01 Technology overview

A different starting point for ECG classification.

Arrhyva is being developed as a patient-independent classification engine: software designed to work from a new patient’s first recording, without a patient-specific calibration period.

02 Core difference

From raw ECG signal to actionable cardiac intelligence.

ECG acquisition

High-fidelity signals captured across devices and conditions.

Signal acquiredMulti-device input

Signal isolation

Mathematically isolate cardiac signal from background noise and variation.

Signal cleanedNoise reduced

Beat intelligence

Advanced models classify each beat and extract clinically relevant features.

Live analysisModel A-03

Beat classificationNormal sinus rhythmBeat morphology and timing remain within the expected range.

72BPM96%Confidence18 msLatency

NormalPVCPAC

Device integration

Seamless integration into clinical workflows and connected health ecosystems.

Connected ecosystemClinical output

Connected ECG monitor, laptop, and wearable ecosystem

Integrated outputConnected review workflow

03 Patient-independent architecture

Static Arrhyva architecture principles overview showing four simplified design principles: no patient-specific calibration, patient-independent evaluation, signal-first architecture, and software-level integration.

04 Public technical view

From incoming ECG to classified beat.

This public overview intentionally protects patent-pending implementation details. Deeper architecture, reproducibility material and integration requirements are reserved for qualified technical conversations under NDA.

Input

ECG input

Raw waveform

Processing

Signal engine

Protected architecture

Classification

Beat class

PVC / PAC / Normal

Detailed implementation and model internals remain confidential and available under NDA.

05 Next step

Explore the technology behind the signal.

Let’s connect to discuss how Arrhyva can integrate into your platform and workflows.

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