Design and development of EMG controlled prosthetic hand

People have been working on prosthetic hands from many centuries. In recent years, the trend has been shifted from passive to active prosthetic hands because they can deliver power and mimic hand movements up to some extent. Still most commercially available prosthetic hands are unreliable and can o

Project Title

Design and development of EMG controlled prosthetic hand

Project Area of Specialization

Electrical/Electronic Engineering

Project Summary

People have been working on prosthetic hands from many centuries. In recent years, the trend has been shifted from passive to active prosthetic hands because they can deliver power and mimic hand movements up to some extent. Still most commercially available prosthetic hands are unreliable and can only replicate two or three hand movements.

 In an active prosthetic hands, actuators are used as replacement of muscles. Actuators can be controlled by microcontroller, which needs some kind of controlling signal. Mainly, two types of controlling signals are being used. One is electroencephalogram (EEG) and other is electromyography (EMG). EMG signals are generally used for this purpose because it is easy to detect and process EMG signal. Raw EMG signals cannot be used to control the actuators. Some pre-processing is needed. Mostly, myoware devices are used for detection and processing of EMG signal, this data is used to classify movements of the hand but there are some limitations of myoware devices.

The purpose of this study is to design and develop a gear based prosthetic hand with built in device, which can detect EMG signal and process it so it can be used as controlling signal. These devices usually consist of amplifying circuit, which is used to feed data into microcontroller. At last stage a classification algorithm is used which classifies that which movement is happened. Once this controlling signal is generated it is used to control the actuators in the prosthetic hand. These actuators control the movement of the fingers.

Project Objectives

Prosthesis can play a vital role in rehabilitation of amputees. It can improve mobility of an amputee and can be a mean to be independent. This study is a base to develop a functional electromyography (EMG) controlled gear based prosthetic hand. EMG is a complex signal and cannot be used to control a device. The purpose of this study is to develop a device, which can convert EMG signal from forearm into a controlling signal by doing some processing and to develop a gear based low cost, reliable prosthetic hand which can be controlled by that signal.

Project Implementation Method

An EMG classification device will be designed in order to classify the movements from the forearm of the amputee. Amplification circuit, arduino mega and artificial neural network will be the part of this device. This device will convert the EMG signal into controlling signal in order to control the gear based prosthetic hand. Solidworks is used to design the prosthetic hand and printed with the help of 3d printer. Motors will be used to control the movements of the finger and Controlling signal will control the motors.

Benefits of the Project

When an arm  is amputated or lost, a proshtetic device, or prosthesis, can play an important role in rehabilitation. For many people, an artificial limb can improve mobility and the ability to manage daily activities, as well as provide the means to stay independent. The proposed project will have own built EMG clasification device which is more accurate than the available devices. It also cost less than the devices available in the market. The prosthetic hand itself has gear actuation mechanism which is more reliable than the thread based prosthetic hands available in the market. Worm gear mechanism helps finger to lock at a position.

Technical Details of Final Deliverable

Design and development of amplification circuit for EMG signal. Emg signals have very low amplitude that is why this device is necessary.

Collection of data from single channel with the help of EMG electrodes and Amplification circuit.  For initial testing only single channel is developed and data is collected from it.

 Extracting important features from collected data with the help of Arduino. 

Single channel classification with the help of artificial neural network.

Designing of prosthetic hand in Solidworks.

Convert the prototype amplification circuit in PCBs.

3d printing of prosthetic hand in order to run tests on it.

Extracting feature from all five channels in order to control five finger movement.

Classification with the help of all five channels

Interfacing classification device to prosthetic hand and finalizing the device.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Health

Other Industries

Medical

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