Prosthetic Hand

New ideas for 2017-2018:

  • Utilize a Convolutional Neural Network to interpret the brain waves into control signals, (Computer Science emphasis).
  • Replace the prototype electronics board by a custom built printed circuit board, (Electrical Engineering emphasis).

Finger actuation Test 1 (video)

With an aging population and many war veterans, the medical device industry is growing rapidly. In particular, prosthesis are finding their way into the lives of many individuals. The goal of this project is to break free of the typical robotics stereotype of wires and metals, and create a more lifelike product. Currently, prosthetic arms and hands are controlled either by using a sling with various linkage that creates the hand movements based upon how the sling is moved at the shoulder of by finding individual nerve endings that connect to the phantom appendage. What has not been done, however, is a robotic hand that operates by the use of an EEG sensor, measuring brain wave activity to control hand movements. This project applies to a wide variety of majors, as mechanical engineers are needed in the actual hand design and construction, bioengineers for the EEG sensor application and the tie between robot and human, electrical engineers for wiring and circuit design, and computer engineers for programming microcontroller functions. This project aims to take a cross-disciplinary approach to solving a real world problem.

We are proposing to construct a prosthetic hand that will be controlled by the mind. This project is very different than other robotics projects the club is currently working on in that it has direct human interaction via the brain. This project will give group members the opportunity to be part of an interdisciplinary team to solve a complicated design problem. Members will learn how to tie biological systems into inanimate ones as well as the engineering process behind constructing a functioning prosthesis.

Objectives

  • Construct a prototype prosthetic hand with the following control systems:
    • Mimicking by use of glove on operator’s hand
    • Control by measuring brain wave activity with EEG sensors
  • Tutorials/team learning will be done in the following topics:
    • Microcontrollers – programming and functionality
    • Brain Anatomy and Physiology
    • Brain interfacing (from a bioengineering professor)
    • 3D Modeling/Force Analysis
    • 3D Printing
    • Circuit Design and Analysis

Members:

2016-2017

Brian Miller, BS Bio-Engineering
Joslynn Deaver, BS Bio-Engineering
Glenn Duncan, BS Computer Science

2015 – 2016

Bryce Johnson, BS Electrical Engineering (Team Leader)
Douglas Behrend, BS Mechanical Engineering
Katie Iverson, BS Mechanical Engineering
Kevin Gray, PhD Student
Robert Thonney, BS Bio-Engineering
Austin Jensen, BS Bio-Engineering
Brian Miller, BS Bio-Engineering
Tyler Lloyd, BS Bio-Engineering
Samantha Kaonis, BS Bio-Engineering
Kurtis Tramel, BS Bio-Engineering
Jonathan Stern, BS Bio-Engineering/Electrical Engineering
Sinclair Wilson, BS Bio-Engineering