Attention Makers


EMG controlled Humanoid Robotic Arm for Amputees

MAKERS: Mamoon , Zohaib , Ali , Maham COUNTRY: Pakistan

This project provides robust gesture classification from myoelectric signals acquired using surface electrodes, used to drive a complete low-cost human arm having 6 DOF enabling amputees to perform basic functions.


The Purpose

A large number of amputees and paralyzed are among us who are not able to compete with others only because they are held back by the fact that some part of their body is not fully functional. WHO estimates that there are 40 million amputees throughout the world, 30 percent of which are upper limb amputees. While there is no commercially available solution for the paralyzed, the prosthetic limbs available for the amputees in the market are too expensive and only available in developed countries. With our project, we provide an affordable solution for the upper limb amputees.

The Technology

4 sensors are used for detection of surface EMG signals in the upper limb. NI MyRIO is used for signal processing. After preprocessing and noise filtering, feature extraction is applied to the signals. The features include RMS, Variance, Zero Crossings. These features have values lying in a close proximity for each gesture. Once feature extraction is done, multiple gestures are distinguished based on the feature?s values for 4 sensors. A fuzzy classifier is used for gesture classification based on the features extracted. Once gestures are classified, MyRIO is used to run 6 servo motors of the robotic arm.

Additional Details

Main objectives of the project, achieved during the one-year timeline are mentioned below: Detection of Electromyography signals of the upper limb. Filtering the sEMG signals of the upper limb. Training the classifier for gesture detection with 100 cases of each gesture. Classification of 6 Upper Limb Gestures, based on the trained classifier. Designing and assembling of Humanoid Robotic Arm and Hand with 4 DOF and 6 DOF respectively. The gesture recognition can also be used for controlling a gadget, gaming and virtual reality gesture detection.

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