Invasive brain/bio-medical signal sensing and processing
Closed-loop stimulation & recording system for homeostasis regulation of Parkinson’s disease
Parkinson’s disease (PD) is a progressive and degenerative brain disease, including motor dysfunctions and other non-motor symptoms caused by gradual loss of dopaminergic neurons in substantia nigra of the brain. However, techniques for treating PD in clinical practice have side effects, and the mechanism of treatment is not clearly known. We develop the multi-modal closed-loop system that overcomes the limitations of the existing levodopa therapy and deep brain stimulation(DBS).
Stimulation artifact cancellation for simultaneous stimulation and recording system
In conventional closed-loop DBS systems, the stimulation artifact is too large to observe neural signals during stimulation. We contributes to the development of an advanced closed-loop system by removing stimulation artifacts and restoring spikes signals.
Non-invasive brain/bio-medical signal sensing and processing
Diagnosis of Alzheimer’s disease using portable fNIRS
Alzheimer’s disease (AD) is a chronic progressive neurodegenerative brain disease that typically presents as dementia. Although a cure for AD is currently lacking, medication therapies in the early stage can alleviate disease progression. Therefore, we develop an early diagnosis and management system for AD.
Signal processing and machine learning techniques for brain connectivity and bio-signal quality enhancement
Because the bio-signals measured with non-invasive devices are suffered by several artifacts, It is required to process signals before analyzing. Also due to the size and complexity of the data, a machine learning technique can be an effective tool for finding features. Therefore we are studying how to apply these techniques effectively to the bio-signal.
Human-inspired networks for the next generation communication (humanoid)
Humanoid will require amazing ability to process extensive information from various sensors and to react as fast as possible. In the case of humans, they process many sensory data in energy efficient. Furthermore, they can react fast against fatal sensory inputs with autonomic reflex. We study the ability of information processing in human and implement these ability for the innovative humanoid robots.
Sensory signal processing for artificial biomimetic sensors (olfactory, auditory and tactile)
We develop hardware-software convergence technology for cognitive sensory signal generation by simulating human mental sense and processing signals similar to human, and implements bio-mimetic AI for artificial touch.
Calcium Imaging signal processing
In the calcium imaging data, we find the hidden implications of the experiment through neuron detection, SNR enhancement, and behavioral experiment analysis.
- Development of multi-modal sensing and control for brain functional homeostasis (KRF)
- Development of mobile platform for Alzheimer’s disease (AD) diagnosis and relief using AI based neuro-feedback (KRF)
- Development of core technology for fusion interface based on high efficiency sensors mimicking human five senses (MSIP)