Highly Effective, Patient-Specific Neuromodulation Therapy

Description

This technology is a novel personalized neuromodulation therapy. There are more than 600 neurological disorders affecting patients and they impact an estimated 50 million patients each year in the US alone. In recent years, deep brain stimulation (DBS), which uses the focused delivery of current to the brain to affect neural processes, has been used as a treatment for nervous system disorders. However, the outcome of the DBS varies from patient to patient and is not predictable. Scientists at Georgia State have developed a novel machine learning process that can accurately link the stimulation parameters to the brain response in each individual patient, leading to better patient outcomes.

Benefits

• Higher Success Rate –Personalized control systems generate stimulation that effectively treats the disorder in a higher percentage of patients.
• Lower Visit Costs and Time – The appropriate stimulation processes to create the bet clinical outcome are established more rapidly, reducing visit time and therefore costs.
• Better Clinical Outcomes – Personalized stimulation processes can select the appropriate stimulation for the required outcome for each patient individually, leading to more patients receiving optimal therapeutic outcomes.

Applications

• Parkinson's disease
• Essential tremor
• Conditions that cause dystonia, such as Meige syndrome
• Epilepsy
• Tourette syndrome
• Obsessive-compulsive disorder
• Major Depression
• Tinnitus
• Stroke recovery

Patent Status

• PCT filed

Publications

An active learning framework for quantifying the effect of neuromodulation