BIONIC HAND: A REVOLUTION IN ROBOTICS
DONE BY: Al Anoud Al Shamsi, Raysa, Fatima Al Ameri, Al Anoud Al Sawafii, Mouza Nabeel 11AG
OBJECTIVES
Objective 1:
Create an affordable robotic hand to assist people with disabilities.
Objective 2:
2. Use sensors or brain control for better responsiveness and adaptability.
Objective 3:
3. Ensure the robotic hand is user-friendly, efficient, and reliable.
Purpose
This robotic hand is designed to replicate the movement and functionality of a human hand, making it useful in prosthetics, hazardous environments, and precision-based tasks. In prosthetic applications, it can restore mobility to individuals with limb loss, allowing them to perform daily activities with greater independence. Its integration of sensors and actuators enables natural and responsive motion. Additionally, in scientific fields such as chemistry, this technology enhances safety by allowing chemists to handle corrosive or toxic substances remotely, reducing the risk of chemical burns and exposure. By minimizing direct human contact with hazardous materials, robotic hands improve both efficiency and workplace safety. This project demonstrates how robotics and engineering can be applied to solve real-world problems, advancing both medical and industrial fields.
Hypothesis
If we build a bionic robotic hand with sensors or brain-controlled technology, then people with paralysis or limb loss will find it easier to complete everyday tasks. By making the hand lightweight and responsive, we expect it to be more comfortable and functional. Through testing, we believe this design will show that assistive technology can improve mobility and independence, making life easier for those who need it.
ALL THE MATERIALS NEEDED
1. Robotic Hand Kit (A ready-made plastic hand with moving fingers)
2. Servo Motors (Small motors that make the fingers move)
3. Arduino Board (A small computer that controls the hand)
4. Motor Driver (A small board that helps connect motors to Arduino)
5. Battery Pack (A power source (9V battery or USB) )
6. Wires & Breadboard (Easy plug-in wires for connecting parts (comes in kits) )
7. Pre-Made Code (Simple programs to make the hand work)
8. Screws (So we can secure the parts)
PROCEDURE
Step 1: Gather Materials
-Get a Robotic Hand Kit.
-Make sure you have wires, a breadboard, and a USB cable.
Step 2: Palm rest
- Now we assembled the palm rest and the hand frame.
Step 3: Wiring
- We cut the wires into the desired measurements to be able to connect the fingers to the hydraulic system.
Step 4: Hydraulic system
-We connected the hydraulic system to the fingers using the wires.
Step 5: Test & Fix
-After assembling all the parts we must test how well they perform by trying to pick up objects.
RESULTS
After assembling and programming the robotic hand, the fingers successfully moved in response to sensor inputs. The servo motors accurately controlled finger movements, allowing the hand to grasp small objects. When using flex sensors or EMG signals, the robotic hand responded effectively to muscle movements. Some adjustments were needed to improve grip strength and response time. Overall, the project demonstrated that a simple, low-cost robotic hand can help people with disabilities by restoring basic hand functions. The results confirmed that using sensors and Arduino technology makes assistive robotics more accessible and functional.
How It Works?
Biology
The bionic hand integrates with the human nervous system through surgically implanted electrodes or non-invasive sensors that detect electrical impulses generated by neural activity. These bioelectrical signals, normally responsible for triggering muscle contractions, are intercepted and converted into digital data. This conversion enables the robotic hand to mimic natural movements.
Physics
Concepts such as torque, leverage, and kinematics ensure that the artificial joints move with realistic force and precision. Sensors measure forces and positions. The design optimizes energy efficiency and minimizes friction, enabling smooth and reliable operation.
AI
Artificial Intelligence algorithms analyze the neural signals captured by the sensors to interpret the user’s intent. Machine learning models, trained on large datasets of muscle and nerve patterns, predict and refine hand movements in real time.
Math
Calculus and differential equations model the dynamics of movement, while linear algebra supports the processing of complex neural data. Probability theory helps filter noise and predict user intentions. Overall, mathematical modeling and computations are critical for optimizing performance.
CONCLUSION
The robotic hand successfully showed that a simple and affordable device can assist people with paralysis or limb loss in performing basic tasks. The hand was able to move and grasp objects based on user input, proving that assistive technology can be both effective and accessible. While small adjustments were needed to improve movement and grip, the project demonstrated the potential for robotic hands to improve daily life. With further development, this technology could become even more useful in helping individuals regain independence and control in their everyday activities.
RESOURCES
-Robotic Hand Kit Manuals – Assembly and -Wiring guides from pre-made kits. -Arduino Website (www.arduino.cc) – Coding tutorials and project examples. -YouTube Tutorials – Videos on building and programming robotic hands. -Science Fair Project Books – Guides on documenting and presenting STEM projects. -Online Articles on Bionic Hands – Research on how robotic prosthetics help people.