The future of medical and assistive device prescriptions: Artificial Intelligence-guided personalised device prescriptions for improved clinical outcomes and adherence

In current pedorthic practice, the design of personalised devices (such as orthopedic footwear, foot orthotics, ankle-foot orthoses, etc.) is often overlooked, which impacts patients’ adherence and eventually results in poor clinical outcomes. Such outcomes can lead to lower limb amputation, which might cause permanent disability or even death. This study aims to explore the potential of artificial intelligence to guide personalised medical and assistive device prescriptions, solving the problem of generic medical and assistive device prescriptions that do not consider individual patient preferences and lifestyle and intended activity (such as outdoor, indoor, or occupational use). By leveraging machine learning algorithms to analyse patient data, the system will create a personalised medical and assistive device prescription plan that considers individual patient needs, which will be further validated in industry settings. The study will contribute to enhancing healthcare efficiency and accessibility by providing a valuable tool for medical professionals to make evidence-based decisions and reduce the time and resources required to create personalised medical and assistive device prescription plans.