Computational Physiology Research

SIAGNOS

Research in Computational Physiology & Neuroengineering

Research in cerebrocardiovascular modeling, neurostimulation, wearable sensing, and computational physiology.

brain–heart signals

live
ECG
EEG
fNIRS
6Research Areas
12+Open-source Projects
ResearchGatePublications

Research

My work sits at the intersection of physiology, signal processing, and control theory — developing computational tools to understand and augment the human body. Focus areas span the following themes.

Cerebrocardiovascular Modeling

Coupling cardiovascular and cerebrovascular dynamics to understand brain–heart interactions across states.

Wearable ECG, EEG, & Hemodynamics

Multimodal sensing and signal processing of ambulatory ECG, EEG, and hemodynamic waveforms.

Neurostimulation

Neuromuscular and neural electrical stimulation strategies for modulation, recovery, and control.

Computational Physiology

Building computational models that couple cardiovascular, cerebrovascular, and neural systems.

Machine Learning for Biomedical Signals

Data-driven methods for decoding, denoising, and interpreting physiological time series.

Rehabilitation Engineering

Stimulation- and sensing-driven approaches to support recovery, conditioning, and assisted movement.

Featured Projects

CV-Model-NMES

Siagnos / CV-Model-NMES

Computational

Computational modeling framework for investigating interactions between cardiovascular and cerebrovascular dynamics.

Hemodynamic Changes During Hypnosis

NIRS-Hypnosis · PHFD Conference 2026

Neuroimaging

Exploratory whole-head time-domain functional near-infrared spectroscopy of audio-locked haemodynamic responses across hypnotic induction, suggestion, and awakening. This four-participant healthy case series uses time-domain moment-zero signals; the observed forehead responses are candidate state-related readouts, not validated cortical biomarkers.

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Original Hemodynamic Changes During Hypnosis presentation, slide 1 of 20

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PHFD 2026 presentation · 20 original PNG slides (2933 × 1650). The slides are displayed without recreation or modification.

Contact

Open to collaboration and conversation. Reach out through any of the channels below.