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    Home > Active Ingredient News > Study of Nervous System > Neural robotic system decodes the way Parkinson's disease interferes with patients' walking|Science Translational Medicine

    Neural robotic system decodes the way Parkinson's disease interferes with patients' walking|Science Translational Medicine

    • Last Update: 2022-09-21
    • Source: Internet
    • Author: User
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    Using a new type of neural robotic platform and electrode measurements, the scientists cracked the way Parkinson's disease impairs the ability of patients to coordinate walking and moving in their brains
    .

    The discovery sheds light on the way a brain region called the thalamus base nucleus coordinates leg muscle activity, proposing algorithms
    that could detect "freezing" and other walking disorders in patients during exercise.

    Yohann Thenaisie, author of the study, and colleagues said: "These results reveal the key principle of dynamically changing thalamus coding walk, opening up the possibility
    of using these signals to manipulate the neuroprosthetic system to improve walking in people with Parkinson's disease.
    "
    "
    People with Parkinson's disease often experience movement problems such as tremors, difficulty walking, and freezing
    during exercise.

    Scientists speculate that processing specific areas of the brain, such as deep brain stimulation, may help treat these motor symptoms
    .

    Previous studies have linked the hypothalamus to arm movements, but how this brain region coordinates leg movements and walking has not been explored
    .
    Thenaisie et al.
    built a chair-like neural robotic platform that comprehensively measured the activation
    of leg muscles in 18 Parkinson's patients.

    The team combined their device with measurements from brain electrodes to track activity in the thalamus base nucleus, allowing them to deconstruct the most important components
    of walking.
    When patients move their legs, the platform shows that the thalamus base nucleus controls the initiation and termination
    of muscle activity in their legs.

    The scientists then created several algorithms that distinguish normal gait from impaired gait and can identify freezing episodes when patients undergo short-distance walking tests
    .

    Thenaisie et al.
    say that future research could potentially apply similar techniques to other brain regions or other neurological disorders
    .
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