1 citations · 2 across the 9 of their papers we have counts for
9 papers
Blood Pressure Estimation from PPG: A Comparative Study of Direct and ECG-Mediated Deep Learning Pipelines
Bo Wu, Haoling Wang, Zhuodiao Kuang +1
Continuous cuffless blood pressure (BP) monitoring is essential for connected health systems and wearable devices, enabling early detection, longitudinal tracking, and personalized…
ASPEN: Spectral-Temporal Fusion for Cross-Subject Brain Decoding
Megan Lee, Seung Ha Hwang, Inhyeok Choi +3
Cross-subject generalization in EEG-based brain-computer interfaces (BCIs) remains challenging due to individual variability in neural signals. We investigate whether spectral repr…
MultiDiffNet: A Multi-Objective Diffusion Framework for Generalizable Brain Decoding
Mengchun Zhang, Kateryna Shapovalenko, Yucheng Shao +2
Neural decoding from electroencephalography (EEG) remains fundamentally limited by poor generalization to unseen subjects, driven by high inter-subject variability and the lack of…
Typing Reinvented: Towards Hands-Free Input via sEMG
Kunwoo Lee, Dhivya Sreedhar, Pushkar Saraf +2
We explore surface electromyography (sEMG) as a non-invasive input modality for mapping muscle activity to keyboard inputs, targeting immersive typing in next-generation human-comp…
Aligning Brain Signals with Multimodal Speech and Vision Embeddings
Kateryna Shapovalenko, Quentin Auster
When we hear the word "house", we don't just process sound, we imagine walls, doors, memories. The brain builds meaning through layers, moving from raw acoustics to rich, multimoda…
A Penny for Your Thoughts: Decoding Speech from Inexpensive Brain Signals
Quentin Auster, Kateryna Shapovalenko, Chuang Ma +1
We explore whether neural networks can decode brain activity into speech by mapping EEG recordings to audio representations. Using EEG data recorded as subjects listened to natural…
SVeritas: Benchmark for Robust Speaker Verification under Diverse Conditions
Massa Baali, Sarthak Bisht, Francisco Teixeira +3
Speaker verification (SV) models are increasingly integrated into security, personalization, and access control systems, yet their robustness to many real-world challenges remains…
Decoding EEG Speech Perception with Transformers and VAE-based Data Augmentation
Terrance Yu-Hao Chen, Yulin Chen, Pontus Soederhaell +2
Decoding speech from non-invasive brain signals, such as electroencephalography (EEG), has the potential to advance brain-computer interfaces (BCIs), with applications in silent co…
Improving SSVEP BCI Spellers With Data Augmentation and Language Models
Joseph Zhang, Ruiming Zhang, Kipngeno Koech +2
Steady-State Visual Evoked Potential (SSVEP) spellers are a promising communication tool for individuals with disabilities. This Brain-Computer Interface utilizes scalp potential d…