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3.7 KiB


A myoelectric neural interface.

This is intended as a human input device (like a keyboard) that predicts your intention from muscle signals. Using a neural network, trained through a process where you press keys at the exact same time that you make movements with the limb wearing the device, it learns correlations between the muscle signals and intended keys, and can press them for you.

Software used to create/edit/run these files

  • Schematics, PCB Layouts: KiCad 5.1.5
  • Arduino IDE 1.8.19
    • ArduinoBLE 1.2.1
    • Arduino_LSM9DS1 1.1.0
  • Python 3.8
    • For library versions, see the respective requirements.txt file
  • GnuRadio


This describes prototype 4.

photo of the device

  • Features:
    • Battery-powered
    • Wireless, using Bluetooth Low Energy (BLE)
    • Supports 17 electrodes (8 pairs + 1 ground)
    • Transmits 8 signals at 8-bit resolution, 500Hz sampling rate
    • Linux graphical user interface for:
      • Mapping keyboard key presses to muscle signals
      • Training a neural network to predict key presses from signals
      • Simulating key presses based on neural network predictions
    • GNURadio integration for plotting the raw signals + FFT
  • Hardware overview:
  • Software dependencies:
  • Components:
  • Power ratings
    • Supply Voltage: 4.5-6V
    • Power dissipation:
      • Idle: ~86.9mW (16.9mA x 5.14V)
      • Transmitting at 6-7kB/s: 92.5mW (18.0mA x 5.14V)
  • Weight: ~85g (at 9.81m/s² gravitational acceleration)


Copyright (C) 2022 Roman Zimbelmann

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License version 3 as published by the Free Software Foundation.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see