News Release

Precision assistance, transparent existence: Toward an ideal shoulder exoskeleton for robotic rehabilitation

Reports and Proceedings

The University of Electro-Communications

Fig. 1  Concept of 'transparency' in human-assistive rehabilitation robots

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Fig. 1  Concept of 'transparency' in human-assistive rehabilitation robots: (a) Conventional robot: The robot's inherent dynamics constrain the user's movement. (b) Conventional transparency concept: The interaction force between the robot and the user is zero, suggesting no physical assistance. (c) Proposed transparency concept for essential human assistance: Despite the presence of an interaction force indicating assistance, the robot's inherent dynamics do not constrain the user's movement. This transparency is crucial for patients with moderate to severe impairments who may not be able to move independently; in such cases, the proposed interaction force provides necessary assistance without restricting movement.

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Credit: Dr. Yoshihiro Nakata, the University of Electro-Communications

A research group led by Senior Researcher Tomoyuki Noda from the Brain Information Communication Research Laboratory Group at the Advanced Telecommunications Research Institute International, Japan, and Associate Professor Yoshihiro Nakata from the University of Electro-Communications, Japan, collaborated on a project aimed at advancing rehabilitation robotics. Their research focuses on improving the mechanical transparency of robots during assistance. This research was presented at the 2024 IEEE International Conference on Robotics and Automation, highlighting its significance in the field of robotics.

The term 'transparency,' in this context, refers to mechanical transparency, not color transparency. The shoulder actuation testbed for rehabilitation, a product of this research, embodies the 'Transparent Existence' concept (Fig. 1), seamlessly integrating into simulated rehabilitation scenarios where its presence is barely noticeable. It is designed to maintain interaction forces without disrupting movements during disturbances, striking an ideal balance between assistance and transparency. This design principle makes the rehabilitation experience as natural as possible. The testbed, which utilizes a fusion hybrid linear actuator (The paper on this actuator, published in the IEEE/ASME Transactions on Mechatronics, has been selected as a finalist for the 2024 Best Transaction Paper Award. doi: 10.1109/TMECH.2023.3237725) that combines pneumatic and electromagnetic forces, this testbed (Fig. 2) achieves a high level of precision in force application and control. It maintains precise joint torque, which is crucial for rehabilitation, even under disturbances such as user movement (Fig. 3). The system has ability to maintain joint torque accurately also implies the capability to sustain the constant interaction force with the user. By effectively simulating the conditions that patients may face in real-world environments, the testbed allows for the development of safer and more efficient rehabilitation protocols.

Building on the results of this study, the research team plans to develop a rehabilitation exoskeleton robot and conduct clinical trials to assess its effectiveness and safety. This initiative aims to translate laboratory findings into practical applications tailored to individual patients' rehabilitation needs. While the current focus is on refining and testing these technologies within Japan, there is potential for future applications and collaborations internationally, which could enhance the quality and accessibility of rehabilitation services on a broader scale, albeit this aspect remains more tentative at this stage.

 

Key contributors include:

Takuma Shimoyama (Master student at the University of Electro-Communications)(*1)

Tatsuya Teramae (Researcher, Advanced Telecommunications Research Institute International)

 

(*1) Award:

Takuma Shimoyama, the first author of this paper presented at the 2024 IEEE International Conference on Robotics and Automation, has received the 2024 IEEE Robotics and Automation Society Japan Joint Chapter Young Award for this paper.

 


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