Brandon Lee--Andrew Pfeifer--Thomas Phillips--Ryan Quinn

18-549 Design and Architecture: 2/19/2014

Rapid Ocular Sideline Concussion Diagnostics

Team 8

1

Status Update

• Our Project consists of a head-mounted eye-set that provides automated ocular-based concussion testing and diagnosis for sideline use. o Project Status

In communication with several experts, planned meetings and phone calls to gather concussion-based research and contacts

• General idea endorsement by Dr. Vincent Miele, with suggested addition of integrated balance testing

Proposal submitted to NFL-UA-GE Head Health Challenge II

o Parts Status Prototype parts ordered on February 8th, most acquired this morning

2

Architecture

WiFiModule

CameraTFT

Display

Android Tablet

Concussion-Testing Eyeset

(Existing) Accelerometer Sensor / Observer

PlayerTrainer App

1

3

2RasPi

Diagnosis

A

C

1. Severe impact observed, player brought to sideline2. Concussion testing

A. Tests administered via TFT displayB. Eye movements recorded in response to tests

C. Image/Video Processing on responsesD. Resultant data sent over WiFi link3. Trainer analyzes data in tablet interface 3

OpenCV Kernel

B

D

Use Cases Application Eyeset

Waiting for Trainer

Tests in Progress...

Present Test Results

Begin Test Cycle*

Begin Test Procedure

Gather/Process Test Results

Send Test Results

1. Severe impact observed2. Player moved to sideline3. Eye-set equipped4. Trainer activates testing

via App interface5. Test cycle begins

A. Visual test on TFT displayB. Eye (pupil) responses recorded 6. Image/video processing on

responsesto compile test results

7. Next test administered 8. Diagnosis given

*Test cycle includes:1. Dilation Test2. Depth Test3. Tracking Test 4

Startup

Shutdown

Display Visual Test

Record Responses

*

Risks and MitigationRisks Mitigation Plan

Direct access to concussed patients for testing might not be available

Extensive testing with un-concussed subjects; UPMC contacts may help

Eye-set design may be uncomfortable, unbalanced, or clunky

Design a compact housing for RasPi and sensors, possibly with counter balance

Camera focus may lack sharpness and clarity to perform eye analysis on a wide

variety of eye types

Alternative lenses may need to be acquired; image and video processing

algorithms may account for possible blurs

Plan A Plan B Plan C

Android App works smoothly; ergonomic eye-set performs accurate tests; individualized

player diagnoses

Individualized player diagnoses give way to more general tests; the eye-set and App are still well

packaged and easy-to-use

Less refined eye-set performs accurate, general tests that are reliably sent to an easy-to-use

App interface5