Team Limbo’s goal is to create an affordable biomechatronic prosthetic arm and hand for trans-radial amputees. Our project focuses on controlling the prosthetic device through analyzing electromyography (EMG) signals with machine learning models. Our design also aims to integrate an array of sensors and a functional haptic feedback systems in order to simulate a sense of touch for users. Finally, by incorporating custom 3D printed components created through computer-aided design (CAD), our team will be able to lower the total cost of the prosthetic, increasing the accessibility and affordability of the device for consumers.


Mechanical Team:
  • Modeled and 3D printed prototypes for finger and palm designs
  • Developing two competitive designs for our finger mechanisms
  • Integrated motor into designs
  • Makes CAD Models using Fusion 360
Electrical Team:
  • Slip sensor PCB and C++ code created
  • Servo lever arm CAD designed
  • EMG filter SPICE simulation and working breadboard prototype
  • Integrate force sensor into slip sensor PCB
  • Design EMG sensor to gather signals from multiple electrodes
  • Create sensory feedback wearable
  • Design power management circuitry for portable Li-Po battery power
  • Create low-profile microcontroller PCB and C++ code to control electronics on the hand
Software Team:
  • Collected, stored, and organized EMG data
  • Set up a method to preprocess data
  • Created a binary classifier to recognize opening/closing of a hand
  • Researched and began implementing LSTM as a network architecture
  • Uses Python and Pytorch for Machine Learning Models