Bioelectronics and Medical Devices
1st Edition
From Materials to Devices - Fabrication, Applications and Reliability
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Table of Contents
1 Light-fidelity based biosignal transmission 1
Pratyush K. Patnaik, Suraj K. Nayak, Ashirbad Pradhan, Amrutha V,
Champak Bhattacharya, Sirsendu S. Ray and Kunal Pal
Introduction 1
Literature review 2
Components and methodology 5
Components 5
Methodology 5
Results and discussions 8
Designing the device 8
Testing of device 8
Conclusion 11
References 12
2 Development of a low-cost color sensor for biomedical applications 15
Pratyush K. Patnaik, Paresh Mahapatra, Dibyajyoti Biswal,
Suraj K. Nayak, Sachin Kumar, Biswajeet Champaty and Kunal Pal
Introduction 15
Literature review 16
Color models 16
Application of colorimeter in the medical industry 17
Color measurement of dental prosthesis 18
Blood glucose level measurement 19
Materials 20
Methods 21
Designing the color sensor 21
Designing the graphical user interface 22
Color sensor calibration 22
Results and discussion 25
Development of the color sensor 25
Testing of color sensor 26
Conclusion 27
References 27
3 Development of a voice-controlled home automation system for the
differently-abled 31
Karan Pande, Ashirbad Pradhan, Suraj Kumar Nayak, Pratyush Kumar
Patnaik, Biswajeet Champaty, Arfat Anis and Kunal Pal
Introduction 31
Literature review 32
Materials and methods 36
Materials 36
Development of Arduino program 36
Development of Android app 38
Design and development of printed circuit board 39
Results and discussion 39
Conclusion 42
References 42
4 Lab-on-a-chip sensing devices for biomedical applications 47
Pavel Sengupta, Kalap Khanra, Amit Roy Chowdhury
and Pallab Datta
Introduction 47
Advantages and disadvantages of lab-on-a-chip devices 48
Techno-commercial appraisal of lab-on-a-chips 48
Materials and physical laws relevant for lab-on-a-chips 51
Materials that can be used 51
Physical laws 52
Reynolds number and Stokes flow 52
Navier<STOKES P 53< equation>
Poiseuille flow 53
Peclet number 54
Components of lab-on-a-chip devices 54
Liquid pumping methods 54
Fluid mixing 60
Sample and reagent introduction 61
Sample and reagent preconcentration 63
Sample and reagent separation 64
Fabrication methods 66
Lithography and second cast processes 66
Micromachining etching techniques 68
Bonding methods 68
Maskless patterning techniques 70
Detection processes 72
Chemical sensing 72
Optical detection methods 74
Other detection techniques 75
Some applications of lab-on-a-chip 76
Conclusions 82
Acknowledgment 82
References 82
Further reading 95
5 Impedance-based biosensors 97
Avishek Chakraborty, Dewaki Nandan Tibarewala
and Ananya Barui
Introduction 97
Overview of impedance biosensors 98
Transducer architecture of impedance biosensor 98
Theoretical principle of impedance biosensors 98
Representation of impedance data 101
Design and fabrication 103
Measurement and instrumentation 105
Types and application of impedance biosensor 106
Biocatalytic impedance biosensor: enzyme as biorecognition
molecules 106
Bioaffinity impedance biosensors 106
Cellular biosensing 113
Recent trends in impedance biosensors 115
Microfluidics 115
Magneto-impedimetric biosensors 116
Surface plasmon resonance-based electrochemical impedance
spectroscopy imaging 116
Conclusion 118
References 118
6 Acoustophoresis-based biomedical device applications 123
Sharda Gupta and Arindam Bit
Introduction 123
Acoustic phenomena 124
Theory behind acoustophoresis 125
Measuring physical properties of acoustophoresis 132
Measuring motion of particles under acoustic field 132
Acoustic control 133
Fabrication of device 136
Application of acoustophoresis in bioengineering 139
Acknowledgment 141
Declaration 141
References 141
Further reading 143
7 Electroencephalography and near-infrared spectroscopy-based
hybrid biomarker for brain imaging 145
Raghavendra Prasad, N.P. Guhan Seshadri, R. Periyasamy,
Stephanie Miller, Arindam Bit and Kunal Mitra
Introduction to brain imaging modalities 145
Computed axial tomography 146
Magnetic resonance imaging 146
Functional magnetic resonance imaging 147
Positron emission tomography 147
Functional near-infrared spectroscopy 147
Electroencephalogram 148
Near-infrared spectroscopy system principle and architecture 149
Propagation of light in tissue and modified Beer<LAMBERT P 150< law>
Near-infrared spectroscopy data acquisition system 151
Near-infrared spectroscopy device 151
Types of spectrometers 152
Electroencephalography system architecture and principle 155
History and working mechanism 155
Electroencephalography data acquisition system 156
Electrode placement procedure 159
Montage selection/modes of Electroencephalography acquisition 160
Application of near-infrared spectroscopy and
electroencephalography system for brain imaging 161
Applications 161
Application to the cognitive and psychological sciences 161
Brain development 161
Brain<COMPUTER P 162< interface>
Hyper scanning 162
Biomarkers of brain physiological conditions 163
Identifying disease-specific biomarkers 164
Aspects of association and handy biomarkers 164
The ideal surrogate biomarker 165
Biomarkers: advantages and limitations 165
Real-time imaging 165
Recent advances 166
Electroencephalography 166
Magneto encephalography 167
Functional magnetic resonance imaging 168
Functional near-infrared spectroscopy 168
Computed axial tomography 169
Positron emission tomography 169
Functional imaging 169
Functional imaging properties 170
Hemodynamic methods (fMRI) 170
Electromagnetic methods (EEG) 171
Tempero-spatial imaging 171
Hybrid system for brain imaging 172
Hybrid brain imaging 172
Conclusion 173
References 174
Further reading 181
8 Micro-electro-mechanical system<BASED P 183< devices delivery drug>
Ankur Gupta and Pramod Pal
Introduction 183
Need for drug delivery technology 183
Existing drug delivery devices 185
About micro-electro-mechanical systems 186
Various components in micro-electro-mechanical system<BASED< P>
drug delivery systems 187
Micro pump 187
Micro valves 194
Microneedles 196
Micro biosensors 198
Microfluid channels 200
Micro reservoirs 201
Micro-electro-mechanical system<BASED P delivery drug 202< system>
Advantages of micro-electro-mechanical system devices in
drug delivery system 206
Limitations and challenges 207
Conclusion and scope 207
References 207
9 Enzyme-based biosensors 211
Jaspreet Kaur, Sandeep Choudhary, Rashmi Chaudhari,
Rahul D. Jayant and Abhijeet Joshi
Introduction 211
Background 212
Characteristics of a biosensor 212
Biological recognition and transducing mechanisms 214
Enzyme immobilization 216
Techniques for enzyme immobilization 216
Immobilization techniques for developing micro-nano-sized particles 218
Materials and carriers for fabrication of enzyme-based biosensors 220
Natural polymers 220
Synthetic polymers 221
Inorganic materials as support 221
Enzyme-based biosensors 222
Electrochemical enzyme-based biosensors 222
Optical biosensors 226
Electrochemilumiescent biosensors 227
In vivo biosensors 228
Piezoelectric quartz crystal biosensors 229
Thermistor/calorimetric biosensors 230
Challenges in developing enzyme-based biosensors 231
Applications of enzyme-based biosensors in various fields 232
Health and biological applications 233
Environment and agriculture applications 233
Bioprocessing industry applications 234
Food processing and drink analysis applications 234
Security and bioterrorism 235
Conclusions 235
References 236
10 Ultrasound-based drug delivery systems 241
Bhavana Joshi and Abhijeet Joshi
Introduction 241
Physics of ultrasound-based drug delivery system 241
Factors affecting ultrasound-mediated drug delivery 242
Implications of the ultrasound-mediated delivery 243
Types of drug carriers 246
Applications of ultrasound-mediated drug delivery systems 252
Cancer 252
Alzheimer’s disease 255
Transdermal drug delivery 255
Pulmonary diseases 256
Cardiovascular disease 257
Conclusions and future aspects 258
References 259
11 Electroencephalogram-controlled assistive devices 261
Abdulhamit Subasi
Introduction 261
Literature review 263
Electroencephalogram 265
Brain<COMPUTER P interface 266<>
Signal denoising methods 267
Principal component analysis 268
Independent component analysis 268
Multiscale principal component analysis 268
Feature extraction methods 269
Wavelet packed decomposition 270
Dual tree complex wavelet transform 271
Dimension reduction methods 271
Machine learning methods 272
Artificial neural networks 272
k-Nearest neighbor 273
Support vector machine 273
Classification and regression tree 273
C4.5 decision tree 274
REP tree 274
ADTree 274
Random tree classifiers 274
Random forests 275
Rotation forest 275
Results 275
Experimental results for ERP P300 brain<COMPUTER P interface<>
database 276
Experimental results for motor imagery brain<COMPUTER P interface<>
data set 279
Discussion and conclusion 280
References 281
12 Electromyogram-controlled assistive devices 285
Abdulhamit Subasi
Introduction 285
Literature review 288
Electromyogram 290
Man<MACHINE P interface 291<>
Electromyography for prosthetic control 291
Rehabilitation robotics 292
Signal denoising with multiscale principal component analysis 293
Feature extraction methods 294
Discrete wavelet transform 295
Tunable Q-factor wavelet transform 295
Dimension reduction methods 296
Machine learning methods 296
Artificial neural networks 297
k-Nearest neighbor 297
Support vector machine 297
Classification and regression tree 298
Reduced-error pruning tree 298
Logical analysis of data tree 298
C4.5 decision tree 298
Random tree classifiers 299
Random forests 299
Rotation forest 299
Results and discussion 300
Performance evaluation measures 300
Experimental results 301
Discussion 305
Conclusion and future directions 306
References 306
13 Electrical safety 313
Mana Sezdi
What is electrical safety? 313
Why is it important in medical applications? 313
Physiological effects of electricity 314
Leakage current 314
Electrical shock 315
Macroshock 316
Microshock 316
Measurement of electrical leakage current 317
International standards in electrical safety 320
IEC 60601-1:2005 standard 320
IEC 62353:2014 standard 325
Electrical safety analyzer 326
Conclusion 329
References 329
Further reading 330
14 Biomedical metrology 331
Mana Sezdi
What is biomedical metrology 331
The difference between the biomedical metrology and calibration 331
Application of biomedical metrology 332
The devices used in biomedical metrology 333
Simulators 333
Analyzers 333
Testing/measuring instruments 334
Phantoms 334
Workflow in biomedical metrology 336
Determination of the devices to be measured 338
Performing of the measurements according to the international
standards 340
Interpretation of the measurement results 341
Labeling of devices after the measurements 346
Preparation of the certificates 350
Supervision of biomedical metrology services 351
Conclusion 352
References 352
15 Bone-implantable devices for drug delivery applications 355
Priyanka Ray, Md Saquib Hasnain, Abir Koley and Amit Kumar Nayak
Introduction 355
Morphology of bone 356
Bone fracture healing process 357
Polymer-based bone-implantable drug delivery devices 357
Natural polymers 357
Synthetic polymers 363
Inorganic material-based bone-implantable drug delivery devices 370
Ceramics 370
Polymeric-inorganic bone-implantable drug delivery devices 376
Conclusion 379
References 379
16 Iontophoretic drug delivery systems 393
Amit Kumar Nayak, Sanjay Dey, Kunal Pal and Indranil Banerjee
Introduction 393
Historical background 394
Principles and mechanisms of iontophoretic drug delivery 395
Advantages and disadvantages of iontophoresis systems 397
Factors influencing the iontophoretic drug delivery 398
Physicochemical characteristics of drugs 398
Drug formulation characteristics 400
Experimental factors 400
Biological factors 402
Applications of iontophoretic drug delivery 402
Iontophoretic delivery of nonsteroidal antiinflammatory drugs 402
Iontophoretic delivery of opioids 404
Iontophoretic delivery of steroids 404
Iontophoretic delivery of local anesthetics 405
Iontophoretic delivery of drugs acting on the central nervous system 406
Iontophoretic delivery of cardiovascular drugs 408
Iontophoretic delivery of proteins and peptides 409
Miscellaneous 411
Conclusion 412
References 413
Further reading 420
17 Microneedle platform for biomedical applications 421
Sabahat Shaikh, Nishtha Bhan, Fiona C. Rodrigues, Eshwari Dathathri,
Shounak De and Goutam Thakur
Introduction 421
Microfabrication technology 425
Overview 425
Fabrication materials 425
Fabrication techniques for microneedles 425
Silicon microneedles fabrication 425
Metal, glass, and ceramic microneedles fabrication 427
Polymeric microneedles fabrication 429
Sugar glass microneedles fabrication 430
3D printed microneedles 431
Characterization techniques for microneedles 432
Fluorescent microscopy 432
Scanning electron microscopy 434
Mechanical testing 434
Applications 436
Conclusion 437
References 438
18 Trends in point-of-care microscopy 443
Pallavi Bohidar, Soumya Gupta and Indranil Banerjee
Introduction 443
Point-of-care devices: historical perspective 444
Point-of-care devices: outlining the diversity 447
Point-of-care microscope 449
The need for point-of-care microscope 450
Point-of-care microscopes: fabrication approaches 451
Research trend 463
Point-of-care microscopes: the market view 475
Key players 475
Business projection 475
Conclusion and future direction 475
References 476
19 Development of spectroscopy-based medical devices for
disease diagnosis in low resource point-of-care setting 483
Animesh Halder, Soumendra Singh, Aniruddha Adhikari,
Probir Kumar Sarkar and Samir Kumar Pal
Introduction 483
Optical properties of blood and different body parameters 484
Optical components and software design for the spectroscopy-based
diagnosis 485
A minimally invasive biomedical instrument for hemoglobin detection 486
Noninvasive biomedical instrument for hemoglobin and bilirubin
detection 486
Conclusion 490
References 490
20 Dielectrophoresis-based devices for cell patterning 493
Tarun Agarwal and Tapas Kumar Maiti
Introduction 493
Impact of dielectrophoretic force on a polarizable particle 494
Electrode configurations for nonuniform electric field generation 496
Influence of dielectrophoretic force on mammalian cell behavior 497
Dielectrophoresis suspension buffer influences mammalian cell
behavior under electric field 498
patterning 500
Dielectrophoresis-based three-dimensional cell patterning 504
Immobilization strategies for the patterned cells 506
Challenges and future prospects of dielectrophoresis-based cell-patterning 506
References 508
21 Multichannel surface electromyography 513
Usha Kuruganti
Introduction to surface electromyography 513
Overview of surface electromyography 513
History of electromyography 514
Measurement of surface electromyography 514
Electromyography signal generation 514
Detection of the surface electromyography signal 515
Data analysis methods 516
Amplitude estimation 517
Force estimates 518
Muscle coordination and temporal information 518
Normalization 519
Spectral estimation 520
Time-frequency and wavelet analyses 522
Sensors for surface electromyography collection 523
Applications of surface electromyography 523
Multichannel and high-density surface electromyography 525
Overview of multichannel electromyography 525
Data analysis techniques 527
Sensors for multichannel and high-density surface
electromyography collection 527
Applications of multichannel surface electromyography 528
Future research directions 530
Conclusions 531
References 531
22 Sensors for monitoring workplace health 537
Usha Kuruganti
Introduction to ergonomics and human factors engineering 537
Elements of workplace health 538
Measurement of workplace health 540
Questionnaires 541
Direct observation techniques 541
Direct measurement techniques 543
Sensors to monitor workplace health 543
Pressure sensors 545
Insole sensors 546
Accelerometry-based wearable activity monitors 547
Environmental sensors 547
Neuroergonomics and electroencephalography 548
Future directions in sensor technology for workplace health 549
Conclusion 550
References 551
23 Advances in enzyme-based electrochemical sensors: current trends,
benefits, and constraints 555
George Luka, Syed Ahmad, Natashya Falcone and Heinz-Bernhard Kraatz
Introduction 555
Molecular recognition elements 556
Transducers 557
Enzyme-based electrochemical biosensors 558
Oxidoreductase-based electrochemical biosensors 560
Glucose biosensors 560
Lactate biosensors 563
Cofactors and coenzymes 564
Enzymatic regeneration 566
Chemical regeneration 566
Electrochemical regeneration 567
Photochemical regeneration 568
Nonoxidoreductase-based electrochemical biosensors 568
Kinase-based electrochemical sensors 569
Acetylcholinesterase biosensors 577
Conclusion and future trends 580
Acknowledgments 581
References 581
Further reading 590
24 Electrocardiogram signal processing-based diagnostics: applications
of wavelet transform 591
Suraj K. Nayak, Indranil Banerjee and Kunal Pal
Introduction 591
Morphological description of electrocardiogram signal 592
Wavelets 593
Mexican hat wavelet 593
Morlet wavelet 594
Haar wavelet 595
Daubechies wavelet 595
Biorthogonal wavelet 596
Basics of the wavelet transforms 596
Continuous wavelet transform 597
Discrete wavelet transform 599
Wavelet transforms-based electrocardiogram signal processing
for disease diagnostics 601
Detection of arrhythmia 603
Detection of coronary artery disease 606
Detection of myocardial infarction 607
Conclusion 610
References 611
25 Sensor fusion and control techniques for biorehabilitation 615
Dinesh Bhatia and Sudip Paul
Introduction 615
Control techniques 621
Biological control phenomenon 621
Different control techniques used in industry 621
Available biomimicking control techniques 622
Biorehabilitation techniques 622
Artificial neural network 624
Neurological rehabilitation 625
Intermediate care 626
Acute rehabilitation 626
Occupational rehabilitation 626
Cardiac rehabilitation 626
The acute phase 627
The subacute phase 627
Intensive outpatient therapy 627
Independent ongoing conditioning 627
Drug rehabilitation 627
Physical rehabilitation 628
Vestibular rehabilitation 629
Stroke rehabilitation 629
Poststroke 630
Real-time control of rehabilitation devices 630
Exoskeleton control strategy and existing devices 631
Summary 631
References 632
Further reading 632
26 Biofunctional interfaces for cell culture in microfluidic devices 635
Amid Shakeri, Sara Rahmani, Sara M. Imani, Matthew Osborne,
Hanie Yousefi and Tohid F. Didar
Introduction 635
Approaches for creating biofunctional interfaces in microfluidics 636
Plasma treatment 636
Silanization 638
Microcontact printing 643
Microfluidic patterning 647
Graft polymerization 659
Hydrogels 662
Selected applications 671
Affinity-based cell sorting and separation in microfluidic devices 671
Organ-on-a-chip 675
Biosensing for cell detection 680
Conclusion 683
References 683
27 Microsystems technology for high-throughput single-cell sorting 701
Lindsay Piraino, Tricia Conti, Azmeer Sharipol, Danielle S.W. Benoit
and Lisa A. DeLouise
Microsystems and single-cell assays 701
Convex, spherical, and tubular microwells 704
Microfluidic and microwell device challenges 710
Conclusions 712
Acknowledgments 712
References 712
28 Microfluidic devices for DNA amplification 721
Ali Shahid, Shayan Liaghat and P. Ravi Selvaganapathy
Introduction 721
Polymerase chain reaction 721
Microfluidic systems for polymerase chain reaction 722
Microfluidic devices for polymerase chain reaction with stationary
chambers 723
Microfluidic polymerase chain reaction devices with flow-through
channels 727
Microfluidic devices for polymerase chain reaction with
naturally driven convective flow 731
Microfluidic polymerase chain reaction devices using the droplets 733
Isothermal DNA amplification methods 736
Loop-mediated isothermal amplification 736
Nucleic acid sequence-based amplification 738
Helicase dependent amplification 738
Rolling circle amplification 738
Strand displacement amplification 739
Microfluidic systems for loop-mediated isothermal amplification 739
Microfluidic loop-mediated isothermal amplification systems with
chambers 739
Microfluidic devices for loop-mediated isothermal amplification
using droplets 746
Microfluidic integrated devices for loop-mediated isothermal
amplification 747
Heating methods for loop-mediated isothermal amplification-based
systems 750
Detection methods for loop-mediated isothermal amplification-based
systems 751
Fluorescence detection 751
Electrochemical detection 752
Real-time turbidity detection 753
Naked eye<BASED P 753< detection>
Conclusion 754
References 755
29 Optimizing glucose sensing for diabetes monitoring 765
Robert J. Forster and Loanda R. Cumba
Introduction 765
Glucose monitoring 766
Optimizing glucose monitoring in blood 766
Conclusions 774
References 774
Further reading 777
30 Brain<COMPUTER P from< stimulation: electrical interface
control to neurofeedback in rehabilitation 779
Saugat Bhattacharyya and Mitsuhiro Hayashibe
Introduction 779
Combining brain<COMPUTER P interface electrical< functional with>
stimulation 781
Brain<COMPUTER P electrical interface<functional in< stimulation>
rehabilitation 783
Importance and types of brain<COMPUTER P interface 784< feedback>
Visual feedback 786
Vibrotactile feedback 786
Possibility of functional electrical stimulation as feedback 787
Conclusion 788
References 789
Further reading 790
31 Motor imagery classification enhancement with concurrent
implementation of spatial filtration and modified
stockwell transform 793
Rohit Bose, Kaniska Samanta, Soumya Chatterjee,
Saugat Bhattacharyya and Anwesha Khasnobish
Introduction 793
Methodology 795
Description of electroencephalography signal datasets 795
Channel selection of electroencephalography based on types of
motor imagery tasks 797
Preprocessing: spatial filtration of raw electroencephalography signals 797
Stockwell transform and subsequent feature extraction 798
Classifiers 803
Results 806
Comparative performance analysis among different machine learning
classifiers 807
Performance analysis using least square-support vector machine 807
Discussions 809
Conclusions 812
References 813
Further reading 817
32 A hybrid wireless electroencephalography network based
on the IEEE 802.11 and IEEE 802.15.4 standards 819
Rabia Bilal and Bilal Muhammad Khan
Introduction 819
Background and evolution of electroencephalography 820
Advantages of wireless electroencephalography recorders 820
The IEEE standard wireless standards 821
IEEE 802.11 821
IEEE 802.15.4 822
Architecture and methodology 822
Simulation parameters 823
Results 824
Jitters 824
Medium access control delay 827
Throughput 830
Conclusion 831
References 831
33 Deep learning in medical and surgical instruments 833
Srivarna Settisara Janney and Sumit Chakravarty
Medical and surgical instruments 833
History 833
Concepts and categories of instruments 834
Types of equipment 834
Surgical instruments 835
Deep learning 836
What is deep learning? 836
Difference among artificial intelligence, machine learning, and
deep learning 837
Demo 838
Neural network and its architectures 840
Hardware and software 844
Deep learning in health care 844
Diagnosis in medical images and signals 845
Robotics surgery (autonomous) 846
Genome and bioinformatics 847
Drug discovery 847
Virtual visualization 847
Key papers in deep learning relevant to medical and surgical
instruments 849
Conclusion 853
References 854
34 Electroencephalogram-based brain<COMPUTER P interface<>
systems for controlling rehabilitative devices 859
Kishore K. Tarafdar, Bikash K. Pradhan, Suraj K. Nayak, Anwesha
Khasnobish, Saugat Bhattacharyya and Kunal Pal
Introduction 859
Motivation 863
Recording methods 864
Electroencephalogram signal analysis 867
Linear methods of electroencephalogram feature extraction 870
Nonlinear methods of electroencephalogram feature extraction 873
Brain<COMPUTER P interface 875< applications>
Brain<COMPUTER P 876< wheelchair interface-controlled>
Brain<COMPUTER P 877< environment home smart interface
Brain<COMPUTER P interface<controlled 879< movement limb robotic>
Conclusion 884
References 884
35 A system for automatic cardiac arrhythmia recognition using
electrocardiogram signal 893
Allam Jaya Prakash and Samit Ari
Introduction 893
Database 896
Theoretical background 896
Convolutional neural network 896
Random forest classifier 897
Proposed framework 899
Preprocessing 899
Electrocardiogram arrhythmia classification using convolutional
neural network 901
Electrocardiogram arrhythmia classification using dual-tree
complex wavelet transform and random forest 902
Experimental results 907
The performance of arrhythmia classification using convolutional
neural network 907
The performance of arrhythmia classification using dual-tree
complex wavelet transform-random forest method 908
Performance comparison of different methods for arrhythmia
classification 910
Conclusion 911
Acknowledgment 912
References 912
36 Designing of a biopotential amplifier for the acquisition and processing of subvocal electromyography signals 915
Reddy Vamsi, Suraj K. Nayak, Anilesh Dey, Arindam Bit,
Biswajit Mohapatra, Haladhar Behera and Kunal Pal
Introduction 915
Literature review 917
Materials and software 919
Methods 919
Designing of a subvocal electromyogram biopotential amplifier 919
Development of the printed circuit board 920
Acquisition of subvocal electromyogram signals 921
Processing and feature extraction of subvocal electromyogram signals 921
Statistical analysis and classification using ANN 922
Results and discussion 922
Development of a subvocal electromyogram biopotential amplifier 922
Acquisition and processing of subvocal electromyogram signals 924
Statistical analysis and classification using ANN 926
Conclusion 929
References 929
Index 933
Description
Bioelectronics and Medical Devices: From Materials to Devices-Fabrication, Applications and Reliability reviews the latest research on electronic devices used in the healthcare sector, from materials, to applications, including biosensors, rehabilitation devices, drug delivery devices, and devices based on wireless technology. This information is presented from the unique interdisciplinary perspective of the editors and contributors, all with materials science, biomedical engineering, physics, and chemistry backgrounds. Each applicable chapter includes a discussion of these devices, from materials and fabrication, to reliability and technology applications. Case studies, future research directions and recommendations for additional readings are also included.
The book addresses hot topics, such as the latest, state-of the-art biosensing devices that have the ability for early detection of life-threatening diseases, such as tuberculosis, HIV and cancer. It covers rehabilitation devices and advancements, such as the devices that could be utilized by advanced-stage ALS patients to improve their interactions with the environment. In addition, electronic controlled delivery systems are reviewed, including those that are based on artificial intelligences.
Key Features
- Presents the latest topics, including MEMS-based fabrication of biomedical sensors, Internet of Things, certification of medical and drug delivery devices, and electrical safety considerations
- Presents the interdisciplinary perspective of materials scientists, biomedical engineers, physicists and chemists on biomedical electronic devices
- Features systematic coverage in each chapter, including recent advancements in the field, case studies, future research directions, and recommendations for additional readings
Readership
Materials Scientists and Engineers, biomedical engineers, chemists, physicists, product designers
Details
- No. of pages:
- 1006
- Language:
- English
- Copyright:
- © Woodhead Publishing 2019
- Published:
- 18th June 2019
- Imprint:
- Woodhead Publishing
- Paperback ISBN:
- 9780081024201
- eBook ISBN:
- 9780081024218
Ratings and Reviews
About the Editors
Kunal Pal
Dr. Kunal Pal is Professor-in-Charge of the Medical Electronics and Instrumentation Laboratory, in the Department of Biotechnology and Medical Engineering, National Institute of Technology, Rourkela, India.
Affiliations and Expertise
Professor-in-Charge, Medical Electronics and Instrumentation Laboratory, Department of Biotechnology and Medical Engineering, National Institute of Technology, Rourkela, India
Heinz-Bernhard Kraatz
Dr. Kraatz studied chemistry at the Universities of Düsseldorf and the University of Kent in Canterbury and obtained his PhD in 1993 at the University of Calgary. In 2011, accepting a position at the University of Toronto, where he is a full professor in chemistry and currently serves as Vice-Principal Research at the University of Toronto Scarborough. He has served as Director of the Nanofabrication Facility at Western and as Chair of the Department of Physical and Environmental Sciences at U of T. Awards and recognitions include the Canada Research Chair in Biomaterials, the PetroCanada Young Innovator Award, the Award in Pure or Applied Inorganic Chemistry from the Canadian Society for Chemistry, and the Principal’s Research Award. Bernie’s research interests are at the interface of inorganic chemistry and electrochemistry, focusing on the design of bioconjugates for sensing applications, surface-supported functional bioconjugates, and bio(nano)materials. He has published more than 250 peer-reviewed papers and two books.
Affiliations and Expertise
Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada; Department of Chemistry, University of Toronto, Toronto, ON, Canada; Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, ON, Canada
Anwesha Khasnobish
Dr. Khasnobish is currently employed as a Research Scientist at TATA Consultancy Services (TCS) Innovation Lab, Kolkata, India, where she is actively doing research in cognitive neuroscience, tele-rehabilitation, stress analysis from physiological signals, electrooculography and eye tracking. She completed her graduation and post-graduation in Biomedical Engineering. She completed her Ph. D. in Engineering in the field of “Human- Computer interface based devices for biomedical applications” from Jadavpur University, Kolkata, India in the year 2015. She received fellowship from the Council of Scientific & Industrial Research, Government of India for completing her Ph.D. dissertation work. Her past research experience revolved around biopotential signal (e.g. EEG, HRV, EMG and EOG) acquisition and processing, brain and human computer interactions, circuit design and development, signal and image processing, haptics, somatosensory perceptions, computational intelligence and soft computing techniques. She has >40 research papers to her credit with a total citation of >140.
Affiliations and Expertise
Research and Innovation, TCS, Kolkata, India
Sandip Bag
Dr. Bag is presently an Assistant Professor and Head of the Department of the Department of Biomedical Engineering, JIS College of Engineering, Kalyani, West Bengal since 2005. Dr. Bag obtained his Ph.D. degree in Biomedical Engineering from Jadavpur University, Kolkata in the year 2007. He did his graduation in Pharmaceutical Technology and post- graduation in Biomedical Engineering from Jadavpur University during the year 2000 and 2002, respectively. He has published more than 24 research papers in various national and international journals and proceedings of conferences. He also presented his research accomplishments across the globe. He received various grants from Indian government funding agencies for carrying out research and travel for attending conferences. He is a reviewer and editorial board members of various international journals of repute. He was actively involved in organizing various national/ international conferences.
Affiliations and Expertise
Department of Biomedical Engineering, JIS College of Engineering, Kalyani, West Bengal
Indranil Banerjee
Prof. Indranil Banerjee did his Ph. D. in Biotechnology (Tissue Engineering) from Indian Institute of Technology Kharagpur, India in the year 2011. Presently, is holding the position of an Assistant Professor in the Department of Biotechnology and Medical Engineering at National Institute of Technology- Rourkela. He is the Professor-in-Charge of the Bioprocess Laboratory and Biomicrofludics Laboratory. His group is actively involved in understanding the cell physiology in response to biomaterials developed on a length scale (nano to macro). He was a visiting scientist in Maxplanck Institute of Intelligent System, Germany. Dr. Banerjee has authored 35 SCI cited publications in various journals of repute with a total citation of more than 450. He is also serving as industrial consultant.
Affiliations and Expertise
Department of Bioscience and Bioengineering, Indian Institute of Technology Jodhpur, Rajasthan, India
Usha Kuruganti
Dr. Kuruganti received the B.Sc. and M.Sc. degrees in electrical engineering and a Ph.D. degree in human factors engineering from the University of New Brunswick (UNB), Fredericton, NB, Canada. She joined UNB in 2004 and is currently a Professor in the Faculty of Kinesiology at UNB and Co-Director of the Andrew and Marjorie McCain Human Performance Laboratory within the Richard J. CURRIE Centre at UNB. Dr. Kuruganti has also served as the Assistant Dean (Graduate Studies and Research) of the Faculty of Kinesiology since September 2013. Dr. Kuruganti is a Registered Professional Engineer with the Association of Professional Engineers and Geoscientists (APEGNB), a Fellow of Engineers Canada, a member of the International Society of Electrophysiology and Kinesiology, and the Association of Canadian Ergonomists. Her research interests include human movement analysis, neuromuscular and occupational physiology, electromyography and human factors.
Affiliations and Expertise
University of New Brunswick (UNB), Fredericton, NB, Canada
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