Arrhythmia Detection Specifications | PPG AFib Algorithm Accuracy

Arrhythmia Detection Specifications | PPG AFib Algorithm Accuracy

Disclaimer: The PPG arrhythmia and AFib function is a wellness screening tool only. It cannot be used for medical diagnosis, treatment, or disease assessment. All detection results are for reference. End products must carry mandatory disclaimers before market launch.

Introduction

Vositone’s multi-channel PPG AFib screening algorithm delivers reliable arrhythmia detection for wearable OEM partners. This technical specification document outlines algorithm architecture, clinical validation data, hardware prerequisites, operating limits, API output, power consumption, regulatory routes and OEM integration workflows. This document targets hardware product managers, embedded engineers and compliance teams who build smartwatches and health bracelets.

This AFib detection solution works alongside ECG monitoring modules on wearable hardware. You can learn more about our wearable cardiac sensing hardware from our guide on Vositone Smartwatch Professional ECG & Blood Oxygen Monitoring. For general biometric accuracy tuning techniques, review our Biometric Accuracy Enhancement Guide 2025.

Algorithm Architecture

The Vositone arrhythmia detection engine runs a multi-stage pipeline directly on wearable MCU. Raw optical PPG signals go through five sequential processing blocks before final arrhythmia classification.

First, the signal preprocessing module removes baseline drift, motion artifacts and ambient light noise. Next, the Signal Quality Index (SQI) evaluates waveform integrity; low-quality segments are discarded to avoid false readings. Then the engine extracts IBI (inter-beat interval) values from qualified PPG pulses. After that, a hybrid classifier combining rule-based logic and lightweight machine learning analyzes IBI patterns to flag atrial fibrillation or irregular rhythm events. Finally, the event logger packages detection results, timestamps and SQI scores for local storage or BLE transmission.

This on-device design reduces cloud dependency and preserves user health data privacy. It also cuts latency so wearable devices can return arrhythmia alerts within seconds after a valid measurement window.

Performance Metrics & Hospital‑Validated Validation Methodology

Vositone completed clinical validation cooperation with partner hospitals under controlled resting conditions. The test cohort covers different age groups, skin tones and body types to reflect real-world wearable use cases.

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Performance drops sharply under heavy movement, cold peripheral circulation or poor wrist fit. Our smart wearable devices future personal technology article explains how next-gen wearables will improve motion artifact suppression for biometric sensors.

Minimum Hardware Prerequisites

OEM hardware must meet these baseline specs to run the full arrhythmia detection algorithm. Vositone reference designs VO539 and VO547 are pre-validated for this algorithm stack.

1. Multi-channel PPG sensor with matched wavelength for cardiac pulse capture
2. 3-axis accelerometer for motion artifact detection
3. MCU with minimum 256KB flash and 64KB RAM dedicated to biometric computation
4. Stable power supply with low ripple during optical sampling
5. Firmware support for real-time IBI buffering and event storage

Operating Conditions & Hard Limitations

Best measurement results occur when users stay still, keep the watch snug on the wrist and maintain normal skin temperature. Several scenarios degrade detection reliability. Heavy exercise, hand shaking, low blood perfusion and loose wearing positions will raise false positive and false negative rates.

This PPG algorithm cannot detect ventricular arrhythmia, myocardial infarction or other severe cardiac disorders. It does not replace hospital ECG equipment or professional cardiologist diagnosis. OEM teams must print this limitation clearly in user manuals and on device UI prompts.

Data Output Format, BLE-GATT & REST-API

The algorithm outputs structured data via BLE GATT profiles for paired mobile apps. Available fields include timestamp, heart rate value, SQI score, rhythm classification result and confidence level. The wearable can store up to 50 arrhythmia event logs locally.

The companion mobile app can compile historical screening records and export PDF health reports. OEM developers can customize alert thresholds and report templates according to brand requirements.

Power Consumption Profiles

Two working modes are available for OEM configuration: periodic sampling and continuous monitoring. Periodic sampling consumes only microamps between measurement windows and preserves long battery life. Continuous PPG scanning increases power draw and shortens watch runtime.

OEM engineers can tune sampling frequency to balance detection responsiveness and battery performance. Power tuning is one core topic in our smartwatch buying guide for OEM product design.

Regulatory Positioning & Compliance Path

Product teams have two major market positioning options: wellness-only screening or medical-grade certification. Wellness mode has simpler documentation requirements, while medical classification requires full technical file submission.

For US market access, review guidance from the FDA Digital Health Center of Excellence. For EU sales, MDR Class IIa applies if the product is positioned as a medical device. OEM partners must complete risk analysis, clinical evaluation and post-market surveillance documents.

External link 1: https://www.fda.gov/medical-devices/digital-health-center-excellence

Technical papers on PPG-based AFib detection provide further background for your R&D team.

External link 2: https://ieeexplore.ieee.org/

OEM Integration Guide

Vositone delivers algorithm firmware packages, API documents and porting support for OEM customers. Engineers can enable or disable the arrhythmia detection module at compile time. Key parameters including SQI thresholds and alert rules can be customized.

OTA firmware channels support future algorithm version upgrades after mass production. Our technical team provides L1 and L2 engineering support during prototype testing and mass trial phases.

Algorithm Version History & Roadmap

Current production version: v2.3

• v2.1: Baseline AFib classification engine
• v2.2: Improved motion artifact filtering
• v2.3: Updated SQI scoring logic, optimized MCU memory footprint

Future roadmap:

• Q4 2026: Enhance low perfusion signal processing
• Q2 2027: Add sub-rhythm classification for selected irregular patterns
• Q4 2027: Lower minimum RAM requirement for cost-down hardware variants

FAQ

What is the difference between PPG AFib screening and hospital ECG?

PPG tracks pulse volume changes on the wrist instead of direct cardiac electrical signals. It can screen for irregular pulse patterns linked to AFib, but it cannot capture full ECG waveforms. Hospital ECG remains the gold standard for formal cardiac diagnosis.

Can I turn this PPG arrhythmia function into a medical certified product directly?

No. The algorithm itself does not automatically grant medical certification. Your end product needs full clinical evaluation, risk files and regulatory submissions under FDA or EU MDR rules. Vositone provides technical documentation to support your certification work.

Why does the watch fail to detect arrhythmia when users are moving?

Body movement creates optical noise that distorts PPG waveforms. The algorithm will automatically reject low-quality signals when SQI drops below threshold to reduce false alerts.

Can the algorithm run on existing older Vositone watch hardware?

It depends on your MCU memory and PPG sensor configuration. Submit your hardware schematic to our engineering team for a quick compatibility review.

Will user health data leave the wearable device during arrhythmia detection?

The core arrhythmia calculation runs locally on the watch. Data upload happens only if your mobile app design enables cloud sync. OEMs retain full control over data transmission architecture.

What support will Vositone provide during OEM product development?

We provide firmware packages, API manuals, integration guides and engineering consultation. For full confidential specification sheets, submit an NDA request to our business team.

CTA

Request our full confidential technical specification by signing an NDA. Contact Vositone’s OEM engineering team to discuss PPG arrhythmia detection integration for your next wearable project.

Useful Links:
GSMA Intelligence
IEEE Xplore Digital Library
U.S. FDA Digital Health Center of Excellence
PubMed Central (NIH)
Statista - Wearable Technology