Projects

Development of AI-Based respiratory-synchronized 

wearable and implantable electronic diaphragm system

Funding Period | Apr. 2025 – Feb. 2027

In collaboration with Inha Univ. & Chung-Ang Univ. College of Medicine

Ultrathin Soft Bioelectronics
Development of tissue-conformal, highly conductive ultrathin electrodes for stable multichannel electrical stimulation of the diaphragm.

Minimally & Non-Invasive Interfaces
Design of minimally invasive and non-invasive soft electronic systems that provide efficient diaphragm stimulation while minimizing mechanical and biological burden.

AI-Driven Personalized Therapy
Real-time physiological signal analysis and adaptive stimulation control for personalized diaphragm rehabilitation and spontaneous breathing recovery.

Adaptive Sweat ControlBased Hybrid Multimodal Platform 

for Muscle Function Sensing and Augmentation in Space Environments

Funding Period | Mar. 2026 – Feb. 2031

Independent Project

Adaptive Sweat Management
Control of sweat accumulation at the skin–electrode interface through passive nanostructured wicking and electrowetting–dewetting strategies.

Multimodal Muscle Sensing
Simultaneous acquisition of electrophysiological signals and sweat-derived biomarkers using multifunctional wearable bioelectronic interfaces.

AI-Enabled Closed-Loop Stimulation
Real-time assessment of muscle function from multimodal biosignals and personalized closed-loop stimulation for maintaining and enhancing muscle performance, including under microgravity conditions.

Electrokinetic Biomolecular Manipulation 

for Biofluid-Based Diagnostics

Project Period | Oct. 2025 – Feb. 2027

In collaboration with Sangji Univ.

Electric-Field-Driven Manipulation
Application of electrophoresis (EP) and dielectrophoresis (DEP) for controlled transport and manipulation of biomolecules.

Filtration & Concentration
Selective filtration, separation, and enrichment of low-abundance biomarkers to improve downstream analytical performance.

Integrated Biosensing
Integration of electrokinetic biomolecular handling with multiplexed biosensors to enhance detection sensitivity and support early diagnosis of neurodegenerative diseases.

Hair-Adaptive Bioelectronics interfaces for Neural Monitoring

In collaboration with SKKU

Hair-adaptive scalp bioelectronic technologies are developed to enable stable, high-fidelity neural signal acquisition through hair-covered scalp using ultrathin stretchable electrodes and morphing substrates. Integrated with AI-based biosignal coupling, the platform supports real-time monitoring and prediction of severe neurological conditions.

Hair-Adaptive Scalp Interface
Development of ultrathin stretchable electrodes integrated with morphing substrates to penetrate hair-covered regions and establish conformal contact with the scalp.

High-Fidelity Neural Sensing
Stable, long-term acquisition of EEG signals with reduced contact impedance and improved signal reliability in complex scalp environments.

AI-Enabled Neurological Monitoring
Integration of EEG with physiological signals through AI-based coupling models to enable real-time detection and prognosis prediction of severe neurological disorders.

Multimodal Monitoring of Parkinson’s Disease

Independent Project — Open for Collaboration

Multimodal Gait Analysis
Quantitative assessment of gait and motor function using electromyography (EMG) and motion-derived signals.

Blood-Based Biomarker Profiling
Analysis of circulating biomarkers associated with disease status and motor dysfunction in Parkinson’s disease.

Motor–Biomarker Correlation
Integration of digital motor phenotypes with blood-based biomarkers to identify relationships between physiological changes and disease progression for longitudinal patient monitoring.