Let us turn ECG signals
into actionable results
Cardiomatics is a cloud AI tool for ECG analysis.
Simply give us a raw ECG signal and our algorithms will turn it into valuable analysis.
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Clinically validated results
Our algorithms meet the standard ANSI/AAMI EC57: 2012 and have been validated both on MIT BIH arrhythmia databases and on clinical data.
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Use reliable cloud interface
Our service uses global HIPAA compliant services which guarantee safety and accessibility from anywhere in the world. API is scalable and ready to be integrated with your solutions.
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Adjust to your needs
Our algorithms are divided into modules, which may be used independently of each other. Choose either a simple, user-friendly report or full clinical report.
Trusted by cardiologists and by patients
Paweł Balsam, BA, MD, PhD, FESC
Central Teaching Clinical Hospital of the University Clinical Center, PolandIn the field of cardiac electrophysiology, Cardiomatics facilitates and speeds up the diagnosis of arrhythmia. As a certified medical device perfectly suited our needs.
Ulrich Ingold, MD
Kardiologie Interlaken-Unterseen, SwitzerlandIt used to be very time-consuming to analyze long-term recordings with our conventional Holter software. Using Cardiomatics, the interpretation is now fast and reliable.
Prof. Michael Kühne, MD
Head of Clinic Atrial Fibrillation, University Hospital Basel, SwitzerlandThe web-based platform is very simple and user-friendly. After uploading the raw signal of the ECG, we get access to a detailed report within a few hours. In a clinical routine, this can save a lot of time compared to the time-consuming analysis of Holter recordings with conventional Holter software.
Prof. Christine Meyer-Zürn, MD
Cardiologist, University Hospital Basel, SwitzerlandWithin Swiss-AF Burden, we measure the AF burden manually from a standard 7-day Holter ECG. The medical-grade system which we are using ensures high-quality and trusted outcomes based on accurate algorithms. This helps us to independently validate our results, especially in patients with multiple AF episodes and noisy recordings, where the manual estimation of the AF burden can be challenging.
Certified as Medical Device Class IIa
