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System Design of a Knee Motion Sensor to Prevent
ACL InjuriesTaban Yazdani Anthony Petro Anas Alharbi
Salima Sekandari
Ost1st
http://guardianlv.com/
http://www.nytimes.com/
http://www.themichelicenter.com/
Sponsor:Dr. Lance Sherry
Play harder.Play longer.You kneed it.
ACL tearKnee motion
sensor Situational awareness for athlete during game time
Uninjured athlete
1/13 NCAA female athletes sustain ACL injuries
Agenda: SE V-Model
2
Team Contribution
3
Burns, M., Tesnow, A., Attyah, A., & Miller, S. (2016, April 29).
2016 - BASS 2017- KMS
Arduino Uno Arduino-ESP8266
1 Accelerometer 3-axis accelerometer
1 Flex sensor 2 Flex sensors
2 Pressure Pads
Excessive Testing
1. Context Analysis
4
Enterprise: NCAAThe National Collegiate Athletic Association is a non-profit association which regulates
(NCAA, 2010)
400,000 student-athletes
23 sports
1000 member institutions
Every year more than 55,000 NCAA student-athletes across 15 high-risk sports sustain an
ACL injury (NCAA, 2009). 5
For 2011-12, the NCAA generated $871.6
million in revenue.Hootman, Jennifer M, Randall Dick, and Julie Agel (2007)
What is the ACL?
Anterior - Situated before or at the front
Cruciate - Shaped like a cross or an X
Ligament - A band of fibrous tissue which connects and stabilizes
bones
6
Why are ACL Injuries Important?
1. Occur frequentlya. 100,000-200,000 occur every year in the United States (Rosemont, 2004)
2. Women athletes are more susceptible
a. NCAA female athletes are 2 to 8 times more likely to suffer from an ACL injury
than male athletes (Barber SD, 2006)
3. ACL injuries DO NOT heal on their own
4. Expensive surgery treatmenta. ACL surgery can cost anywhere between $800-$50,000 (Owen, 2013)
5. Long recovery time a. A full recovery can take 6-9 months
7
2. Stakeholders Analysis
8
Stakeholder Diagram
9
+
-
-
- -
-
-
+
Gap Analysis
1 out of every 13 female NCAA
athletes sustains an ACL injury
Force on ACL: No method to actively
measure ACL strain Strain Awareness:
Athletes are unaware of what they are doing wrong in game settings NCAA Data for ACL Injury Rates 2010
10
3. Problem Statement
11
Problem Statement
Despite the large number of studies being done on identifying ACL injuries and its failure mechanisms
1 out of every 13 female NCAA athletes sustains an ACL injury. There is no system in place quantifying the strain on the ACL in
order to prevent ACL injuries from happening to athletes.
12
Need Statement
There is a need for a system that provides situational awareness for athletes in a game environment by:
Estimating the strain applied to the ACL in game situations
Alerting the athlete when a motion they have performed causes a strain that exceeds 2100+-50N
13
Knee Joint Anatomy
1. Bones
- Femur
- Tibia
- Febula
- Patella
14
Five major components construct the
knee:
2. Muscles:- Hamstring
- Quadriceps
- Gastronomio
3. Cartilage
4.Tendons:- Patellar
- Quadriceps
5. Ligament:- MCL- LCL- PCL- ACL(Anterior
Cruciate Ligament)http://www.gettyimages.com
Motions That Cause ACL Injuries
Non-Contact Injuries (70%)
1. Rapid change of direction while running
2. Sudden stop
3. Slowing down while running
4. Landing from a jump incorrectly
Contact Injuries (30%)
5. Direct contact or collision, such as a football tackle
15
http://corewalking.com/
ACL tears at 2100 +- 50 N (Quatman 2010)ACL Tear
Tibia
Femur
Gap puts strain
on ACL
Equations of the Motion of the Knee:
1) Knee Frames 2) Angles
Xsh
Ysh
Xe
YeXe = x-axis of the earth
Ye = y-axis of the earth
Xsh = x-axis of the shank
Ysh = y-axis of the shank
sh= Shank Angle
16
3) Forces on the ACL
Ff = Foot Force
Fs= Shank Force
Fg
= Ground Reaction Force
Fq
= Quadriceps Force
Fh= Hamstring Force
Fc= Gastrocnemius Force
TSF = Tibial Shear Force
17Fg
Fc
Ff
Fs
Fq
Fh
FBones
TSF
YeYsh
Transmitted Forces
Muscle Forces
External Force
Myres (2010)
Myers (2010) 18
4) Newton’s Second Law :
Tibial Shear Force : Tear At 2100 +- 50 N (Quatman 2010)
Muscle Forces in TSF Equation
19
Myers (2010)
FGastr
o
FQua
d
FHa
m
flex
Sh
Sensitivity Analysis on TSF Minimize Maximize
Maximizing Muscle Forces:
Quadriceps
Hamstring
20
Sensitivity Analysis
21
Maximize hamstring muscle force:
→ Shank Angle should be close to 90 degrees
Maximize quadriceps muscle force:
→ Flex angle should be small (closer to 0 degrees)
Maximize
Minimize
Maximize
Maximize
h
h
4. Concept of Operations
22
The solution is to create and implement a knee motion sensor that shall provide real-time situational awareness for the athlete in a game by:
Using inputs retrieved from sensors and converting it into usable data The data will then be used with tibial shear force equations to determine the
amount of strain being placed on the ACL Once the risk of the strain being placed is determined, the system can then
alert the user of an elevated risk The athlete can then use this situational awareness for a post-game
analysis to see what movements they are doing that are dangerous to their ACL
Concept of Operations (CONOPS)
23
5. Requirements
24
Mission RequirementsNumber Requirement
M.1 The system shall alert the user when the estimated TSF is approaching 2100 - 50 N.
M.2 The system shall calculate the strain on the knee with an accuracy of no less than 85%.
M.3 The system shall calculate the knee flex angle with an accuracy of no less than 85%.
M.4 The system shall calculate the ankle flex angle with an accuracy of no less than 85%.
M.5 The system shall calculate pressure with an accuracy of no less than 85%.
M.6 The system shall calculate the acceleration within 3 m/s^2 of error.
M. 7 The system shall not hinder the athlete’s performance.
M.7.1 The system shall not be larger than 10 by 10 cm in size.
M.7.2 The system shall weigh no greater than 6 ounces.
25
Functional Requirements Number Requirement
F.1 The system shall calculate the tibial shear force.
F.2 The system shall measure the shank angle.
F.3 The system shall measure the flexion angle.
F.4 The system shall measure the acceleration of the foot in the x, y and z directions.
F.5 The system shall measure the acceleration of the shank in the x, y and z directions.
F.6 The system shall measure the ground reaction force in the x, y and z directions.
F.7 The system shall acquire data from the sensors.
F.8 The system shall detect a TSF greater than the warning threshold.
F.9 The system shall alert the user when the TSF is greater than the warning 2100 - 50N.
26
Design Requirements
27
Number Requirement
D.1 The system shall include a haptic, visual, and audible device to alert the user when the TSF is greater than the
warning threshold.
D.2 The system shall weigh no more than 6 ounces.
D.3 The system shall be water resistant.
D.4 The system shall not be bigger than 10 by 10 cm in size.
D.5 The battery life shall last no less than 2 hours
D.6 The sensor shall not move and stay attached to the knee sleeve
D.7 The sensor shall be enclosed in a shock resistant cover.
6. Design
28
29
Functional Description Diagram
Estimating TSF with Sensors
30
Term in TSF Sensor
1.Shank Acceleration Accelerometer
2.Shank Angle Flex Sensor
3.Flex Angle Flex Sensor
4.Foot Force Pressure Pad
5.Ground Reaction Force
Pressure Pad + Accelerometer
Circuit Diagram
31
7. Building
32
Arduino Code
33
Accelerometer communication
Multiplexer pin selection
Wifi parameters
Arduino Code (Cntd)
34
Matlab connection starts data collection
Stores accelerometerinputs
Conversions using equations
TSF equation
Matlab Code
35
Collects data from arduino
Plots data
Matlab Interface
36
Matlab Graphical Interface
37
Prototyping Breadboard and Custom Bracketry
39
KMS Device
40
Open Cover
Accelerometer
Pressure pads
Flex sensors
KMS
8. Unit Test
41
Sensor Calibration
42
Resistor(Ω) Minimum(40 lb)
Maximum(260lb)
Range
330 1024 1024 Out of Range
1k 848 287 561
2k 901 252 649
5k 110 46 64
10k 56 44 12
resistor(Ω) Minimum(160 degrees)
Maximum(97 degrees)
Range
<=100k 1024 1024 Out of Range
120k 580 1019 439
137.5k 470 920 450
147k 430 905 475
200k 404 697 293
>=220k 1024 1024 Out of Range
resistor(Ω) Minimum(180 degrees)
Maximum(25 degrees)
Range
<=100k 1024 1024 Out of Range
110k 653 960 307
120k 513 950 437
135k 667 990 323
145k 510 810 300
>=150k 1024 1024 Out of Range
Pressure Pads : Ankle Flex Sensor: Knee Flex Sensor:
System Test
43
System Test Plan
44
Test Item
Description Test Case Requirement Objective Materials
1.0 Pressure Sensor
1.1 Pressure Sensor Calibration1.2 Bent Leg Test 1.3 Straight Leg Test1.4 Placing Weights Test
M5. The system shall calculate
pressure with an accuracy of no
less than 85%.
Validate the pressure sensor
data to find accuracy of sensor.
Two pressure sensor, one
digital Scale, block, Arduino
board,BreadBoard, four jumper
wires.
2.0 Flex Sensor (Knee and Ankle)
2.1 Ankle Sensor Calibration 2.2 Knee Sensor Calibration 2.3 Electronic Goniometer vs Flex Sensor Test
M3.The system shall calculate the
knee flex angle with an accuracy of no
less than 85%.
-----------------------------------------
M4.The system shall calculate the
knee flex angle with an accuracy of no
less than 85%.
Test the accuracy of the angle measurements of the flex sensors attached to the Arduino Device.
Protractor and Electronic Goniometer, Arduino Device
3.0 Accelerometer 3.1 Accelerometer Calibration
3.2 Bent Leg Test
3.3 Straight Leg Test
3.4 Dropping Block Test
M6.The system shall calculate the
acceleration within 3 m/s^2 of
error.
Test the accuracy of the
acceleration measurements of
the Arduino Device
Accelerometer , Arduino
Device, block, Smartphone
(Androsensor App)
4.0 Combination of Sensors
4.1 Calibration of all Sensors4.2 Walk test4.3 RunTest4.4 Jump Test
M2.The system shall calculate the strain on the knee with an accuracy of no less than 85%.
Test the accuracy of the Knee Motion Sensor with all the items together
Knee Motion sensor with all the components
Pressure Sensor Test
45
Objective: Test the accuracy of the pressure pads and compare values with calculated pressures using formula:
Procedure :
1. Apply no pressure to verify that pressure pad is zeroized
2. Place weight on top of pressure pad
3. Record arduino reading
4. Remove weight and repeat steps 5 more trials
Test Item Description
Mission
Requirements
M5. The system shall calculate pressure with an accuracy of no less than
85%.
Data Analysis on Pressure Pads
46
(Pa)
Pressure PadResults:
47
Weight (lb) Arduino Pressure
Calculated Pressure(Pa)
Actual Pressure (Pa)
Percent Error
70 747.92 203894.67 273113.39 25.34%
90 427.81 400155.93 351145.20 13.96%
120 375.99 467641.91 468193.88 0.12%
160 314.51 580093.09 624258.51 7.07%
180 299.48 615412.77 702290.40 12.37%
220 272.79 688793.59 858355.03 19.75%
260 252.26 757028.75 1014419.66 25.37%
Average Error: 14%
Test Item Description
Mission
Requirements
M5. The system shall calculate pressure with an accuracy of no less than
85%.
Test Result The system calculated pressure with an accuracy of 86% on average.
PASS
Flex Sensor TestObjective: Test how accurate the flex sensor measures angles by comparing it with
goniometer
Procedure:
1. Align flex sensor with goniometer
2. Move goniometer to 25°
3. Record arduino reading of flex sensor at 25°
4. Repeat from 30° to 180° in 5° increments
48
Test Item Description
Mission
Requirements
M3. The system shall calculate the ankle flex angle with an accuracy of no less than 85%.
M4. The system shall calculate the knee flex angle with an accuracy of no less than 85%.
Test Results on Ankle Sensor
49
Actual (Degree) Calculated Error Percent Error
120.00 118.72 -1.28 0.05
130.00 121.97 -8.03 0.06
140.00 135.86 -4.14 0.07
150.00 152.17 2.17 0.03
160.00 193.03 33.03 0.21
170.00 162.51 -7.49 0.05
180.00 181.34 1.34 0.03
Average Error: 5%
Test Item Description
Mission
Requirements
M3. The system shall calculate the ankle flex angle with an accuracy of no less than
85%.
Test Result The system calculated pressure with an accuracy of 95% on average.
PASS
Test Results on Knee Sensor
50
Actual(Degree) Calculated Error Percent Error
120.00 114.45 -5.55 0.08
130.00 128.79 -1.21 0.01
140.00 140.30 0.30 0.03
150.00 162.28 12.28 0.08
160.00 138.76 -21.24 0.13
170.00 162.51 -2.92 0.02
180.00 172.45 -7.55 0.04
Average Error: 8%
Test Item Description
Mission
Requirements
M4.The system shall calculate pressure with an accuracy of no less than
85%.
Test Result The system calculated pressure with an accuracy of 92% on average.
PASS
Accelerometer TestObjective: Test the accuracy of the acceleration measurements of the Arduino Device and
compare it with AndroSensor accelerations.
Procedure:
1. Attach phone and accelerometer block.2. Drop block from a 30 cm height .3. Record data from both the AndroSensor app and arduino device.4. Repeat steps 1-3 for 24 more trials.
51
Test Item Description
Mission Requirements M6. The system shall calculate the acceleration within 3 m/s^2 of error.
Accelerometer Data Comparison
Block Drop Graph from Mobile App
Updating speed: 5 ms
Block Drop Graph from Accelerometer
Updating speed: 5 ms
52Landing BounceFree Fall
Accelerometer Test Results
53
X Acceleration(m/s^2)
Y Acceleration(m/s^2)
Z Acceleration (m/s^2)
Calculated Acceleration 0 0 9.8066
Arduino Acceleration Average -0.0282 1.2330 9.6907
Standard Deviation 0.3708 0.1321 0.2192
Error 0.0282 1.233 -0.11
Number of trials 5 5 5
Gravitational constantacceleration
Measured acceleration
Inconsistencies due to wobble
Test Item Description
Mission
Requirements
M6. The system shall calculate the acceleration within 3 m/s^2 in error.
Test Result The system calculated acceleration within 0.625 m/s^2 in error.
PASS
Estimated Tibial Shear Force
54
Walking Running Jumping
Field Test
55
User Survey
56
Who?
GMU students, faculty, and athletes.
Goals?
To determine how comfortable and usable the KMS device is.
Use user comments to improve device.
Market Test
57
Potential Market Opportunity
58
Potential customer Benefit Market Size (individuals)
US Athletes: NCAA student athletes Prevent ACL injury, post game analysis
480,000
Youth athletes (age 5-18)
Prevent ACL injury, post game analysis
35,000,000
Recreational athletes US
Prevent ACL injury, post game analysis
15,000,000
Professional athletes
Prevent ACL injury, post game analysis
18,000
Previously knee Injured Individuals:
knee joint (meniscus). Ligament tears
Prevent further knee injury 2,295
PCL injury Prevent further knee injury 25,000
ACL injury Prevent further knee injury 200,000
Total: 50 M
Component Cost
59
Component Price
2 x Pressure Pads $16.00
2 x Flex Sensors $15.99
Multiplexor $6.95
Accelerometer $7.00
Arduino Buzzer $0.80
Arduino Haptic Disc $1.95
LED $0.10
Arduino board $70.00
Resistors $5.99-$7.99
Wires $8.00
3-D Printed Cover $20.00
Over Knee Sock $12.48
Total $180 +/- $20
The Device Cost Breakdown:
Total Cost
60
Cost Price
4 employees * cost of insurance/year
$4000
Marketing $10,000
Website Host $2,500
Research and Development
$30,000
Brouchures $5,000
Rent + Utilities $54,000 ($30/square feet* 1800 square feet)
Labor (4 * $20/h * 2080 h) $167,000
Device cost(200 units*$180/year)
$36,000
Total $300,000+/- $20,000
Recurring Cost: Start-Up Cost:
Cost Price
Fixed Cost (legal cost, website host)
$10,000
Total Variable Cost (Total Quantity of Output * Variable Cost Per Unit of Output)
$570,000
Overhead (Rent, Utilities, Health Insurance, Marketing for one year)
$60,000
Total Cost $650,000 +/- $20,000
Cost and BenefitOptimistic Case:
KMS will be able to capture 16,000 people
almost 10% of the market share
Penetration rate of 15%
Market price of $1000
Break even in first year with 250 units sold
61
Cost and Benefit
Pessimistic Case:
KMS will be able to capture 6,000 people
almost 3% of the market share
Penetration rate of 5%
Unit price of $1000
Break even in 2 years with 300 units sold
62
ROI & NPV
63
Future Work Miniaturize Electronics
Conductive Thread
Incorporating Muscle Forces
Extensive Testing
Perform the field test Testing KMS device on GMU athletes
Distributing surveys
64
Sources Quatman, C. E., Quatman-Yates, C. C., & Hewett, T. E. (2010). A ‘Plane’Explanation of Anterior Cruciate Ligament Injury Mechanisms. Sports Medicine, 40(9), 729-746. Chapman MW. Chapmans Orthopaedic Surgery. 3rd Edition, Volume 3, 2001; 2348-2388.
Mall, N. A., Chalmers, P. N., Moric, M., Tanaka, M. J., Cole, B. J., Bach, B. R., & Paletta, G. A. (2014). Incidence and trends of anterior cruciate ligament reconstruction in the United States. The American journal of sports
medicine, 42(10), 2363-2370.
Barber-Westin SD, Noyes FR, Galloway M. Jump-land characteristics and muscle-strength development in young athletes: a gender comparison of 1140 athletes 9 to 17 years of age. Am J Sprts Med. 2006;34(3):375-384.
http://www.momsteam.com/health-safety/muscles-joints-bones/knee/acl-injuries-in-female-athletes#ixzz4Nq0ISVPO
Gordon MD, Steiner ME.. Anterior cruciate ligament injuries. In: Orthopaedic Knowledge Update Sports Medicine III, Garrick JG. (Ed), American Academy of Orthopaedic Surgeons, Rosemont 2004. p.169.
American Academy of Orthopaedic Surgeons, July 2007, Anterior Cruciate Ligament Injury: Surgical Considerations, http://orthoinfo.aaos.org/topic.cfm?topic=A00297#A00297_R4_anchor (July 11, 2008)
Hewett, T. E., Ford, K. R., Hoogenboom, B. J., & Myer, G. D. (2010). UNDERSTANDING AND PREVENTING ACL INJURIES: CURRENT BIOMECHANICAL AND EPIDEMIOLOGIC CONSIDERATIONS - UPDATE 2010. North
American Journal of Sports Physical Therapy : NAJSPT, 5(4), 234–251.
C. Myers and D. Hawkins, "Alterations to movement mechanics can greatly reduce anterior cruciate ligament loading without reducing performance", Journal of Biomechanics, vol.43, no. 14, pp. 2657-2664, 2010.
Myers, C. A., & Hawkins, D. (2010). Alterations to movement mechanics can greatly reduce anterior cruciate ligament loading without reducing performance. Journal of biomechanics, 43(14), 2657-2664.
Singhal MC, Gardiner JR, Johnson DL Arthroscopy. 2007 May; 23(5):469-75
Spindler KP, Kuhn JE, Freedman KB, Matthews CE, Dittus RS, Harrell FE Jr, Am J Sports Med. 2004 Dec; 32(8):1986-95.
DeNoon, Daniel, ed. "Torn ACL May Heal without Surgery." WebMD Health News. N.p., 21 July 2010. Web. 13 Sept. 2016.
http://www.webmd.com/pain-management/knee-pain/news/20100721/torn-acl-may-heal-without-surgery
Luks, Howard J. "Partial Anterior Cruciate Ligament – ACL – Tears." Howardluksmd. N.p., 06 Jan. 2012. Web. 13 Sept. 2016.
http://www.howardluksmd.com/knee-common-injuries/acl-knee/partial-anterior-cruciate-ligament-acl-tears/
http://www.ncaa.org/health-and-safety/sport-science-institute/insurance-coverage-student-athletes
http://eorthopod.com/patellar-tendon-graft-reconstruction-of-the-acl/
M. Norcross, S. Johnson, V. Bovbjerg, M. Koester and M. Hoffman, "Factors influencing high school coaches’ adoption of injury prevention programs", Journal of Science and Medicine in Sport, vol. 19, no. 4, pp. 299-304,
2016.
http://www.contentfac.com/how-much-does-social-media-marketing-cost/
http://www.fairfaxcountyeda.org/doing-business-here/commercial-real-estate/office-market
http://files.eric.ed.gov/fulltext/EJ1072598.pdf
https://www.hss.edu/newsroom_young-acl-surgery-patients-need-second-surgery.asp
65
Appendix A: Non-Contact Failure Mechanisms
66Tibia
Femur
Gap puts strain on ACL
Stakeholder Relationship Diagram
67
Pressure Sensor: 260lb
68
trials Arduino Pressure Average
(Pa)
Calculated Pressure
(Pa)
Error Percent Error
trial 1760228.79 1014419.66 0.25 25.06
trial 2764373.14 1014419.66 0.25 24.65
trial 3737585.46 1014419.66 0.27 27.29
trial 4757021.38 1014419.66 0.25 25.37
trial 5766588.85 1014419.66 0.24 24.43
Min 365660.99
Max 436820.65
Median 365660.99
Avg 401316.33
Std Deviation 25169.95
Signal-to-Noise
ratio 15.94
Pressure Sensor: 220lb
69
trials Arduino Pressure Average
(Pa)
Calculated Pressure
(Pa)
Error Percent Error
trial 1688544.88 858355.03 19.78
trial 2674334.37 858355.03 0.21 21.44
trial 3690180.14 858355.03 0.20 19.59
trial 4686233.74 858355.03 0.20 20.05
trial 5705323.95 858355.03 0.18 17.83
Min 674334.37
Max 705323.95
Median 690180.14
Avg 688923.42
Std Deviation 11076.72
Signal-to-Noise
ratio
62.19
Pressure Sensor: 180lb
70
trials Arduino Pressure Average
(Pa)
Calculated Pressure
(Pa)
Error(%) Percent Error
trial 1594786.01 702290.40 0.15 15.31
trial 2615098.11 702290.40 0.12 12.42
trial 3615098.11 702290.40 0.12 12.42
trial 4631609.50 702290.40 0.10 10.06
trial 5621561.05 702290.40 0.11 11.50
Min 594786.01
Max 631609.50
Median 615098.11
Avg 615630.56
Std Deviation 13468.11
Signal-to-Noise
ratio
45.71
Pressure Sensor: 160lb
71
trials Arduino Pressure Average
(Pa)
Calculated Pressure
(Pa)
Error(%) Percent Error
trial 1561842.22 624258.52 0.10 10.00
trial 2573287.94 624258.52 0.08 8.16
trial 3590411.15 624258.52 0.05 5.42
trial 4595680.60 624258.52 0.05 4.58
trial 5580397.05 624258.52 0.07 7.03
Min 561842.22
Max 595680.60
Median 590411.15
Avg 580323.79
Std Deviation 13496.88
Signal-to-Noise
ratio
43.00
Pressure Sensor: 140lb
72
trials Arduino Pressure Average
(Pa)
Calculated Pressure
(Pa)
Error(%) Percent Error
trial 1550107.56 546225.77 0.01 0.71
trial 2533463.64 546225.77 0.02 2.34
trial 3542084.00 546225.77 0.01 0.76
trial 4533175.35 546225.77 0.02 2.39
trial 5561861.44 546225.77 0.03 2.86
Min 533175.35
Max 561861.44
Median 542084.00
Avg 544138.40
Std Deviation 12125.35
Signal-to-Noise
ratio
44.88
Pressure Sensor: 120lb
73
trials Arduino Pressure Average
(Pa)
Calculated Pressure
(Pa)
Error(%) Percent Error
trial 1467498.30 468193.89 0.00 0.15
trial 2445172.27 468193.89 0.05 4.92
trial 3504354.92 468193.89 0.08 7.72
trial 4491596.71 468193.89 0.05 5.00
trial 5436207.80 468193.89 0.07 6.83
Min 436207.80
Max 504354.92
Median 504354.92
Avg 468966.00
Std Deviation 29180.13
Signal-to-Noise
ratio
16.07
Pressure Sensor: 100lb
74
trials Arduino Pressure Average
(Pa)
Calculated Pressure
(Pa)
Error(%) Percent Error
trial 1400002.08 390161.14 0.03 2.52
trial 2435639.67 390161.14 0.12 11.66
trial 3453792.07 390161.14 0.16 16.31
trial 4453850.84 390161.14 0.16 16.32
trial 5413509.74 390161.14 0.06 5.98
Min 365660.99
Max 436820.65
Median 365660.99
Avg 401316.33
Std Deviation 25169.95
Signal-to-Noise
ratio
15.94
Pressure Sensor: 90lb
75
trials Arduino Pressure Average
(Pa)
Calculated Pressure
(Pa)
Error(%) Percent Error
trial 1402112.71 351145.20 0.15 14.51
trial 2401831.39 351145.20 0.14 14.43
trial 3365660.99 351145.20 0.04 4.13
trial 4436820.65 351145.20 0.24 24.40
trial 5400155.94 351145.20 0.14 13.96
Min 365660.99
Max 436820.65
Median 365660.99
Avg 401316.33
Std Deviation 25169.95
Signal-to-Noise
ratio
15.94
Bent Leg Jumps
76Time(ms)
Pre
ssur
e(P
a)
Time(ms)
Pre
ssur
e(P
a)
Time(ms)
Time(ms)
Pre
ssur
e(P
a)P
ress
ure(
Pa)
a
b
: Jump
: Landing
a
b
Straight Leg Jumps
77
Time(ms)
Pre
ssur
e(P
a)
Time(ms)
Pre
ssur
e(P
a)
Time(ms)
Time(ms)
Pre
ssur
e(P
a)P
ress
ure(
Pa)
Time(ms)
a
b
: Jump
: Landing
a
b
Arduino Code (Cntd)
78
Multiplexer pin selection
Buffered data sent to Matlab
Sets threshold and triggers alerts
Knee and AnkleSensor: 110°
79
Knee and AnkleSensor: 150°
80
Knee and AnkleSensor: 180°
81
Optimistic Scenario
82
Pessimistic units
83
Optimistic units
84
Pessimistic Scenario
85
Benefit to Athlete
86
Expected Cost to Athlete (sustaining ACL injury)
1/13 * $60,000 (cost for ACL surgery) = $5000
Manufacturing Cost + Labor
$180 + $1800 = $2000
Profit (+30%) $2000 + $600 = $2600
Savings (Expected Cost to Athlete - Cost of Device)
$5000 - $2600 = $2,400
Price of Device
