Table Of ContentStudies in Big Data 73
Chinmay Chakraborty · Amit Banerjee ·
Maheshkumar H. Kolekar · Lalit Garg ·
Basabi Chakraborty Editors
Internet
of Things
for Healthcare
Technologies
Studies in Big Data
Volume 73
Series Editor
Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland
Theseries“StudiesinBigData”(SBD)publishesnewdevelopmentsandadvances
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Chinmay Chakraborty Amit Banerjee
(cid:129) (cid:129)
Maheshkumar H. Kolekar Lalit Garg
(cid:129) (cid:129)
Basabi Chakraborty
Editors
Internet of Things
for Healthcare Technologies
123
Editors
ChinmayChakraborty Amit Banerjee
Department ofElectronics Department ofElectrical
andCommunication Engineering andComputer Engineering
Birla Institute of Technology, Mesra National University ofSingapore
Ranchi, India Singapore, Singapore
MaheshkumarH.Kolekar Lalit Garg
Department ofElectrical Engineering Department ofComputer Information
Indian Institute of Technology Patna Systems,Faculty ofInformation and
Patna, India Communication Technology
University of Malta
BasabiChakraborty Msida,Malta
FacultyofSoftwareandInformationScience
Iwate Prefectural University
Takizawa, Japan
ISSN 2197-6503 ISSN 2197-6511 (electronic)
Studies in BigData
ISBN978-981-15-4111-7 ISBN978-981-15-4112-4 (eBook)
https://doi.org/10.1007/978-981-15-4112-4
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Preface
The general interest in the Internet of things (IoT) for healthcare technologies has
been increasing significantly because of its enormous and promising application
prospects in the advancement of human civilization. Among literally thousands of
differenttechnologiesrelatedtotheInternetofthingsforhealthcare,therearesome
definite trends that havea high impact in thefuturehealth care and arefocused on
the current title, e.g., Advanced Medical Imaging, Biomedical Signal Processing,
IoT with Different Biomedical Sensors, Biotechnological Advances, etc. This title
focuses on the recent advances and different research issues in biomedical tech-
nology by seeking out for theoretical, methodological, well-established, and vali-
dated empirical work dealing with these different topics. This book volume deals
withtheemergingapplicationsinInternetofthingsforhealthcaretechnologieslike
IoTinsmarthealthcaresystem,IoT-baseddiseasespredictionanddiagnosissystem
for health care, methodology for improving efficiency in data transmission in
healthcare systems, correlation of tension-type headache and diabetes; IoT per-
spectiveinhealthcare,machinelearningapplicationsforareal-timemonitoringof
arrhythmia patients using IoT, human heart arrhythmia identification using ECG
signals; an approach toward biomedical signal processing, deep learning and its
applications in medical imaging, brain tumor classification using deep learning,
early detection of dementia disease using data mining techniques, social, medical,
and educational applications of IoT to assist visually impaired people, design of
embedded system for remote monitoring of malnutrition for people living in rural
v
vi Preface
areas, review on security and privacy concern in IoT health care, applications of
Internet of things in medical area, and bigdata in the management of diabetes
mellitus treatment. This title covers a very vast audience from basic science to
engineering and technology experts and learners. This could eventually work as a
textbookforengineeringandbiomedicalstudentsorsciencemastersprogramsand
forresearchers.Thistitlealsoservesthecommonpublicinterestbypresentingnew
methods to improve the quality of life in general, with better integration into
society.
The title also covers various aspects of future healthcare technologies like
medicalimaging,whichcurrentlyemploysfromsimple2-DX-rays,ultrasound,CT
scans,MRI,andhostofothertechnologies,butresearchersaredevelopingnewand
improved imaging optionslike variousforms ofEM imaging, terahertz orInfrared
imagining, thermography, combined with medical virtual reality, which would
provide more accuracy and better outcomes in image-guided surgery, improved
cardiacandlungimaging,givingphysiciansreal-timeandaccurateviews.Artificial
intelligence is to revolutionize all industries, but perhaps none so much as health
care.Bothbiomedicineandmachinelearningcouldanalyzedataavailedinnational
health databases to identify potential complications, as well as effective protocols,
using the intelligence gained via data. A wave of wearable devices targeting the
biomedical and healthcare applications far beyond tracking your steps each day
emerged. These devices are capable of collecting detailed information about our
health,whilealsoservingasasmartwatchorsimpleattachmentcombinedwithour
mobile phones. The data are collected and analyzed in standard protocols by
machine intelligence looking for possible predictions of health-related issues.
Beyond these, prosthetic technologies have already made significant strides in
recent decades with the advances in materials and development. Chip-enabled
prosthetics are on the horizon with more mobilityand flexibility, or even auxiliary
motors that can help provide additional strength and power, or additional robotic
devices that will continue to blur the lines between therapeutic and assistive
devices.TheIoTenabledwirelessECGsensorstoreducehealthcarecostsandlead
to improving the overall quality of cardio patients’ life. The amount of data
Preface vii
acquiredbyECGsensorsshouldbeminimized fortheefficient performanceofthe
IoThealthcaresystems.Variousbiomedicaladvancesareextremelyprominentand
may transform the way we look at health care.
Ranchi, India Dr. Chinmay Chakraborty
Assistant Professor
[email protected]
Singapore Dr. Amit Banerjee
Senior Scientist
[email protected]
Patna, India Dr. Maheshkumar H. Kolekar
Associate Professor
[email protected]
Msida, Malta Dr. Lalit Garg
Senior Lecturer
[email protected]
Takizawa, Japan Dr. Basabi Chakraborty
Professor
[email protected]
Contents
1 IoT in Smart Healthcare System. . . . . . . . . . . . . . . . . . . . . . . . . . . 1
S. Ananda Kumar and G. Mahesh
2 IoT-Based Diseases Prediction and Diagnosis System
for Healthcare. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Iman Raeesi Vanani and Morteza Amirhosseini
3 A Methodology for Improving Efficiency in Data Transmission
in Healthcare Systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
ReinaldoPadilhaFrança,YuzoIano,AnaCarolinaBorgesMonteiro,
and Rangel Arthur
4 Investigating Correlation of Tension-Type Headache
and Diabetes: IoT Perspective in Health care . . . . . . . . . . . . . . . . . 71
Rohit Rastogi, Parul Singhal, Devendra Kumar Chaturvedi,
and Mayank Gupta
5 Machine Learning Applications for a Real-Time Monitoring
of Arrhythmia Patients Using IoT. . . . . . . . . . . . . . . . . . . . . . . . . . 93
Rajendran Sree Ranjani
6 Human Heart Arrhythmia Identification Using ECG Signals:
An Approach Towards Biomedical Signal Processing. . . . . . . . . . . 109
Ravina Dnyaneshwar Edake
7 Deep Learning and Its Applications in Medical Imaging . . . . . . . . 137
Farzaneh Mansouri Musolu, Saeid Sadeghi Darvazeh,
and Iman Raeesi Vanani
8 Brain Tumor Classification Using Deep Learning. . . . . . . . . . . . . . 155
Vishal K. Waghmare and Maheshkumar H. Kolekar
ix
x Contents
9 Early Detection of Dementia Disease Using Data Mining
Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
M. Sucharitha, Chinmay Chakraborty, S. Srinivasa Rao,
and V. S. K. Reddy
10 Social, Medical, and Educational Applications of IoT to Assist
Visually Impaired People . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
Soham Sharma and M. Umme Salma
11 Design of an Embedded System for Remote Monitoring
of Malnutrition for People Living in Rural Areas. . . . . . . . . . . . . . 215
Bikash Dey
12 A Review on Security and Privacy Concern in IoT
Health Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247
Joy Chatterjee, Manab Kumar Das, Sayon Ghosh, Atanu Das,
and Rajib Bag
13 Applications of Internet of Things in Medical Area . . . . . . . . . . . . 273
Mamata Rath
14 Bigdata in the Management of Diabetes Mellitus Treatment. . . . . . 293
Dhanaraj Rajesh Kumar, K. Rajkumar, K. Lalitha, and V. Dhanakoti
