Оглавление
Группа авторов. Intelligent Systems for Rehabilitation Engineering
Table of Contents
Guide
List of Illustrations
List of Tables
Pages
Intelligent Systems for Rehabilitation Engineering
Preface
1. Different Spheres of Rehabilitation Robotics: A Brief Survey Over the Past Three Decades
1.1 Introduction
1.2 An Overview of Robotics for Medical Applications. 1.2.1 Neurological and Cognitive
1.2.2 Stroke Patients
1.2.3 Biomechanical or Mechatronic Robotic Systems
1.2.4 Human–Machine Interfacing
1.2.5 Smart Robotics
1.2.6 Control and Stability Analysis of Robotic Systems
1.2.7 Assistive Robotic Systems
1.2.8 Limb Injury
1.2.9 Motion Detection
1.3 Discussions and Future Scope of Work
1.4 Conclusion
References
2. Neurorehabilitation Robots Review: Towards a Mechanized Process for Upper Limb
2.1 Introduction
2.2 Recovery and the Robotics
2.2.1 Automated Technological Tools Used in Rehabilitation
2.2.1.1 Exoskeletal-Type RTT
2.2.1.2 End-Effector-Type RTT
2.2.2 Benefits of the RTTs
2.3 New Directions to Explore and Open Problems: Aims of the Editorial. 2.3.1 New Directions of Research and Development and First Aim of the Editorial
2.3.2 Open Problems and Second Aim of the Editorial
2.4 Overview
2.5 Renewal Process
2.5.1 Renovation Team
2.5.2 Renewal Methods and Results
2.6 Neurological Rehabilitation
2.6.1 Evaluation
2.6.2 Treatment Planning
2.6.3 Mediation
2.6.4 Assessment
2.7 State-of-the-Art Healthcare Equipment. 2.7.1 Neuro Renewal of Upper Limb
2.7.1.1 Things and Method. 2.7.1.1.1 Methods of Search
2.7.2 Advanced Equipment for Neuro Revival of the Upper Limb
2.7.2.1 Methods of Testing
2.7.2.2 Renewal Methods and Results
2.8 Towards Autonomous Restoration Processes?
2.8.1 Default Renewal Cycle
2.8.1.1 Computerized Testing Programs
2.8.1.2 Choice Support System
2.8.1.3 Mechanical Rehabilitation Systems
2.9 Conclusion
References
3. Competent and Affordable Rehabilitation Robots for Nervous System Disorders Powered with Dynamic CNN and HMM
3.1 Introduction
3.2 Related Works
3.2.1 Rehabilitation Robot for Lower Limbs
3.2.2 Rehabilitation Using Hip Bot
3.2.3 Rehabilitation Wrist Robot Using MRI Compatibility
3.2.4 Rehabilitation Robot for Gait Training
3.3 Solutions and Methods for the Rehabilitation Process
3.3.1 Gait Analysis
3.3.2 Methods Based on Deep Learning
3.3.3 Use of Convolutional Neural Networks
3.4 Proposed System
3.4.1 Detection of Motion and Rehabilitation Mechanism
3.4.2 Data Collection Using Wearable Sensors
3.4.3 Raspberry Pi
3.4.4 Pre-Processing of the Data
3.5 Analysis of the Data
3.5.1 Feature Extraction
3.5.2 Machine Learning Approach
3.5.3 Remote Rehabilitation Mode
3.6 Results and Discussion
3.7 Conclusion
References
4. Smart Sensors for Activity Recognition
4.1 Introduction
4.2 Wearable Biosensors for Activity Recognition
4.3 Smartphones for Activity Recognition
4.3.1 Early Analysis Activity Recognition
4.3.2 Similar Approaches Activity Recognition
4.3.3 Multi-Sensor Approaches Activity Recognition
4.3.4 Fitness Systems in Activity Recognition
4.3.5 Human–Computer Interaction Processes in Activity Recognition
4.3.6 Healthcare Monitoring in Activity Recognition
4.4 Machine Learning Techniques
4.4.1 Decision Trees Algorithms for Activity Reorganization
4.4.2 Adaptive Boost Algorithms for Activity Reorganization
4.4.3 Random Forest Algorithms for Activity Reorganization
4.4.4 Support Vector Machine (SVM) Algorithms for Activity Reorganization
4.5 Other Applications
4.6 Limitations
4.6.1 Policy Implications and Recommendations
4.7 Discussion
4.8 Conclusion
References
5. Use of Assistive Techniques for the Visually Impaired People
5.1 Introduction
5.2 Rehabilitation Procedure
5.3 Development of Applications for Visually Impaired
5.4 Academic Research and Development for Assisting Visually Impaired
5.5 Conclusion
References
6. IoT-Assisted Smart Device for Blind People
6.1 Introduction
6.1.1 A Convolutional Neural Network
6.1.2 CNN’s Operation
6.1.3 Recurrent Neural Network
6.1.4 Text-to-Speech Conversion
6.1.5 Long Short-Term Memory Network
6.2 Literature Survey
6.3 Smart Stick for Blind People
6.3.1 Hardware Requirements. 6.3.1.1 Ultrasonic Sensor
6.3.1.2 IR Sensor
6.3.1.3 Image Sensor
6.3.1.4 Water Detector
6.3.1.5 Global System for Mobile Communication
6.3.1.6 Microcontroller Based on the Raspberry Pi 3
6.4 System Development Requirements. 6.4.1 Captioning of Images
6.4.2 YOLO (You Only Look Once) Model
6.5 Features of the Proposed Smart Stick
6.6 Code
6.7 Results
6.8 Conclusion
References
7. Accessibility in Disability: Revolutionizing Mobile Technology
7.1 Introduction
7.2 Existing Accessibility Features for Mobile App and Devices
7.2.1 Basic Accessibility Features and Services for Visually Impaired
7.2.2 Basic Accessibility Features and Services for Deaf
7.2.3 Basic Accessibility Features and Services for Cognitive Disabilities
7.2.4 Basic Accessibility Features and Services for Physically Disabled
7.3 Services Offered by Wireless Service Provider
7.3.1 Digital Libraries for Visual
7.3.2 GPS
7.3.3 Relay Services
7.3.4 Living With Independent
7.3.5 Emergency Phone Services
7.3.6 Customer Service
7.4 Mobile Apps for People With Disabilities
7.5 Technology Giants Providing Services
7.5.1 Japan: NTT DoCoMo
7.6 Challenges and Opportunities for Technology Giants to Provide Product & Service
7.6.1 Higher Illiteracy Rate
7.6.2 Reach out to Customers With Disabilities
7.6.3 Higher Cost of Mobile Phones With Accessibility Features
7.6.4 Increasing Percentage of Disability
7.6.5 Unavailability of Assistive Technology in Regional Languages
7.6.6 Lack of Knowledge Concerning Assistive Solutions
7.7 Good Practices for Spreading Awareness
7.8 Conclusion
References
8. Smart Solar Power–Assisted Wheelchairs For the Handicapped
8.1 Introduction
8.2 Power Source
8.2.1 Solar-Powered Wheelchair
8.2.2 Solar Energy Module
8.3 Smart EMG-Based Wheelchair Control System
8.3.1 Techniques of EMG Signal Collection
8.3.2 Pre-Possessing and Segmentation of EMG Signal
8.3.3 Feature Extraction and Pattern Classification
8.3.3.1 Linear Discriminant Analysis (LDA)
8.3.3.2 Support Vector Machine (SVM)
8.3.3.3 Neural Network (NN)
8.3.3.4 Random Forest (RF)
8.4 Smart Navigation Assistance
8.5 Internet of Things (IoT)–Enabled Monitoring
8.6 Future Advancements in Smart Wheelchairs
References
9. Hand-Talk Assistance: An Application for Hearing and Speech Impaired People
9.1 Introduction
9.1.1 Sign Language
9.1.1.1 American Sign Language (ASL)
9.1.1.2 Comparison of ASL With Verbal Language
9.1.2 Recognition of Hand Gesture
9.1.3 Different Techniques for Sign Language Detection
9.1.3.1 Glove-Based Systems
9.1.3.2 Vision-Based Systems
9.2 Related Work
9.3 History and Motivation
9.4 Types of Sensors
9.4.1 Flex Sensor
9.4.1.1 Flex Sensor’s Specification
9.4.1.2 Flex Sensor Types
9.4.1.2.1 Conductive Ink-Based
9.4.1.2.2 Fiber Optic
9.4.1.2.3 Conductive Fabric or Thread or Polymer-Based Sensor Flexible fabric sensors and cord-based or polymer-based flexion sensors usually consist of double layer material with some opposing material (e.g., Velostat) in between. It is mainly wrapped in heavy layers of material, e.g., Neoprene. By bending or directly, if the pressure is applied, then the two layers of moving substance are pushed together and the sensory resistance decreases. This feeling is similar to strong emotional states. In fact, these types of nerves are pressure sensors that feel deviant, bending the sensor on a part of a solid structure causes the expansion of the nerve to the pressure of the nerve. This is a measure of pressure. Foam/polymer sensors reduce their resistance to name as the material is pressed. These nerves are characterized by abnormalities, recurrence, and hysteresis [19]
9.4.1.2.4 Arduino Microcontroller
9.4.1.2.4.1 Power
9.4.1.2.4.2 Memory
9.4.1.2.4.3 Installation and Removal
9.4.1.2.4.4 Communication
9.5 Working of Glove
9.5.1 Hand Gloves
9.5.2 Implementation Details at Server Side. 9.5.2.1 Training Mode
9.5.2.2 Detection Mode
9.5.2.3 Text to Speech
9.6 Architecture
9.7 Advantages and Applications
References
10. The Effective Practice of Assistive Technology to Boom Total Communication Among Children With Hearing Impairment in Inclusive Classroom Settings
10.1 Introduction
10.2 Students With Hearing Impairment
10.3 The Classifications on Hearing Impairment
10.3.1 Conductive Hearing Losses
10.3.2 Sensorineural Hearing Losses
10.3.3 Central Hearing Losses
10.3.4 Mixed Hearing Losses
10.4 Inclusion of Hearing-Impaired Students in Inclusive Classrooms
10.4.1 Assistive Technology
10.4.2 Assistive Technology for Hearing Impairments
10.4.3 Hearing Technology
10.4.4 Assistive Listening Devices
10.4.5 Personal Amplification
10.4.6 Communication Supports
10.5 Total Communication System for Hearing Impairments
10.6 Conclusion
References
Index
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