Wearable hand rehabilitation system with soft gloves

Hand paralysis is one of the most common complications in stroke patients, which severely impacts their daily lives. About 55% to 75% of survivors suffer from disabilities, such as paralysis and aphasia. Hemiparesis, the loss of ipsilateral motor function, is one of the most common after-effects of

Project Title

Wearable hand rehabilitation system with soft gloves

Project Area of Specialization

Electrical/Electronic Engineering

Project Summary

Hand paralysis is one of the most common complications in stroke patients, which severely impacts their daily lives. About 55% to 75% of survivors suffer from disabilities, such as paralysis and aphasia. Hemiparesis, the loss of ipsilateral motor function, is one of the most common after-effects of a stroke This condition often results in a severe degradation of the quality of life quality and a significant burden to family and society. Though recent advances in medicine dramatically increase the survival rate of stroke cases, there is still a high demand for rehabilitative treatments to enhance motor recovery for post stroke patients. Rehabilitative treatments with assistive devices have been effectively used for paralysis with limb disorders, particularly for large motions and extremity function

We want to design a wearable hand rehabilitation system that supports both mirror therapy and task-oriented therapy.

In form of a pair of gloves, i.e., a sensory glove and a motor glove, to be designed and fabricated with a soft, flexible material, providing greater comfort and safety than conventional rigid rehabilitation devices. The sensory glove worn on the non-affected hand, will be used to measure the gripping force and bending angle of each finger joint for motion detection. The motor glove, would provide the affected hand with assisted driving-force to perform training tasks By the use of the robotic hand mirror therapy will be performed

Project Objectives

The project objectives are as follows

• Implementation of light weight robotic hand with finger movement.
• Implement algorithm to read and analyze EMG data.
• Interfacing of flex and muscle sensor with micro-controller.
•  Controlled the movement of individual fingers.
• Controlled the movements of fingers wirelessly via flex sensor
• To build a sensory glove which mirrors and performs hand movements
•  Integration of force and flex sensors
•  To capture non affecting hand gesture of hemiplegic patient
•  To mirror hand gesture of intended motion and replace it with an visual output
•  To allow visual input to restore damaged neurons and as an end result perform task oriented therapy through the robotic glove

Project Implementation Method

The implementation of the hand rehabilitation system proposed is that it consists of a sensory glove, a motor glove, a Machine learning engine, and an evaluation platform. The sensory glove is worn on the non-affected hand to collect the force and flexion information for hand motion detection. The Machine learning engine classifies the gestures and sends the control signals to the motor glove, aiding the patient to perform the training tasks

The sensory glove, worn on the non affected hand, integrates multiple sensors to capture the hand’s motion for gesture recognition and visualization.. flex sensors will be used at the joint of each finger to measure their bending angles  In mirror therapy, the raw data captured from the flexion sensors are used as the input data of classifiers

Similarly servo motors will be used to control the movement of the hand. As the data input will be taken from the flex sensors and servo motors,using arduino the movement of the hand will be controlled by programming the code.

After implementing the robotic hand then mirror therapy will be performed by capturing hand movements from the non affected hand and then perform them with the help of the robotic hand

Benefits of the Project

A hand rehabilitation system that supports both mirror therapy and task-oriented therapy for fine motor recovery of post-stroke patients. The gloves with sensing-actuation combination exploit flexible and wearable techniques, which provide a safe, comfort, portable, and affordable solution over the rigid exoskeleton devices. Compared to those using biomedical signals, a dedicated data glove with sensors integrated offers improved signal quality while eliminates the need for precise placement of electrode, thus ensures fine-grained classification of training gestures. The user-friendly application software allows patients or non professionals to carry out daily training tasks and interact with therapists.

Technical Details of Final Deliverable

A robotic hand with uses servo motors flex sensors to do movements of fingers and joint and using the data from these sensors mirror therapy of phsically impaired people will be done The sensory glove worn on the non-affected hand, will be used to measure the gripping force and bending angle of each finger joint for motion detection. The motor glove, would provide the affected hand with assisted driving-force to perform training tasks .Bluetooth module used will transmitt data and recieve it to interface it with the aurduino and the myomware sensors will help to send emg signals to send the data to the arduino By the use of the robotic hand mirror therapy will be performed

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Education

Other Industries

Core Technology

Wearables and Implantables

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com