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Signals and Systems in Biomedical Engineering Signal Processing and Physiological Systems Modeling /

The use of digital signal processing is ubiquitous in the field of physiology and biomedical engineering. The application of such mathematical and computational tools requires a formal or explicit understanding of physiology. Formal models and analytical techniques are interlinked in physiology as i...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Devasahayam, Suresh R. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer US : Imprint: Springer, 2013.
Edición:2nd ed. 2013.
Temas:
Acceso en línea:Texto Completo

MARC

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245 1 0 |a Signals and Systems in Biomedical Engineering  |h [electronic resource] :  |b Signal Processing and Physiological Systems Modeling /  |c by Suresh R. Devasahayam. 
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300 |a XIV, 390 p.  |b online resource. 
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505 0 |a Introduction -- Signal Measurement -- Signals and Systems Basics -- Signal Filtering and System Control -- Digitization and Discrete Systems -- Discrete Signal Processing -- Numerical Methods and Geometry for Graphics -- Nerve Action Potentials -- External Stimulation of Excitable Tissue -- Skeletal Muscle Contraction -- The Electromyogram -- Neuromuscular Control -- Neural Firing Rate Analysis -- Immune Response to Infection -- Linear Model of Blood Flow -- Appendix: Data Acquisition and Real-Time Signal Processing -- Description of Computer Demonstrations -- Further Reading -- Solutions to Exercises -- Index. 
520 |a The use of digital signal processing is ubiquitous in the field of physiology and biomedical engineering. The application of such mathematical and computational tools requires a formal or explicit understanding of physiology. Formal models and analytical techniques are interlinked in physiology as in any other field. This book takes a unitary approach to physiological systems, beginning with signal measurement and acquisition, followed by signal processing, linear systems modelling, and computer simulations. The signal processing techniques range across filtering, spectral analysis and wavelet analysis. Emphasis is placed on fundamental understanding of the concepts as well as solving numerical problems. Graphs and analogies are used extensively to supplement the mathematics. Detailed models of nerve and muscle at the cellular and systemic levels provide examples for the mathematical methods and computer simulations. Several of the models are sufficiently sophisticated to be of value in understanding real world issues like neuromuscular disease. This second edition features expanded problem sets and a link to extra downloadable material. 
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