PhysioSense.AI — Physiological Signal Intelligence

Making Sense of Physiological Signals

PhysioSense is an applied research company transforming waveform and sensor data into interpretable physiological intelligence for payers, pharma, clinical, device partners, and research organizations to detect, track, and act on physiological change earlier than conventional vital signs allow.

Signal → Intelligence Pipeline
WAVEFORM INPUT PPG · rPPG · ABP · ECG VASCUSENSE ENGINE SensorFusion + AI Models PHYSIOLOGICAL OUTPUTS Load Compliance Reserve Timing Coupling Applications CLINICAL Vascular Radar ICU Monitoring State-Space PAYER / EMPLOYER PulseVu Platform Member Programs Risk Stratification DEVICE / WEARABLE REST API PhysioStack SDK Embedded Inference PHARMA / RESEARCH Drug Response Tracking Study Enrichment Academic Collab

PhysioSense converts raw physiological waveforms into structured, interpretable intelligence.

50,000+ Patient records analyzed
100% Explainable Mechanistic Model
6+ Validated Clinical Domains
Regulatory Pedigree De Novo & 510(k) Cleared Device Experience

The Intelligence Layer for Physiological Waveforms

We leverage foundational waveform science and sensor-agnostic infrastructure to provide clinical, enterprise, and research partners with a unified pathway to predictive insights.

Three-Layer Architecture

Layer 1: Signals In

Multimodal Data Ingestion

PPG, rPPG (camera), ABP, ECG — raw and multimodal sensor data from bedside, wearable, or smartphone.

Layer 2: The VascuSense Engine + SensorFusion

Kinetic Decomposition

Patent-protected kinetic decomposition extracts high-level vascular proxies across load, compliance, reserve, timing, and coupling dimensions. SensorFusion creates higher-value multimodal embeddings.

Layer 3: Interpretable Intelligence

Actionable Phenotyping

Explainable physiological state, trajectory, and response — not black-box scores. Continuous longitudinal tracking of vascular phenotype across clinical and programmatic contexts.

Universal Vascular Phenotyping

Mechanistic extraction of interpretable vascular proxies from pulsatile waveforms — capturing vascular load, compliance, reserve, timing, and coupling - with a clinical translation for each dimension.

MechanisticHigh-FidelitySensor-agnostic

SensorFusion Layer

Combines raw signals and derived physiological descriptors into higher-value fusion embeddings — optimized for risk prediction, longitudinal monitoring, real-time alerting, and integration into partner analytics platforms.

MultimodalReal-timeAPI-ready

State-Space Trajectory Modeling

Patient physiological state is tracked as a continuous trajectory through an interpretable multi-dimensional space — enabling deterioration detection, treatment response monitoring, and longitudinal phenotype comparison.

LongitudinalExplainablePredictiveAlerting

From Smartphone to Clinical Platform

The same foundational waveform science powers both an enterprise-deployed member engagement platform and an advanced clinical monitoring app — demonstrating the full deployment range of PhysioSense technology.

● Enterprise Platform

PulseVu

A 30-second smartphone pulse reading delivers an enterprise-grade physiological assessment — white-label configurable for payer member engagement, employer wellness, and care management programs.

Composite physiological health score (0–100) with 8 evidence-based vascular and autonomic metrics
Cohort-Specific Tracking Modules — Configurable physiological baselines designed to support care management for complex chronic populations (Cardiac, Neuro, and Renal).
On-device AI assessment and member-facing or clinician-facing chat interface
Vascular embedding API — physiological signals integrated into partner risk models, EHRs, and claims analytics
Regulatory positioned as physiological tracking and alerting — not diagnosis or treatment
PulseVu Smartphone Interface
● CLINICAL PLATFORM

Vascular Radar

Real-time physiological state visualization for ICU and critical care. Continuous trajectory mapping visualizes a patient's past, present, and future physiological state—identifying critical shifts before conventional vitals react.

Dynamic Mapping: Real-time visualization of complex vascular phenotypes.
Trajectory Intelligence: Proactive forecasting of physiological drift and patient trends.
Automated alerting that bridges the gap between data and clinical intervention.
Conceptual Example: Hydration Volume Trajectory Optimal Hydration Mild Fluid Loss Moderate Fluid Deficit Severe Volume Loss Median historic track Historic points Current status

SensorFusion REST API

Processes PPG, ECG, and ABP signals with minimal integration effort. Designed for embedding PhysioSense intelligence into partner analytics, EHR, or care management platforms.

REST API Cloud Deploy

PhysioStack SDK

Plug-and-play software stack for signal conditioning, feature extraction, and on-device physiological inference — deployable in wearable, mobile, and embedded environments.

On-device SDK

Foundational AI Models

Pre-trained models for physiological signal interpretation across multiple modalities. Fine-tunable for partner-specific populations, clinical contexts, and proprietary signal datasets.

Pre-trained Fine-tunable

Evidence Across Critical Care

PhysioSense has been evaluated across multiple acute care cohorts, consistently demonstrating that non-invasive waveform-derived physiological features correlate with clinically meaningful changes — often well before conventional vital signs reflect them.

Sepsis & SIRS
Early detection
Vascular phenotype signatures consistently aligned with zero-hour SIRS onset were detectable well before clinical confirmation. Distinct physiological profiles separated stable, deteriorating, survivor, and non-survivor cohorts — without reliance on lab values.
↑ Research showed separation hours before clinical onset.
Hemorrhage & Hypovolemia
Pre-symptomatic detection
Arterial compliance changes were detected before any heart-rate or blood-pressure response in controlled physiological challenge models. Findings replicated in real-world ICU validation, with distinct waveform signatures separating hemorrhagic from non-hemorrhagic states.
↑ Detects before hemodynamic instability
Traumatic Brain Injury
Non-invasive ICP surrogate
Peripheral PPG-derived signatures were associated with intracranial physiological events across the critical 48–72 hour cerebral edema window — validated against direct intracranial pressure measurements. Distinct "spiker" vs. "flatliner" phenotypes with diverging outcomes identified non-invasively.
↑ ICP-correlated signal from peripheral PPG
Shock — Multi-Type
Trajectory differentiation
Survivor and non-survivor vascular trajectories exhibited distince patterns across hemorrhagic, septic, and cardiogenic shock types. State-space trajectories clearly differentiated outcome groups in ways that aggregate vital signs could not — enabling earlier clinical decision support.
↑ Survivor/non-survivor separation in state-space
Burns
Phase transition detection
Vasoconstricted early burn shock and late distributive burn phases produce physiologically distinct state-space trajectories. Vascular phenotyping mapped burn-phase identification from waveform alone — with direct relevance for fluid management timing and prognostication.
↑ Burn phase identified from PPG alone
Medication Response Tracking
Real-time drug footprinting
Waveform-derived indices allow for the visualization of distinct vasodilatory and vasoconstrictive signatures, alongside broader shifts in vascular properties. This provides a method for tracking physiological trendsfollowing medication administration without requiring additional instrumentation.
VASCULAR RESPONSE MEDICATION DOSE Vasoconstrictor Vasodilator Time Post-Admin →

Extending into Chronic Disease, Aging & Payer Programs

Beyond acute care, PhysioSense has research addressing dementia and cognitive decline, cardiopulmonary deterioration, CHF, CKD, stroke, diabetes, and related metabolic and neurovascular physiology — creating collaborative opportunities at the intersection of longitudinal physiological monitoring, early risk identification, and enterprise payer programs.

Dementia / Cognitive Decline Cardiopulmonary / CHF CKD / Diabetes Stroke & Metabolic Risk

Regulatory Status: PhysioSense technology is currently for Research Use Only (RUO). The clinical findings and physiological "signatures" described above are results from investigational studies and have not been cleared by the FDA for diagnostic or therapeutic use.

Who We Serve

The PhysioSense platform is broad enough to serve enterprise, clinical, scientific, and translational partners — while each deployment is tailored to the specific organization's signals, workflows, and outcomes.

Health Insurers

Signal-enabled member programs, risk stratification, and proactive care management — deployed via PulseVu or embedded API.


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Pharmaceutical

Mechanistic drug response tracking, study enrichment, patient stratification, and longitudinal physiological phenotyping for clinical programs.


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Patient Monitoring

Next-generation waveform interpretation layers and product differentiation for ICU and hospital-grade monitoring systems.


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Wearable Companies

Advanced physiological insights extending sensor value beyond standard vitals — vascular load, compliance, and autonomic reserve dimensions.


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Research & Academia

Translational research models, analytics infrastructure, and collaborative programs for NIH-funded and institutional science efforts.


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Defense & Gov't

Physiological monitoring for operational health, combat casualty care, and non-invasive field-deployable assessment programs.


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Protected Innovation

PhysioSense holds an active patent portfolio covering its core waveform phenotyping, state estimation, hemodynamic characterization, and visualization methods — establishing defensible IP across the physiological signal interpretation space. Patent details are available to qualified partners under NDA.

PhysioSense VascuSense Waveform Representation Physiological State Estimation Hemodynamic Characterization Metabolic & Organ Function Multi-Dimensional Visualization Pulsatile Signal Interpretation

IP Coverage Areas

The PhysioSense portfolio protects core methods across six distinct technology areas — spanning waveform interpretation, physiological state modeling, hemodynamic characterization, metabolic assessment, clinical visualization, and signal representation. This breadth establishes a defensible competitive moat across the physiological signal intelligence space.

Waveform Representation & Feature Extraction
Multi-Compartment Physiological State Estimation
Hemodynamic Characterization via Kinetic Decomposition
Metabolic & Organ Function Estimation from Physiological Signals
Multi-Dimensional Vascular State Visualization
Pulsatile Signal Interpretation Using Physiological Proxies

Available to qualified partners. Patent details, coverage maps, and licensing terms are available under NDA for organizations evaluating strategic partnerships or technology licensing.

Deep Domain Expertise

Decades of combined experience in physiological signal processing, AI/ML, embedded systems, FDA-regulated medical device development, and translational product commercialization.

John Jedziniak
John Jedziniak
CEO / CTO
Deep background in physiological signal processing, medical device development, and FDA-regulated product commercialization spanning de novo and 510(k) submissions. Experience leading product development and technology strategy for companies including Amgen, Proteus, Medtronic, and Quidel. Advisor to healthcare organizations on how physiological signal technologies can unlock clinical and commercial value.
Medical Devices FDA Regulatory Waveform Science Signal Advisory
Abhi Jaiantilal
Abhishek Jaiantilal, PhD
Chief Science Officer
Deep expertise in physiological AI/ML, signal processing algorithms, and translational research. Led development of multiple FDA-cleared physiological signal technologies including PPG, ECG, and hemodynamic monitoring systems. Extensive experience in large-scale R&D programs and clinical validation across acute and chronic disease populations.
AI / ML Signal Processing Translational Research

Built for Collaboration

PhysioSense can engage through multiple partnership models — each tailored to the partner's product stage, clinical context, and commercialization path. We are the explainable physiology and waveform intelligence layer within your program.

Signal Intelligence Advisory — opportunity mapping, program design, and technical strategy for healthcare organizations exploring the ROI of physiological signal data. An ideal starting point for payers, pharma, and device companies evaluating where signals unlock value.
Pilot Programs — focused feasibility studies to validate PhysioSense intelligence in your specific population, claims cohort, or clinical workflow. Structured 8–12 week sprints with clear go/no-go milestones.
Technology Licensing — platform components, models, and IP for integration into partner products, EHRs, or analytics platforms.
Co-Development — joint development of clinical or enterprise applications built on PhysioSense infrastructure, co-owned IP pathways available.
Translational Research — collaborative programs with academic, government, and clinical institutions. NIH and DOD funding-compatible.
How Partners Engage
Health Insurer

Deploy PulseVu to support population health initiatives for complex cohorts. Vascular embeddings provide additional context for longitudinal tracking, helping care teams prioritize outreach and support clinical management goals.

Pharmaceutical

Non-invasive physiological phenotyping to enrich clinical trial populations, visualize physiological trends post-administration, and characterize mechanistic shifts in vascular state — particularly where waveform-derived biomarkers add precision.

Wearable / Device

Embed PhysioSense signal intelligence into existing PPG-capable devices to unlock physiological descriptors beyond heart rate and SpO2 — differentiated features that justify premium positioning and enterprise channel strategies.


DISCLAIMER: PhysioSense technology, including PulseVu and Vascular Radar, is for research and investigational purposes only. It is not an FDA-cleared medical device and is not intended for use in the diagnosis, cure, mitigation, treatment, or prevention of disease. All "detections" or "identifications" mentioned refer to patterns observed in research settings and are not clinical diagnoses.