Phone camera + machine learning detect concussion

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Shwetak Patel and UW colleagues have developed PupilScreen, an app that uses a phone’s camera to detect concussion from the pupil.

The phone’s video camera and flash check the eye for its pupillary light reflex, measures size changes associated with concussion.  Machine learning algorithms confirm the diagnosis.

Hospitals typically use a pen light to check for concussions, which is much less accurate than a pupillometer.

PupilScreen was tested on  48 healthy and tbi patients. The team reported that it “diagnosed brain injuries with almost perfect accuracy using the app’s output alone.”

Click to view University of Washington video


Stanford professor Jamshid Ghajar will discuss the rapid concussion detection and treatment platform SyncThink at ApplySci’s Wearable Tech + Digital Health + Neurotech Boston conference, on September 19th at the MIT Media Lab.


Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston on September 19, 2017 at the MIT Media Lab – featuring  Joi Ito – Ed Boyden – Roz Picard – George Church – Nathan Intrator –  Tom Insel – John Rogers – Jamshid Ghajar – Riccardo Sabatini – Phillip Alvelda – Michael Weintraub – Nancy Brown – Steve Kraus – Bill Geary – Mary Lou Jepsen


ANNOUNCING WEARABLE TECH + DIGITAL HEALTH + NEUROTECH SILICON VALLEY – FEBRUARY 26 -27, 2018 @ STANFORD UNIVERSITY –  FEATURING:  ZHENAN BAO – JUSTIN SANCHEZ – BRYAN JOHNSON – NATHAN INTRATOR – VINOD KHOSLA