HemodynamiQ

WEARABLE SENSING + PHYSIOLOGICAL MODELLING

Connect physiology
to treatment response.

For heart-failure teams, HemodynamiQ connects two questions: what is changing in a patient’s physiology, and how might treatment affect it? ArteroSense targets fluid, flow and rhythm trends; CardioMetaIQ clinical software models treatment trajectories. Together, they are designed to support clinician-led assessment and follow-up.

Contact the teamExplore the platform

ArteroSense prototype · CardioMetaIQ clinical software
Development status & evidence ↓

CARDIOMETAIQ / THE DIGITAL TWIN

Sense the change.
Understand
the response.

The clinical value we are working towards: interpreting observed change alongside a modelled response, then checking both against follow-up evidence.

MODELCardioMetaIQ

Heart · kidney · metabolism

SENSEArteroSense

Bioimpedance + ECG prototype

Discover CardioMetaIQClinician-led interpretation

01 / THE CLINICAL VALUE

Observe change.
Explore what it means.

A physiological trend and a treatment forecast answer different clinical questions. Our proposed workflow connects them through targeted confirmation and clinician interpretation.

BEFORE TREATMENT

Which response
can we expect?

CardioMetaIQ uses the patient’s clinical context to model possible heart, kidney and metabolic responses. Clinicians can inspect the assumptions and compare trajectories before drawing conclusions.

DURING FOLLOW-UP

What is happening
between observations?

ArteroSense targets repeat observations of fluid, flow and rhythm. The intended value is a trend clinicians can investigate with targeted assessment and compare with the subsequent response.

02 / TWO PRODUCTS. ONE CARE LOOP.

Sense. Forecast.
Decide with context.

ArteroSense provides the sensing layer. CardioMetaIQ provides the modelling layer. Clinical assessment connects the two.

ARTEROSENSE01 / SENSING

Physiology you can follow.

A neck–chest bioimpedance and ECG prototype. Its development programme targets the following estimated or calculated outputs.

LVEDP
Left ventricular end-diastolic pressure
JVP
Jugular venous pressure
Pulmonary ECF
Pulmonary extracellular fluid
Cardiac output
Blood flow per minute
Stroke volume
Blood volume per heartbeat
HR
Heart rate
HRV
Heart rate variability

SIGNALS TO PHYSIOLOGY

  1. AcquireNeck–chest bioimpedance + ECG
  2. InterpretExtract beat timing, fluid and flow features
  3. Estimate & calculatePhysiological modelling + clinical calibration

Pressure and fluid estimates · Calculated flow and beat-to-beat rhythm metrics

Target outputs under development; clinical validation is pending.

CARDIOMETAIQ02 / FORECASTING

Mechanism behind the model.

Clinical software that connects patient inputs with physiological models to explore possible treatment responses.

PHYSIOLOGY-BASED CLINICAL SOFTWARE

Explore the trajectory.
Understand the mechanism.
Inspect the evidence.

Explore the modelling capabilities
  • Compare SGLT2i and incretin scenarios
  • Inspect time courses and physiological mechanisms
  • Explore 3D twin, uncertainty and validation views in the full prototype

ARTEROSENSE + CARDIOMETAIQ

The proposed clinician-mediated loop.

The aim: check modelled response against observed physiology over time, with clinical confirmation at each decision.

  1. 01Wearable sensingArteroSense · bioimpedance + ECG
  2. 02Physiological interpretationFluid, flow, pressure and rhythm
  3. 03Targeted confirmationRelevant clinical assessment
  4. 04Digital-twin integrationCardioMetaIQ · signals, echo + labs
  5. 05Individualised interpretationClinical review of modelled trajectories
  6. 06Clinician decisionReview, select and adjust care
  7. 07Longitudinal follow-upTrack observed response over time

Close the loop: compare the observed follow-up with the modelled trajectory, then review the clinical interpretation.

CARDIOMETAIQ / A HEMODYNAMIQ WEARABLES PRODUCT

The patient’s phenotype.
The possible response.

CardioMetaIQ is clinical software for modelling treatment response across heart, kidney and metabolism, with a focus on HFpEF, obesity and type 2 diabetes.

Visit the CardioMetaIQ website (opens in a new tab)

IN-SILICO CLINICAL TRIALS

Explore the design before the study.

Generate a virtual cohort, apply eligibility criteria and compare simulated treatment and control outcomes. Explore how eligibility and response assumptions change synthetic outcome distributions.

Open trial workspace ↗
How CardioMetaIQ works · capabilities & sources
01 / DEFINE

Enter the phenotype.

Baseline weight, cardiac function, symptoms, biomarkers, diabetes status and background therapy establish the clinical context.

02 / SIMULATE

Explore a therapy.

Agent, dose and sequencing feed a coupled physiological model. Cardiac, renal and metabolic responses evolve together over time.

03 / REVIEW

Read beyond a score.

Inspect 52-week trajectories, comparator-adjusted effects, uncertainty and the evidence behind the projected response. Nothing is auto-prescribed.

SOFTWARE CAPABILITIES

Therapy comparisonReceptor pharmacology52-week trajectoriesMonte Carlo uncertaintyMechanistic explainabilityValidation workflows

Evidence you can inspect. The CardioMetaIQ site documents calibration against SUMMIT, STEP-HFpEF and STEP-HFpEF-DM, alongside echocardiography and sensitivity analyses.

Technology (new tab)Validation (new tab)Evidence & walkthrough (new tab)

Calibration and model reproduction do not establish individual-patient predictive accuracy. See the development status below.

03 / RESEARCH DEMONSTRATION

Explore a modelled
treatment trajectory.

Explore the STEP-HFpEF base simulation: semaglutide versus placebo across 52 weeks of modelled response.

CardioMetaIQTrajectories · v4.8
STEP-HFpEF · 52 WEEKS

MODELLED BODY WEIGHT

90.77 kg

Total body weight.

89.195.0100.9106.8BaselineW13W26W39W52
SemaglutidePlacebo
Placebo · week 52102.91kg
Semaglutide change from baseline-14.33kg
Semaglutide − placebo-12.14kg
Scope, assumptions & provenance

CardioMetaIQ v4.8 · supplied release dated 4 October 2026. Trial-defined baseline, 52-week horizon, 96.4% without and 3.6% with empagliflozin background in each arm. Curves are arithmetic mixture averages.

The 3.6% fraction is a release input from secondary summaries, checked for consistency with pooled primary counts. Unreported mechanistic baseline fields are reference-imputed. Renal slopes and dip remain carried assumptions. No uncertainty intervals are shown.

KCCQ-CSS and 6-minute walk distance are derived read-outs calibrated to this trial. Matching those endpoints does not demonstrate independent or individual-patient predictive accuracy.

Numerical audit · 4 October 2026 · STEP-HFpEF publication · 25 August 2023 (new tab)

Precomputed simulations for research illustration. Not patient measurements, a personalised forecast or treatment advice.

52-week trajectories · STEP-HFpEF baseline · v4.8Investigational demonstration

04 / DEVELOPMENT & EVIDENCE

What works today.
What comes next.

Status reviewed 4 October 2026. Source dates and the scope of each evidence item are shown below.

ENGINEERING FEASIBILITY

Signals acquired.

Company-reported alpha-board recording of ECG and dual-site neck–chest bioimpedance. Accuracy of the target clinical outputs remains to be evaluated.

Source: THT2027 Shark Tank deck · reviewed . Recording date not specified.Source scope
CLINICAL SOFTWARE

Models implemented.

Implemented physiological modelling and virtual-cohort workflows. The website demonstrates stored v4.8 trajectories and a separate analytic trial model.

v4.8 numerical audit · . Reproducibility is distinct from clinical validation.View numerical audit (JSON)
PLANNED CLINICAL EVALUATION

Patient-level testing.

A signed principal-investigator letter of intent supports a proposed retrospective CardioMetaIQ study at Fortis Mohali.

LOI signed · study intent, not completed validation or institutional endorsement.Read study-source summary
Demonstration methods, evidence & limitations
STEP-HFpEF trajectories

Semaglutide and placebo simulations over 52 weeks, generated with the supplied v4.8 engine. The controls inspect stored results; they do not predict an individual patient’s response.

Virtual trial exploration

An analytic weight-loss model generates synthetic profiles and responses. Results show the consequences of assumptions, not prospective drug efficacy or a validated enrolment recommendation.

Model evidence and limitations

In the supplied v4.8 endpoint audit, the week-52 weight-loss treatment difference is −11.55 percentage points versus the reported −10.7. KCCQ-CSS and 6-minute walk treatment differences are calibration anchors, so matching them is not an independent test.

The hs-CRP treatment ratio is approximately 0.727, slightly outside the supplied published interval of 0.51–0.72. Mechanistic baseline fields may be imputed, and some renal assumptions remain unanchored. These limitations are retained rather than hidden by a single accuracy score.

Source: v4.8 numerical audit, 4 October 2026; STEP-HFpEF trial, 25 August 2023 (new tab). Clinical validity, prospective utility and performance of the combined wearable–software workflow remain to be established.

05 / THE FOUNDING TEAM

Built on science.
Led by experience.

Computational modelling, wearable engineering and MedTech operations—brought together to build HemodynamiQ.

FOUNDER · CHIEF TECHNOLOGY OFFICER

Dr. Deepanjan Datta, PhD

CTO

PhD in Electrical Engineering
Purdue University
BTech in Electrical Engineering
IIT Dhanbad

15 years of experience in computational modelling, impedance physics and wearables. Inventor and developer of the ArteroSense sensing platform and the CardioMetaIQ mechanistic digital twin.

SCIENTIFIC & TECHNICAL LEADERSHIP

Physiological modelling · Bioimpedance · Wearable systems

LinkedIn profile ↗

CO-FOUNDER · CHIEF EXECUTIVE OFFICER

Sai Kamalesh, MSc

CEO

MSc in Electrical Engineering
Acharya Nagarjuna University, India

30+ years across aerospace, defence, MedTech and telecommunications. Co-inventor of the sensing platform, with experience scaling product engineering and operations for global MedTech OEMs.

BUSINESS & OPERATIONAL LEADERSHIP

Product engineering · MedTech operations · Commercial execution

LinkedIn profile ↗
Explore our patent portfolio

06 / INTELLECTUAL PROPERTY

A foundation
of invention.

Our sensing patent portfolio includes two patents granted by the USPTO and one published patent family, with a US application publication and a PCT international publication.

Two US grants and one additional published US/PCT application family. Publications are distinguished from grants.

These records concern sensing technology. A patent grant does not establish clinical performance or regulatory clearance. The US and PCT publications of the pending application are counted together.

07 / BUILD THE NEXT CHAPTER WITH US

A better view
starts with
a conversation.

For clinical research, technology partnerships, company information and investor enquiries.

Contact the team

Tell us about your interest in HemodynamiQ. For a direct conversation, email deepanjan.datta@hemodynamiq.com.

Contact HemodynamiQ

Please don’t submit patient information. This is a company enquiry form, not a clinical consultation or patient-enrolment service.

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