12 citations · 12 across the 11 of their papers we have counts for
5 papers · 1 filter
Property-Specific Recoverability from Contact PPG to Camera rPPG under Heterogeneous Observation Conditions
Timothy Oladunni, Farouk Ganiyu-Adewumi
Camera-derived remote photoplethysmography (rPPG) is commonly validated through endpoint accuracy, but endpoint performance does not establish whether other physiological propertie…
CFD-Guided Detection of Concept Drift in Multimodal Physiologic Signals
Farouk Ganiyu Adewumi, Timothy Oladunni, Rochak Ghimire +3
Cardiovascular AI models can classify clean elec- trocardiogram (ECG) signals, but real wearable signals change because of motion, breathing, posture, sensor contact, and true clin…
A Nonlinear Complexity Index for Wearable PPG Cardiovascular Stability: Multiscale Validation, Systematic Evaluation Correction, and Bayesian Parameter Optimization
Timothy Oladunni, Farouk Ganiyu Adewumi
Cardiovascular stability estimation from wearable photoplethysmography (PPG) requires a principled nonlinear framework, yet major gaps persist in heuristic parameter selection and…
Complementarity-Preserving Generative Theory for Multimodal ECG Synthesis: A Quantum-Inspired Approach
Timothy Oladunni, Farouk Ganiyu-Adewumi, Clyde Baidoo +1
Multimodal deep learning has substantially improved electrocardiogram (ECG) classification by jointly leveraging time, frequency, and time-frequency representations. However, exist…
Explainable Deep Neural Network for Multimodal ECG Signals: Intermediate vs Late Fusion
Timothy Oladunni, Ehimen Aneni
The limitations of unimodal deep learning models, particularly their tendency to overfit and limited generalizability, have renewed interest in multimodal fusion strategies. Multim…