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Intelligent systems for rehabilitation engineering / edited by Roshani Raut [and three others].
- Format:
- Book
- Language:
- English
- Subjects (All):
- Rehabilitation technology.
- Robotics in medicine.
- Artificial intelligence--Medical applications.
- Artificial intelligence.
- Physical Description:
- 1 online resource (265 pages)
- Edition:
- 1st edition.
- Place of Publication:
- Hoboken, NJ : John Wiley & Sons, Inc., 2022.
- Summary:
- 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.
- Contents:
- Cover
- Half-Title Page
- Series Page
- Title Page
- Copyright Page
- Contents
- 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 RobotsReview: 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
- 2.2.2 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
- 2.7.2 Advanced Equipment for Neuro Revival of the Upper Limb
- 2.8 Towards Autonomous Restoration Processes?
- 2.8.1 Default Renewal Cycle
- 2.9 Conclusion
- 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
- 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
- 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
- 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
- 6.4 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
- 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
- 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
- 8.4 Smart Navigation Assistance
- 8.5 Internet of Things (IoT)-Enabled Monitoring
- 8.6 Future Advancements in Smart Wheelchairs
- 9 Hand-Talk Assistance: An Applicationfor Hearing and Speech Impaired People
- 9.1 Introduction
- 9.1.1 Sign Language
- 9.1.2 Recognition of Hand Gesture
- 9.1.3 Different Techniques for Sign Language Detection
- 9.2 Related Work
- 9.3 History and Motivation
- 9.4 Types of Sensors
- 9.4.1 Flex Sensor
- 9.5 Working of Glove
- 9.5.1 Hand Gloves
- 9.5.2 Implementation Details at Server Side
- 9.6 Architecture
- 9.7 Advantages and Applications
- 10 The Effective Practice of AssistiveTechnology to Boom Total Communication Among ChildrenWith Hearing Impairment inInclusive 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 HearingImpairments
- 10.6 Conclusion
- Index
- EULA.
- Notes:
- Description based on print version record.
- Other Format:
- Print version: Raut, Roshani Intelligent Systems for Rehabilitation Engineering
- ISBN:
- 9781119785651
- 1119785650
- 9781119785637
- 1119785634
- 9781119785644
- 1119785642
- OCLC:
- 1291315547
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