Transradial Amputation, Upper Limb Amputation, Upper Limb Amputation Below Elbow
Conditions
Keywords
Robotic Hand, Artificial Intelligence, 3D Scanning, 3D Printing, Low-cost Prosthetics, Adaptive Grasping, EMG
Brief summary
The purpose of this research is to create an intelligent robotic hand for people who have lost a limb below their elbow. By using artificial intelligence to adaptively grasp different types of objects, this will improve both the accuracy and flexibility of robotic prosthetic control. In addition, the project will integrate mechanical design and artificial intelligence based controls in order to produce a more functional and user-friendly prosthetic solution.
Detailed description
This research develops a low-cost, AI-powered prosthetic system for individuals with transradial amputations. The process begins with a 3D scan of the participant's residual limb to design customized, 3D-printed sockets and robotic hands. The core of the system integrates Artificial Intelligence to classify surface Electromyography (EMG) signals captured from the limb's muscles. This AI-driven pattern recognition allows for adaptive grasping of various objects. The study's primary objective is to compare this AI control system against traditional rule-based EMG programming. Both systems will be evaluated based on their effectiveness, adaptability, and response efficiency while the participant performs real-world grasping activities.
Interventions
DEVICEAI-Powered Robotic Hand
A low-cost, 3D-printed prosthetic hand and customized socket. The device uses AI algorithms to identify objects and adapt grasping patterns, which will be compared against standard rule-based programming.
Sponsors
Al-Nahrain University
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DEVICE_FEASIBILITY
Masking
NONE
Intervention model description
A single-arm feasibility study to compare AI-based grasping control versus traditional rule-based programming in a 3D-printed prosthetic hand.
Eligibility
Sex/Gender
MALE
Age
18 Years to 60 Years
Healthy volunteers
No
Inclusion criteria
* Participants with unilateral transradial amputation. * Age between 18 and 60 years. * Sufficient muscle activity in the residual limb to generate detectable EMG signals. * Stable physical and mental health condition to undergo the testing.
Exclusion criteria
* History of severe skin diseases or open wounds at the site of EMG electrode placement. * Cognitive impairments that prevent the participant from understanding or following instructions. * Participation in other clinical trials that might interfere with the current study outcomes.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Feasibility and Technical Performance of the AI-driven Prosthetic System. | During the experimental testing sessions (approximately 1 day). | To evaluate the feasibility of the integrated prosthetic system (3D-printed socket and AI-controlled hand). Feasibility will be assessed by the successful execution of grasp commands using EMG signal classification and the mechanical stability of the 3D-printed components during real-world tasks. This includes the system's ability to maintain functional operation throughout the testing session without hardware or software failure." |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Real-time AI Classification Latency | During the real-time control evaluation | Measurement of the time delay (in milliseconds) required by the AI algorithm to process raw EMG data and identify the intended grasp pattern |
Countries
Iraq
Contacts
STUDY_DIRECTORWajdi Sadik Aboud, Prof. Dr.
Al-Nahrain University
Outcome results
None listed