عنوان المشروع: Implementation of a Voice Controlled Intelligent Robotic Prosthesis Hand
الوصف:
Project Comprehensive Description
1. Problem Statement
Upper-limb amputees and individuals with neuromuscular disorders often rely on prosthetic devices to regain a degree of functional independence in their daily lives. However, many existing prosthetic hands are controlled using EMG signals generated by residual muscles. While this approach can be effective for some users, it may not be suitable for everyone. Patients with severe nerve damage, muscle weakness, paralysis, neurological disorders, or insufficient residual muscle activity may experience difficulty generating stable muscle signals required for reliable prosthetic control. As a result, these individuals may face limitations in operating conventional prosthetic devices and performing basic tasks such as grasping, holding, and manipulating objects. The inability to effectively control assistive devices can reduce independence, restrict participation in daily activities, and negatively impact overall quality of life.
2. Proposed Solution / Innovation
This project proposes a voice-controlled AI robotic prosthetic hand integrated with a custom-manufactured carbon socket and powered by a Raspberry Pi, utilizing the VOSK toolkit for offline speech recognition. The system operates by capturing real-time vocal inputs via a microphone connected directly to the system. The captured audio is processed offline using the VOSK speech recognition library. When a valid command is identified, the controller instantly triggers the dedicated servo motors to perform the corresponding mechanical gestures, such as opening, closing, holding, or displaying the "OK" and "Victory" signs. To enhance system flexibility, a dedicated mobile application is developed to allow the user to dynamically manage, add, or modify these voice commands.
This proposed approach effectively addresses the limitations of other active prostheses in a low-cost system and a lightweight carbon socket prosthesis. The novelty of this project lies in a smart voice-controlled robotic hand with a low-cost lightweight and robust prosthesis. Compared to existing solutions, the proposed system overcomes the EMG based problems and mitigates the training needs significantly.
3. Method / Implementation
The project is implemented through four stages:
• Requirement Analysis, where the Raspberry Pi 4B, high-torque servo motors, and the local VOSK API is selected.
• System Design, which focuses on engineering a lightweight, durable carbon socket using advanced casting alongside optimized wiring and active thermal management.
• Development and Implementation, where the five-fingered robotic hand is assembled, its actuators are mapped to the GPIO pins, the VOSK speech recognition software (utilizing MFCC, PLP, and TDNN models) is developed, and a dedicated mobile application is built for dynamic command management.
• Testing and Evaluation, where the fully assembled system is successfully verified using actual voice commands like open, close, hold, OK, and victory, with continuous software refinements to drastically reduce latency and maximize physical gesture accuracy.
4. Key Components (HW/SW/AI)
• Hardware (HW): Raspberry Pi 4B (Central Unit), MG996R Servo Motors (Actuators), and a USB Microphone (Input).
• Software (SW): VOSK API, Python 3.x, Linux-based Raspbian OS, Flutter application framework, and Dart programming language.
• Artificial Intelligence (AI): VOSK API selected since it utilizes advanced MFCC (Mel-Frequency Cepstral Coefficients) and PLP (Perceptual Linear Prediction) audio feature extraction and TDNN (Time Delay Neural Network).
5. Expected Results / Impact
• Results: The implemented voice-controlled prosthetic hand demonstrated encouraging results, successfully executing five essential gestures ("open", "close", "hold", "OK", and "victory") with quick, precise mechanical transitions supported by a lightweight, durable custom carbon socket. Powered entirely offline by a standard 5V rechargeable lithium battery, the system relies on the VOSK toolkit to deliver rapid, real-time speech recognition, seamlessly translating vocal inputs into immediate actuator movements. Furthermore, the accompanying mobile application connects wirelessly to the controller, enabling the user to dynamically add, modify, or delete custom voice commands that the system remembers and executes instantly without requiring an internet connection.
• Impact: The project empowers individuals with limb impairments by providing an intuitive, hands-free interface. It enhances autonomy and psychological well-being by offering a high-tech smart prosthesis.
6. What the 70-second Video Demonstrates
The video shows the implemented voice-controlled prosthetic hand and the developed app in action:
• Demonstration: The user issues live vocal commands such as open, OK Sign, and victory, and the prosthetic hand performs the required gestures. Then the developed companion app is shown, which can connect to the prosthetic hand and allow users to add, edit, and delete hand gestures, in addition to recording new voice commands.
• Validation: Upon issuing a voice command, the robotic hand executes these movements in real-time, demonstrating the efficiency of the AI model (pre-trained/offline) and the reliability of the mechanical assembly under actual operating conditions.
تاريخ رفع الملفات: 2026-07-03 12:04:59