Hand Exoskeleton for Assistance in Grasping Using Force Myography
This project is about developing a wearble device that includes a sensor band and hand exoskeleton. The purpose is to assist hand motion when it is closed to grasp an object. A soft hand exoskeleton will be designed in this project. The exoskeleton will be driven using cables, which are contr
2025-06-28 16:27:32 - Adil Khan
Hand Exoskeleton for Assistance in Grasping Using Force Myography
Project Area of Specialization Wearables and ImplantableProject SummaryThis project is about developing a wearble device that includes a sensor band and hand exoskeleton. The purpose is to assist hand motion when it is closed to grasp an object.
A soft hand exoskeleton will be designed in this project. The exoskeleton will be driven using cables, which are controlled via servo motor.
Sensor band is developed to detect muscle activity. Muscle activity is recorded using forcemyography technique. In this technique force sensors are used that are placed around the muscles, which measures the force when a movement is performed. The data from muscle activity is processed to classify two hand motions, open and close, using machine learning technique. In this project two techniques logistic regression and support vector machine will be implemented. Logistic regression is the most basic technique in machine learning domain that will be implemented to develop understanding of AI domain. Support vector machine is an optimized machine learning algorithm and extensively used for is good performance.
Project Objectives- Understanding biomechanics of hand movements and forcemyography approach to record muscle activity.
- Processing forearm muscles FMG data for hand opening and closing tasks.
- Design and Develop machine learning technique for classifying hand opening and closing movement.
- Design and Develop a soft hand exoskeleton for providing support in object handlilng tasks.
- Testing of individual systems.
- Integrate motion detection method with hand exoskeleton for providing support in real-time processes.
- Testing the developed system with healthy subjects.
Waterfall methadology will be implemented in this project. In this method tasks are listed down sequentially and exceuted one after the other in the exact sequence they are listed in.
The tasks that will be performed to achieve the objectives of this project are shown below:
| Analysis |
| Design |
| Prototyping |
| Integration |
| Stage 1 Testing |
| Stage 2 testing |
| Final product |
- In analysis we will study existing literature on hand motion mechanics and muscle activity detection technique foce mypgraphy that will be emplyed in this project.
- Design part will inclide sensor band and exoskeleton designing.
- The designd systems will them be manufactured in the process of prototyping.
- In stage 1 testing, sensor band and exoskeleton will be tested separately.
- In integration process, the output of sensor band will be connected to exoskeleton control.
- In stage 2 testing, the integrated system will be tested.
- The results of stage 2 testing, might end up in making alterations in any of the sub system. This will be performed to obtain the final product.
Analysis
Design
Prototyping
Integration
Stage 1 Testing
Stage 2 testing
Final product
Benefits of the ProjectFollowing are the benefits of this project.
- Injuries to hand can happen due to repeative movements or accident, which results in poor grasping ability. Prople with such conditions will be able to get help in grasping objects properly, with less effort.
- Even for healthy workers who performed repeatitive tasks intensively, can get strain and injuries. This project can assist those workers to avoid getting injury.
- This project can also help people who are in rehabilitation process after operation and elderly whoes grasping strength degrades naturally because of age factor.
The platform that will be developed could be used by researchers in field of biomedical engineering and real-time machine learning applications
Technical Details of Final DeliverableThe final deliverable will comprise the details of following components.
- Design and development of FMG sensor band:
- Software for recording muscle acitivity:
- Machine learning method for muscle activity detection:
- Design and development of hand exoskeleton:
- Testing report of FMG sensor band and hand exoskeleton:
- System Integration, results and testing report:
| Design |