Healthcare Systems Design of Intelligent Testing Centers
Latest Technologies to Battle Pandemics such as Covid-19
- 1st Edition - January 25, 2023
- Latest edition
- Authors: Tawanda Mushiri, Marvellous Moyo
- Language: English
Healthcare Systems Design of Intelligent Testing Centers: Latest Technologies to Battle Pandemics such as Covid-19 highlights the importance of designing intelligent testing center… Read more
Healthcare Systems Design of Intelligent Testing Centers: Latest Technologies to Battle Pandemics such as Covid-19 highlights the importance of designing intelligent testing centers requiring no human intervention during sample collection and testing of the Covid-19 virus and all similar viruses. This book introduces the background, medical requirements, and new research on medical robotics applications, including general Covid-19 testing techniques, development considerations for intelligent testing booths, kinematic and dynamic modeling, design specifications and optimization, numerical verifications, actuators, and sensors in medical applications of artificial intelligence and robotics systems.
- Demonstrates how to design an intelligent healthcare testing center from scratch
- Presents the basics of AI and robotics technology in healthcare testing
- Covers technical-economic evaluation of robotic systems, which is crucial for decision-makers in the field
Graduate students in Engineering, and Computer Science; Researchers or engineers working in robotics application domains. Practitioners in robotics application domains. Biomedical Engineers working in the medical device industry
Computer Science professionals; electricians, mechanical fitters, instrument technicians who help Engineers construct the designs
Computer Science professionals; electricians, mechanical fitters, instrument technicians who help Engineers construct the designs
Table of contents
List of figures
List of tables
List of abbreviations
Chapter 1: Introduction
1. ARTIFICIAL INTELLIGENCE AND ROBOTICS IN HEALTH CARE SYSTEMS
1.1. INTRODUCTION
1.2. BACKGROUND
1.2.1. The novel corona virus(covid-19)
1.2.2. Testing Covid-19 virus
1.3. MOTIVATION
1.3.1. Challenges at Sally Mugabe Central Hospital due to Covid-19 pandemic
1.3.2. Covid-19 effects around the World
1.4. PROBLEM STATEMENT
1.5. AIM
1.6. OBJECTIVES
1.6.1. Laws of robotics
1.7. JUSTIFICATION
1.7.1. Enhance human safety
1.7.2. Improve testing rate
1.7.3. Practical solution
1.7.4. Improved accuracy
1.8. RELATED STUDIES
1.8.1. Drone use during covid-19(International Transport Forum., 2020)
1.9. CONCLUSION
Chapter 2: Uses of Artificial Intelligence and Robotics in Healthcare Systems
2.A LITERATURE SURVEY ON THE USE OF ROBOTICS AND ARFICIAL INTELLIGENCE IN HEALTH CARE
2.1. INTRODUCTION
2.2. ROBOTICS PARTS AND COMPONENTS
2.3. MEDICAL ROBOT’S MANIPULATOR CONFIGURATIONS
2.3.1. Articulated or revolute geometry arm
2.3.2. Cartesian robots
2.3.3. Cylindrical robots
2.3.4. Polar robots
2.3.5. SCARA robots
2.4. END EFFECTOR DESIGN
2.4.1. Mechanical Grippers
2.5. ARTIFICIAL INTELLIGENCE AND ROBOTICS IN THE MEDICAL FIELD
2.5.1. Internet of Things (IoT)
2.5.2. Fuzzy Logic
2.5.3. Application of robots in the medical field
2.5.3.1. Robots for surgical precision
2.5.3.2. Handling repetitive tasks
2.5.3.3. Telemedicine
2.5.3.4. Disinfecting hospitals
2.5.3.5. Nanorobots swimming in blood
2.6. STEPS IN DESIGN AND DEVELOPMENT OF ROBOTS
2.6.1. Mechanical design
2.6.2. Electronics
2.6.3. Programming
2.6.4. Fabrication
2.7. POWER SUPPLY OF ROBOTS
2.7.1. Generator Systems
2.7.2. Batteries
2.7.3. Photovoltaic Cells
2.8. DEGREE OF AUTONOMY OF ROBOTS
2.9. ACTUATORS USED IN ROBOTICS
2.10. SENSORS USED IN MEDICAL ROBOTS
2.10.1. Force-torque sensors
2.11. CONCLUSION
Chapter 3
3. ROBOTIC MANIPULATOR COMPONENTS DESCRIPTION
3.1. INTRODUCTION
3.2. Materials and methods
3.2.1. Design process for the intelligent robotic machine
3.2.1.1. Concept generation and development
3.2.1.2. Concept selection
3.2.1.3. Detailed design of the selected concept
3.2.2. Tools for design & prototype testing
3.2.3. Project management
3.2.4. Project time frame
3.2.5. Deliverables
3.3. Possible solutions
3.3.1. Concept one
3.3.2. Concept two
3.3.3. Concept three
3.4. CONCEPT SELECTION
3.5. Drawing description
3.6. Conclusion
Chapter 4
4. A STUDY OF CURRENT COVID-19 TESTING TECHNIQUES IN HOSPITALS
4.1. Introduction and back ground
4.2. Covid-19: The global health emergency
4.2.1. Symptoms of Covid-19
4.2.2. Covid-19 causes and prevention
4.3. COVID-19 TESTING TECHNIQUES
4.3.1. Molecular Tests
4.3.1.1. Limitations of the molecular diagnostic test.
4.3.2. Serologic (Antibody) testing
4.3.2.1. Strengths and limitations of Antibody Tests
4.3.3. Antigen test
4.3.3.1. Working principle of the antigen test
4.3.3.2. Strengths and limitations of antigen test.
4.3.4. Summary of Covid-19 testing techniques
4.3.5. Importance of testing Covid-19
4.4. Materials and methods
4.5. Results and discussion
4.6. FEEDBACK FROM THE QUESTIONNAIRE
4.6.1. Discussion of the questionnaire results
4.7. Conclusion
Chapter 5
5. DESIGN OF AN INTELLIGENT COVID-19 TESTING CENTRE
5.1. Introduction
5.2. Literature review
5.2.1. Current Covid-19 testing machines
5.2.1.1. Abbott ID NOW
5.2.1.2. MIT Covid-19 testing trailer
5.3. Materials and methods
5.4. INTELLIGENT ROBOTIC MACHINE ARCHITECTURE AT THE ENTRANCE
5.4.1. Determining the anthropometry
5.5. Results and discussion
5.5.1. Design of the system architecture at the hospital entrance
5.5.1.1. Booth design
5.6. Conclusion
Chapter 6
6. USING ROBOTICS, ARTIFICIAL INTELLIGENCE AND DEEP LEARNING TO COLLECT COVID-19 SAMPLES
6.1. Introduction
6.2. Literature review
6.3. Materials and methods
6.3.1. Determination of the force exerted by the swab on the nasal passage.
6.3.2. Determination of the nostrils position
6.3.3. Determining how to align the swab with nostril opening
6.3.4. The testing process of the Intelligent robotic testing machine
6.3.5. Robotic manipulator control during sample collection
6.4. Results and discussion
6.4.1. Proposed web application
6.4.2. Design of the fuzzy logic controller
6.5. Conclusion
Chapter 7
7. VALIDATION OF THE KINEMATICS AND DYNAMICS MODELS OF A ROBOTIC MANIPULATOR USING THE ROBOTICS-TOOLBOX
7.1. Introduction and background
7.2. Literature review
7.2.1. Inverse dynamics
7.2.2. Forward dynamics
7.2.3. Equations of Motion
7.2.4. Dynamics Algorithms
7.2.4.1. Lagrange Euler formulation
7.2.4.2. Degrees of freedom
7.2.5. Forward Kinematics
7.2.6. Inverse Kinematics
7.2.7. Robotics toolbox
7.3. Materials and methods
7.3.1. Determining the DH parameters for the robotic arm
7.3.2. Determining the joint velocities
7.3.3. Determining the mass of each link
7.3.4. Determining the degrees of freedom of the robotic arm
7.4. Results and discussion
7.4.1.1. Kinematic modelling
7.4.1.1.1. Forward kinematics
7.4.1.1.2. Inverse kinematics
7.4.1.1.3. Robotic manipulator’s workspace
7.4.1.1.4. Numerical validation using Matlab robotic toolbox
7.4.1.1.4.1. Manipulator velocity
7.4.1.2. Dynamic modelling
7.4.1.2.1. Dynamics numerical solution
7.4.1.2.2. Motor sizing and selection
7.5. Recommendations and conclusion
Chapter 8
8. DESIGN OPTIMISATION OF A MEDICAL ROBOTIC MANIPULATOR USING FINITE ELEMENT ANALYSIS
8.1. Introduction
8.2. Literature review
8.3. Materials and methods
8.3.1. Structural loading
8.3.2. Static structural analysis
8.3.3. Modal analysis
8.3.4. Topology optimization
8.4. Results
8.4.1. Stress and displacement analysis
8.4.1.1. Base link static structural analysis results
8.4.1.2. Link 1 sub assembly 2 static structural analysis results
8.4.1.3. Link 2 sub assembly 1 static structural analysis results
8.4.1.4. Link 3 static structural analysis results
8.4.2. Modal analysis
8.4.3. Topology optimization
8.5. Discussion
8.6. Conclusion
Chapter 9
9. ECONOMIC ANALYSIS OF THE ROBOTIC TESTING MACHINE
9.1. THE BILL OF MATERIALS
References
List of figures
List of tables
List of abbreviations
Chapter 1: Introduction
1. ARTIFICIAL INTELLIGENCE AND ROBOTICS IN HEALTH CARE SYSTEMS
1.1. INTRODUCTION
1.2. BACKGROUND
1.2.1. The novel corona virus(covid-19)
1.2.2. Testing Covid-19 virus
1.3. MOTIVATION
1.3.1. Challenges at Sally Mugabe Central Hospital due to Covid-19 pandemic
1.3.2. Covid-19 effects around the World
1.4. PROBLEM STATEMENT
1.5. AIM
1.6. OBJECTIVES
1.6.1. Laws of robotics
1.7. JUSTIFICATION
1.7.1. Enhance human safety
1.7.2. Improve testing rate
1.7.3. Practical solution
1.7.4. Improved accuracy
1.8. RELATED STUDIES
1.8.1. Drone use during covid-19(International Transport Forum., 2020)
1.9. CONCLUSION
Chapter 2: Uses of Artificial Intelligence and Robotics in Healthcare Systems
2.A LITERATURE SURVEY ON THE USE OF ROBOTICS AND ARFICIAL INTELLIGENCE IN HEALTH CARE
2.1. INTRODUCTION
2.2. ROBOTICS PARTS AND COMPONENTS
2.3. MEDICAL ROBOT’S MANIPULATOR CONFIGURATIONS
2.3.1. Articulated or revolute geometry arm
2.3.2. Cartesian robots
2.3.3. Cylindrical robots
2.3.4. Polar robots
2.3.5. SCARA robots
2.4. END EFFECTOR DESIGN
2.4.1. Mechanical Grippers
2.5. ARTIFICIAL INTELLIGENCE AND ROBOTICS IN THE MEDICAL FIELD
2.5.1. Internet of Things (IoT)
2.5.2. Fuzzy Logic
2.5.3. Application of robots in the medical field
2.5.3.1. Robots for surgical precision
2.5.3.2. Handling repetitive tasks
2.5.3.3. Telemedicine
2.5.3.4. Disinfecting hospitals
2.5.3.5. Nanorobots swimming in blood
2.6. STEPS IN DESIGN AND DEVELOPMENT OF ROBOTS
2.6.1. Mechanical design
2.6.2. Electronics
2.6.3. Programming
2.6.4. Fabrication
2.7. POWER SUPPLY OF ROBOTS
2.7.1. Generator Systems
2.7.2. Batteries
2.7.3. Photovoltaic Cells
2.8. DEGREE OF AUTONOMY OF ROBOTS
2.9. ACTUATORS USED IN ROBOTICS
2.10. SENSORS USED IN MEDICAL ROBOTS
2.10.1. Force-torque sensors
2.11. CONCLUSION
Chapter 3
3. ROBOTIC MANIPULATOR COMPONENTS DESCRIPTION
3.1. INTRODUCTION
3.2. Materials and methods
3.2.1. Design process for the intelligent robotic machine
3.2.1.1. Concept generation and development
3.2.1.2. Concept selection
3.2.1.3. Detailed design of the selected concept
3.2.2. Tools for design & prototype testing
3.2.3. Project management
3.2.4. Project time frame
3.2.5. Deliverables
3.3. Possible solutions
3.3.1. Concept one
3.3.2. Concept two
3.3.3. Concept three
3.4. CONCEPT SELECTION
3.5. Drawing description
3.6. Conclusion
Chapter 4
4. A STUDY OF CURRENT COVID-19 TESTING TECHNIQUES IN HOSPITALS
4.1. Introduction and back ground
4.2. Covid-19: The global health emergency
4.2.1. Symptoms of Covid-19
4.2.2. Covid-19 causes and prevention
4.3. COVID-19 TESTING TECHNIQUES
4.3.1. Molecular Tests
4.3.1.1. Limitations of the molecular diagnostic test.
4.3.2. Serologic (Antibody) testing
4.3.2.1. Strengths and limitations of Antibody Tests
4.3.3. Antigen test
4.3.3.1. Working principle of the antigen test
4.3.3.2. Strengths and limitations of antigen test.
4.3.4. Summary of Covid-19 testing techniques
4.3.5. Importance of testing Covid-19
4.4. Materials and methods
4.5. Results and discussion
4.6. FEEDBACK FROM THE QUESTIONNAIRE
4.6.1. Discussion of the questionnaire results
4.7. Conclusion
Chapter 5
5. DESIGN OF AN INTELLIGENT COVID-19 TESTING CENTRE
5.1. Introduction
5.2. Literature review
5.2.1. Current Covid-19 testing machines
5.2.1.1. Abbott ID NOW
5.2.1.2. MIT Covid-19 testing trailer
5.3. Materials and methods
5.4. INTELLIGENT ROBOTIC MACHINE ARCHITECTURE AT THE ENTRANCE
5.4.1. Determining the anthropometry
5.5. Results and discussion
5.5.1. Design of the system architecture at the hospital entrance
5.5.1.1. Booth design
5.6. Conclusion
Chapter 6
6. USING ROBOTICS, ARTIFICIAL INTELLIGENCE AND DEEP LEARNING TO COLLECT COVID-19 SAMPLES
6.1. Introduction
6.2. Literature review
6.3. Materials and methods
6.3.1. Determination of the force exerted by the swab on the nasal passage.
6.3.2. Determination of the nostrils position
6.3.3. Determining how to align the swab with nostril opening
6.3.4. The testing process of the Intelligent robotic testing machine
6.3.5. Robotic manipulator control during sample collection
6.4. Results and discussion
6.4.1. Proposed web application
6.4.2. Design of the fuzzy logic controller
6.5. Conclusion
Chapter 7
7. VALIDATION OF THE KINEMATICS AND DYNAMICS MODELS OF A ROBOTIC MANIPULATOR USING THE ROBOTICS-TOOLBOX
7.1. Introduction and background
7.2. Literature review
7.2.1. Inverse dynamics
7.2.2. Forward dynamics
7.2.3. Equations of Motion
7.2.4. Dynamics Algorithms
7.2.4.1. Lagrange Euler formulation
7.2.4.2. Degrees of freedom
7.2.5. Forward Kinematics
7.2.6. Inverse Kinematics
7.2.7. Robotics toolbox
7.3. Materials and methods
7.3.1. Determining the DH parameters for the robotic arm
7.3.2. Determining the joint velocities
7.3.3. Determining the mass of each link
7.3.4. Determining the degrees of freedom of the robotic arm
7.4. Results and discussion
7.4.1.1. Kinematic modelling
7.4.1.1.1. Forward kinematics
7.4.1.1.2. Inverse kinematics
7.4.1.1.3. Robotic manipulator’s workspace
7.4.1.1.4. Numerical validation using Matlab robotic toolbox
7.4.1.1.4.1. Manipulator velocity
7.4.1.2. Dynamic modelling
7.4.1.2.1. Dynamics numerical solution
7.4.1.2.2. Motor sizing and selection
7.5. Recommendations and conclusion
Chapter 8
8. DESIGN OPTIMISATION OF A MEDICAL ROBOTIC MANIPULATOR USING FINITE ELEMENT ANALYSIS
8.1. Introduction
8.2. Literature review
8.3. Materials and methods
8.3.1. Structural loading
8.3.2. Static structural analysis
8.3.3. Modal analysis
8.3.4. Topology optimization
8.4. Results
8.4.1. Stress and displacement analysis
8.4.1.1. Base link static structural analysis results
8.4.1.2. Link 1 sub assembly 2 static structural analysis results
8.4.1.3. Link 2 sub assembly 1 static structural analysis results
8.4.1.4. Link 3 static structural analysis results
8.4.2. Modal analysis
8.4.3. Topology optimization
8.5. Discussion
8.6. Conclusion
Chapter 9
9. ECONOMIC ANALYSIS OF THE ROBOTIC TESTING MACHINE
9.1. THE BILL OF MATERIALS
References
- Edition: 1
- Latest edition
- Published: January 25, 2023
- Language: English
TM
Tawanda Mushiri
Tawanda Mushiri is an Executive Director—Technical (ED-Tech) at the Scienti c and Industrial Research and Development Centre (SIRDC) in, Harare, Zimbabwe and a Senior Research Associate in the Department of Sport and Movement Studies, Biomedical Engineering and Healthcare Technology (BEAHT) Research Centre, Faculty of Health Sciences, University of Johannesburg, South Africa. His research interests are in AI, robotics, biomedical engineering, medical physics, and healthcare systems design. He is a member of both the Zimbabwe Institute of Engineers and the Engineering Council of Zimbabwe.
Affiliations and expertise
Executive Director—Technical (ED-Tech), Scientific and Industrial Research and Development Centre (SIRDC), Harare, ZimbabweMM
Marvellous Moyo
Marvellous Moyo is a PhD candidate in the Department of Biomedical Engineering at the University of Twente, Enscede, the Netherlands. He possesses advanced skills in engineering design, 3D modeling, and simulation and specializes in the elds of robotics, AI, Health 4.0, biomedical engineering, and renewable energy.
Affiliations and expertise
University of Twente, Enschede, The NetherlandsRead Healthcare Systems Design of Intelligent Testing Centers on ScienceDirect