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In the medical field, the use of artificial intelligence (AI) has demonstrated its importance in improving disease diagnosis, patient monitoring and treatment. AI can help medical staff deliver quality care by harnessing large quantities of clinical data. Integrating AI into medical procedures can improve the accessibility to healthcare for everyone, save time for medical personnel, and help them making better-informed data-driven decisions. To be fully operational, AI may be deployed in tools such as robots to perform various tasks.
In recent years, robots have been widely used to help hospitals meet the challenges they face, including staff shortages, improving quality of care and combating patient isolation. During the COVID-19 pandemic, the use of robots was stepped up to help reduce the spread of the virus by reducing direct contact between medical staff and patients 1. Alongside these use cases, we also note the presence of elderly care robots, which have been developed to help provide daily care for the elderly. In addition, the healthcare landscape also includes surgery assistant robots, transportation robots and so forth.
According to the European Council 2, 27% of the EU population over the age of 16 had some form of disability. Recent advances in robotics and AI offer hope for a brighter and healthier future for people with disabilities, providing them high quality and personalized care. The use of a robot with natural language processing or NLP (a subset of AI that leverages machine learning to enable computers to understand and communicate with human language) to enable interaction between the robot and young children with disabilities to provide personalized care and support is an example of these advances
Despite recent advances in robotics and AI in healthcare, various challenges need to be addressed to facilitate the full adoption of robots in healthcare, particularly for young children with disabilities. These challenges include acceptability, reliability and security.
Acceptability
In the context of healthcare, robot acceptance can be defined as the willingness of medical staff, patients and other stakeholders to adopt and integrate robotic technologies into medical practices, treatments and care environments. Like any technology, if robotics is not accepted by its users, its usage will be inevitably declined, regardless of its capabilities. The robot’s ease of use and behavior, combined with a non-intimidating appearance, will contribute significantly to its acceptance by users. Given these three parameters, considerable research effort has been devoted to improving the acceptability of robots to their users (e.g. medical staff and patients). Acceptance of robots in the healthcare sector is key to the successful uptake of robotics innovation to enhance patients’ outcome.
Reliability
The reliability of AI-driven robots in healthcare is a key factor in determining their effectiveness and overall acceptability. Indeed, due to their advantages, these cutting-edge solutions are used for critical tasks such as disease diagnosis, patient care and surgery. For these tasks, where a minor error can lead to irreversible consequences, it is essential to guarantee reliability. This requires operations such as testing, real-time monitoring and safety mechanisms to ensure the operational integrity of the AI-driven robot in the healthcare environment. In addition, as these solutions can be used to make decisions in situations where complex judgments are required, the AI model must be comprehensible to developers, users and regulators.
Security
In the healthcare sector, AI-driven robots are often used to perform critical tasks (e.g. disease diagnosis and surgery). During this process, sensitive data are used to help deliver personalized care to patients. However, since confidential data is involved in the care delivery process, robust cybersecurity must be guaranteed. To achieve this, strong encryption protocols, secure communications and regular security updates are needed to protect these systems from data breaches, hacking and malware.
Summary
The adoption of an AI-driven robot in a healthcare environment could be beneficial for young children with disabilities, as they can help monitor the condition of patients and combat social isolation. Furthermore, these robots can also help medical staff to deliver tailored care.
Recently, SogetiLabs launched an R&D project called “Medibot” in collaboration with a French hospital to propose an AI-driven robot that will address the aforementioned challenges.
