PupilScreen
| Autor: | Alex Mariakakis, Shwetak N. Patel, Lynn B. McGrath, Vardhman Mehta, Jacob Baudin, Anthony Law, Eric Whitmire, Megan A. Banks |
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| Rok vydání: | 2017 |
| Předmět: |
medicine.medical_specialty
Computer Networks and Communications Traumatic brain injury business.industry Pupil diameter 030229 sport sciences Virtual reality medicine.disease Convolutional neural network Emergency situations Human-Computer Interaction 03 medical and health sciences 0302 clinical medicine Physical medicine and rehabilitation Hardware and Architecture Smartphone app medicine Pupillary response Computer vision Pupillary light reflex Artificial intelligence Psychology business 030217 neurology & neurosurgery |
| Zdroj: | Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 1:1-27 |
| ISSN: | 2474-9567 |
| DOI: | 10.1145/3131896 |
| Popis: | Before a person suffering from a traumatic brain injury reaches a medical facility, measuring their pupillary light reflex (PLR) is one of the few quantitative measures a clinician can use to predict their outcome. We propose PupilScreen, a smartphone app and accompanying 3D-printed box that combines the repeatability, accuracy, and precision of a clinical device with the ubiquity and convenience of the penlight test that clinicians regularly use in emergency situations. The PupilScreen app stimulates the patient's eyes using the smartphone's flash and records the response using the camera. The PupilScreen box, akin to a head-mounted virtual reality display, controls the eyes' exposure to light. The recorded video is processed using convolutional neural networks that track the pupil diameter over time, allowing for the derivation of clinically relevant measures. We tested two different network architectures and found that a fully convolutional neural network was able to track pupil diameter with a median error of 0.30 mm. We also conducted a pilot clinical evaluation with six patients who had suffered a TBI and found that clinicians were almost perfect when separating unhealthy pupillary light reflexes from healthy ones using PupilScreen alone. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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