Upload
beatrice-williamson
View
212
Download
0
Embed Size (px)
Citation preview
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