IIT Kanpur’s innovation for stroke patients-Read

The robotic hand deploys a unique closed-loop control system that actively engages the patient’s brain during therapy

Kanpur: The Indian Institute of Technology Kanpur (IITK) said on Saturday it has developed a unique brain-computer interface-based robotic hand exoskeleton that can help in stroke rehabilitation and redefine post-stroke therapy by accelerating recovery.

The robotic hand deploys a unique closed-loop control system that actively engages the patient’s brain during therapy.

It integrates three essential components: a brain-computer interface that captures EEG signals from the brain’s motor cortex to assess the patient’s intent to move, a robotic hand exoskeleton that performs therapeutic hand movements, and software that synchronizes brain signals with the exoskeleton for real-time assist-as-required force feedback, according to a IITK statement.

This synchronised approach ensures continuous engagement of the brain, fostering faster and more effective recovery.

“Stroke recovery is a long and often uncertain process. Our device bridges the gap between physical therapy, brain engagement, and visual feedback creating a closed-loop control system that activates brain plasticity, which is the brain’s ability to change its structure and function in response to stimuli,” said professor Ashish Dutta from the Department of Mechanical Engineering at IIT Kanpur.

This is especially significant for patients whose recovery has plateaued, as it offers renewed hope for further improvement and regaining mobility.

“With promising results in both India and the UK, we are optimistic that this device will make a significant impact in the field of neurorehabilitation,” Dutta added.

The innovation is supported by Department of Science and Technology (DST), UK India Education and Research Initiative (UKIERI), and Indian Council of Medical Research (ICMR).

Stroke-induced motor impairments often result from damage to the motor cortex, and traditional physiotherapy methods have limitations due to insufficient brain involvement.

This device addresses this by linking brain activity with physical movement.