🦾 Bionic Arm using EMG Muscle Sensor and Arduino

Description

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🔧 Final Year College Projects 🎓 School Science Exhibition Models
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Bionic Arm/ Hand using Arduino & EMG Sensor

📘 Introduction:

The World Health Organization (WHO) estimates that there are currently more than 1 billion persons with disabilities worldwide. 80 percent of them reside in low-income nations where only 1–2 percent of the disabled population gets access to therapy. Many individuals in impoverished nations are born without hands or digits as a result of various conflicts, diseases, etc. An individual’s control, integration with the body, and feeling can all be improved with the use of bionic hands. Electromyography (EMG) signals from a group of body muscles can be used to control this system. The major purpose behind the project is to help an individual to improve the sensation, integration with the body, and the control. The development and operation of bionic hand has been explained and controlled by Electromyography Muscle Sensor.
This project shows a Bionic Hand implemented with Arduino and EMG Sensors. The EMG sensor picks up minute electrical signals generated by the muscle contractions in the forearm. These signals get filtered and amplified and are given as input to the Arduino microcontroller. The Arduino acts on the data and provides PWM outputs to servo motors fixed on the robotic hand frame. Consequently, when a user contracts their muscles, the matching servo motors spin, driving the robot fingers and simulating gestures of the human hand. This project illustrates a Bionic Hand based on Arduino and EMG Sensors. An EMG sensor picks up small electrical signals generated by muscle contractions in the forearm. These are filtered and amplified and supplied to the Arduino microcontroller. The Arduino executes the data and provides PWM signals to servo motors on the robotic hand frame. Consequently, when the user flexes his muscles, the respective servo motors turn, generating movement in the robotic fingers and mimicking human hand movement.

🔧 Objectives:

• To detect forearm muscle activation using EMG sensors and convert it into servo-driven hand movement.
• To create an intuitive robotic hand interface that mimics natural hand motions.
• To learning EMG signal processing, embedded control, and real-time actuation.
• To explore applications in wearable robotics and assistive devices for motor-impaired users.

🔁 Block Diagram:

Block Diagram: Bionic Hand/ ARM using Arduino, EMG Muscle Sensor & Servo Motor

Components Required:

• Arduino UNO
• EMG Sensors
• 1 Servo Motor
• Robotic Hand Frame ( Mechanical Assembly)
• Signal Conditioning Components (e.g., resistors, amplifiers)
• Jumper Wires & Breadboard
• Power Supply
• 16×2 LCD

💻 Software Required:

• Arduino IDE (for EMG signal read, filter, mapping, servo control)
• Serial Monitor (for calibration and debugging)

Methodology and Calculations: Bionic Arm Using EMG Muscle Sensor

The methodology of the bionic arm using a muscle sensor (EMG) involves acquiring bioelectric signals from human muscles and converting them into mechanical movement. EMG electrodes are placed on the muscle to detect electrical signals generated during contraction, typically in the range of 0–5 mV. These weak signals are amplified using an EMG sensor module with a gain of approximately 1000 and filtered to remove noise. The amplified signal is then fed into an Arduino microcontroller, which converts the analog signal into digital form using a 10-bit ADC.

Digital Value = (Vin / Vref) × 1023

Where:
Vref = 5V

Example:
Vin = 1V
Digital Value = (1 / 5) × 1023 = 205

A threshold value is set to detect muscle activity:
Threshold ≈ 200

If Sensor Value > Threshold → Muscle Detected
If Sensor Value < Threshold → No Movement

Based on this condition, the servo motor is controlled to move the arm.

Angle = (Sensor Value / 1023) × 180

Example:
Sensor Value = 300
Angle ≈ 52.8°

EMG Signal Amplification:
Vout = Gain × Vin
Gain = 1000
Vin = 0.001V
Vout = 1V

Power Calculation:
Itotal = IArduino + IEMG + IServo
Itotal = 50mA + 10mA + 500mA = 560mA

Power:
P = V × I
P = 5 × 0.56 = 2.8W

Thus, the system converts muscle signals into mechanical motion effectively for prosthetic and rehabilitation applications.

🤖 Product Title Suggestions:

• Arduino & EMG-Controlled Bionic Hand
• EMG-Guided Robotic Prosthetic Hand (Arduino-based)
• Myoelectric Robotic Hand Automation with Arduino
• Bionic Hand Gesture Control via EMG Sensors
• Arduino Prosthetic Hand with EMG Interface
• Embedded Myoelectric Controlled Robotic Hand
• Servo-Driven Bionic Hand using EMG Signals
• EMG-Responsive Robotic Hand Prototype
• Biometric Arduino Hand for Science Exhibitions
• Final Year Bionic Hand Project: EMG to Movement

Keywords:
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📦 Get the full working project with components list, code, diagrams & explanation

No branding on project; handmade appearance suitable for students; customizable design as per requirements.

📩 To Buy/ Make this project with training:
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