heartKIT

On-Device Heart Intelligence

Train, test, and deploy real-time cardiac models on Ambiq’s ultra-low-power SoCs. Perfect for fitness wearables, wellness devices, and remote patient monitoring—covering denoise, ECG/PPG segmentation, rhythm, and beat classification.

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heartKIT Highlights

Real-Time Edge AI

Run cardiac models locally on Ambiq’s ultra-low-power SoCs for instant, reliable insights on wearables and RPM devices. Low latency, battery-friendly inference—no cloud required.

Day One Ready

Kickstart projects with pre-trained models, datasets, and task-level demos. Clone, run, and showcase results in minutes—with configuration recipes you can adapt to your use case.

Extensible by Design

Tune tasks, models, datasets, and training via simple YAML. Add your own data or define new tasks with HeartKIT’s extensible factories to build custom workflows with minimal code.

Optimized to Deploy

Ship efficient inference with optimized architectures and deployment routines. Export compact models for HeliaAOT, HeliaRT, or TFLM and validate with provided metrics—perfect for battery-powered devices.

Tasks & Capabilities

Denoise

Clean ECG/PPG signals with real-time denoising/dereverberation to boost downstream accuracy—ideal for noisy, everyday wear.

Segmentation

Locate beats and intervals from ECG/PPG for reliable event boundaries and feature extraction.

Rhythm Classification

Classify rhythms such as AFIB and AFL on-device for immediate, private insights.

Beat Classification

Label beats (NORM, PAC, PVC, NOISE) for fine-grained analytics and alerts.

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heartKIT

On-Device Heart Intelligence

heartKIT Highlights

Real-Time Edge AI

Day One Ready

Extensible by Design

Optimized to Deploy

Tasks & Capabilities

Denoise

Segmentation

Rhythm Classification

Beat Classification

Video Library

Design Resources

Additional Documentation

Instant Download

Additional Resources

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