team rca march 1, 2013
DESCRIPTION
Cumulative Design Review. Team RCA March 1, 2013. RCA (Real-Time Concussion Analyzer). Timothy Coyle, EE Impact Processing & Communication. Kenneth Van Tassell, EE User Interface & Communication. Scott Rosa, CSE Server & Data Analysis. Justin Kober, EE Sensor Network & Power. - PowerPoint PPT PresentationTRANSCRIPT
1Department of Electrical and Computer EngineeringDepartment of Electrical and Computer Engineering Advisor: Professor Hollot
Team RCAMarch 1, 2013
Cumulative Design Review
2Department of Electrical and Computer EngineeringDepartment of Electrical and Computer Engineering Advisor: Professor Hollot
Kenneth Van Tassell, EEUser Interface & Communication
Scott Rosa, CSEServer & Data Analysis
Justin Kober, EESensor Network & Power
Timothy Coyle, EEImpact Processing & Communication
RCA (Real-Time Concussion Analyzer)
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Current concussion detection• Train coaches to recognize symptoms
Players may hide or not experience symptoms right away
RCA will monitor each player and alert the coach with the risk of concussion after each collision
Customer feedback• College trainers and high school athletic director
Concussion Detection in High School Football
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Our Solution: Block Diagram
Bluetooth
Android
Server
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Demonstration of Impact Data Collection• Single accelerometer interfaced with processor• Helmet processor transmission
Demonstration of Base Station/UI Interaction• Using test data
− Receive from helmet− Run algorithm
• UI able to receive and display test results
Review of MDR
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Sensors
ADXL 78 MEMS Accelerometer• Single axis• +/- 70 g range• 27 mV/g sensitivity• 5 V and 1.3 mA
PCB Design• 3 connection wires• 1 noise filtering capacitor• 1 sensor
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Battery
System Power Requirements • Maximum current ≈ 300 mA• 5 volts• 5 hour duration• Total energy consumption = 1390 mAh
USB Battery Pack• 2000 mAh• 5.5 V, 700 mA • Rechargeable• Packaging in helmet
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Sensor Packaging in Helmet
Sensors
IC and battery
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Human Skull
Loaded vs empty helmet
Simulate the neck
Controlled test for impact duration
• Small increase
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Application / User Interface and UI Communication Design Requirements
• Simple Operation / User Friendly• Displays Meaningful Information• User Adaptable
− Coach vs. Trainer• Player Adaptable
− Adaptive Threshold Monitoring
Challenges• Improving Processing • Maintaining Continuity• Redesigning Bluetooth Parsing for Variable Hits
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Application / User Interface and UI Communication
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Application / User Interface and UI Communication
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Risk Function
C1= -12.531C2= 0.0020
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Calculating Magnitude Hit Vector
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Isolated Algorithm Error Characterization
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Isolated Algorithm Error Characterization
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Impact Processing & Communication
ATmega32U4 8-bit AVR Microcontroller• MDR sample rate = 2.08ms per sample• 0.152ms per sample (92.7% increase)• Threshold triggering
Wireless Transmission
Maximum Data Rate (Kbps)
Effective Data Rate (Kbps)
Maximum Range (m)
Effective Range (m)
Bluetooth 240 154.2 100 30XBee 20 15.1 610 100Bluetooth vs Xbee
12xRate 10.2xRate 0.2xRange 0.3xRange
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Experiments• Threshold Estimation
- Mean, Standard Deviation
Impact Processing & Communication Experiments
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Demonstration of Complete System Functionality• Show implementation of battery powered system• Impact the helmet with a known force• Transmit impact data with required sample rate from the
sensor array to Android device• Display risk of concussion with confidence interval on
Android device• Display player impact history on Android device upon
user request
Proposed CDR Deliverables
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Demo
Demo
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Timeline
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Fully Integrated and Wearable Helmet• Stable battery• Player specific adaptability
Reliable User Friendly Android Application• User specific settings
Risk Calculation with Confidence Interval• Probability of Error
DEMO• Impact Dummy• Server, Impact Location & Application
FPR and Demo Day
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Questions
Thank You
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Questions
Thank You
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Data Processing and Storage
Requirements From MDR• Calculate a magnitude hit vector from the
accelerometer data• Calculate risk for each hit as well as cumulative risk• Be able to store raw accelerometer data
Accomplished• Calculates the hit vector in an average of 411.6 ms.
The overall program calculates risk in an average of 1.06 s
• Tested and graphed data• Set up server with database to store raw
accelerometer data and hit data
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Material Costs
This cost could be reduced by $1,200 purchasing the RN-41 and designing the BlueTooth modem ourselves
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Computational Analysis
Storage and computation can be done on a phone
Server hosts MySQL database
Max phone memory size: 64 GB
Min phone memory size: 2 GBTop Ten Paid apps in Itunes 11/26/12
Max App memory size: 791MBMin App memory size: 3.1MB
Average of max and min memory size: 397.05 MB
Size of Entry in table is
40Bytes
0.00004 MB9926250 hits in total
90
Avg hits per college season per player: 1177seasons played by college player: 4
hits for college team in 1 years 423720Team data for 4 years 17MB
Team data per year 4MBStore data for 99 teams per yearStore data for 23 college teams for 4 years
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Preliminary Weight Analysis
NFL Helmet Approximately 6lbs. or 2.722kg ATMega328P = 2g MEMS each approximately 1g Gyroscope approximately 2g Power approximately 23g Estimated total system weight (not including
packaging) = 35g-40g
5% of helmet is approximately 136g
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Requirements Analysis: Specifications
Real-Time continuous impact measurements Player specific adaptability Equipment weight increase less than 5% Effective range 150 m Responds in under two seconds Robust
• Interference• Durable
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Measured System Energy Consumption
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Worst Case Power
Worst Case Power AnalysisDevice Max Voltage (V) Max Current (mA) Max Power (W)
ATmega32U4 5 200 1
BlueSMiRF Gold 3.3 100 0.33
ADXL 193 5 2 0.01
Total Power (W)
1.39
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Lower frequency response• Vibrations
Mapping to graph
• More data points
Cost
Single-Axis VS. Multi-Axis
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Impact Data Collection Power circuit Sensor array Processing and transmission of sensor array
User Interface Cumulative linear acceleration User preferences Risk display Stability
Data Analysis Sub-concussive impacts integrated Statistical analysis for entire system
Proposed CDR Goals