Neurometry offers a clinically validated digital platform providing non-verbal cognitive games for stroke and brain injury recovery. This mobile solution enables daily cognitive tracking through accessible, measurable assessments performed at home. The platform bridges the gap between infrequent clinical visits and real-life cognitive function monitoring.
Funding
$350K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Current tools for assessing and monitoring cognitive health often lack the sensitivity and adaptability needed for continuous and dynamic evaluation, particularly for older adults and individuals facing mental or physical health challenges. Subclinical cognitive deficits frequently go undetected, impacting daily activities and overall well-being.
Solution
Neurometry offers AI-powered, game-based cognitive assessment and training tools designed to enhance the management of neurocognitive deficits. The platform delivers engaging games that target specific cognitive functions, adapting dynamically to individual cognitive levels. Real-time health interfaces and mobile apps enable continuous digital care and remote monitoring. The platform provides a data-driven approach to monitor cognitive health and risks, generating performance reports for clinical assessment.
Target Audience
The primary users are families seeking to monitor cognitive performance and institutions aiming to implement data-driven cognitive health monitoring.
Features
- Game-based cognitive assessment and training delivered through mobile apps
- AI-powered adaptation of game difficulty to individual cognitive levels
- Real-time monitoring via health interface and mobile apps
- Generation of performance reports for clinical assessment
- Integration with eye-tracking and wearable devices for deeper insights
- Games are designed to be inclusive, removing language, cultural, and socioeconomic biases