FDA Radiology AI Devices

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.

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.