Frequent hospital visits during facial paralysis rehabilitation strain medical resources and affect patient experience. Current home exercises are often ineffective and do not consider value creation from the patient’s perspective, nor do they utilize the vast amount of video data generated during the rehabilitation process. Additionally, current human-robot interaction rehabilitation methods either focus on technical implementation without addressing patient psychological needs or existing high costs and other issues affecting patient accessibility for widespread home use.
This study proposes an HRI and lean digital healthcare approach for facial paralysis, combining a wearable exoskeleton with a smartphone app for AR-assisted muscle training and assessment. Leveraging patients’ smartphones, the system is cost-effective, accessible, and enhances engagement through real-time feedback, supporting long-term home rehabilitation. It also utilizes video data for automated evaluation, laying the foundation for a lean digital healthcare to improve patient outcomes.
A two-week controlled trial of rehabilitation intervention found that the robot-assisted facial paralysis rehabilitation training presented in this study decreased the patients’ facial nerve function scores, possibly somewhat better than traditional rehabilitation training. It also significantly improved motor motivation and experience. The assessment model built using a substantial volume of face movement video outperforms current approaches.
This study innovatively integrates HRI and lean digital healthcare, focusing on value creation by offering a comprehensive and autonomous training solution. The extended intervention duration and diverse metrics demonstrate a significant advantage over earlier HCI or HRI-based facial paralysis training approaches, reinforcing the potential for further advancements in this field.
