series featuring physiological parameters.

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Table of Contents
Rezaul Begg, Joarder Kamruzzaman, Ruhul Sarker
Rezaul Begg, Joarder Kamruzzaman, Ruhul Sarker
Chapter 1
Joarder Kamruzzaman, Rezaul Begg, Ruhul Sarker
Artificial neural network (ANN) is one of the main constituents of the artificial intelligence techniques. Like in many other areas, ANN has made a... Sample PDF
Overview of Artificial Neural Networks and their Applications in Healthcare
Chapter 2
Wolfgang I. Schollhorn, Jörg M. Jager
This chapter gives an overview of artificial neural networks as instruments for processing miscellaneous biomedical signals. A variety of... Sample PDF
A Survey on Various Applications of Artificial Neural Networks in Selected Fields of Healthcare
Chapter 3
Chris D. Nugent, Dewar D. Finlay, Mark P. Donnelly, Norman D. Black
Electrical forces generated by the heart are transmitted to the skin through the body’s tissues. These forces can be recorded on the body’s surface... Sample PDF
The Role of Neural Networks in Computerized Classification of the Electrocardiogram
Chapter 4
G. Camps-Valls, J. F. Guerrero-Martinez
In this chapter, we review the vast field of application of artificial neural networks in cardiac pathology discrimination based on... Sample PDF
Neural Networks in ECG Classification: What is Next for Adaptive Systems?
Chapter 5
Peng Li, Kap L. Chan, Sheng Fu, Shankar M. Krishnan
n this chapter, a new concept learning-based approach is presented for abnormal ECG beat detection to facilitate long-term monitoring of heart... Sample PDF
A Concept Learning-Based Patient-Adaptable Abnormal ECG Beat Detector for Long-Term Monitoring of Heart Patients
Chapter 6
Toshio Tsuji, Nan Bu, Osamu Fukuda
In the field of pattern recognition, probabilistic neural networks (PNNs) have been proven as an important classifier. For pattern recognition of... Sample PDF
A Recurrent Probabilistic Neural Network for EMG Pattern Recognition
Chapter 7
Toshio Tsuji, Kouji Tsujimura, Yoshiyuki Tanaka
In this chapter, an advanced intelligent dual-arm manipulator system teleoperated by EMG signals and hand positions is described. This myoelectric... Sample PDF
Myoelectric Teleoperation of a Dual-Arm Manipulator Using Neural Networks
Chapter 8
Markad V. Kamath, Adrian R. Upton, Jie Wu, Harjeet S. Bajaj, Skip Poehlman, Robert Spaziani
The artificial neural networks (ANNs) are regularly employed in EEG signal processing because of their effectiveness as pattern classifiers. In this... Sample PDF
Artificial Neural Networks in EEG Analysis
Chapter 9
Robert T. Davey, Paul J. McCullagh, H. Gerry McAllister, H. Glen Houston
We have analyzed high and low level auditory brainstem response data (550 waveforms over a large age range; 126 were repeated sessions used in... Sample PDF
The Use of Artificial Neural Networks for Objective Determination of Hearing Threshold Using the Auditory Brainstem Response
Chapter 10
Rezaul Begg, Joarder Kamruzzaman
This chapter provides an overview of artificial neural network applications for the detection and classification of various gaits based on their... Sample PDF
Movement Pattern Recognition Using Neural Networks
Chapter 11
G. Camps-Valls, J. D. Martin-Guerrero
Recently, important advances in dosage formulations, therapeutic drug monitoring (TDM), and the emerging role of combined therapies have resulted in... Sample PDF
Neural and Kernal Methods for Therapeutic Drug Monitoring
Chapter 12
Yos S. Morsi, Subrat Das
This chapter describes the utilization of computational fluid dynamics (CFD) with neural network (NN) for analysis of medical devices. First, the... Sample PDF
Computational Fluid Dynamics and Neural Network for Modeling and Simulations of Medical Devices
Chapter 13
Balázs Benyo
This chapter deals with the analysis of spontaneous changes occurring in two physiological parameters: the cerebral blood flow and respiration.... Sample PDF
Analysis of Temporal Patterns of Physiological Parameters
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