Advancing wearable robotics through open-source innovation

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Credit: University of Twente

Researchers at the University of Twente have developed CEINMS-RT, an open-source platform designed to transform the field of wearable robotics.

This innovative framework enables real-time, neuro-mechanical model-based control for movement-assistive robots such as exoskeletons, exosuits, and bionic limbs, offering unprecedented potential for advancements in rehabilitation and human movement augmentation.

The project was led by Prof. Massimo Sartori, in collaboration with global academic institutions, including McGill University (Canada) and Griffith University (Australia). Their paper is posted on the TechRxiv preprint server.






CEINMS-RT is used to convert elbow muscle electrical signals into control commands for an elbow exosuit. Credit: University of Twente

CEINMS-RT (Calibrated EMG-informed Neuromusculoskeletal Modeling Software—Real-Time) is poised to address significant challenges in wearable robotics by bridging the gap between human intent and robotic actions. Traditional approaches often rely on proprietary systems or rigid, predefined control schemes, limiting adaptability and accessibility. CEINMS-RT offers a freely available, open-source alternative that empowers researchers and developers worldwide to harness the power of personalized, task-agnostic control strategies.

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CEINMS-RT is used to convert back muscle electrical signals into control commands for a back support exosuit. Credit: University of Twente

Advancing personalized and adaptive robotics

By leveraging real-time electromyography (EMG) data and biomechanical modeling, CEINMS-RT delivers precise estimates of muscle activation, muscle-tendon force, and joint dynamics. This level of detail facilitates the development of wearable robots that operate as natural extensions of the human body, adapting seamlessly to diverse tasks and movements.

The platform’s unique capabilities include:

  • Real-time neuro-mechanical modeling: Providing continuous, personalized data to inform robotic control in dynamic environments.
  • Open-source accessibility: Fostering global collaboration and standardization in neuromusculoskeletal modeling.
  • Task-agnostic control: Supporting several applications, from assisting mobility-impaired individuals to enhancing athletic performance.
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Neural control of bionic arms. CEINMS-RT is used to convert muscle electrical signals into prosthetic hand control commands. The video shows a trans-radial amputee controlling a bionic arm. Credit: University of Twente

Applications across domains

CEINMS-RT has already demonstrated its transformative potential in various scenarios. In clinical trials, patients with neurological impairments successfully regained volitional control of their limbs using robotic exoskeletons powered by the platform. In another instance, CEINMS-RT enabled real-time biofeedback for personalized rehabilitation, optimizing muscle and joint loading to prevent injuries and enhance recovery outcomes.

Moreover, the platform has been utilized to create adaptive control systems for back-support exosuits, reducing lumbar spine loads during heavy lifting tasks, and bionic limbs, allowing users to achieve natural and intuitive movement.






Neural control of bionic legs in a transtibial amputee. Credit: University of Twente

The development of CEINMS-RT marks a significant milestone in the evolution of wearable robotics. As an open-source initiative, it invites researchers, engineers, and clinicians to join a growing community dedicated to advancing human-machine interfaces. Future iterations aim to integrate enhanced capabilities, such as muscle fatigue modeling and joint stiffness estimation, further broadening its impact.

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More information:
Massimo Sartori et al, CEINMS-RT: an open-source framework for the continuous neuro-mechanical model-based control of wearable robots, TechRxiv (2024). DOI: 10.36227/techrxiv.173397962.28177284/v1

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Advancing wearable robotics through open-source innovation (2025, January 27)
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