// A new concept

Smartphone-Based Neurobehavioral Testing in the Blink of an Eye

An app that turns an ordinary mobile phone into a device for conducting neurobehavioral evaluations could make it easier and more cost-effective to diagnose neurological disorders. 

BlinkLab enables remote neurobehavioral testing in children and adults to aid in the diagnosis and treatment of neurological disorders such as schizophrenia, autism, and attention deficit hyperactivity disorder. Furthermore, the app can be used in neuroscience and psychology research to study fundamental mechanisms underlying learning and memory formation.

"This app is easy to operate, substantially reduces the costs of studies, and produces reliable and reproducible results."

Prof. Samuel S.-H. Wang
Princeton University

 

In the past, these tests required specialized hardware in a permanent lab environment with considerable face-to-face interaction between the researcher and participant. Using the Blinklab smartphone app, users can perform neurobehavioral tests remotely using their own cell phones. It is user-friendly, especially for infants and autistic patients, since no face attachments are needed and it provides easy instructions for performing the tests in the comfort of the subject’s home.

A healthcare professional or researcher can program experiments that are then selected by the user from a list on the smartphone. This data can be securely shared and analyzed by healthcare professionals or researchers.

During a typical evaluation, the user watches an entertaining movie or plays a simple video game on the smartphone, while the smartphone delivers short visual and auditory stimuli in specific patterns, which lasts about 10-20 minutes. Using state-of-the-art machine-vision algorithms, BlinkLab will measure the motor and emotional responses of the user to these stimuli. For most experiments, the main focus will be on eye movements and eye blinks. Through these algorithms, BlinkLab can provide a behavioral assessment of specific movements and behaviors captured in video frames.