Emerging Technologies in Robot-aided Therapy with Microsoft Azure for Telerehabilitation

Research Objectives: This study will evaluate the effectiveness of robot-aided therapy (RAT) systems enhanced by Microsoft Azure, focusing on how interactive telerehabilitation impacts patient engagement, motivation, and therapeutic outcomes. It will also explore real-time monitoring and adaptive interventions to improve the precision of remote rehabilitation services and extend these services to underserved populations through advanced technologies and cloud computing.

Design: Experimental study.

Setting: In the BioRobotics Laboratory.

Participants: The study engaged two healthy human subjects (age 22 - 32), selected to initially evaluate the robotic system and its integration with Microsoft Azure for telerehabilitation. These participants represented a controlled group to test the system's functionality and effectiveness in delivering interactive rehabilitation exercises before broader application to diverse patient demographics with actual rehabilitation needs.

Interventions: The intervention featured a sophisticated telerehabilitation system combining a 3DoF robotic arm with Microsoft Azure for improved real-time data processing and responsiveness. Participants interacted through a mixed-reality interface using Unity and HoloLens 2, enabling precise control of the robot within a virtual environment. Digital twin technology mirrored the robot's actions for accurate therapy delivery, while Azure IoT managed data flows, adapting the system dynamically to each participant's engagement and performance during exercises.

Main Outcome Measures: The primary outcomes of this study evaluated the effectiveness of integrating robot-aided therapy with Microsoft Azure for telerehabilitation, focusing on real-time monitoring and precise data visualization. Participant feedback and activity metrics assessed therapeutic engagement and motivation, while ease of technology use highlighted patient accessibility. User satisfaction was gauged through surveys and feedback, reflecting the overall experience and perceived effectiveness of the therapy.

Results: The results showed that the telerehabilitation system effectively enabled remote rehabilitation through a dual-site setup, with a therapist's control panel and a patient's interaction space. Live therapy sessions via Microsoft Teams allowed therapists to monitor and visualize robot movements in real time, enhancing patient engagement in upper limb exercises. This real-time interaction facilitated various tailored rehabilitation exercises, indicating that the system significantly improves the capacity for precise and personalized remote rehabilitation. Initial findings highlight its potential for broader telerehabilitation applications.

Conclusions: The benefits of integrating robot-aided therapy (RAT) with Microsoft Azure for the telerehabilitation approach significantly enhance the accessibility, personalization, and engagement of rehabilitative care, demonstrating its potential to extend services to underserved populations effectively. Utilizing advanced AI and cloud computing allows for therapy tailored to individual needs, potentially revolutionizing patient care and extending services to underserved populations.

Author(s) Disclosures: The authors declare that they have no conflict of interest.