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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 Vecchio·IEEE 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 …