Biomedical Engineering Tools for Management of Patients with COVID-19 presents biomedical engineering tools under research (and in development) that can be used for the management of COVID-19 patients, along with BME tools in the global environment that curtail and prevent the spread of the virus. BME tools covered in the book include new disinfectants and sterilization equipment, testing devices for rapid and accurate COVID-19 diagnosis, Internet of Things applications in COVID-19 hospitals, analytics, Data Science and statistical modeling applied to COVID-19 tracking, Smart City instruments and applications, and more. Later sections discuss smart tools in telemedicine and e-health.
Biomedical engineering tools can provide engineers, computer scientists, clinicians and other policymakers with solutions for managing patient treatment, applying data analysis techniques, and applying tools to help the general population curtail spread of the virus.
1. Cover - p. iii 2. Title page - p. iii 3. Copyright - p. iv 4. Table of Contents - p. iv 5. List of contributors - p. ix 6. Chapter 1 A review: novel coronavirus (COVID-19): an evidence-based approach - p. 1 7. Chapter 2 State-of-the-art equipment for rapid and accurate diagnosis of COVID-19 - p. 19 8. Chapter 3 Radiotherapy challenges in COVID era - p. 41 9. Chapter 4 In-person versus virtual activities: Assessing the usefulness and impact of simulated experiments, a case study - p. 73 10. Chapter 5 Coronavirus disease COVID-19 tracking the global outbreak. SEIR compartmental model applied to SARS-CoV-2 epidemic in Romania - p. 87 11. Chapter 6 ROI extraction in CT lung images of COVID-19 using Fast Fuzzy C means clustering - p. 103 12. Chapter 7 Smart equipment to protect patients and people from COVID disease - p. 121 13. Chapter 8 The role of physical activities for patients infected with SARS-CoV-2 after convalescence period - p. 135 14. Chapter 9 Physiotherapeutic management for patients with Covid-19 - p. 149 15. Chapter 10 Daily confirmed cases and deaths prediction of novel coronavirus in Asian continent Polynomial Neural Network - p. 163 16. Chapter 11 Smart sensing systems for in-home health status and emotional well-being monitoring during COVID-19 - p. 173 17. Chapter 12 Methods of prophylaxis and control for young people during COVID-19 period - p. 187 18. Index - p. 201
Biomedical Engineering Tools for Management of Patients with COVID-19 presents biomedical engineering tools under research (and in development) that can be used for the management of COVID-19 patients, along with BME tools in the global environment that curtail and prevent the spread of the virus. BME tools covered in the book include new disinfectants and sterilization equipment, testing devices for rapid and accurate COVID-19 diagnosis, Internet of Things applications in COVID-19 hospitals, analytics, Data Science and statistical modeling applied to COVID-19 tracking, Smart City instruments and applications, and more. Later sections discuss smart tools in telemedicine and e-health.
Biomedical engineering tools can provide engineers, computer scientists, clinicians and other policymakers with solutions for managing patient treatment, applying data analysis techniques, and applying tools to help the general population curtail spread of the virus.
1. Cover - p. iii 2. Title page - p. iii 3. Copyright - p. iv 4. Table of Contents - p. iv 5. List of contributors - p. ix 6. Chapter 1 A review: novel coronavirus (COVID-19): an evidence-based approach - p. 1 7. Chapter 2 State-of-the-art equipment for rapid and accurate diagnosis of COVID-19 - p. 19 8. Chapter 3 Radiotherapy challenges in COVID era - p. 41 9. Chapter 4 In-person versus virtual activities: Assessing the usefulness and impact of simulated experiments, a case study - p. 73 10. Chapter 5 Coronavirus disease COVID-19 tracking the global outbreak. SEIR compartmental model applied to SARS-CoV-2 epidemic in Romania - p. 87 11. Chapter 6 ROI extraction in CT lung images of COVID-19 using Fast Fuzzy C means clustering - p. 103 12. Chapter 7 Smart equipment to protect patients and people from COVID disease - p. 121 13. Chapter 8 The role of physical activities for patients infected with SARS-CoV-2 after convalescence period - p. 135 14. Chapter 9 Physiotherapeutic management for patients with Covid-19 - p. 149 15. Chapter 10 Daily confirmed cases and deaths prediction of novel coronavirus in Asian continent Polynomial Neural Network - p. 163 16. Chapter 11 Smart sensing systems for in-home health status and emotional well-being monitoring during COVID-19 - p. 173 17. Chapter 12 Methods of prophylaxis and control for young people during COVID-19 period - p. 187 18. Index - p. 201
