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DALT : Detection Algorithm of Throwing Form

Changing to Prevent the Baseball Players’ Throwing Related Injuries

Keio UniversityYuuki Nishiyama

[email protected]

12年6月10日日曜日

mailto:[email protected]

mailto:[email protected]

Abstract• We achieved creating the algorithm (DALT)

to detect the change in throwing form by using wearable gyroscope sensor.


Introduction• In baseball, the injury of shoulder and

elbow(throwing injury) issues for many baseball players

- it is caused by overwork or unsuitwork- 72% of high school baseball players experience

the injury in Japan

• the player has to manage their condition by themselves

- there are fewer numbers of coaches than baseball players in a team


Status of Throwing Injury-Questionnaire of the Keio Univ. and high school baseball team-

• Questionnaire survey (to 181 players)[Fig.1] 57% of players have experience of throwing injury

[Fig.2] 63% of players practicing with throwing injury even now

[Fig3.] 83% of throwing injuries are the cause of overwork

43%57%

have an experience don’t have an experience

20%

38%43%

usuallysometimesseldom or never

13%17%

33%

37%

overworkbad formeitheranother

Fig1. experience of throwing injury

Fig2. throwing injury even now

Fig3. cause of throwing injuries


Motivation

• We want to prevent the baseball players’ throwing related injuries


Throwing motion• Throwing motion is consist of five

phases(Frank Jobe)- Wind-up, Early-cocking, Late-cocking,

Acceleration, Follow-through

• Definition of Motion Points- Takeback, Cock, Top, Maxout, Release- between phase

and phaseTakeback Cock Top Maxout Release

Wind-up Early-cocking Late-cocking Acceleration Follow-through


Pathogenic mechanism of throwing injuries

• Fatigue of deltoid muscle and supraspinatus muscle from increase in number of throw

• Increase of shearing strength to shoulder joint at late-cocking

• Accumulation of fatigue to joint lip and a ligament

• Lead to throwing injure - SLAP lesion，Bennett lesion

Takeback Cock Top Maxout Release

Wind-up Early-cocking Late-cocking Acceleration Follow-through


Method of prevention of throwing injuries• Limit the number of throwing

- Limit of the number of the throws in Little League‣ http://www.littleleague.org/media/newsarchive/2007stories/

07pitching_rule_reg_changes_10_07.htm

• Detection fatigue statue- blood lactate level- measurement of joint motion and power- analysis throwing from


http://www.littleleague.org/media/newsarchive/2007stories/07pitching_rule_reg_changes_10_07.htm




Related work

• High speed camera (DLT)• 3D motion capture system• Motion sensor

(acceleration and gyro sensor)


Problem

• The perception of objective throw fatigue is difficult by self management

• Existing systems have difficulty in use by the exercise


Approach

• Detect the throw form change with increase of the number of he throws

• Using only one sensor device- 3D wireless gyro sensor


DALT:Detection Algorithm of Throwing Form Changing

• Sensor was put on the lower part of upper arm

- 200Hz, 1500deg/sec(LOGICAL PRODUCT)

• Using personal throw data( =base throwing data )

• Three step of DLAT1. Detection of the Throwing Motion2. Decomposition of Throwing Form3. Calculate Rate of Throwing Form Change

Z

Y X


Angular velocity data of throwing

-400-300-200-1000

100200300400500

ZYX

Takeback Cock Top Maxout Release


Base Throwing Data1. The personal data of angle velocity in

throw motion- Normal throw from ×10 throws- Fatigue throw from ×10 throws

2. Detect the release ; I will state this later3. Save the data for 400 frames from release4. Calculate data of average from ten throws


1. Detection of the Throwing Motion

1. Save 400 frame datas(angle verosity)2. Detect of release

- using threshold3. Judge of throwing motion

- using correlation coefficient

STEP1 STEP2 STEP312年6月10日日曜日

• Y-axis value becomes 0 at near release- “Measurement of motion of upper limb and trunk with inertial

sensors during baseball pitch”

2011, Kenji saito, Journal of Nagoya Gakuin University

• A shape upper arm internal rotation motion and external rotation

- Increase of shape Y-axis value

• Threshold...1. Y-axis : -350deg/sec2. Y-axis : 0deg/sec

‣ release point

Detect of release

-400-300-200-1000

100200300400500

Time ( 1/200sec )

deg/sec

Y-angleX-angle

Z-angle

1. Y < -350deg/sec

2. Y = 0deg/sec = release

-350deg/sec


Judge of throwing motion using coefficient correlation• Calculate a coefficient correlation of

NormalData and NowData• Judge the throw motion from result of

coefficient correlation- Y-axis > 0.8- X-axis > 0.5- Z-axis > 0.5

STEP1 STEP2 STEP312年6月10日日曜日

2. Decomposition of Throwing Form• Decomposition throwing form from Model

of kinetic chain- back calculation from release- detect distinctive actions

in order of release, maxout, top, cock, takeback

STEP1 STEP2 STEP3

motion points distinctive data

release start position of the analysis

maxout Y-axis < 0top Z-axis > 0cock Y-axis > 0

takeback X-axis > 0


3. Calculate Rate of Throwing Form Change

• The acquisition of angular velocity data between Top and Maxout

- Now form data (nowData)- Normal form data (normalData)- Fatigue form data (fatigueData)

• Calculate a coefficient correlation(NowR) of nowData and normalData

• Calculate a coefficient correlation(BaseR) of normalData and fatigueData

• Rate of throwing form change(Rtc) = Now / BaseR×100

STEP1 STEP2 STEP3

angular velocity(deg/sec)

time( 1/200sec )normal form datafatigue form data

Maxout Release


Hardware organization• Program language

- java

• PC of data analysis- MacBook Pro 15inch- 8GB, Intel Core 2 Duo

• Using sensor- 9 axis wireless sensor

‣ Logical Product

SpecificationsAngular velocity sensor ±1500dps

Sampling interval 200Hz

Size 55mm×40mm×22mm

Weight 35g


Software configuration

Data of angular velocity

Rate of throwing form change

Personal throwing data of angular velocity

Module of decomposition of throwing form

Module of calculating rate of throwing form change

Part of coefficient correlation

Part of detecting release

Save 400 frame datas

Module of detection of throwing motion

The layer of calculating change of throw motion

Layer of judging throw motion

基準角速度データ

基準角速度データ

angular velocity

angular velocity

angular velocity

angular velocity angular velocity

angular velocity

angular velocity


Evaluation Experiment• Goal of evaluation

- Evaluation of suggestion algorithm (DALT)

• Method of evaluation- 100 pitches of consecutive throws of rundown (27.431m)

‣ Ability of the ball control

‣ DTL-method : 3D motion analysis using two high speed camera

‣ DALT : Detection Algorithm of Throwing Form Changing

• Examinee- College baseball player × 5

• Place - The Keio university’s

baseball field

Z

Y X


Estimation Procedure1. Divide result of 100 throws into three terms

- 1~10(Term1), 45~55(Term2), 91~100(Term3)2. Analysis of variance (ANOVA) at each three

terms3. Analysis of Dunnett’s test as the multiple

comparisons- term1 is control term


Result of ANOVA• Ball control ability had no significant

- ball control ability could not be a barometer of fatigue state

• DALT and DLT-method were different significantly

- DALT and DLT-method could be a barometer of fatigue state

Methods Average (±Standard Deviation)Average (±Standard Deviation)Average (±Standard Deviation) F p SignificanceMethodsTerm1 Term2 Term3

F p Significance

Ball control Ability 3.44(±1.24) 3.56(±1.36) 3.3(±1.28) 0.23 0.8 n.s.

DTL-method 11.41(±3.95) 12.43(±4.48) 15.36(±5.99) 8.7928 0.0002 **

DALT 40.71(±22.21) 70.64(±29.9) 73.04(±32.12) 20.38 0.0001 **

F : F-distribution * : p<0.05 ** : p<0.001 n.s. : not significantF : F-distribution * : p<0.05 ** : p<0.001 n.s. : not significantF : F-distribution * : p<0.05 ** : p<0.001 n.s. : not significantF : F-distribution * : p<0.05 ** : p<0.001 n.s. : not significantF : F-distribution * : p<0.05 ** : p<0.001 n.s. : not significantF : F-distribution * : p<0.05 ** : p<0.001 n.s. : not significantF : F-distribution * : p<0.05 ** : p<0.001 n.s. : not significant12年6月10日日曜日

Evaluation of Dunnett’s test• DALT was significantly different between

Term1 and Term2, and Term1 and Term3• DTL-method was significantly different

between Term1 and Term 3

0

20

40

60

80

100

1 2 3

Rtc

(%)

Group

****

****

0

5

10

15

20

25

1 2 3

Max

-SA

(ang

le)

Group

**n.s

**n.s

n.s : not significant * : p < 0.05 ** : p < 0.00112年6月10日日曜日

Result of Analysis Time

• DLT-method- 45minutes / 1 throw

• DALT- 22.5 seconds / 1 throw


Conclusion

• We proposed the Detection algorithm of throwing form changing(DALT)

- DALT can detect throwing form changing- DALT analyzes state in mach shorter time

than DAT-method- DALT is executed automatically


Future work• The implementation of the learning

system• Necessary to conduct the experiment

with various distance • Comparison with the 3D motion capture

system• Real time feedback system


Thank you for listening


Support Documentation


Injures of shoulder joint

• SPLA lesion- Superior labrum anterior and posterior lesion

• Bennett Lesion• Shoulder Impingement Syndrome• Dead arm syndrome


SLAP lesion-superior labrum anterior and posterior lesion-

• Superior Labrum Anterior and Posterior

• Term definition- articular lip- long head of biceps brachii muscle- infraspinatus muscle- deltoid muscle


Misdetection on Decomposition of Throwing Form

• Normal form data • Fatigue form data


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