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E-raamat: Intelligent Systems for Rehabilitation Engineering

Edited by (LBEF Campus, Kathmandu Nepal), Edited by (Visveswaraya National Institute of Technology, Nagpur, India), Edited by (Pune University, India), Edited by (Bapuji Institute of Engineering and Technology, Karnataka, India)
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 05-Jan-2022
  • Kirjastus: Wiley-Scrivener
  • Keel: eng
  • ISBN-13: 9781119785637
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Intelligent Systems for Rehabilitation EngineeringSuurem pilt
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 05-Jan-2022
  • Kirjastus: Wiley-Scrivener
  • Keel: eng
  • ISBN-13: 9781119785637
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INTELLIGENT SYSTEMS FOR REHABILITATION ENGINEERING Encapsulates different case studies where technology can be used as assistive technology for the physically challenged, visually and hearing impaired.

Rehabilitation engineering includes the development of technological solutions and devices to assist individuals with disabilities, while also supporting the recovery of the disabled who have lost their physical and cognitive functions. These systems can be designed and built to meet a wide range of needs that can help individuals with mobility, communication, vision, hearing, and cognition. The growing technological developments in machine learning, deep learning, robotics, virtual intelligence, etc., play an important role in rehabilitation engineering.

Intelligent Systems for Rehabilitation Engineering focuses on trending research of intelligent systems in rehabilitation engineering which involves the design and development of innovative technologies and techniques including rehabilitation robotics, visual rehabilitation, physical prosthetics, brain computer interfaces, sensory rehabilitation, motion rehabilitation, etc.

This groundbreaking book





Provides a comprehensive reference covering different computer assistive techniques for the physically disabled, visually and hearing impaired. Focuses on trending research of intelligent systems in rehabilitation engineering which involves the design and development of innovative technologies and techniques. Provides insights into the role of intelligent systems in rehabilitation engineering.

Audience

Engineers and device manufacturers working in rehabilitation engineering as well as researchers in computer science, artificial intelligence, electronic engineering, who are working on intelligent systems.
Preface xiii
1 Different Spheres of Rehabilitation Robotics: A Brief Survey Over the Past Three Decades
1(18)
Saumyadip Hazra
Abhimanyu Kumar
Yashonidhi Srivastava
Souvik Ganguli
1.1 Introduction
1(2)
1.2 An Overview of Robotics for Medical Applications
3(7)
1.2.1 Neurological and Cognitive
3(1)
1.2.2 Stroke Patients
3(1)
1.2.3 Biomechanical or Mechatronic Robotic Systems
4(1)
1.2.4 Human-Machine Interfacing
5(1)
1.2.5 Smart Robotics
5(2)
1.2.6 Control and Stability Analysis of Robotic Systems
7(2)
1.2.7 Assistive Robotic Systems
9(1)
1.2.8 Limb Injury
9(1)
1.2.9 Motion Detection
9(1)
1.3 Discussions and Future Scope of Work
10(2)
1.4 Conclusion
12(7)
References
12(7)
2 Neurorehabilitation Robots Review: Towards a Mechanized Process for Upper Limb
19(38)
Yogini Dilip Borole
Roshani Raut
2.1 Introduction
19(4)
2.2 Recovery and the Robotics
23(3)
2.2.1 Automated Technological Tools Used in Rehabilitation
24(1)
2.2.1.1 Exoskeletal-Type RTT
24(1)
2.2.1.2 End-Effector-Type RTT
25(1)
2.2.2 Benefits of the RTTs
25(1)
2.3 New Directions to Explore and Open Problems: Aims of the Editorial
26(2)
2.3.1 New Directions of Research and Development and First Aim of the Editorial
26(1)
2.3.2 Open Problems and Second Aim of the Editorial
27(1)
2.4 Overview
28(1)
2.5 Renewal Process
29(2)
2.5.1 Renovation Team
30(1)
2.5.2 Renewal Methods and Results
30(1)
2.6 Neurological Rehabilitation
31(4)
2.6.1 Evaluation
31(2)
2.6.2 Treatment Planning
33(1)
2.6.3 Mediation
34(1)
2.6.4 Assessment
34(1)
2.7 State-of-the-Art Healthcare Equipment
35(4)
2.7.1 Neuro Renewal of Upper Limb
35(1)
2.7.1.1 Things and Method
35(1)
2.7.2 Advanced Equipment for Neuro Revival of the Upper Limb
35(2)
2.7.2.1 Methods of Testing
37(1)
2.7.2.2 Renewal Methods and Results
38(1)
2.8 Towards Autonomous Restoration Processes?
39(7)
2.8.1 Default Renewal Cycle
40(2)
2.8.1.1 Computerized Testing Programs
42(1)
2.8.1.2 Choice Support System
43(2)
2.8.1.3 Mechanical Rehabilitation Systems
45(1)
2.9 Conclusion
46(11)
References
47(10)
3 Competent and Affordable Rehabilitation Robots for Nervous System Disorders Powered with Dynamic CNN and HMM
57(38)
Sundaresan Sabapathy
Surendar Maruthu
Suresh Kumar Krishnadhas
Ananth Kumar Tamilarasan
Nishanth Raghavan
3.1 Introduction
58(1)
3.2 Related Works
59(4)
3.2.1 Rehabilitation Robot for Lower Limbs
59(1)
3.2.2 Rehabilitation Using Hip Bot
60(1)
3.2.3 Rehabilitation Wrist Robot Using MRI Compatibility
61(1)
3.2.4 Rehabilitation Robot for Gait Training
62(1)
3.3 Solutions and Methods for the Rehabilitation Process
63(2)
3.3.1 Gait Analysis
63(1)
3.3.2 Methods Based on Deep Learning
64(1)
3.3.3 Use of Convolutional Neural Networks
64(1)
3.4 Proposed System
65(4)
3.4.1 Detection of Motion and Rehabilitation Mechanism
66(2)
3.4.2 Data Collection Using Wearable Sensors
68(1)
3.4.3 Raspberry Pi
68(1)
3.4.4 Pre-Processing of the Data
68(1)
3.5 Analysis of the Data
69(3)
3.5.1 Feature Extraction
69(1)
3.5.2 Machine Learning Approach
70(1)
3.5.3 Remote Rehabilitation Mode
71(1)
3.6 Results and Discussion
72(18)
3.7 Conclusion
90(5)
References
90(5)
4 Smart Sensors for Activity Recognition
95(20)
Rehab A. Rayan
Imran Zafar
Aamna Rafique
Christos Tsagkaris
4.1 Introduction
95(3)
4.2 Wearable Biosensors for Activity Recognition
98(2)
4.3 Smartphones for Activity Recognition
100(5)
4.3.1 Early Analysis Activity Recognition
101(1)
4.3.2 Similar Approaches Activity Recognition
101(1)
4.3.3 Multi-Sensor Approaches Activity Recognition
102(1)
4.3.4 Fitness Systems in Activity Recognition
103(1)
4.3.5 Human-Computer Interaction Processes in Activity Recognition
104(1)
4.3.6 Healthcare Monitoring in Activity Recognition
104(1)
4.4 Machine Learning Techniques
105(2)
4.4.1 Decision Trees Algorithms for Activity Reorganization
106(1)
4.4.2 Adaptive Boost Algorithms for Activity Reorganization
106(1)
4.4.3 Random Forest Algorithms for Activity Reorganization
106(1)
4.4.4 Support Vector Machine (SVM) Algorithms for Activity Reorganization
106(1)
4.5 Other Applications
107(1)
4.6 Limitations
108(1)
4.6.1 Policy Implications and Recommendations
109(1)
4.7 Discussion
109(1)
4.8 Conclusion
110(5)
References
110(5)
5 Use of Assistive Techniques for the Visually Impaired People
115(14)
Anuja Jadhav
Hirkani Padwad
M.B. Chandak
Roshani Raut
5.1 Introduction
115(2)
5.2 Rehabilitation Procedure
117(4)
5.3 Development of Applications for Visually Impaired
121(2)
5.4 Academic Research and Development for Assisting Visually Impaired
123(2)
5.5 Conclusion
125(4)
References
125(4)
6 IoT-Assisted Smart Device for Blind People
129(22)
Roshani Raut
Anuja Jadhav
Swati Jaiswal
Pranav Pathak
6.1 Introduction
129(9)
6.1.1 A Convolutional Neural Network
130(1)
6.1.2 CNN's Operation
131(3)
6.1.3 Recurrent Neural Network
134(1)
6.1.4 Text-to-Speech Conversion
134(1)
6.1.5 Long Short-Term Memory Network
134(4)
6.2 Literature Survey
138(1)
6.3 Smart Stick for Blind People
138(5)
6.3.1 Hardware Requirements
140(1)
6.3.1.1 Ultrasonic Sensor
140(1)
6.3.1.2 IR Sensor
141(1)
6.3.1.3 Image Sensor
141(1)
6.3.1.4 Water Detector
141(1)
6.3.1.5 Global System for Mobile Communication
142(1)
6.3.1.6 Microcontroller Based on the Raspberry Pi 3
142(1)
6.4 System Development Requirements
143(2)
6.4.1 Captioning of Images
143(1)
6.4.2 YOLO (You Only Look Once) Model
143(2)
6.5 Features of the Proposed Smart Stick
145(1)
6.6 Code
146(1)
6.7 Results
147(1)
6.8 Conclusion
147(4)
References
148(3)
7 Accessibility in Disability: Revolutionizing Mobile Technology
151(24)
Nisarg Gandhewar
Senthilkumar Mohan
7.1 Introduction
152(1)
7.2 Existing Accessibility Features for Mobile App and Devices
153(7)
7.2.1 Basic Accessibility Features and Services for Visually Impaired
154(1)
7.2.2 Basic Accessibility Features and Services for Deaf
155(3)
7.2.3 Basic Accessibility Features and Services for Cognitive Disabilities
158(1)
7.2.4 Basic Accessibility Features and Services for Physically Disabled
159(1)
7.3 Services Offered by Wireless Service Provider
160(2)
7.3.1 Digital Libraries for Visual
161(1)
7.3.2 GPS
161(1)
7.3.3 Relay Services
162(1)
7.3.4 Living With Independent
162(1)
7.3.5 Emergency Phone Services
162(1)
7.3.6 Customer Service
162(1)
7.4 Mobile Apps for a Person With Disability
162(4)
7.5 Technology Giants Providing Services
166(3)
7.5.1 Japan: NTT DoCoMo
169(1)
7.6 Challenges and Opportunities for Technology Giants to Provide Product & Service
169(2)
7.6.1 Higher Illiteracy Rate
169(1)
7.6.2 Reach out to Customers With Disabilities
170(1)
7.6.3 Higher Cost of Mobile Phones With Accessibility Features
170(1)
7.6.4 Increasing Percentage of Disability
170(1)
7.6.5 Unavailability of Assistive Technology in Regional Languages
170(1)
7.6.6 Lack of Knowledge Concerning Assistive Solutions
171(1)
7.7 Good Practices for Spreading Awareness
171(1)
7.8 Conclusion
172(3)
References
172(3)
8 Smart Solar Power-Assisted Wheelchairs For the Handicapped
175(22)
Abhinav Bhatnagar
Sidharth Pancholi
Vijay Janyani
8.1 Introduction
176(2)
8.2 Power Source
178(4)
8.2.1 Solar-Powered Wheelchair
179(1)
8.2.2 Solar Energy Module
180(2)
8.3 Smart EMG-Based Wheelchair Control System
182(7)
8.3.1 Techniques of EMG Signal Collection
184(1)
8.3.2 Pre-Possessing and Segmentation of EMG Signal
185(1)
8.3.3 Feature Extraction and Pattern Classification
186(2)
8.3.3.1 Linear Discriminant Analysis (LDA)
188(1)
8.3.3.2 Support Vector Machine (SVM)
188(1)
8.3.3.3 Neural Network (NN)
189(1)
8.3.3.4 Random Forest (RF)
189(1)
8.4 Smart Navigation Assistance
189(1)
8.5 Internet of Things (IoT)-Enabled Monitoring
190(1)
8.6 Future Advancements in Smart Wheelchairs
191(6)
References
192(5)
9 Hand-Talk Assistance: An Application for Hearing and Speech Impaired People
197(26)
Pradnya Borkar
Vijaya Balpande
Ujjwala Aher
Roshani Raut
9.1 Introduction
198(5)
9.1.1 Sign Language
199(1)
9.1.1.1 American Sign Language (ASL)
199(1)
9.1.1.2 Comparison of ASL With Verbal Language
199(3)
9.1.2 Recognition of Hand Gesture
202(1)
9.1.3 Different Techniques for Sign Language Detection
202(1)
9.1.3.1 Glove-Based Systems
202(1)
9.1.3.2 Vision-Based Systems
202(1)
9.2 Related Work
203(1)
9.3 History and Motivation
204(1)
9.4 Types of Sensors
205(8)
9.4.1 Flex Sensor
205(1)
9.4.1.1 Flex Sensor's Specification
205(1)
9.4.1.2 Flex Sensor Types
206(7)
9.5 Working of Glove
213(3)
9.5.1 Hand Gloves
213(1)
9.5.2 Implementation Details at Server Side
214(1)
9.5.2.1 Training Mode
214(1)
9.5.2.2 Detection Mode
215(1)
9.5.2.3 Text to Speech
215(1)
9.6 Architecture
216(4)
9.7 Advantages and Applications
220(3)
References
221(2)
10 The Effective Practice of Assistive Technology to Boom Total Communication Among Children With Hearing Impairment in Inclusive Classroom Settings
223(13)
Fr. Baiju Thomas
10.1 Introduction
224(1)
10.2 Students With Hearing Impairment
225(1)
10.3 The Classifications on Hearing Impairment
226(3)
10.3.1 Conductive Hearing Losses
226(1)
10.3.2 Sensorineural Hearing Losses
227(1)
10.3.3 Central Hearing Losses
227(1)
10.3.4 Mixed Hearing Losses
227(2)
10.4 Inclusion of Hearing-Impaired Students in Inclusive Classrooms
229(4)
10.4.1 Assistive Technology
229(1)
10.4.2 Assistive Technology for Hearing Impairments
230(1)
10.4.3 Hearing Technology
231(1)
10.4.4 Assistive Listening Devices
231(1)
10.4.5 Personal Amplification
232(1)
10.4.6 Communication Supports
233(1)
10.5 Total Communication System for Hearing Impairments
233(3)
10.6 Conclusion
236(1)
References 236(3)
Index 239
Roshani Raut, PhD is an associate professor in the Department of Information Technology at Pimpri Chinchwad College of Engineering, Pune University, India. She has presented and published more than 70 research communications in national/ international conferences and journals and has published 13 patents.

Pranav D. Pathak, PhD from Visveswaraya National Institute of Technology, Nagpur, India. He is currently an assistant professor at MIT School of Bioengineering Sciences & Research, Pune.

Sandeep Kautish, PhD in Computer Science on Intelligent Systems in Social Networks is Professor & Dean of Academics with LBEF Campus, Kathmandu Nepal. He has published more than 40 papers in international journals.

Pradeep N., PhD is an associate professor in Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Karnataka, India. He has a number of edited books and journal research articles to his credit.
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