Mobile Networks for Biometric Data Analysis / edited by Massimo Conti, Natividad Martínez Madrid, Ralf Seepold, Simone Orcioni

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Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Lecture Notes in Electrical Engineering ; 392 | SpringerLink BücherVerlag: Cham ; s.l. : Springer International Publishing, 2016Beschreibung: Online-Ressource (IX, 323 p. 160 illus., 104 illus. in color, online resource)ISBN:

9783319397009

Schlagwörter:

Andere physische Formen: 9783319396989 | Druckausg.: 978-3-319-39698-9 LOC-Klassifikation:

TK1-9971

DOI: DOI: 10.1007/978-3-319-39700-9Online-Ressourcen:

Zusammenfassung: 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.Zusammenfassung: 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.PPN: PPN: 1658384407Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SXE | ZDB-2-ENG

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