Voice And EMG controlled Prosthetic Hand

It is assessed that more than 1.5 million people live with an absence of an upper limb. Prosthetic hands can dramatically improve their quality of life by contributing to their dignity, independence, and more effective inclusion in society. This study shows the development of prosthetic hand control

Project Title

Voice And EMG controlled Prosthetic Hand

Project Area of Specialization

Robotics

Project Summary

It is assessed that more than 1.5 million people live with an absence of an upper limb. Prosthetic hands can dramatically improve their quality of life by contributing to their dignity, independence, and more effective inclusion in society. This study shows the development of prosthetic hand controlled by EMG signal and voice commands. In this project, we used data of five-arm motion class discrimination which is recorded by EMG (iEMG and sEMG) of eight able-bodied subjects. Each subject performed five motions four times lasting for four seconds each: hand grasp, hand open, rest, wrist extension, and wrist flexion. For controlling the prosthetic hand with voice commands, voice data was collected of five-hand motion classes of 41 subjects. These classes are similar as the above mentioned. We are planning to print 3D parts of the open bionics hand model. This prosthetic hand prototype has the main material is PLA. The mentioned prosthetic hand is actuated by five PQ12 linear actuators. All the algorithms written for this project will be embedded in the systems like Arduino or Raspberry Pi.

Project Objectives

Replicating the human hand has become one of the most desired achievements in robotics and prosthesis, but also one of the most difficult goals ever set in engineering. In the pursuit of this goal, there have been several researches aiming to reproduce the mechanical behavior of the hand and to get control signals from the remaining muscles or nerves near the amputation, in order to create an ultimate hand prosthesis that can retrieve part or full functionality to an amputee.

Project Implementation Method

In this project, we used data of five-arm motion class discrimination which is recorded by EMG (iEMG and sEMG) of eight able-bodied subjects. Each subject performed five motions: hand grasp, hand open, rest, wrist extension, and wrist flexion. Preprocessing was implemented by filtering and windowing the dataset using MATLAB. For controlling the prosthetic hand with voice commands, voice data was collected of five hand motion classes of 41 subjects. These classes are similar as above mentioned. We are planning to print 3D parts of the ADA V1.1 open bionics hand model. This prosthetic hand prototype has the main material is PLA. The palm is to be printed in Ninjaflex, and all of the other components are printed in PLA. The mentioned prosthetic hand is actuated by five PQ12 linear actuators, actuators act as a muscle of human. Fish line threads is use as a human tendon which is connected to the actuators. All the algorithms written for this project will be embedded in the systems like Arduino or Raspberry Pi. The myoarm band will use to take input of EMG signals.

Benefits of the Project

Prosthetic hands can dramatically improve their quality of life by contributing to their dignity, independence, and more effective inclusion in society. This work serves as the entrance to deeper and more natural prosthetic hand interactions in future. By focusing on the design of hand a fully functional prosthetic hand could be manufactured to improve life of amputees in the society.

Technical Details of Final Deliverable

The end product is 3D printed prosthetic hand will perform five motions. The prosthetic hand will control by EMG signals (brain signals) as well as voice commands. 

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Medical

Other Industries

Health

Core Technology

Robotics

Other Technologies

Wearables and Implantables

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com