CHARAIBETI

Electromyography-Controlled Wheelchair

Assistive Technology • Biomedical Engineering • Embedded Systems

Year: 2024–Present Development: 10–20% Complete Controller: Arduino Mega 2560 Control: EMG + Joystick + Touchscreen

This project has been selected for the 14th National Biennial Competition under the National Innovation Foundation–India, an autonomous body under the Department of Science and Technology, Government of India.

Introduction

The EMG-Controlled Wheelchair is a smart mobility solution designed for individuals with mobility impairments. It utilizes electromyography signals to control the movement of the wheelchair, allowing users to navigate their surroundings using muscle activity.

CHARAIBETI combines biomedical signal acquisition, microcontroller-based processing, high-current motor control and an interactive display system to support assistive mobility. A joystick is retained as a backup control method, while a touchscreen interface is being developed for system status, settings and assistance functions.

CHARAIBETI electromyography-controlled wheelchair prototype — CHARAIBETI development prototype, user interface, battery-status display and wheelchair assembly.

Objective

The primary objective of this project is to develop a hands-free wheelchair system that provides independence to users by detecting muscle signals and translating them into motion commands.

Current Development Status

Prototype Progress Early Development — Approximately 10–20% Complete

10% Approximate progress 20%

CHARAIBETI is currently in the early prototype development stage and is approximately 10–20% complete. Major progress achieved so far includes the procurement of essential electronic and mechanical components, fabrication of the main wheelchair frame, implementation of joystick and touchscreen controls, and successful installation and testing of the drive motors.

Component Procurement Essential electronic, electrical and mechanical components have been acquired for prototype development.

Frame Fabrication The primary wheelchair frame and physical structure have been fabricated.

Joystick Control Joystick-based manual movement control has been implemented as a backup and testing system.

Touchscreen Implementation Touchscreen-based status, control and assistance interfaces have been implemented for prototype testing.

Motor Operation The drive motors have been installed and their basic movement operation has been successfully tested.

EMG Control Integration EMG signal acquisition, threshold calibration and movement-command mapping remain under development.

Safety and Automation Emergency protection, automated control logic and user-specific safety testing are yet to be completed.

Final Prototype Validation Complete system integration, load testing, battery optimization and user validation remain pending.

Recognition and Selection

National-Level Selection

14th National Biennial Competition

The Electromyography-Controlled Wheelchair entry was accepted under the National Innovation Foundation–India, an autonomous body under the Department of Science and Technology, Government of India.

View NIF Acceptance Record

Working Principle

The electromyography sensor captures electrical activity generated by muscle contraction. The captured signal is amplified and filtered to reduce noise before being supplied to the Arduino Mega.

Based on the signal intensity and predefined threshold values, the Arduino processes the signal and maps it to a movement command. The motor driver then controls the wheelchair motors to move the wheelchair in the intended direction.

The complete EMG control system is currently under development. At the present stage, the motors and mechanical platform are being operated and tested through joystick and touchscreen-based controls.

Stage 01 Muscle contraction generates an electrical signal

Stage 02 Surface electrodes detect the EMG activity

Stage 03 Signal amplification, filtering and threshold analysis

Stage 04 Arduino maps the signal to a movement command

Stage 05 BTS7960 driver controls the wheelchair motor

Implementation

The EMG sensor detects muscle signals through surface electrodes.
The captured signals are amplified and filtered to reduce electrical noise.
The Arduino Mega processes the signals and maps them to movement commands.
The BTS7960 motor driver controls the wheelchair motors according to the processed command.
The touchscreen display presents real-time system status, assistance options and battery information.
A joystick provides manual backup control during development, calibration and safety testing.

Features

Planned hands-free control using muscle signals.

Implemented joystick control for safety and testing.

Touchscreen display for feedback and system status.

Rechargeable battery system for mobility.

Adjustable electromyography sensitivity.

Battery-level and estimated time-remaining display.

Assistance and control-settings interface.

Emergency-stop provision for safer testing.

Advantages

Intended to increase independence for users with mobility impairments.

Uses non-invasive muscle-signal detection through surface electrodes.

Supports customizable control settings for different signal strengths.

Designed as a cost-conscious alternative to many commercial assistive systems.

Components Used

SmartElex BTS7960 DC Motor Driver Module
Raspberry Pi 5 Display
Arduino Mega 2560
MY1016Z3 Motor
Surface Electrodes
GIPO Circuit Board
Raspberry Pi 5 with 8 GB RAM
Soldering Station
I2C Display
Electromyography Sensor
24 V Amaron Battery
XL4015 5 A Variable Voltage and Current Step-Down Module
Joystick
Emergency-Stop Switch
3D-Printer Filament

Development Results

CHARAIBETI development prototype and interface — Battery-status interface, assistance menu, touchscreen controls and wheelchair development prototype.

The project is presently approximately 10–20% complete. The acquired components, fabricated frame, touchscreen interface, joystick control and drive motors have been assembled or tested successfully. EMG-based movement control, signal calibration, automation, final safety systems and complete prototype validation remain under development.

Mechanical Progress Wheelchair frame fabricated and primary drive components installed.

Control Progress Joystick and touchscreen controls implemented for movement and interface testing.

Motor Progress Drive motors installed and successfully operated during initial testing.

Challenges

Signal-noise interference during electromyography acquisition.
Calibration for users with different muscle strengths.
Battery-efficiency and power-management optimization.
Safe integration of EMG control with the already implemented joystick and touchscreen systems.
Complete load testing and user-specific validation of the wheelchair.

Future Scope

Completion of EMG-based movement control and user-specific signal calibration.
Integration with artificial intelligence for improved muscle-signal processing.
Wireless control and configuration through smartphone applications.
Improved battery-management and range-estimation system.
Voice-controlled assistance.
Advanced collision avoidance and emergency safety features.

CHARAIBETI and the Electromyography-Controlled Wheelchair project are not open source. The project design, documentation, software, source code, control logic, circuit architecture, hardware arrangements, images, interface designs and technical material may not be copied, reproduced, modified, redistributed, reverse-engineered or used commercially without prior written permission, except where permitted by applicable law.