26-30 July 2026

EMBC 2026

Toronto, Canada
We.1.2: Generative and Self-Supervised Learning for Neural Signals
Wednesday, 29 July, 08:30 - 10:00
Location: Room 801A
Session Type: Oral
Session Co-Chairs: Bramsh Qamar Chandio and Xinqi Bao
Theme 1: Biomedical Signal Processing
Wed, 29 Jul, 08:30 - 08:45

We.1.2.1: Diffusion-Based Heart Sound Generation Evaluation with Physiological Signal Metrics, Classifiers, and Expert Listening
Xinqi Bao, KTH Royal Institute of Technology; Jia Bi, Rutherford Appleton Laboratory; Xin Chen, Peng Cheng Laboratory; Ernest Kamavuako,, King's College London; Saikat Chatterjee, KTH Royal Institute of Technology
Wed, 29 Jul, 08:45 - 09:00

We.1.2.2: Random Feature Mapping vs. Last-Layer Fine-Tuning for Biosignal Transfer Learning: Toward a Zero-Source Baseline
Takayuki Hoshino, Keio University / National Institute of Advanced Industrial Science and Technology; Suguru Kanoga, National Institute of Advanced Industrial Science and Technology; Atsushi Aoyama, Keio University
Wed, 29 Jul, 09:00 - 09:15

We.1.2.3: RL-BIOAUG: LABEL-EFFICIENT REINFORCEMENT LEARNING FOR SELF-SUPERVISED EEG REPRESENTATION LEARNING
Cheol-Hui Lee, Hwa-Yeon Lee, Seoul National University Hospital; Dong-Joo Kim, Korea Unversity
Wed, 29 Jul, 09:15 - 09:30

We.1.2.4: MTSSRL-MD: Multi-Task Self-Supervised Representation Learning for EEG Signals across Multiple Datasets
I-Hui Li, Oscar Tai-Yuan Chen, Vincent S. Tseng, National Yang Ming Chiao Tung University
Wed, 29 Jul, 09:30 - 09:45

We.1.2.5: WaveTok: A Wavelet Tokenizer for Self-Supervised EEG Representation Learning
Jing Wang, Ercan Engin Kuruoglu, Tsinghua University
Wed, 29 Jul, 09:45 - 10:00

We.1.2.6: Class-Conditioned Diffusion-Based EEG Generation for Motor Imagery in the Spectral Domain
Deeksha Kashyap, Srirama Swamy, Chaitanya Makkar, Gowri Srinivasa, PES University