University of Twente: revolutionising wearable robotics through open source innovation

Researchers at the UT led by Prof. Massimo Sartori, in collaboration with global academic institutions including McGill University (Canada) and Griffith University (Australia), have announced the release of CEINMS-RT, a groundbreaking 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.

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 personalised, task-agnostic control strategies.

CEINMS-RT graphical user interface: The figures show EMG signals from the tibialis anterior muscles (tib_ant_r) used to drive a musculoskeletal model (i.e., the skeleton avatar on the right-hand window), which in turn estimates biological ankle moments (bottom graph) in real-time. Estimated biological moments are used to control bionic limbs and exoskeletons.

Advancing personalised and adaptive robotics 

By leveraging real-time electromyography (EMG) data and biomechanical modelling, 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 modelling: Providing continuous, personalised data to inform robotic control in dynamic environments.
Open-source accessibility: Fostering global collaboration and standardisation in neuromusculoskeletal modelling.
Task-agnostic control: Supporting several applications, from assisting mobility-impaired individuals to enhancing athletic performance.

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 personalised rehabilitation, optimising muscle and joint loading to prevent injuries and enhance recovery outcomes. Moreover, the platform has been utilised 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.

A Vision for the Future 

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 modelling and joint stiffness estimation, further broadening its impact.

This article was first published on 27 January by University of Twente.