Ocula develops an AI-powered pupillometer that measures pupil biomarkers under varying lighting conditions, providing immediate diagnostic support for neurological assessments related to concussions and impairment from substances. This technology enables clinicians and researchers to capture precise pupil measurements, enhancing the accuracy of neurological evaluations and research outcomes.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional neurological assessments for conditions like concussions and substance-related impairment often rely on subjective observations. Existing pupillometry methods may lack the precision and adaptability needed for accurate, real-time diagnostic support in diverse environments.
Solution
Ocula has developed an AI-powered pupillometer that uses mobile devices to capture objective pupil measurements under varying lighting conditions. The Ocula AI Engine™ employs machine learning and computer vision to provide immediate diagnostic support for neurological assessments. This technology enables researchers and clinicians to record precise pupil diameter measurements, enhancing the accuracy of neurological evaluations and research outcomes related to concussion, impairment, and other neurological conditions.
Target Audience
The primary users are medical researchers and clinicians, including neurologists, ophthalmologists, physiotherapists, and chiropractors, involved in research using ocular assessments. The technology also caters to students and workplaces seeking fatigue and impairment applications.
Features
- AI-powered pupillometry using standard mobile device cameras
- Measures pupil biomarkers in diverse lighting conditions
- Pupillary Light Reflex (PLR) module analyzes constriction distance and velocity, response latency, and recovery time
- On-the-spot diagnostic support for head trauma and impairment
- Cloud-based data storage and analysis