Mobile Networks for Biometric Data Analysis

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This book showcases new and innovative approaches to biometric data capture and analysis, focusing especially on those that are characterized by non-intrusiveness, reliable prediction algorithms, and high user acceptance. It comprises the peer-reviewed papers from the international workshop on the subject that was held in Ancona, Italy, in October 2014 and featured sessions on ICT for health care, biometric data in automotive and home applications, embedded systems for biometric data analysis, biometric data analysis: EMG and ECG, and ICT for gait analysis. The background to the book is the challenge posed by the prevention and treatment of common, widespread chronic diseases in modern, aging societies. Capture of biometric data is a cornerstone for any analysis and treatment strategy. The latest advances in sensor technology allow accurate data measurement in a non-intrusive way, and in many cases it is necessary to provide online monitoring and real-time data capturing to support a patient's prevention plans or to allow medical professionals to access the patient's current status. This book will be of value to all with an interest in this expanding field.

Describes innovative, non-intrusive approaches to biometric data capture and analysis Considers a wide range of examples, including in relation to EMG and ECG, gait analysis, and automotive applications Highlights the importance of the latest advances in sensor technology Includes supplementary material: sn.pub/extras

Inhalt
ICT for health care.- Embedded systems for biometric data acquisition.- Biometric data in automotive and home applications.- Biometric data analysis of cardiac signals.- Gait analysis.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783319396989
    • Lesemotiv Verstehen
    • Genre Electrical Engineering
    • Auflage 1st edition 2016
    • Editor Massimo Conti, Simone Orcioni, Ralf Seepold, Natividad Martínez Madrid
    • Sprache Englisch
    • Anzahl Seiten 336
    • Herausgeber Springer International Publishing
    • Größe H241mm x B160mm x T24mm
    • Jahr 2016
    • EAN 9783319396989
    • Format Fester Einband
    • ISBN 3319396986
    • Veröffentlichung 28.07.2016
    • Titel Mobile Networks for Biometric Data Analysis
    • Untertitel Lecture Notes in Electrical Engineering 392
    • Gewicht 670g

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