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Stroke stands as a prominent cause of disability globally, impacting millions annually. Among its devastating consequences is the loss of hand function, significantly hindering individuals in their daily activities and compromising their overall quality of life.
(Photo : Lou Bosshart/UBC Media Relations)
UBC electrical and computer engineering professor Dr. Peyman Servati, Ph.D. student Arvin Tashakori and their team at their startup, Texavie, created the smart glove for collaboration on a stroke therapy study.
Developing ‘Smart Glove’
In a ray of hope for stroke survivors seeking to reclaim their hand functions, researchers at the University of British Columbia (UBC) have developed a groundbreaking wearable technology.
Termed a “smart glove,” Interesting Engineering reported that this device has the capability to monitor and transmit the hand and finger movements of the wearer during rehabilitation exercises.
This innovative smart glove is currently undergoing testing in a pilot study involving a group of stroke survivors in British Columbia.
As part of the study, participants will wear the smart glove while engaging in rehabilitation exercises under the supervision of Dr. Janice Eng, a distinguished professor of medicine at UBC and an expert in stroke rehabilitation.
According to Dr. Eng, the smart glove offers a valuable means of tracking patient progress and delivering feedback to enhance exercise programs. This glove enables them to monitor the movements of patients’ hands and fingers without the necessity for cameras.
Constructed from a flexible fabric embedded with a network of sensor yarns and pressure sensors, the smart glove can detect and capture minute hand and finger movements, as well as grasping force. This data is wirelessly transmitted to a computer or smartphone for analysis.
Highlighting the Glove’s Precision, Speed
In a recent publication in Nature Machine Intelligence, Dr. Servati and his team detailed the technical intricacies and breakthroughs of the smart glove.
Describing it as the most accurate glove available for tracking hand and finger movement and grasping force without the need for motion-capture cameras, they highlight the glove’s precision and speed.
The developed machine learning models enable the glove to accurately determine the angles of all finger joints and the wrist as they move, achieving a remarkable 99-percent accuracy, on par with the performance of expensive motion-capture cameras.
Beyond its accuracy, the smart glove boasts additional advantages over existing products in the market. It is wireless, comfortable, and easily washable after removing the battery. Dr. Servati and his team have also devised advanced, cost-effective methods for local manufacturing of smart gloves and related apparel.
Also Read: Soft Robo-Glove Can Help Stroke Patients Relearn to Play Musical Instruments
As posted in its official press release, the smart glove emerges as a groundbreaking tool for stroke recovery and promises to revolutionize various fields centered around involvement and interactions.
Dr. Servati envisions a seamless transition of the glove into the consumer market, collaborating with diverse industrial partners for ongoing improvements. Beyond stroke recovery, he sees potential applications in virtual and augmented reality, animation, and robotics.
Consider the capability to precisely capture hand movements and interactions with objects, automatically displayed on a screen.
The applications are diverse, ranging from typing text without a physical keyboard to controlling a robot or translating American Sign Language into written speech in real-time, an innovation that could significantly improve communication for individuals who are deaf or hard of hearing.
Related Article: Researchers Use Machine Learning Model for Accurate Prediction of Strokes
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