Moving Towards Everlasting Artificial Intelligent Battery-Powered Implants presents the development process of new artificial intelligent 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 artificial intelligent (AI) medical implants industry. Researchers, engineers, and graduate students in the fields 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.
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 Sensors
6. Cardiovascular Disease Prediction Using Machine Learning Models and Ensemble Technique
7. Improve Disease Prediction Using Deep Learning Approach
8. Boosting P6 Medicine aAnd Its Ethical Considerations
9. Development and Validation of a Biomodified Fuel Cell Using Matlab
10. Thermoelectric And Biomodified Fuel Cell Hybrid Power Generation
11. Alternative Road to Commercialisation of Medical Implants Designs: A Case for a New AI Pacemaker
12. Risk Assesment of an AI Charging System for Medical Implants
13. Lifetime Cost and Economic Analysis of an AI Charging System for Medical Implants
14. Future and Way Forward of an AI Charging System for Medical Battery Powered Implants
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. Tawanda Mushiri is an Executive DirectorTechnical (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.
