FDA Radiology AI Devices

The EyeBOX is an eye-tracking device designed to assist clinicians in diagnosing concussion by analyzing eye movements. Patients watch a video on a screen while a near-infrared camera records their eye gaze data. The device processes this data using advanced algorithms to detect subtle abnormalities in eye movement that indicate concussion, helping doctors make timely and accurate assessments.

The 7D Surgical System Cranial Biopsy and Ventricular Catheter Placement Application is a stereotaxic image-guided navigation system that assists surgeons in performing precise cranial surgery. It provides real-time tracking of instruments, image registration with preoperative scans, and step-by-step guidance for biopsies and ventricular catheter placement, improving surgical accuracy and safety.

BrainScope TBI is a portable, non-invasive device that assists clinicians in evaluating patients with mild traumatic brain injury and concussion by analyzing brain electrical activity through EEG along with cognitive tests and clinical symptoms. It helps identify the likelihood of structural brain injury and assesses brain function, supporting decisions about the need for further imaging like CT scans.

EyeBOX is an eye-tracking device designed to help diagnose concussion by measuring and analyzing eye movements in patients within one week of a head injury. It uses near-infrared cameras to track gaze positions and an AI-driven algorithm to detect subtle changes in eye movements associated with concussion, aiding clinicians in neurological assessment.

EyeBOX is a device that uses an eye-tracking camera and software to measure and analyze eye movements as an aid in assessing concussion within one week of head injury for patients aged 5 to 67. It provides clinicians with a score indicating possible brain injury based on abnormal eye movement patterns, helping supplement traditional neurological assessment.

Embrace is a wearable device worn on the wrist that monitors physiological signals such as Electrodermal Activity, motion, and temperature to detect generalized tonic clonic seizures in patients with epilepsy. It helps alert caregivers by sending notifications during seizure events, assisting in timely monitoring and care for patients both at home and in healthcare facilities.

EnsoSleep is a software tool that uses AI algorithms to analyze sleep study data, including brain waves and breathing patterns, to help physicians evaluate sleep quality and diagnose sleep-related disorders such as sleep apnea. It automates scoring of sleep stages, detection of arousals, leg movements, and breathing events, improving efficiency while requiring clinician verification.

The Ahead 300 is a portable, non-invasive medical device that records and analyzes brain electrical activity to assist clinicians in evaluating patients with closed head injuries. It provides algorithm-based classifications of structural brain injury and measures brain function and cognitive performance to support diagnosis and treatment decisions, particularly to aid in deciding on the necessity of head CT scans.

The BrainScope Ahead 200 is a portable EEG device designed to aid physicians in evaluating patients with mild traumatic brain injury by measuring and analyzing brain electrical activity. It supports clinical decision-making regarding the need for head CT scans by providing objective quantitative EEG parameters. The device is intended for use as an adjunct to standard clinical practice and includes features such as continuous impedance monitoring and cognitive assessment tools for military use. It helps clinicians by providing rapid brain activity data to support the assessment of brain injury severity without replacing imaging such as CT scans.

The BrainScope Ahead 100 is a portable EEG-based device designed to assist physicians in evaluating patients with mild traumatic brain injury. It analyzes brain electrical activity to help decide if a head CT scan is needed, potentially reducing unnecessary CT scans and radiation exposure. The device processes EEG data using AI-driven algorithms to classify patients based on the likelihood of structural brain injury visible on CT.