New ‘smart glove’ can boost hand mobility of stroke patients: Study

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Tokyo– Canadian researchers have developed a new “smart glove” to aid recovery and ultimately restore use of limbs and hands in survivors of stroke.

The new “smart glove” is capable of tracking the patients’ hand and finger movements during rehabilitation exercises.

The glove incorporates a sophisticated network of highly sensitive sensor yarns and pressure sensors that are woven into a comfortable stretchy fabric, enabling it to track, capture and wirelessly transmit even the smallest hand and finger movements.

“With this glove, we can monitor patients’ hand and finger movements without the need for cameras. We can then analyse and fine-tune their exercise programmes for the best possible results, even remotely,” said Janice Eng, a leading stroke rehabilitation specialist and professor of medicine at University of British Columbia (UBC).

“This is the most accurate glove we know of that can track hand and finger movement and grasping force without requiring motion-capture cameras,” added Peyman Servati, professor of electrical and computer engineering at UBC.

Using machine learning models the team developed the glove, which can accurately determine the angles of all finger joints and the wrist as the patients move.

The technology, described in a paper published in the journal Nature Machine Intelligence, is highly precise and fast, capable of detecting small stretches and pressures and predicting movement with at least 99 per cent accuracy — matching the performance of costly motion-capture cameras, the researchers said.

Unlike other products in the market, the glove is wireless and comfortable, and can also be easily washed after removing the battery. Servati and his team have developed advanced methods to manufacture the smart gloves and related apparel at a relatively low cost locally.

Servati envisions a seamless transition of the glove into the consumer market with ongoing improvements, in collaboration with different industrial partners. The team also sees potential applications in virtual reality and augmented reality, animation and robotics.

“Imagine being able to accurately capture hand movements and interactions with objects and have it automatically displayed on a screen. There are endless applications. You can type text without needing a physical keyboard, control a robot, or translate American Sign Language into written speech in real time, providing easier communication for individuals who are deaf or hard of hearing,” Servati said. (IANS)

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