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The Big Data Difference: Neuro-Sensing and Stimulation

By Battelle
03:00 AM
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Millions of people are struggling with conditions caused by neurological damage or disease, with impacts ranging from speech problems to total paralysis. The future of treatment for many of them may not lie not in new and different drugs but in smart devices that can monitor, interpret and generate neurological signals. Data analytics is making these treatments possible.

The Promise of Bioelectric Medicine

Interpreting neurological signals is the ultimate big data problem; the human brain processes trillions of bits per second. Powerful analytical engines are needed to sort through vast amounts of neurological data to find meaningful signals in the noise. By pairing data analytics with neurosensing technologies, manufacturers can put that information to work to help patients with damaged brains and nervous systems.

Bioelectronic medicine, for example, uses the body’s nervous system to affect therapy. By stimulating specific nerves, neural stimulation/neuromodulation may be able to treat or ease a variety of diseases and conditions. Spinal cord stimulators have long been an accepted treatment option for certain kinds of chronic pain, reducing patient dependence on opiate-based drugs. Deep brain stimulation is another example of bioelectric medicine already in use for conditions such as Parkinson’s disease. It has also shown promise for a number of other brain-based conditions, including major depression, OCD, Tourette’s syndrome, essential tremor, epilepsy and chronic pain.

There are other applications of bioelectronic medicine as well. For example, stimulation of the vagus nerve seems to suppress certain immune responses, providing a new alternative for the growing number of people struggling with autoimmune diseases such as rheumatoid arthritis or MS. Recent studies have even demonstrated the efficacy of neural stimulation to slow internal bleeding.

‘Closing the loop’ using neurosensing and data analytics will soon make these new methods even more valuable. Smart neurostimulators could be programed to fire in response to data from an implanted neural sensor. For example, patients with Parkinson’s disease have to periodically have their deep brain stimulation device adjusted. Combining neurosensing technologies and advanced algorithms would allow these devices to be self-regulating.

New Hope for Paralyzed Patients

Data analytics is also providing new options for restoring function in paralyzed patients. Neural-bypass technologies transmit signals from the brain directly to a prosthetic device, bypassing damaged parts of the nervous system entirely.

Neural-bypass technologies combine neurosensing, data analytics, neurostimulation and prosthetics to simulate the action the nervous system. A small chip is implanted in the patient’s brain to pick up signals generated by the patient’s conscious thoughts. These signals can then be decoded and put into formats that can be used by medical devices, prosthetics and other assistive technologies.

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