Brain Implant Market to Develop Further with Technological Advancement that Forecasts Seizure Risk Days

  • Analysis
  • 22-January-2021

Epilepsy refers to a chronic disease in which patients suffer from recurring seizures. Their brain goes through momentary storms of electrical activity that may cause loss of consciousness, hallucinations, and even convulsions.

NeuroPace RNS is an implanted brain stimulation device. It has the ability to halt seizures by accurately stimulating the patient’s brain the moment it receives the first sign of an imminent episode. The researchers have brought forward a new development in the Brain Implants Market by finding further use for this device. They have used it to study seizure-related brain activity, taken over a period that extended from months to years. They studied patients while they went about their daily lives. It is the first time such research has taken place in the field of neuroscience.

For years, researchers around the globe have invested their resources in learning patterns of electrical activity in the brain that would warn them of a nearing seizure. However, none of the researches was successful. This is because technology restricted the field to only recording brain activity for weeks at max and that too in artificial inpatient settings.

Currently, there is no method like this is available in the market. If this research is successful, people would be better equipped to know when to avoid potentially dangerous situations like sports, cooking, bathing, etc, as it leads to high risk of suffering from a seizure.

The team analyzed data received by NeuroPace RNS and found that seizures are not as random as they appear. They looked at week-to-month cycles of “brain irritability” and identified those cycles that can predict a greater likelihood of having a seizure. These regular patterns may help them to construct a clinically reliable forecast of seizure risk.

They looked at the trial data and detected those periods when patients were about ten times more expected to have a seizure than at baseline. In some patients, these heightened risks could be identified several days in advance.

It is important to note that technology will only determine the likelihood of a seizure occurring and not the exact date and time when it will happen. This study brings us a step closer to guessing 90 percent accurately when a patient may suffer from a seizure in the coming days. Moreover, knowing accurate forecasts may allow neurologists to modify dosage as per a patient’s need. This will lead to less dosage, and in turn, reduction in side effects as doses would be increased during high seizure risk only.

Although the team has achieved a feat through this report, much needs to be done further in terms of variability. To determine how the forecasts will be beneficial and to which patients, further tests and prospective trials are required.

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