Brain Machine Interface Team
Closed-loop system for regulation of Parkinson’s disease
Stimulation artifact cancellation
Diagnosis of Alzheimer’s disease using fNIRS
Brain connectivity and bio-signal quality enhancement
Human-inspired networks for future robots
Sensory signal processing
Calcium imaging signal processing
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.
Additional researches
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.
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 way. 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.
Related projects
The prefrontal circuit motifs in healthy brain and brain with emotional abnormalities(KBRI)
Minimum invasive AI-based E-brain development for brain disease relief (MSIP)
Development of core technology for fusion interface based on high efficiency sensors mimicking human five senses(NRF)
Development of multi-modal sensing and control for brain functional homeostasis (NRF)
Development of mobile platform for Alzheimer’s disease (AD) diagnosis and relief using AI based neuro-feedback(NRF)
Development of fusion parts for 3.5 Tesla 6 channel magnetic stimulation and information feedback for a cure for intractable brain disease(MEST),
Rehabilitation and replacement technology for brain damage employing electrical method(MSIP)
Development of microbiorobotic systems for surgical treatment of chronic total occlusion(MEST)
Physiological tactile sensor developments(Samsung Electronics)
Development of bi-directional multi-channel neural electrodes and implantable wireless power/data transmission modules(NRF)
Related Societies
IEEE Engineering in Medicine and Biology Society https://www.embs.org/
Organization for Computational Neurosciences https://www.cnsorg.org/
Society for Neuroscience https://www.sfn.org/
The Society for functional Near Infrared Spectroscopy (SfNIRS) https://fnirs.org/
The Korean Society for Brain and Neural Sciences (KSBNS, 한국뇌신경과학회) http://www.ksbns.org/
Korean Society for EEG and Neurophysiology (KEEG, 대한뇌파신경생리학회) https://keeg.or.kr/index.htm?
Brain Engineering Society of Korea (BESK,한국뇌공학회) http://besk.kr/
The Korean Society of Medical & Biological Engineering (KOSOMBE, 대한의용생체공학회) http://www.kosombe.or.kr/
Related Conferences
Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) https://embc.embs.org/
IEEE International Winter Conference on Brain-Computer Interface https://brain.korea.ac.kr/bci2018/registration/registration.php
Organization for computational neuroscience (CNS) https://www.cnsorg.org/calendar
Society for Neuroscience SFN https://www.sfn.org/meetings/calendar
KSBNS Conference https://www.ksbns.org/notice/?gbn=2&htop=MN0005&ctop=MN0032&ptop=MN0005
KEEG Conference https://keeg.or.kr/index.htm