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Bioelectronics and Medical Devices. Woodhead Publishing Series in Electronic and Optical Materials

  • ID: 4720814
  • Book
  • June 2019
  • 1006 Pages
  • Elsevier Science and Technology

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.

  • 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

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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


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

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


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

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

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

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


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

database 276

Experimental results for motor imagery brain

data set 279

Discussion and conclusion 280

References 281

12 Electromyogram-controlled assistive devices 285

Abdulhamit Subasi

Introduction 285

Literature review 288

Electromyogram 290


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

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

control to neurofeedback in rehabilitation 779

Saugat Bhattacharyya and Mitsuhiro Hayashibe

Introduction 779

Combining brain

stimulation 781


rehabilitation 783

Importance and types of brain

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

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





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
Note: Product cover images may vary from those shown
Pal, Dr. Kunal
Dr. Pal pursued his graduation in Pharmacy from University of Delhi, New Delhi, India in the year 2002 followed by post-graduation in Biomedical Engineering from Jadavpur University, Kolkata, India in the year 2004. Later, he did his Ph.D. in Materials Science from Indian Institute of Technology, Kharagpur, India in the year 2006. Subsequently, he joined Ryerson University, Toronto, Canada as a post-doctoral fellow in the year 2007. During his tenure at Ryerson University, he served as Vice-Chair (Elect), HQPA, AFMNet Network of Excellence, Canada. He joined National Institute of Technology, Rourkela, India in the year 2009 as an Assistant Professor in Biomedical Engineering. He is currently the Professor-in-Charge of Medical Electronics and Instrumentation Laboratory in the Department of Biotechnology and Medical Engineering, National Institute of technology, Rourkela, India. His major research interests revolve around Biomedical Signal Processing and Biomedical Equipment Design. He is also working in the fields of soft materials and controlled drug delivery. He has more than 140 publications in SCI cited journals of high repute, Book Chapters and peer-reviewed conferences. He is a very well cited researcher having more than 1800 citations.
Kraatz, Heinz-Bernhard
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.
Khasnobish, Anwesha
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.
Bag, Sandip
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.
Banerjee, Indranil
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.
Kuruganti, Usha
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.
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