BlinkLab develops AI-powered, smartphone-based healthcare technology to aid clinicians in the assessment of autism. This diagnostic tool utilizes objective, reflex-based measures delivered via at-home testing to reduce subjectivity in evaluations. The platform aims to enable earlier and more accurate identification of autism spectrum conditions for specialists.
Funding
Funding not disclosed
Founders
Product
Problem
Current diagnostic methods for neurological and neurodevelopmental conditions, such as autism and ADHD, often rely on subjective assessments and can be time-consuming, costly, and inaccessible, leading to delayed diagnoses and interventions. Traditional methods may also miss the crucial early window for effective intervention, particularly in young children.
Solution
BlinkLab develops smartphone-based diagnostic tools that leverage AI and machine learning to provide objective and accessible screening for neurological and neurodevelopmental conditions. The platform uses digital sensory phenotyping to analyze facial reflexes elicited by specific audio cues during short, engaging video sessions. This approach enables large-scale remote neurobehavioral testing, facilitating early detection and intervention for conditions like autism and ADHD. The technology aims to improve the accuracy, efficiency, and accessibility of diagnostic evaluations, making them available from home and at younger ages than traditional methods.
Target Audience
BlinkLab serves families seeking early and accessible screening for autism and ADHD, as well as clinical researchers and healthcare providers aiming to improve diagnostic accuracy and efficiency in neurological and neurodevelopmental assessments.
Features
- Smartphone-based platform for remote neurobehavioral testing
- AI-powered analysis of facial reflexes using digital sensory phenotyping
- Screening tests designed for children as young as 18 months old
- Prepulse inhibition (PPI) measurement as an objective behavioral marker
- Machine learning techniques to uncover novel, homogeneous clusters of data
- Integration of digital biomarkers with validated behavioral and neurocognitive markers
- Customizable experiment options for research purposes