Sydney, Jan 17 (IANS) A team of researchers are in the process of developing smart garment technologies that would prevent falls in people with Parkinson's disease.
Falls, which are frequently caused by gait impairments and postural instability, are common and often devastating in the lives of people with Parkinson's - a neurodegenerative disease.
The researchers from Neuroscience Research Australia (NeuRA) and University of New South Wales (UNSW) are set to make StandingTall-PD -- a neuro-rehabilitation programme -- that aims to prevent freezing-of-gait and falls, and enhance patients' independence.
The programme uses visual, audio and haptic sensory cues to help rewire the parts of the brain that control walking and preventing falls in people with Parkinson's disease.
The combination of visual, audio and sensory elements helps to form new connections in less affected parts of the brain, leading to improved walking ability, the researchers said.
"Existing dopamine therapies offer benefit in treating motor dysfunction in Parkinson's but may not alleviate gait and balance challenges," said Jamie L. Hamilton, Associate Director at the Michael J. Fox Foundation (MJFF) in the US.
"The new programme has the potential to become an affordable option to address gait and balance issues and improve overall quality of life for people with Parkinson's," said Hamilton.
For the study, researchers will give participants a mat with colour-coded stepping targets, a pair of Sensoria Smart Socks, an iPad and phone.
The programme can help enable participants to self-manage and monitor their own progress via an app on their phone. The app can also trigger stimuli during everyday activities, such as vibration in their Smart Socks, if they are in danger of experiencing freezing-of-gait, falls or if they show signs of shuffling feet.
In addition, clinicians can monitor participants' progress remotely and adjust the programme to provide ongoing and personalised continuity of care.
(This story has not been edited by Social News XYZ staff and is auto-generated from a syndicated feed.)
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