Dr.-Ing. defence expected December 2026

Neural interfaces for hand control.

I build neural interfaces that turn muscle activity into control of virtual hands, orthoses and prostheses.

n-squared lab · FAUErlangen · Germany
Clean-line comic illustration of a pastel desert: Raul, seen from behind in a linen shirt, scarf, satchel and desert boots with a bamboo staff, stands on a dune ridge looking at a giant segmented robotic hand half-buried in the sand, a ribbon cable snaking toward him
02 · Featured work

Research areas.

Three landmarks
Clean-line comic desert with three landmarks joined by a ribbon cable: a stone hand wearing an electrode band, a robotic hand on a pedestal steered by a small traveller, and a tree shaped like a neuron
I · Decoding

Decoding hand movement from forearm EMG

We use forearm muscle recordings to estimate hand movement in real time, then investigate what the network learns.

From spinal motor neurons to a 22-degree-of-freedom hand model
II · MyoGestic

Decoding spared muscle activity for assistive control

We train decoders with participants to turn spared muscle activity into control of assistive devices.

A participant wearing the EMG bracelet controls a virtual hand, an orthosis, a prosthesis and a cursor
III · MyoGen

Simulating neural drive, muscle and EMG

MyoGen links models of neural drive, muscle and EMG, letting us test decoders against known simulated signals.

Cortical neurons, spinal motor neurons, afferents, muscle and the resulting EMG, simulated
03 · Papers

Selected publications.

Click a paper to open it
I

Decoding hand kinematics from EMG

  1. Camera setup, raw HD-sEMG, the 3D convolutional network and predicted joint angles

    14 jointspredicted from forearm EMG, 2.78° mean absolute error

    Accurate continuous prediction of 14 degrees of freedom of the hand from myoelectrical signals through convolutive deep learning. Raul C. Sîmpetru, Marius Osswald, Dominik I. Braun, Daniela S. Oliveira, Andre L. Cakici, Alessandro Del Vecchio. 44th IEEE EMBC · Glasgow, July 2022.

  2. Neural-to-EMG pathway and real-time hand-kinematics estimates compared with camera-based estimates

    >20 DoFdecoded live, under 50 ms latency, 32 predictions a second

    Paper ↗

    Proportional and simultaneous real-time control of the full human hand from high-density electromyography. Raul C. Sîmpetru, Michael März, Alessandro Del Vecchio. IEEE Trans. Neural Syst. Rehabil. Eng. 31 · July 2023.

II

Filtering and learned representations

  1. Neural information, movements and EMG, then filtering, a neural network and a comparison of filters

    320electrodes; best with all of them and no low-pass filtering

    Influence of spatio-temporal filtering on hand kinematics estimation from high-density EMG signals. Raul C. Sîmpetru, Vlad Cnejevici, Dario Farina, Alessandro Del Vecchio. J. Neural Eng. 21 · March 2024 · Open access.

  2. Neural pathway, the movement set, electrode grid placement and the 22-degree-of-freedom hand model

    22 DoFkinematics and force from 320 EMG sensors

    Learning a hand model from dynamic movements using high-density EMG and convolutional neural networks. Raul C. Sîmpetru, Andreas Arkudas, Dominik I. Braun, Marius Osswald, Daniela Souza de Oliveira, Bjoern Eskofier, Thomas M. Kinfe, Alessandro Del Vecchio. IEEE Trans. Biomed. Eng. 71 · 2024.

III

Assistive control after injury or amputation

  1. Uninjured and motor-complete SCI participants, EMG and kinematics feed a deep learning model whose latent space separates gestures and groups

    98.3%mean accuracy across 8 attempted movements, 8 tetraplegic participants

    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, Alessandro Del Vecchio. IEEE Trans. Neural Syst. Rehabil. Eng. 32 · October 2024 · Open access.

  2. A participant wearing the EMG bracelet controls a virtual hand, an orthosis, a prosthesis and a cursor

    7 participantscontrol demonstrated with a virtual hand, orthosis, prosthesis and cursor

    MyoGestic: EMG interfacing framework for decoding multiple spared motor dimensions in individuals with neural lesions. Raul C. Sîmpetru†, Dominik I. Braun†, Arndt U. Simon, Michael März, Vlad Cnejevici, Daniela Souza de Oliveira, Nico Weber, Jonas Walter, Jörg Franke, Daniel Höglinger, Cosima Prahm, Matthias Ponfick, Alessandro Del Vecchio († equal contribution). Sci. Adv. 11, eads9150 · April 2025.

IV

Biophysical simulation of neuromotor activity

  1. Cortical neurons, interneurons, motor neurons, afferents, a Hill-type muscle, volume conductor and resulting surface and intramuscular EMG

    Cortex to EMGsimulation of neural drive, muscle force, and surface and intramuscular EMG

    MyoGen: unified biophysical modeling of human neuromotor activity and resulting signals. Raul C. Sîmpetru*, Ricardo G. Molinari*, Devon R. Rohlf, Rebeka L. Batichotti, Renato N. Watanabe, Leonardo A. Elias, Alessandro Del Vecchio (* joint first authors). bioRxiv · January 2026.

04 · Software

Research software.

Open source
Clean-line comic workshop under a striped awning: a cloaked figure seen from behind repairs a segmented robotic hand at a workbench, a hover-glider parked beside it

Real-time myocontrol software with decoder calibration during participant sessions.

Co-creator and core developer · v2.0, 2026

Biophysical simulation from neural drive to EMG.

Author and maintainer · v0.11.0

$ pip install myogen
05 · Tools

Smaller tools.

github.com/RaulSimpetru

Recording and tracking

Rust · CLI

LSL Recording Toolbox

Records several Lab Streaming Layer streams in sync to Zarr, with tools to manage and analyse the recordings.

Rust

Muovi LSL interface

Streams the OT Bioelettronica Muovi EMG device into Lab Streaming Layer in real time.

Rust

Sessantaquattro LSL interface

Streams the OT Bioelettronica Sessantaquattro into Lab Streaming Layer in real time.

Python · napari plugin

napari-cotrack

Label keypoints on a few frames; CoTracker3 tracks them through the rest of the video.

Research workflow

PythonMCP

Zotero Library MCP

Lets Claude, Codex and ChatGPT add papers and books to Zotero by DOI, arXiv ID or ISBN, and manage collections and tags.

TypeScript

Synology Site Hub

Live previews of every git branch of your websites, on your own Synology NAS behind its login.

Python · local LLM

GrantBridge

Watches German and EU funding calls, ranks them against a researcher’s confirmed capabilities and drafts project concepts.

PythonMCP

Seatsurfing MCP

Book desks and rooms in Seatsurfing from Claude Code.

Objective-C · macOS

Netron Quick Look

Preview machine-learning model files in Finder with Netron: select one and press Space.

Python

PDF Form Filler

Fills PDF forms with text and checkboxes so they render correctly in any viewer.

06 · Experience

Research, teaching, talks.

Clean-line comic amphitheatre carved into terracotta rock: a cloaked speaker stands in front of a large stone screen while an audience in cloaks, seen from behind, listens
Photo: Raul C. Sîmpetru at a lectern at Georgian Technical University in Tbilisi, presenting MyoGestic
Tbilisi, Georgia · 2026Public lecture at Georgian Technical University
Photo: Raul C. Sîmpetru at the lectern at ISEK 2026 in Jyväskylä, presenting a slide titled The neural manifold
Jyväskylä, Finland · June 2026Invited symposium talk at ISEK 2026
Now

Doctoral researcher

n-squared lab, FAU Erlangen-Nürnberg

Dr.-Ing. defence expected December 2026

Now

Invited professor

Kutaisi International University

Teaching neurocomputing, robotics, deep learning and DSP

Talks and recognition

TalkRecognition
2023
Recognition

Young Talent Award, 3rd prize

DMEA

Talk

Selected oral talk

The Physiological Society

2024
Recognition

Featured Article

IEEE TBME

Talk

Oral talk

ISEK

2025
Talk

Rapid-fire talk

International Motoneuron Society

2026
Talk · June

Invited symposium talk

ISEK, Jyväskylä ↗

Recognition

Best Student Paper, co-author

IEEE CBS

Public lecture

Muscles, Machines, and Movement

Georgian Technical University, Tbilisi ↗

Before
  • Research and teaching assistantFAU Erlangen-Nürnberg
  • Research assistantFraunhofer IIS
Education
  • Dr.-Ing. candidateFAU Erlangen-Nürnberg
  • MSc and BSc Medical EngineeringFAU Erlangen-Nürnberg
Teaching
  • Neurocomputing, robotics, deep learning, DSPKutaisi International University
  • Seminars and thesis supervisionFAU Erlangen-Nürnberg