Greater independence as our goal
Research as our foundation
Research
Our research in numbers
publications
citations in total
research funding raised
The total covers all grants for the underlying research. This includes GRASPAGAIN’s start-up funding from EXIST research transfer and the Medical Valley Award.
Research
Number of our heroes
Patients who have taken part in our research in recent years.
Scientific foundations
Research in Action
Videos from the research and development of GRASPAGAIN.
MyoGestic - Real-time control
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Our neural interface allows people with lived experience to control up to four different gestures in real-time using the forearm muscles of their paralyzed hand.
Proportional Control of a Soft Cable-Driven Exoskeleton via a Myoelectrical Interface
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Early Proof-of-Concept of our cable-driven neuroorthosis with an EMG-based control interface.
IEEE TNSRE | Control of a Robotic Sixth-Finger in Tetraplegia
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D. S. d. Oliveira et al., "Spared Motor Neurons Enable Control of a Robotic Sixth Finger for Functional Grasping in Tetraplegia," in IEEE Transactions on Neural Systems and Rehabilitation Engineering, doi: 10.1109/TNSRE.2026.3732031.
Scientific foundations
Publications
Peer-reviewed research on the science and technology behind GRASPAGAIN.
ADJUHand - A Passive Anthropomorphic Hand Model with Adjustable Finger Stiffness for Exoskeleton Evaluation
Nico G. M. Weber, Sebastian Dietz, Jonas Walter, et al.2026 IEEE/SICE International Symposium on System Integration (SII)
Spared Motor Neurons Enable Control of a Robotic Sixth Finger for Functional Grasping in Tetraplegia
Daniela Souza de Oliveira, Dominik I. Braun, Maria Pozzi, et al.IEEE Transactions on Neural Systems and Rehabilitation Engineering
Non-Invasive Neural Interfacing for Tetraplegic Individuals Using Residual Motor Neuron Activity Decoded at the Forearm or Wrist
Xingchen Yang, Daniela Souza de Oliveira, Dominik I. Braun, et al.IEEE Journal of Biomedical and Health Informatics
Hand paralysis after spinal cord injury leaves residual motor unit activity that can be decoded from surface EMG to infer finger motion intent, even u…
MyoGestic: EMG interfacing framework for decoding multiple spared motor dimensions in individuals with neural lesions
Raul C. Sîmpetru, Dominik I. Braun, Arndt U. Simon, et al.Science Advances
We present MyoGestic, an open-source framework for real-time EMG-based hand gesture decoding that enables individuals with spinal cord injuries to con…
A direct spinal cord–computer interface enables the control of the paralysed hand in spinal cord injury
Daniela S. Oliveira, Matthias Ponfick, Dominik I. Braun, et al.Brain
We demonstrate the first direct spinal cord–computer interface that enables individuals with complete spinal cord injury to control their paralyzed ha…
Learning a Hand Model From Dynamic Movements Using High-Density EMG and Convolutional Neural Networks
Raul C. Sîmpetru, Andreas Arkudas, Dominik I. Braun, et al.IEEE Transactions on Biomedical Engineering
We developed a convolutional neural network approach for continuous hand kinematics estimation from high-density EMG during dynamic movements. The mod…
Identification of Spared and Proportionally Controllable Hand Motor Dimensions in Motor Complete Spinal Cord Injuries Using Latent Manifold Analysis
Raul C. Sîmpetru, Daniela Souza De Oliveira, Matthias Ponfick, et al.IEEE Transactions on Neural Systems and Rehabilitation Engineering
This study demonstrates that individuals with motor complete spinal cord injuries retain spared motor neuron populations that can be voluntarily activ…
Influence of spatio-temporal filtering on hand kinematics estimation from high-density EMG signals
Raul C. Sîmpetru, Vlad Cnejevici, Dario Farina, et al.Journal of Neural Engineering
This paper investigates how different spatio-temporal filtering approaches affect the accuracy of hand kinematics estimation from high-density EMG. We…
Compact and Lightweight Cable Decoupling Unit for Bio-Inspired Tendon Drives in Wearable Robots
Nico Weber, Jonas Walter, Dominik Braun, et al.2024 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob)
We present a compact and lightweight cable decoupling unit designed for bio-inspired tendon-driven wearable robots, enabling natural finger movements …
Proportional and Simultaneous Real-Time Control of the Full Human Hand From High-Density Electromyography
Raul C. Sîmpetru, Michael März, Alessandro Del VecchioIEEE Transactions on Neural Systems and Rehabilitation Engineering
This work presents a breakthrough in EMG-based hand control, achieving proportional and simultaneous control of all fingers in real-time. Using high-d…
Proportional Control of a Soft Cable-Driven Exoskeleton via a Myoelectrical Interface Enables Force-Controlled Finger Motions
Jonas Walter, Paul Rosmanith, Daniela Souza De Oliveira, et al.2022 9th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob)
Accurate Continuous Prediction of 14 Degrees of Freedom of the Hand from Myoelectrical Signals through Convolutive Deep Learning
Raul C. Simpetru, Marius Osswald, Dominik I. Braun, et al.2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
This study presents a convolutive deep learning approach for accurate continuous prediction of 14 degrees of freedom of the hand from high-density EMG…
Sensing and decoding the neural drive to paralyzed muscles during attempted movements of a person with tetraplegia using a sleeve array
Jordyn E. Ting, Alessandro Del Vecchio, Devapratim Sarma, et al.Journal of Neurophysiology
A wearable electrode array and machine learning methods were used to record and decode myoelectric signals and motor unit firing in paralyzed muscles …
Scientific foundations
Funding
Research grants and awards that make the development of GRASPAGAIN possible.
AI-assisted neurorehabilitation and support in everyday life
b2m labs is a neuromechatronics spin-off from Friedrich-Alexander-Universität Erlangen-Nürnberg, restoring motor function in paralyzed individuals. Ou…
The GraspAgain project is funded under the EXIST programme by the Federal Ministry for Economic Affairs and Energy and the European Social Fund.
Bidirectional Interface between Neuroorthoses and Users for Interactive Control
Motivation Following a stroke or spinal cord injury, many people are left with limited mobility in limbs such as their hands and arms. They rely on o…
Restoration of hand function following a spinal cord injury
Financial support to further develop our neuroorthosis with an integrated neural interface, and expert consultation on legal, intellectual property, a…
PlayAgain - Decoding and training spared motor neuron activity in children with paralyzed hands
Adaptation of neural interface technology for pediatric rehabilitation, enabling children with hand paralysis to engage in playful training activities…
Restoring hand function in individuals with neuromuscular impairments using an intelligent neuroorthosis
Clinical validation study at the Spinal Cord Injury Center Rummelsberg to evaluate the effectiveness of the GraspAgain neuroorthosis in real-world reh…
Decoding the Exact and Representative Motor Output of The Human Spinal Cord
The DeMOTUS project investigates how the central nervous system controls motor units comprising a motor neuron and its muscle fibers during human move…
A Direct Sensorimotor Connection with the Spared Neural Code of Movement to Regain Motor Function
Current neural interfaces that assist patients with muscle paralysis generally entail surgical risks and offer poor control of movements. In cases of …
GraspAgain - Restoring hand function in individuals with neuromuscular impairments using an intelligent neuroorthosis
Development of an intelligent neuroorthosis that combines high-density EMG sensing with a powered exoskeleton to restore functional hand movements in …
