Brain Machine Interface Team

We measure data through invasive and non-invasive measuring methods to understand bio-systems such as the brain and senses. In most cases, researchers use non-invasive procedures to measure human data. To investigate deep brain tissue, we use an invasive measurement method. We try to understand the bio/brain system by analyzing acquired data.

      Neuromodulation is a research area that studies how to modulate neural circuits well to improve the quality of life for patients with neurological diseases. In the case of neurodegenerative diseases, the exact mechanism has not yet been identified. Therefore, various methods, such as drug prescription and electrical stimulation, are being studied, and precise treatment has yet to be found. Drug-based treatment has the advantage of treating patients by oral administration or injection without surgery.

However, there are two difficulties in drug treatment. First is the drug resistance. Second is the low transparency of drugs to the brain due to a blood-brain barrier (BBB). For these two reasons, in the end, drug-based treatment doesn't work. For these reasons, electrical stimulation methods such as deep brain stimulation (DBS) are used, and it is known to control Parkinson's syndrome well.

We are interested in enhancing the performance and useability of electrical stimulation devices (e.g., DBS systems). For example, we are developing a fully implanted wireless closed-loop DBS system by working with various institutions.

We believe an enhanced DBS system can bring a big jump in Parkinson’s patients. Also, we can use this system to understand the underlying mechanisms of neurodegenerative diseases.

The five senses of humans are critical since we absorb the world using our senses. The harmony of the sensing organ and brain does sensing. We look at this phenomenon as a system that mimics an artificial system.

Our current interests are a sense of touch and smell. Since both work needs an accurate sensor, we collaborate with other institutes. Both artificial systems have a similar workflow. Both systems sense touch or smell through the sensor. Artificial intelligence is used to model complex non-linear sense-to-cognitive output relationships.

Making an artificial system has various strengths. However, the most significant strength is that this system can be adapted to multiple applications, such as mobile devices.