Design and Implementation of an Ontology-Driven Cyber–Physical Prosthesis Service System for Personalised and Adaptive Care
Source abstract
Abstract
As prosthetic technologies become increasingly data-rich and embedded in care systems, traditional human-centred approaches often fall short of addressing evolving use realities. This paper contributes an applied computing framework that enables semantic reasoning and data-driven adaptation within prosthesis aftercare. We present an ontology-driven, cyber–physical prosthesis service system designed to enable personalised and adaptive care. Implemented through the Adaptive Prosthesis Life-Cycle Service System (adProLiSS) framework and demonstrated via a smart prosthesis prototype, the system treats the prosthesis as a semi-autonomous actor within an emotionally responsive and semantically mediated ecosystem. The proposed architecture integrates sensor data acquisition, ontology-based knowledge representation, and semantic reasoning to enable context-aware decision support and adaptive personalisation. A layered cyber–physical infrastructure, comprising embedded sensors, semantic reasoning, and user feedback through a digital twin interface, supports personalised aftercare, cross-disciplinary collaboration, and reflective design engagement. Evaluation with 26 participants across clinical, engineering, and user groups confirmed the system’s value in enhancing functionality, reducing downtime, and supporting emotional well-being. By positioning ontologies as both computational enablers and design support mechanisms, this research contributes a practical and scalable model for prosthetic service systems that adapt across bodily, emotional, and ecological dimensions, advancing more responsive and consequence-aware care practices.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Prosthetics and Rehabilitation Robotics · Muscle activation and electromyography studies · Context-Aware Activity Recognition Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Industrial & Manufacturing Engineering, Faculty of Engineering, University of Malta, 2080 MSD Msida, Malta
Department of Podiatry, Faculty of Health Sciences, University of Malta, 2080 MSD Msida, Malta
Department of Microelectronics & Nanoelectronics, Faculty of Information & Communication, University of Malta, 2080 MSD Msida, Malta
Funding
FUSION R&I Technology Development Programme LITE, Xjenza Malta
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