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Our Research
User Authentication Using Biosignal
User Authentication Using Biosignal
User authentication using biosignals
that reflect individual-specific physiological characteristics.
Research Achievements
University Priority Research Centers Program
"User Authentication Technology Based on Wearable Devices Using Multi-Biosignal"Multi-Stream Conformer-Based User Identification System Using 2D CQT Spectrogram Tailored to Multiple Biosignals, IEEE Access.
User Identification System Based on 2D CQT Spectrogram of EMG with Adaptive Frequency Resolution Adjustment, Scientific Reports.
Electromyogram Based Personal Recognition Using Attention Mechanism for IoT Security, Computers, Materials & Continua.
Driver Identification System Using 2D ECG and EMG Based on Multi-stream CNN for Intelligent Vehicle, IEEE Sensors Letters.
Multimodal Biosignal Dataset Development
Multimodal Biosignal Dataset Development
Development of multimodal biosignal datasets
for user identification and mental state analysis.
Research Achievements
Multi-Session Electrocardiogram-Electromyogram Database for User Recognition, Applied Sciences.
Multi-Session Surface Electromyogram Signal Database for Personal Identification, Sustainability.
The database is publicly available on the IT Research Institute website. (www.chosun.ac.kr/riit)
Biosignal-based Psychological State Classification
Biosignal-based Psychological State Classification
Psychological state classification using biosignals
to model human physiological and mental variations.
Research Achievements
Stress Classification using ECGs based on a Multi-dimensional Feature Fusion of LSTM and Xception, IEEE Access.
Deep Facial Emotion Recognition Using Local Features Based on Facial Landmarks for Security System, Computers, Materials & Continua.
Improvement of Negative Emotion Recognition in Visible Images Enhanced by Thermal Imaging, Sustainability.
Biometric Information Protection
Biometric Information Protection
Privacy-preserving biometric information protection
based on bio-hashing and cancelable biometric templates.
Research Achievements
Research Subsidies for Ph.D. Candidates
"A Study on Bio-Hashing Technology based on Contrastive Learning for Cancelable Biosignal Template Generation"Fake Electrocardiogram Signal Analysis to Detect Spoofing Attacks in Biometrics, IEEE Sensors.
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