TUM develops exoskeleton-FES system to aid stroke recovery in arm and hand mobility.
Researchers at the Technical University of Munich (TUM) have developed a modular exoskeleton system that integrates control loops, motion control, and robotics to support movement recovery in paralyzed arms and hands following a stroke. The approach combines functional electrical stimulation (FES) of forearm muscles with mechanical assistance through an exoskeleton. It has been tested with 24 stroke patients at the Schön Klinik Bad Aibling.
Researchers at the Technical University of Munich (TUM) have developed a modular exoskeleton system that intrates control loops, motion control, and robotics to support movement recovery in paralyzed arms and hands following a stroke. An image from the TUM YouTube video shows Dr. Satoshi Endo, senior researcher, TUM, working with a patient, in a TUM video at https://youtube.com/watch?v=OboVMCkM9Yk Courtesy: Technical University of Munich (TUM).
The researchers use FES to activate specific muscles in the forearm, enabling finger movement and object manipulation. Since post-stroke paralysis often extends beyond the hand to include the arm and shoulder, a support structure is also used to assist the full range of arm motion.
Modular system with computer game: independent training
Twenty-four stroke patients have tested the system, which combines an exoskeleton for the arm and shoulder with FES, as part of the ReHyb research project. Half of the patients were treated at the Schön Klinik Bad Aibling Harthausen, which is leading the study. The researchers also incorporated a computer-based task that adapts to each user’s motor abilities. It helps train grip and arm movement by having users respond to moving colored targets and direct them to matching areas on a screen.
Core elements: neuromuscular digital twin, optimized FES parameters, and arm exoskeleton
The system developed by TUM Professor Sandra Hirche uses a digital twin to model patient-specific movement parameters within a control framework. Researchers assess each patient’s ability to move their arm and hand to tailor support. Stroke-related paralysis often stems from damage to the motor cortex, though the degree of signal impairment between the brain and forearm muscles can be difficult to determine in advance.
“Individual muscle strands in the forearm can be stimulated to the right extent for hands and fingers to move,” says Prof. Hirche, who holds the Chair of Information-Oriented Control at TUM. Along with forearm muscle activity data, researchers determine the required stimulation intensity to coordinate with exoskeleton support. “We use algorithms to bring this individual information together in a control loop,” says the control engineering expert. The digital twin enables personalized assistance for arm and hand movement.
Schön Klinik: modular system as a home trainer
Prof. Hirche uses the term “intention-controlled intelligent control” to describe how the technology enables patients to initiate and guide their own movements during rehabilitation following a stroke. Carmen Krewer, team lead of the research group at the Schön Klinik cooperation partner in Bad Aibling, said: “Such a modular system with electrical stimulation and exoskeleton has never existed. It also enables stroke sufferers to continue training at home without the support of others.”
Features of the digital twin
- Muscle activity recording: A stroke can impair the musculoskeletal system, motor function and neuromuscular pathways to different extents. Measuring muscle electrical voltage helps assess nerve damage affecting signal transmission between the brain and muscles involved in finger and hand movement.
- Forearm muscle stimulation: For functional electrical stimulation (FES), a film with 32 electrodes is attached to the forearm. Fingers movement is determined by the specific electrodes activated, causing the hand to open or close. The activation threshold for finger and hand movement can be set individually.
- Exoskeleton support: The exoskeleton supports arm and shoulder movement through spring mechanism or actuators, compensating for stroke-related muscle weakness. It also addresses the difficulty of electrode placement on the shoulder by facilitating muscle activation. The system aids in practicing coordinated upper limb movements.
Glove is based on the same principle as the “Exoglove”
A study involving a glove exoskeleton worn by healthy participants demonstrates the feasibility of integrating FES with mechanical assistance in hybrid system. Developed by Prof Lorenzo Masia, Director of the Munich Institute of Robotics and Machine Intelligence (MIRMI) at TUM, the system increased finger mobility at least twofold compared to purely electrical stimulation alone, and up to threefold for the thumb.
Edited by Puja Mitra, WTWH Media, for Control Engineering, from a Technical University of Munich news release.
