PsyLink

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.

• Video demos @ PeerTube
• Development Log

Software used to create/edit/run these files

• Schematics, PCB Layouts: KiCad 5.1.5e
• 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 3.8.1.0

Datasheet

This describes prototype 4.

• 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:
  • A fabric glove/sleeve with a central component (arduino + power supply) and 8 distributed signal clean-up units close to individual electrodes.
  • KiCad Schematic
  • KiCad PCB of one distributed signal clean-up unit
• Software dependencies: