FDA Radiology AI Devices

The Zio XT and Zio AT ECG Monitoring Systems by iRhythm Technologies, Inc. analyze continuous ECG data collected via wearable patches and generate detailed reports on cardiac events. These systems help clinicians diagnose heart rhythm abnormalities by providing comprehensive, beat-to-beat ECG analysis over long monitoring periods for patients with or without symptoms.

Biovitals Analytics Engine is a cloud-based software that analyzes continuous biometric data from sensors measuring heart rate, respiratory rate, and activity in ambulatory patients. It creates a personalized biometric signature for each patient and computes a Biovitals Index to track changes in vital signs over time, providing clinicians with additional insight for routine monitoring without replacing traditional vital sign monitoring.

HeartFlow FFRct Analysis is a software tool that uses AI to analyze previously acquired coronary CT images (CT DICOM data). It creates a 3D computer model of the coronary arteries and simulates blood flow and pressure to help clinicians evaluate coronary artery disease. This aids in diagnosis and treatment planning by providing functional insights beyond traditional imaging.

The physIQ Heart Rhythm and Respiration Module is a software device that analyzes ECG signals and movement data to calculate heart rate, heart rate variability, detect atrial fibrillation, and determine respiration rate. It helps clinicians remotely monitor cardiac and respiratory health in adult patients outside of critical care settings, enhancing patient care through advanced signal processing and automated analysis.

The Loop System by Spry Health, Inc. is a prescription-only wearable device designed for adult patients to collect physiological data such as oxygen saturation, heart rate, and respiration rate during resting periods. It passively records data using reflectance-based photoplethysmography from the wrist and uploads the information to a server for remote clinician review, aiding in patient monitoring in home environments.

KardiaAI is a software library by AliveCor that analyzes ambulatory ECG rhythms to identify heart conditions such as atrial fibrillation, bradycardia, and tachycardia. It supports integration into other ECG devices and helps clinicians by providing automated ECG noise filtering, heart rate measurement, and rhythm classification to inform diagnosis and monitoring.

The AI-ECG Platform by Shenzhen Carewell Electronics is an AI-powered software that assists healthcare professionals in measuring and interpreting 12-lead resting electrocardiograms (ECGs). It automatically analyzes ECG data, provides diagnostic interpretations for common cardiac abnormalities, and enables physicians to review and modify results. This helps clinicians make more informed cardiac assessments in hospitals and healthcare facilities.

The Zio AT ECG Monitoring System and its ZEUS System component are used for long-term cardiac monitoring by capturing continuous ECG data and analyzing it with AI algorithms to detect arrhythmias. The system helps clinicians by automatically detecting and reporting symptomatic and asymptomatic cardiac events, allowing improved cardiac care and diagnostics.

The Acumen Hypotension Prediction Index (HPI) Feature Software is a clinical decision support tool that uses arterial blood pressure waveform data and patient demographics to predict the likelihood that a patient will experience hypotension within 15 minutes. It provides clinicians real-time, adjunctive physiological insights to help anticipate and manage hypotensive events in operating room patients with advanced hemodynamic monitoring.

The CardioLogs ECG Analysis Platform is a software tool that helps qualified healthcare professionals analyze ECG data to assess arrhythmias in adults. It supports uploading ECG recordings from various devices, processes them using a proprietary proprietary algorithm to detect heartbeats and rhythm abnormalities, and provides analysis results as an advisory support to clinicians. This cloud-based platform helps improve ECG interpretation efficiency and accuracy.