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Details of Grant 

EPSRC Reference: EP/X028631/1
Title: ATRACT: A Trustworthy Robotic Autonomous system to support Casualty Triage
Principal Investigator: Behera, Professor A
Other Investigators:
Lee, Professor P De Silva, Dr VD Saeed, Dr K
Researcher Co-Investigators:
Project Partners:
University Hospitals Birmingham NHS FT
Department: Computer Science
Organisation: Edge Hill University
Scheme: Standard Research
Starts: 09 January 2023 Ends: 08 January 2026 Value (£): 869,031
EPSRC Research Topic Classifications:
Artificial Intelligence Image & Vision Computing
Robotics & Autonomy
EPSRC Industrial Sector Classifications:
Aerospace, Defence and Marine Healthcare
Related Grants:
Panel History:
Panel DatePanel NameOutcome
01 Jan 3000 National Security Sandpit 1 Full Proposal Announced
Summary on Grant Application Form
In the Vietnam War, American evacuation helicopters transformed soldier survivability with the emergence of the 'Golden Hour'. This relied on air superiority and relative freedom of movement and has been the UK/US/NATO approach to battlefield casualty treatment since. However, recent proliferation and effectiveness of low-cost, accurate, shoulder-launched ground-to-air missiles has significantly disrupted helicopter operations in Ukraine and thus, presenting a heightened risk to Casualty Evacuation (CASEVAC) operations. Moreover, frontline army doctors work in world's most harsh and hostile environments, and often risk their lives while marching out and stepping in when they are needed near fighting forces. They are often required to monitor multiple casualties at a given time and prioritise whom they should be attending first based on the severity of injuries. Thus, there is an urgent unmet need for enhancing casualty survival in a contested environment where conventional helicopter CASEVAC is slow or unavailable.

Recent advancement in Artificial Intelligence (AI) and Robotic Autonomous System (RAS) provides new and future opportunities to meet this challenge. In line with this, the proposed ATRACT system is a disruptive innovation to address this unmet need in a novel way by designing, developing and field-testing a trustworthy drone-driven RAS to help frontline medics in decision-making in the first 'platinum ten minutes' following trauma. ATRACT will adopt an interdisciplinary and transformative research approach focusing on: 1) accurate search and localisation of injured soldiers using advanced manoeuvring of a drone in difficult terrains, 2) a novel platform that combines advanced multimodal sensing, beyond state-of-the-art algorithms for a robotic system to detect frontline soldiers, 3) real-time monitoring of their injury severity and vital signs for effective triage prediction/update, and 4) where medical emergency response team is available, real-time casualty information to the enroute medical team as it approaches, enabling more effective crew resource management and casualty prioritisation, thereby reducing time on the ground to maximise survivability and to minimise risk of the frontline medics being attacked.

AI and RAS are the driving forces in many industries (e.g., manufacturing, agriculture, transport, healthcare, etc.) and helping to address some of the most pressing issues facing humankind. Many such technologies have a major limitation of trustworthiness (technically robust, ethically adherent and lawful) and mainly because they typically use a "black box" approach, where AI elements are often less visible and transparent in the way data is used and operationalised from multiple sources, and frequently exhibits unconscious biases resulting in lack of control in decision-making. Moreover, they do not provide contextualised services or customised interventions to changing conditions and/or environmental settings. ATRACT will address these limitations via design and development processes which comply with the latest ethical and legal MoD AI standards, and military medical practice, incorporating principles from the WHO Surgical Checklist to align medical considerations with data quality, bias avoidance and system reliability factors. We will ensure that ATRACT is transparent, consistent and interpretable so that potential bias, legal and medical compliance, and MoD ethics can be addressed systematically at every stage of design, development and testing with expert-in-the-loop. Successful results in this context will revolutionise the way frontline health services, casualty evacuation and the delivery of emergency and lifesaving medical aid is delivered, resulting in significant health, social and economic benefits.

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