The use case will focus on robots used for the assessment of patients’ walking abilities, assessing the various ethical, social and legal challenges raised by human-machine interaction in terms of verbal and physical interaction, psychological relationship, and data management.
In the current context where chronic illnesses and population aging are growing in an unprecedented way, the demand for rehabilitation services is higher than ever. An effective rehabilitation plan must be intensive, repetitive and supervised by trained professionals. However, this growing demand cannot be adequately addressed given the low number of clinicians and caregivers, both in and (especially) out of the clinical environment. A robotic platform offers the potential of delivering high intensity and repetitive therapy, while providing a reliable and reproducible way to measure improvements in performance and promoting the patient’s engagement and motivation.
The robot explains the test to perform, navigating the environment to indicate the salient points set out for the test, and interacts verbally with the patient to reply to potential questions. The interaction between humans and humanoid robots poses various ethical and social challenges that require careful monitoring of verbal communication, physical interaction and psychological relationship. This last aspect is paramount when the robot interacts with patients and people with some deficiency, disease or other medical condition. In addition, the robot capabilities to evaluate patients’ improvements and to learn, tailor and adapt their therapies raise concerns about the robustness, fairness, security and transparency of the system that governs those capabilities.
This use case will therefore explore, using the ETAPAS framework, a wide spectrum of social impacts from beneficial ones such as faster recovery, healthcare cost optimisation, to potential negative effects such as better treatment to privileged groups, as well as the legal aspects related to the acquisition and management of sensitive data which are related to the identity of the subjects and their health status.