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Internet of Things (IoT) Technologies for HealthCare

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Cover of 'Internet of Things (IoT) Technologies for HealthCare'

Table of Contents

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    Book Overview
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    Chapter 1 A Secured Smartphone-Based Architecture for Prolonged Monitoring of Neurological Gait
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    Chapter 2 Vision-Based Remote Heart Rate Variability Monitoring Using Camera
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    Chapter 3 How Accurate Are Smartphone Accelerometers to Identify Intermittent Claudication?
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    Chapter 4 Distributed Multivariate Physiological Signal Analytics for Drivers’ Mental State Monitoring
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    Chapter 5 An Efficient Design of a Machine Learning-Based Elderly Fall Detector
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    Chapter 6 Characterization of Home-Acquired Blood Pressure Time Series Using Multiscale Entropy for Patients Treated Against Kidney Cancer
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    Chapter 7 A Heterogeneous IoT-Based Architecture for Remote Monitoring of Physiological and Environmental Parameters
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    Chapter 8 An RFID Based Activity of Daily Living for Elderly with Alzheimer’s
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    Chapter 9 Automated Recognition and Difficulty Assessment of Boulder Routes
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    Chapter 10 e-PWV: A Web Application for Assessing Online Carotid-Femoral Pulse Wave Velocity
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    Chapter 11 Automatic Autism Spectrum Disorder Detection Thanks to Eye-Tracking and Neural Network-Based Approach
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    Chapter 12 Automatic Detector of Abnormal EEG for Preterm Infants
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    Chapter 13 Non-invasive Analytics Based Smart System for Diabetes Monitoring
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    Chapter 14 Cloud-Based Data Analytics on Human Factor Measurement to Improve Safer Transport
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    Chapter 15 Run-Time Assurance for the E-care@home System
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    Chapter 16 Scalable Framework for Distributed Case-Based Reasoning for Big Data Analytics
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    Chapter 17 Deep Learning Based Person Identification Using Facial Images
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    Chapter 18 Erratum to: Internet of Things (IoT) Technologies for HealthCare
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Title
Internet of Things (IoT) Technologies for HealthCare
Published by
Springer, Cham, January 2017
DOI 10.1007/978-3-319-76213-5
ISBNs
978-3-31-976212-8, 978-3-31-976213-5
Editors

Mobyen Uddin Ahmed, Shahina Begum, Jean-Baptiste Bastel

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 20%
Lecturer 2 20%
Other 1 10%
Student > Ph. D. Student 1 10%
Student > Postgraduate 1 10%
Other 0 0%
Unknown 3 30%
Readers by discipline Count As %
Computer Science 5 50%
Psychology 1 10%
Economics, Econometrics and Finance 1 10%
Unknown 3 30%