System and Method for Optimizing Neural Stimulation


In 2002 deep brain stimulation (DBS) was first approved for the treatment of Parkinson’s disease (PD). Since then it has been used in over 40,000 PD patients and is currently being investigated for a variety of additional neurological disorders. DBS utilizes electrodes implanted within the brain to generate electrical stimuli which regulates abnormal brain activity. The amount of stimulation is controlled by a device placed under the skin in the upper chest of the patient. To help guide the control device, endogenous neural activity (e.g. brain waves) are recorded and analyzed. However, endogenous neural activity is highly complex, poorly understood, and has large patient-to-patient variance.

Prof. Bradley Greger at Arizona State University developed a system of sensors and automated methodology for optimizing neural stimulation. As opposed to measuring endogenous neural activity, this system measures biophysical properties of brain tissue directly to guide neural stimulation and automate programming of the DBS control device. Because the automated programming of the DBS control devices is based on objective measures, rather than more subjective human programming, it may improve patient outcomes, lower costs, and expand the applications for DBS treatment.

By using measured biophysical properties, this system can directly measure the effect of DBS on neural tissue and use this to guide stimulation and DBS device programming creating a more targeted, optimized and effective DBS treatment for a variety of neural disorders.

Potential Applications

• Optimization of DBS treatments

o Neurological disorders e.g. epilepsy, Parkinson’s, Alzheimer’s, seizures, dystonia, essential tremor, etc.,

o Cognitive disorders e.g. amnesia, dementia, delirium, etc.

o Affective disorders e.g depression, bipolar, etc.

o Obsessive-compulsive disorder

Benefits and Advantages

• More targeted and effective DBS treatment

o The biophysical properties that are measured provide quantitative input for determining optimal tissue stimulation parameters as well as objective metrices for assessing stimulation performance

• Automated programming of DBS devices is based on objective measures

o Improves patient outcomes

o Lowers costs

• Quantifies biomarker neural stimulation efficacy

For more information about the inventor(s) and their research, please see

Dr. Greger's departmental webpage

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Bradley Greger

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