Proceedings Article | 14 May 2019
KEYWORDS: Data modeling, Medicine, Surgery, Machine learning, Telecommunications, Virtual reality, Artificial intelligence, Injuries, Evolutionary algorithms
Providing advanced healthcare to the warfighters in the battlefield has proven challenging due to the difficult environmental conditions and geographical separation between the injured warrior and healthcare providers. The introduction of Cyber Medicine enables physicians and soldiers to utilize technologies including mobile apps, robotics, connectivity to wired/wireless networks, satellites, clouds, HPCs, and software to identify, assess and treat the injured. However, what happens when the adversary attacks the cyber domain in addition to the physical domain? The answer could be that all automated systems will become suspect whether they are embedded systems, information processing systems, diagnosis and triage systems, or remote surgical robotics. This analysis identifies areas where the intelligent Cyber-Medical System can provide better healthcare to the battlefield including services to the disadvantaged soldier at the edge. Architecting intelligent systems starts with learning the desired system operation, sifting through historical data and procedure outcomes, assessing vulnerabilities, then delivering systems that mimics and augment human performance to solve problems. The battlefield Cybermedicine has the challenge of increased cyber security risks due to the need to be deployed in hostile environment, and the challenge of dealing with injuries that are unique to the battlefield. Moreover, the viability of intelligent automation depends on reliable connectivity and availability of reliable data and infrastructure, while the battlefield lacks both those conditions. The goal of this study is to deliver medical services and alleviate the vulnerability impacts through more secure design, development, deployment, maintenance, and operations. Additionally, this paper introduces new cybermedicine concepts and architectures that benefit from the various types of Machine Learning and Artificial Intelligence to build Cyber-Medical System that can resist corruption from unauthenticated users/data, and from active malware and physical media attacks.