advances cardiac signal processing (20 resultados)

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Taschenbuch. Condición: Neu. Advances in Cardiac Signal Processing | U. Rajendra Acharya | Taschenbuch | xxii | Englisch | 2010 | Springer | EAN 9783642071744 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Condición: New. pp. 490.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Various disciplines have been bene ted by the advent of high-performance computing in achieving practical solutions to their problems and the area of health care is no exception to this. Signal processing and data mining tools have been developed to enhance the computational capabilities so as to help clinicians in diagnosis and treatment. The electrocardiogram (ECG) is a representative signal containing inf- mation about the condition of the heart. The shape and size of the P-QRS-T wave and the time intervals between various peaks contains useful infor- tion about the nature of disease a icting the heart. However, the human - server cannot directly monitor these subtle details. Besides, since biosignals are highly subjective, the symptoms may appear at random in the timescale. The presence of cardiac abnormalities are generally re ected in the shape of ECG waveform and heart rate. However, by the very nature of biosignals, this re ection would be random in the timescale. That is, the diseases may not show up all the time, but would manifest at certain irregular (random) intervals during the day. Therefore the study of ECG pattern and heart rate variability has to be carried out over extended periods of time (i. e. , for 24 hours). Naturally the volume of the data to be handled is enormous and its study is tedious and time consuming. As a consequence, the possibility of the analyst missing (or misreading) vital information is high.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Various disciplines have been bene ted by the advent of high-performance computing in achieving practical solutions to their problems and the area of health care is no exception to this. Signal processing and data mining tools have been developed to enhance the computational capabilities so as to help clinicians in diagnosis and treatment. The electrocardiogram (ECG) is a representative signal containing inf- mation about the condition of the heart. The shape and size of the P-QRS-T wave and the time intervals between various peaks contains useful infor- tion about the nature of disease a icting the heart. However, the human - server cannot directly monitor these subtle details. Besides, since biosignals are highly subjective, the symptoms may appear at random in the timescale. The presence of cardiac abnormalities are generally re ected in the shape of ECG waveform and heart rate. However, by the very nature of biosignals, this re ection would be random in the timescale. That is, the diseases may not show up all the time, but would manifest at certain irregular (random) intervals during the day. Therefore the study of ECG pattern and heart rate variability has to be carried out over extended periods of time (i. e. , for 24 hours). Naturally the volume of the data to be handled is enormous and its study is tedious and time consuming. As a consequence, the possibility of the analyst missing (or misreading) vital information is high.

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Paperback. Condición: Brand New. reprint edition. 490 pages. 9.25x6.00x1.16 inches. In Stock.

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a comprehensive review of progress in the acquisition and extraction of electrocardiogram signals. The coverage is extensive, from a review of filtering techniques to measurement of heart rate variability, to aortic pressure measurement, to strategies for assessing contractile effort of the left ventricle and more. The book concludes by assessing the future of cardiac signal processing, leading to next generation research which directly impact cardiac health care. 492 pp. Englisch.

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a comprehensive review of progress in the acquisition and extraction of electrocardiogram signals. The coverage is extensive, from a review of filtering techniques to measurement of heart rate variability, to aortic pressure measurement, to strategies for assessing contractile effort of the left ventricle and more. The book concludes by assessing the future of cardiac signal processing, leading to next generation research which directly impact cardiac health care. 492 pp. Englisch.

Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Offers extensive coverage of current and cutting-edge ECG diagnosticsReviews filtering techniques, aortic pressure measurement, visualization of data and moreAssesses future developments and proposes new research topicsIncludes s.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Offers extensive coverage of current and cutting-edge ECG diagnosticsReviews filtering techniques, aortic pressure measurement, visualization of data and moreAssesses future developments and proposes new research topicsIncludes s.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Various disciplines have been bene ted by the advent of high-performance computing in achieving practical solutions to their problems and the area of health care is no exception to this. Signal processing and data mining tools have been developed to enhance the computational capabilities so as to help clinicians in diagnosis and treatment. The electrocardiogram (ECG) is a representative signal containing inf- mation about the condition of the heart. The shape and size of the P-QRS-T wave and the time intervals between various peaks contains useful infor- tion about the nature of disease a icting the heart. However, the human - server cannot directly monitor these subtle details. Besides, since biosignals are highly subjective, the symptoms may appear at random in the timescale. The presence of cardiac abnormalities are generally re ected in the shape of ECG waveform and heart rate. However, by the very nature of biosignals, this re ection would be random in the timescale. That is, the diseases may not show up all the time, but would manifest at certain irregular (random) intervals during the day. Therefore the study of ECG pattern and heart rate variability has to be carried out over extended periods of time (i. e. , for 24 hours). Naturally the volume of the data to be handled is enormous and its study is tedious and time consuming. As a consequence, the possibility of the analyst missing (or misreading) vital information is high.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 492 pp. Englisch.

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Various disciplines have been bene ted by the advent of high-performance computing in achieving practical solutions to their problems and the area of health care is no exception to this. Signal processing and data mining tools have been developed to enhance the computational capabilities so as to help clinicians in diagnosis and treatment. The electrocardiogram (ECG) is a representative signal containing inf- mation about the condition of the heart. The shape and size of the P-QRS-T wave and the time intervals between various peaks contains useful infor- tion about the nature of disease a icting the heart. However, the human - server cannot directly monitor these subtle details. Besides, since biosignals are highly subjective, the symptoms may appear at random in the timescale. The presence of cardiac abnormalities are generally re ected in the shape of ECG waveform and heart rate. However, by the very nature of biosignals, this re ection would be random in the timescale. That is, the diseases may not show up all the time, but would manifest at certain irregular (random) intervals during the day. Therefore the study of ECG pattern and heart rate variability has to be carried out over extended periods of time (i. e. , for 24 hours). Naturally the volume of the data to be handled is enormous and its study is tedious and time consuming. As a consequence, the possibility of the analyst missing (or misreading) vital information is high.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 492 pp. Englisch.

Condición: New. Print on Demand pp. 490.

Condición: New. PRINT ON DEMAND pp. 490.