Moving Towards Everlasting Artificial Intelligent Battery-Powered Implants

Erscheinungsjahr 2024
ISBN: 978-0-443-24830-6
Verlag: Elsevier Science

Buch, Englisch, 420 Seiten, Format (B × H): 188 mm x 234 mm, Gewicht: 798 g

Moving Towards Everlasting Artificial Intelligent Battery-Powered Implants presents the development process of new artificial intelligent (AI) charging systems for battery-powered implants that can last for a lifetime after implantation. This book introduces new strategies to address the limitations of technologies that have been employed to improve the lifespan of medical implants. This book also provides guidelines that medical implant manufacturers can adopt during their product development stages-this adds a new dimension of research on medical device implants that can be a game changer for the AI medical implants industry. Researchers, engineers, and graduate students in the elds of biomedical engineering, electrical engineering, and computer science will find this text helpful as they seek to understand the potential of AI systems to help achieve sustainability in healthcare and make current medical implants relevant in the future.

Autoren/Hrsg.

Moyo, Marvellous

Mushiri, Tawanda

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie

Inhaltsverzeichnis

1. Artificial Intelligence and Medical Devices Implants
2. Trends in Pacemaker Technology: A Literature Survey
3. Power Technologies of Cardiac Pacemakers
4. Materials And Modelling of an Artificial Intelligent Charging System for a Cardiac Pacemaker
5. Modelling of an In Vivo Electrochemical Biosense
6. Cardiovascular Disease Prediction Using Machine Learning Models and Ensemble Technique
7. Improved Disease Prediction Using Deep Learning
8. Boosting P6 Medicine and Its Ethical Considerations
9. Development and Validation of a Biomodified Fuel Cell Using MATLAB
10. In Vivo Thermoelectrical Generator Design for Medical Implants Applications
11. Alternative Road to Commercialization of Medical Implants Designs: A Case for a New AI Pacemaker
12. Risk Assessment of an AI Charging System for Medical Implants
13. Life Cycle, Economic, and Viability Analysis of an AI Charging System for Medical Implants
14. Future and Way Forward of an AI Charging System for Medical Battery Powered Implants

Über Autor(innen)

Mushiri, Tawanda
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.

Moyo, Marvellous
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.