Advances in materials and actuation strategies for wearable medical robotics: optimization for biomedical applications
The human musculoskeletal system, refined over millions of years of evolution, enables highly adaptive and efficient movement. However, aging, neuromuscular disorders, and physical injuries can severely impair mobility, necessitating advanced assistive technologies. While conventional approaches such as surgery, rehabilitation training, and pharmacological treatments remain widely used, they are often costly, time-intensive, and associated with potential risks. Wearable robotics has emerged as a promising alternative, offering personalized movement assistance, rehabilitation support, and mobility augmentation. Early wearable robots, particularly rigid exoskeletons, demonstrated potential in assisting movement but were hindered by excessive weight, mechanical rigidity, and misalignment with natural biomechanics, limiting their practicality. Recent advancements in flexible wearable robotics, leveraging Bowden cable transmissions and thermoplastic polyurethane-based actuators, have sought to overcome these challenges. However, critical limitations—including low torque output, energy inefficiency, and challenges in actuator integration—remain significant barriers to widespread adoption. This review provides a comprehensive analysis of recent advancements in biomechanical modeling, flexible actuator technologies, and simulation-driven optimization methods for wearable medical robotics. It highlights the need for a unified theoretical framework to improve design efficiency, control adaptability, and real-time human–robot interaction. This review uniquely integrates biomechanical modeling with optimization strategies, offering a holistic approach to enhance wearable robotics for medical applications. Addressing these challenges could enable wearable robotics to evolve into highly efficient, intelligent, and seamlessly integrated assistive systems, transforming rehabilitation, industrial support, and human augmentation.
Authors
- Jing Fang (ORCID: https://orcid.org/0000-0002-0778-2979)
- Yue Li (ORCID: https://orcid.org/0000-0003-3728-218X)
- Lei Shi (ORCID: https://orcid.org/0000-0002-1968-9704)
Institutions
- Kennesaw State University (US)
- Dalian Maritime University (CN)
Publication Details
- Journal
- MedMat.
- Published
- 2025-09-29
- DOI
- https://doi.org/10.1097/mm9.0000000000000027
- Primary Topic
- Advanced Sensor and Energy Harvesting Materials
- Type
- article
- Field-Weighted Citation Impact
- 0.00