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El. knyga: Advances in Telemedicine for Health Monitoring: Technologies, design and applications

Edited by (University of Kurdistan Hewlźr, Department of Computer Science and Engineering, School of Science and Engineering, Kurdistan Region of Iraq), Edited by (Birla Institute of Technology, Department of Electronics and Communication Engineering, Mesr), Edited by
  • Formatas: PDF+DRM
  • Serija: Healthcare Technologies
  • Išleidimo metai: 11-Jun-2020
  • Leidėjas: Institution of Engineering and Technology
  • Kalba: eng
  • ISBN-13: 9781785619878
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Advances in Telemedicine for Health Monitoring: Technologies, design and applicationsDidesnis paveikslėlis
  • Formatas: PDF+DRM
  • Serija: Healthcare Technologies
  • Išleidimo metai: 11-Jun-2020
  • Leidėjas: Institution of Engineering and Technology
  • Kalba: eng
  • ISBN-13: 9781785619878
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This book presents a variety of technologies with applications in telemedicine, originating from the fields of biomedical sensors, wireless sensor networking, computer-aided diagnosis methods, signal and image processing and analysis, automation and control, virtual and augmented reality, multivariate analysis, and data acquisition devices.



Advances in telemedicine technologies have offered clinicians greater levels of real-time guidance and technical assistance for diagnoses, monitoring, operations or interventions from colleagues based in remote locations. The topic includes the use of videoconferencing, mentorship during surgical procedures, or machine-to-machine communication to process data from one location by programmes running in another.

This edited book presents a variety of technologies with applications in telemedicine, originating from the fields of biomedical sensors, wireless sensor networking, computer-aided diagnosis methods, signal and image processing and analysis, automation and control, virtual and augmented reality, multivariate analysis, and data acquisition devices. The Internet of Medical Things (IoMT), surgical robots, telemonitoring, and teleoperation systems are also explored, as well as the associated security and privacy concerns in this field.

Topics covered include critical factors in the development, implementation and evaluation of telemedicine; surgical tele-mentoring; technologies in medical information processing; recent advances of signal/image processing techniques in healthcare; a real-time ECG processing platform for telemedicine applications; data mining in telemedicine; social work and tele-mental health services for rural and remote communities; applying telemedicine to social work practice and education; advanced telemedicine systems for remote healthcare monitoring; the impact of tone-mapping operators and viewing devices on visual quality of experience of colour and grey-scale HDR images; modelling the relationships between changes in EEG features and subjective quality of HDR images; IoMT and healthcare delivery in chronic diseases; and transform domain robust watermarking method using Riesz wavelet transform for medical data security and privacy.

Foreword xiii
About the editors xv
Preface xvii
1 Critical factors in the development, implementation and evaluation of telemedicine
1(14)
Saravana Kumar
Esther Jie Tian
1.1 Introduction
1(8)
1.1.1 Critical factor 1: address a gap in service
3(2)
1.1.2 Critical factor 2: clearly defining the purpose of the telemedicine service
5(1)
1.1.3 Critical factor 3: integrate into the organizational structure
5(1)
1.1.4 Critical factor 4: the role of change management
6(1)
1.1.5 Critical factor 5: the crucial role of infrastructure
6(1)
1.1.6 Critical factor 6: buy-in from stakeholders
7(1)
1.1.7 Critical factor 7: financial sustainability
7(1)
1.1.8 Critical factor 8: legislative and policy requirements
8(1)
1.1.9 Critical factor 9: intersectoral collaboration
8(1)
1.1.10 Critical factor 10: review and re-focus
9(1)
1.2 Conclusion
9(2)
1.3 Future work
11(4)
References
12(3)
2 Surgical tele-mentoring
15(16)
Ramkrishna Mondal
Abbreviations
15(1)
Definitions
16(1)
2.1 Introduction
17(2)
2.2 History of tele-mentoring
19(2)
2.3 Applications of tele-mentoring systems
21(2)
2.3.1 Videoconferencing techniques
21(1)
2.3.2 Wearable technology
22(1)
2.3.3 Robotic tele-mentoring platforms
22(1)
2.3.4 Augmented reality
23(1)
2.4 Challenges
23(1)
2.5 Limitations
24(1)
2.6 Conclusion and future directions
25(6)
References
26(5)
3 Technologies in medical information processing
31(24)
Hoger Mahmud
Mokhtar Mohammadi
Nabeel Ali Khan
Tarik Ahmed Rashid
Nawzad K. Al-Salihi
Rebaz Mohammed Dler Omer
Joan Lu
3.1 Introduction
32(1)
3.2 Data collection
33(3)
3.2.1 Temperature
34(1)
3.2.2 Heart rate
34(1)
3.2.3 Blood pressure
35(1)
3.2.4 Respiration rate
35(1)
3.2.5 Blood oxygen saturation
36(1)
3.3 Bio-signal transmission and processing
36(6)
3.3.1 Medical imaging
37(3)
3.3.2 Medical image transmission and analysis
40(1)
3.3.3 Image compression
41(1)
3.3.4 Biopotential electrode sensing
42(1)
3.4 Data mining and knowledge management
42(2)
3.5 Virtual collaboration framework for information interpretation
44(6)
3.5.1 The interpretation framework
45(2)
3.5.2 Components of interpretation layer
47(1)
3.5.3 How the framework works
48(1)
3.5.4 Case study example
49(1)
3.6 Conclusions and future work
50(5)
References
51(4)
4 A comparative note on recent advances of signal/image processing techniques in healthcare
55(22)
Bala Subramanian Chockalingam
Hemalatha Jeyaprakash
Geetha Subbiah
4.1 Introduction
55(2)
4.2 Data-driven cardiac gating signal extraction method for PET
57(3)
4.2.1 Discussion
59(1)
4.3 3-D subject-specific shape and density estimation of the lumbar spine
60(6)
4.3.1 Discussion
63(3)
4.4 Abnormality detection based on ECG signal preprocessing in remote healthcare application
66(2)
4.4.1 Preprocessing using DENLMS algorithm
67(1)
4.5 Breast cancer classification using histology images
68(2)
4.5.1 CNN architecture
69(1)
4.6 Conclusion
70(1)
4.7 Future work
70(7)
References
70(7)
5 A real-time ECG-processing platform for telemedicine applications
77(26)
Sandeep Raj
5.1 Introduction
78(2)
5.2 Methods
80(2)
5.2.1 Stockwell transform (ST)
80(1)
5.2.2 Twin support vector machines (TSVMs)
81(1)
5.2.3 Particle swarm optimization (PSO)
82(1)
5.3 Proposed method
82(9)
5.3.1 MIT-BIH data
83(1)
5.3.2 Preprocessing
84(2)
5.3.3 R-wave localization and ECG segmentation
86(1)
5.3.4 Feature extraction
87(2)
5.3.5 CST feature recognition using TSVMs
89(2)
5.4 Hardware implementation on Wi-Fi integrated embedded platform
91(3)
5.4.1 Performance metrics
94(1)
5.5 Results and discussion
94(4)
5.5.1 Comparison with literature
97(1)
5.6 Conclusion and future scope
98(5)
References
99(4)
6 Data mining in telemedicine
103(30)
Md Fashiar Rahman
Yuxin Wen
Honglun Xu
Tzu-Liang (Bill) Tseng
Satya Akundi
6.1 Introduction to data mining
103(1)
6.2 Data mining in telemedicine
104(5)
6.2.1 Role of data mining in telemedicine
105(3)
6.2.2 Big data sources and characterization
108(1)
6.3 Integration of data mining techniques into telemedicine
109(13)
6.3.1 Data mining framework
109(2)
6.3.2 Data mining techniques
111(11)
6.4 Case study
122(4)
6.4.1 Heart diseases prediction
123(2)
6.4.2 Breast cancer prediction
125(1)
6.5 Challenges of deploying data mining techniques into telemedicine
126(2)
6.6 Conclusion
128(5)
References
128(5)
7 Social work and tele-mental health services for rural and remote communities
133(16)
Lia Bryant
Bridget Garnham
Deirdre Tedmanson
Sophie Diamandi
7.1 Introduction
133(1)
7.2 Rural heterogeneity and complexity challenge mental health service provision
134(1)
7.3 Bridging the rural/urban divide using ICT for mental health service provision
135(1)
7.4 An ambivalent engagement: social work and ICT
136(2)
7.5 Sustainable engagement with ICT to meet rural community mental health needs
138(3)
7.6 Conclusion
141(8)
References
142(7)
8 Technology-enhanced social work practice and education
149(14)
Kalpana Goel
Lia Bryant
Renae Summers
Sophie Diamandi
8.1 Introduction
149(1)
8.2 Tele-social work practice
150(2)
8.3 Tele-social work education
152(5)
8.3.1 Teaching tele-social work in group work
153(2)
8.3.2 Applying tele-social work in field education
155(2)
8.4 Conclusion
157(1)
8.5 Future work
158(5)
References
158(5)
9 Advanced telemedicine system for remote healthcare monitoring
163(24)
Akash Gupta
Chinmay Chakraborty
Bharat Gupta
9.1 Introduction
163(6)
9.1.1 Monitoring of remotely located epileptic patients
166(1)
9.1.2 Motivation
167(1)
9.1.3 Objective
168(1)
9.1.4 Organization of the chapter
168(1)
9.2 Monitoring of remotely located patients
169(4)
9.2.1 Remote patients' chronic wound monitoring
169(1)
9.2.2 Remote patients monitoring related to heart patients
170(2)
9.2.3 Remote patients monitoring related to diabetic patients
172(1)
9.2.4 Remote monitoring for intensive care unit (ICU) patients
172(1)
9.3 Standards for telemedicine system
173(1)
9.4 Types of a telemedicine system
173(1)
9.5 Special features of the telemedicine system
174(2)
9.6 Cloud-based workflow model of a telemedicine system for remote patient monitoring
176(1)
9.7 Advantage and disadvantage of the telemedicine system
177(2)
9.8 Challenges for designing the telemedicine system
179(1)
9.9 Conclusion
180(1)
9.10 Future scope
180(7)
References
181(6)
10 Impact of tone-mapping operators and viewing devices on visual quality of experience of colour and grey-scale HDR images
187(26)
Shaymaa Al-Juboori
Is-Haka Mkwawa
Lingfen Sun
Emmanuel Ifeachor
10.1 Introduction
187(2)
10.2 Comparison of HDR images with traditional images (LDR)
189(1)
10.3 Characteristics of SSDs
190(1)
10.4 Methodology
191(7)
10.4.1 Subjective assessment of the impact of TMOS and viewing devices
192(4)
10.4.2 Objective assessment of the impact of TMOs and viewing devices
196(2)
10.5 Results
198(7)
10.5.1 Results from subjective assessments
198(3)
10.5.2 Results from objective assessments
201(4)
10.6 Comparison of subjective and objective assessments of HDR image quality
205(1)
10.7 Discussion
206(2)
10.8 Conclusions and future work
208(5)
References
209(4)
11 Modeling the relationships between changes in EEC features and subjective quality of HDR images
213(26)
Shaymaa Al-Juboori
Is-Haka Mkwawa
Lingfen Sun
Emmanuel Ifeachor
11.1 Introduction
213(3)
11.2 Related work
216(2)
11.3 Dataset generation
218(4)
11.3.1 Tone-mapping operators
218(1)
11.3.2 Test stimuli
218(1)
11.3.3 Participants
219(1)
11.3.4 Test setup
220(1)
11.3.5 Test methodology
220(1)
11.3.6 Preprocessing
221(1)
11.3.7 Feature extraction
222(1)
11.4 EEG signal acquisition
222(1)
11.5 Analysis of results
223(5)
11.5.1 Subjective rating analysis
223(1)
11.5.2 EEG signal analysis
223(3)
11.5.3 Correlation and analysis of variance
226(1)
11.5.4 The coupling measurements
227(1)
11.6 A mobile EEG-based QoE model
228(2)
11.6.1 EEG-based QoE model based on regression technique
228(1)
11.6.2 Model evaluation
229(1)
11.7 Limitations
230(3)
11.7.1 Experimental set-up
230(1)
11.7.2 Limitations using mobile devices
230(3)
11.7.3 Limitations using the EEG device
233(1)
11.8 Summary
233(6)
References
233(6)
12 IoMT and healthcare delivery in chronic diseases
239(20)
Yogesh Shelke
12.1 IoMT and healthcare delivery
239(1)
12.2 Impact of the IoMT in chronic disease treatment protocols/functional areas
240(7)
12.2.1 Remote clinical diagnosis and communication
241(2)
12.2.2 Product procurement
243(1)
12.2.3 Imaging and post-processing
243(3)
12.2.4 Drug/treatment planning
246(1)
12.2.5 Preventive health, wellness and patient education
247(1)
12.3 Chronic disease-specific implementation
247(8)
12.3.1 Chronic disease monitoring as the lucrative application of IoMT
247(3)
12.3.2 Implementation in diabetes
250(4)
12.3.3 Implementation challenges
254(1)
12.3.4 Future for IoMT in chronic disease monitoring
254(1)
12.4 Conclusion
255(4)
References
255(4)
13 Transform domain robust watermarking method using Riesz wavelet transform for medical data security and privacy
259(26)
Gajanan K. Birajdar
Vishwesh A. Vyawahare
Smitha Raveendran
Pooja Patil
13.1 Introduction
259(4)
13.2 Background work
263(2)
13.3 Proposed medical image watermarking algorithm using RWT
265(1)
13.3.1 Watermark embedding steps
265(1)
13.3.2 Watermark extraction steps
266(1)
13.4 RWT and SVD
266(2)
13.4.1 Generalized Riesz wavelet transform (GRWT)
266(1)
13.4.2 Singular value decomposition
267(1)
13.5 Simulation results and discussions
268(12)
13.6 Conclusion
280(5)
References
281(4)
14 Conclusion
285(2)
Index 287
Tarik A. Rashid is a professor in the Computer Science and Engineering Department, School of Science and Engineering, University of Kurdistan Hewlźr, Erbil, KRG, Iraq. He received his Ph.D. degree in computer science and informatics from the Computer Science and Informatics Department, College of Engineering, Mathematical, and Physical Sciences, University College Dublin (UCD) in 2006. He was a Postdoctoral Fellow of the Computer Science and Informatics School, University College Dublin (UCD) from 2006 to 2007. His research covers three fields of interest. The first field is the expansion of machine learning and data mining to deal with time series applications. The second field is the development of DNA computing, optimization, swarm intelligence, and nature-inspired algorithms and their applications. The third field is networking, telecommunication and telemedicine applications. He has established collaborative relationships with several international research institutions and published over 100 research articles in internationally refereed books, journals and conferences.



Chinmay Chakraborty is an Assistant Professor (Sr.) in the Department of Electronics and Communication Engineering, BIT Mesra, India. His primary areas of research include wireless body area network, internet of medical things, energy efficient wireless communications and networking and point-of-care diagnosis. He authored the books PSTN-IP Telephony Gateway for Ensuring QoS in Heterogeneous Networks (2014), Advanced Classification Techniques for Healthcare Analysis (2019) and Smart Medical Data Sensing and IoT Systems Design in Healthcare (2019). He is an Editorial Board Member in the Journal of Wireless Communication Technology, Int. Journal of Telecomm. Engg., etc. and also a member of the International Advisory Board for Malaysia Technical Scientist Congress and the Machine Intelligence Research Labs. He received a young research excellence award, Global Peer Review Award, Young Faculty Award and Outstanding Researcher Award.



Kym Fraser is a researcher at the Future Industries Institute, University of South Australia, Adelaide, Australia. He also holds professorships at the University of Brawijaya, Indonesia, University of Kurdistan Hewlźr, Iraq and Aalborg University, Denmark. Before becoming an academic, he spent 25 years in practice in the areas of operations, service and quality management. Since entering academia his research efforts have tended to fall within the broad field of business and management. He has published in top-tier journals such as International Journal of Production Research, Journal of Biomedical Science; Computer Methods and Programs in Biomedicine, Sustainability, Studies in Higher Education to name a few. He has established collaborative relationships with five international research institutions and published over 80 research articles in internationally refereed books, journals and conferences.
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