GS3-4-6
LIFE2012 2012 ೥ 11 ݄ 2 ೔–4 ೔ Ѫ஌ (໊‫ݹ‬԰େֶ)ಛఆ‫ے‬τϨʔχϯάΛ໨తͱ͢ΔχϡʔϥϧωοτϫʔΫΛ༻͍ͨӡಈ‫ي‬ಓͷઃ‫ͱܭ‬ධՁ

Design and Evaluation of Motion Path for Speciﬁed Muscle Training Using Neural Network˓ࢳ਺‫ݐ‬ଠʢ๛‫ٕڮ‬Պେʣࡾ޷޹యʢ๛‫ٕڮ‬ՊେʣࣉౢҰ඙ʢ๛‫ٕڮ‬Պେʣ
Kenta ITOKAZU, Takanori MIYOSHI, Kazuhiko TERASHIMA, Toyohashi University of Technology
Abstract: In recent years, ageing of the population has been emerged as a social issue in Japan. Therefore, it isimportant to regain and maintain muscle strength for care prevention. Speciﬁed muscle training is expected for eﬃcientrehabilitation and care prevention. In the present study, design of a motion path is proposed for the speciﬁed muscle
training using neural network. For training, the load is applied by using a 2-link arm. By using the proposed method
to estimate muscle activity level, it is possible to design a motion path that maximizes the activity of agonist muscles
and minimizes the activity of other muscles. EMG signal is measured during a trainig experiment and the degree ofmuscular revitalization is evaluated by the amplitude of EMG signal. Finally, the eﬀectiveness of proposed approachis demonstrated through experiments.
Key Words: Muscle Training, Rehabilitation, Care Prevention, Neural Network, EMG signal

6 axis force sensor
1.

ॹ‫ݴ‬ۙ೥, ೔ຊʹ͓͍ͯগࢠߴྸԽʹ൐͏ཁհ‫ऀޢ‬ͷ૿Ճ, հ‫ऀޢ‬ͷ‫ݮ‬গ͕໰୊ͱͳ͍ͬͯΔ. ·ͨ, հ‫ऀޢ‬ͷߴྸԽ΋ਐΜͰ͓Γ, ෛ୲͕૿Ճ͍ͯ͠Δ. ͜ͷΑ͏ͳঢ়‫͍͓ʹگ‬ͯ͸, ‫ྗے‬τϨʔχϯά౳ͷհ‫ޢ‬༧๷ʹΑΔཁհ‫ऀޢ‬ͷ‫ݮ‬গ͕ॏཁͰ͋Δ.
্ࢶ͸೔ৗੜ‫׆‬ಈ࡞ (ADL:Activity of Daily Living) ʹਂؔ͘Θ͓ͬͯΓ, ӡಈ‫ػ‬ೳ͕௿Լ͢Δͱੜ‫ʹ༷ࣜ׆‬େ͖ͳӨ‫ڹ‬Λ‫͢΅ٴ‬. ͦͷͨΊ, ߴྸऀʹର͢ΔϦϋϏϦγεςϜΛߏங͠, QOL(Quality of Life) ͷҡ࣋‫্͕޲ͼٴ‬๬ΊΔ‫ڥ؀‬Λఏ‫͢ڙ‬Δ͜ͱ͕େ੾Ͱ͋Δ.
࿝ਰ΍ප‫ؾ‬౳ʹΑΓ৸͖ͨΓͷঢ়ଶͱͳͬͨ৔߹, ‫ྗے‬ͷਰ͑ํ͸Ұ༷Ͱ͸ͳ͘, ֤‫Ͱے‬ҟͳΔ. ਰ͑ͨ‫ʹے‬ରͯ͠ͷΈෛՙΛ͔͚Δ͜ͱͰ, ޮ཰తͳ‫ྗے‬τϨʔχϯά͕‫ظ‬଴Ͱ͖Δ.
ஶऀΒͷैདྷ‫͍͓ͯʹڀݚ‬͸, ‫۽‬ຊΒ͕ఏҊͨ͠ 3 ର 6‫ے‬ͷ‫֨ࠎے‬ϞσϧΛ࢖༻͠, ಛఆ‫ے‬ͷ‫ڧ૿ྗے‬Λ໨తͱͨ͠ӡಈ‫ي‬ಓͷઃ‫ܭ‬Λߦͬͨ (1)(2) . ‫ي‬ಓઃ‫ʹܭ‬͸, ‫׆ے‬ಈͷਪఆͱͯ͠, ‫֨ࠎے‬Ϟσϧʹ‫͍ͨͮج‬ਪఆ๏Λ༻͍͍͕ͯͨ, ຊ‫Ͱڀݚ‬͸, ਪఆਫ਼౓ͷ޲্Λ໨తͱ͠, ‫׆ے‬ಈਪఆͷͨΊ, χϡʔϥϧωοτϫʔΫΛར༻͠, ͦΕΛ༻͍ͯಛఆ‫ے‬Λ‫׆‬ಈͤ͞Δӡಈ‫ي‬ಓΛઃ‫͢ܭ‬Δ. ·ͨ, ࣮‫࣌ݧ‬ͷද໘‫ిے‬Ґ (EMG) ৴߸͔Β, ఏҊख๏ͷධՁΛߦ͏.

2.

γεςϜߏ੒

DC motor
Rotaryencoder

Emergency
stop switch

Fig. 1 2-Link Arm
3. χϡʔϥϧωοτϫʔΫ
3-1 ֓ཁຊ‫͍༻Ͱڀݚ‬ΔχϡʔϥϧωοτϫʔΫͷ໛ࣜਤΛ Fig.
2 ʹࣔ͢. தؒ૚ͷϢχοτ਺͸ 10 ͱͨ͠. ೖྗ͸‫ٴݞ‬ͼගͷؔઅτϧΫ T1 , T2 , ؔઅ֯౓ θ1 , θ2 , ؔઅ֯଎౓ θ˙1 ,θ˙2 Ͱ͋Δ. ·ͨ, ग़ྗ͸֤‫ے‬ͷ‫׆ے‬ಈϨϕϧ αi Ͱ͋Δ. ‫ے‬‫׆‬ಈϨϕϧ͸ (1) ࣜʹΑΓఆٛ͞ΕΔ.

αi (t) =EM Gi (t)(i = 1 ∼ 5)
maxEM Gi(1)͜͜Ͱ, EM Gi (t) ͸, ࣮‫ݧ‬தͷ֤‫ے‬ͷ EMG ৴߸Ͱ͋Γ, maxEM Gi ͸֤‫ے‬ͷ࠷େਵҙ‫࣌شൃྗے‬ͷ EMG ৴߸Ͱ͋Δ. maxEM Gi ͸༧Ί, ౳ईੑӡಈʹͯ‫ܭ‬ଌ͢Δ.
(1) ࣜʹΑΓ, ‫׆ے‬ಈϨϕϧ͸ 0∼1 ͷ஋ͱͳΓ, ‫׆ے‬ಈͷ౓߹͍Λࣔ͢.

Fig. 1 ʹ, ຊ‫͢༻࢖Ͱڀݚ‬Δ 2 ϦϯΫΞʔϜΛࣔ͢. ֤ؔઅ෦ʹ DC Ϟʔλ, ϩʔλϦʔΤϯίʔμ, खઌҐஔʹ 6࣠ྗ֮ηϯα͕౥ࡌ͞Ε͍ͯΔ. ·ͨ, Ծ૝ͷ೪ੑ͕ઃఆ
͞Ε͓ͯΓ, खઌͷҠಈ଎౓ʹൺྫͨ͠ෛՙΛඃ‫ʹऀݧ‬༩͑Δ.
ຊ‫ڀݚ‬͸, 2 ࣍‫ݩ‬ฏ໘্ͷӡಈΛର৅ͱ͢Δ. ࣮‫ݧ‬ͷࡍʹ͸, ඃ‫ऀݧ‬ͷࠨ࿹Λ 2 ϦϯΫΞʔϜʹԊ͏Α͏ʹࡌͤΔ.
ߋʹ, ઃ‫ͨ͠ܭ‬ӡಈ‫ي‬ಓΛϞχλʹදࣔ͠, खઌҐஔΛࣔ͢ϚʔΧʔ͕ͦͷ‫ي‬ಓΛͳͧΔΑ͏ 2 ϦϯΫΞʔϜΛಈ
͔͢.

T1
ǩ1

T2
ǰ1
ǰ2࡮࡮࡮

࡮

ǰ1
࡮
ǰ2

ǩ4
ǩ5Fig. 2 Neural Network

−1−

ǩ2
ǩ3

0.7

3-2 σʔλֶशσʔλͷֶशํ๏͸‫఻ٯࠩޡ‬೻๏ͱ͠, ‫׆‬ੑԽؔ਺͸ (2)ࣜͰද͞ΕΔγάϞΠυؔ਺ͱͨ͠.

1
1 + e−x0.6

Rate of Muscle Activationf (x) =

˳Measured Value
Estimated Value(2)·ͨ, ֶशσʔλͱͯ͠, Fig. 3 ʹࣔ͢ӡಈ‫ي‬ಓͰ, ௚ઢӡಈΛߦͬͨ৔߹ͷ֤࣮‫ݧ‬஋Λ༻͍ͨ. ࣮‫࣌ݧ‬͸, Table 1Ͱࣔ͞ΕΔ‫ے‬ͷද໘‫ిے‬ҐΛଌఆͨ͠.
Fig. 4ʙ8 ͸, ֶश‫ޙ‬ͷχϡʔϥϧωοτϫʔΫΛ༻͍ͯ‫׆ے‬ಈϨϕϧΛਪఆͨ݁͠ՌͰ͋Δ. ೖྗσʔλ͸, ‫ۂ‬ઢӡಈΛ‫ؚ‬Μ্ͩࢶӡಈΛߦͬͨ৔߹ͷ֤࣮‫ݧ‬஋Ͱ͋Δ.
·ͨ, ֶशσʔλΛ༻͍ͯਪఆͨ͠৔߹ͷೋ৐ฏ‫ࠩޡۉ‬͸
0.04048, ೚ҙσʔλΛ༻͍ͨ৔߹͸ 0.04496 ͱͳΓ, ֶशʹ༻͍ͨӡಈͱ͸ҟͳΔೖྗσʔλʹ͓͍ͯ΋, ྑ޷ͳਪఆ݁ՌΛಘΔ͜ͱ͕Ͱ͖ͨ.

0.5
0.4
0.3
0.2
0.1
00˳

100.87080

Rate of Muscle Activation

0.5
0.4
0.30.2

˳

10203040
Time [s]50607080

Fig. 7 Estimation Result(M4)0.05
y [m]60

0.6

0.1

00.8

0.05

0.7

Rate of Muscle Activation

0.1
0.15
0.2
0.25
0.25

0.2

0.15

0.1

0.05

0x [m]

0.05

0.1

0.15

0.2

0.25

Fig. 3 Motion Path
Table 1 Measured Muscles

0.9

4.

0.6
0.5
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30

40
Time [s]

50

0.4
0.3
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60

2030

40
Time [s]

50

60

70

80

7080

˳

Measured Value
Estimated Value

0.3ӡಈ‫ي‬ಓઃ‫ܭ‬ຊ‫ڀݚ‬͸, ಛఆ‫ے‬೑ͷ‫ڧ૿ྗے‬Λ໨తͱ͍ͯ͠ΔͨΊ, ର৅‫ے‬೑ͷΈ͕‫׆‬ಈ͠, ͦͷଞͷ‫ے‬ͷ‫׆‬ಈ͕࠷খͱͳΔΑ͏ͳӡಈ‫ي‬ಓΛઃ‫͢ܭ‬Δ. ‫ي‬ಓઃ‫ʹܭ‬͸, χϡʔϥϧωοτϫʔΫΛ࢖༻͠, ࠷దͳྗํ޲Λ୳ࡧ͢Δ͜ͱͰલड़ͷ໨తΛୡ੒͢Δ.
·ͣ, ॳ‫࢟ظ‬੎Ͱ, ਫฏ໘্ͷશํ޲ʹखઌग़ྗΛ 30[N]ൃ‫͢ش‬Δ৔߹ʹ͓͍ͯ, (3) ࣜͷଟ໨త࠷దԽ໰୊Λղ͖,࠷దͳྗํ޲Λ‫ٻ‬ΊΔ. ͜͜Ͱ, αn (θ) ͸, ‫ྗے‬τϨʔχϯάର৅‫ے‬ͷ‫׆ے‬ಈϨϕϧ, ᾱ(θ) ͸, ର৅‫ے‬Ҏ֎ͷ‫׆ے‬ಈϨϕϧͷฏ‫ۉ‬, σ 2 (θ) ͸ର৅‫ے‬Ҏ֎ͷ‫׆ے‬ಈϨϕϧͷ෼ࢄͰ
͋Δ. ·ͨ, θ ͸ྗํ޲Λද͢.

Fig. 4 Estimation Result(M1)
0.35

10

Fig. 8 Estimation Result(M5)

0.7

20

0.5

˳

˳

10

0.6

00

Measured Value
Estimated Value

0.8

˳Measured Value
Estimated Value

0.1NamePectoralis major
Latissimus dorsi
BrachioradialisTriceps brachii Lateral head
Biceps brachii

M1M2M3M4M5Rate of Muscle Activation50˳

000.15Rate of Muscle Activation

40
Time [s]0.10.2

˳

30

Measured Value
Estimated Value

0.7

0.25

0020

Fig. 6 Estimation Result(M3)maxαn (θ)

minsubject toᾱ(θ), σ 2 (θ)
0 ≤ θ < 2π(3)࣍ʹ, (3) ࣜͰಘΒΕͨྗํ޲ʹ, खઌҐஔΛ 1[cm] Ҡಈͤͨ࢟͞੎ʹ͓͍ͯ, ্‫ه‬खॱΛ‫܁‬Γฦ͢͜ͱͰӡಈ‫ي‬ಓΛಘΔ.
ࠓճ͸, Table 1 Ͱࣔ͢‫ے‬Λ‫ྗے‬τϨʔχϯάͷର৅ͱ
ͨ͠. M1 ∼M5 ʹؔͯ͠, ಘΒΕͨӡಈ‫ي‬ಓΛ Fig. 9 ʹ
ࣔ͢.

0.25
0.20.150.1
0.05
00˳

10203040
Time [s]

5060

7080

Fig. 5 Estimation Result(M2)

−2−˳

0.2

10.15

0.90.1

M1

M4

0.8
Rate of Muscle Activation

Yaxis [m]

0.05
00.05
M5

0.1
M2

0.15
0.2

M3

0.25

0.7
0.6
0.5
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˳

0.2

0.15

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0.05
0Xaxis [m]

0.05

0.1

0.1

0.15

0Fig. 9 Designed Motion Path
EMG ଌఆ࣮‫ݧ‬ࠓճ৽ͨʹઃ‫ͨ͠ܭ‬ӡಈ‫ي‬ಓͱैདྷ‫͚͓ʹڀݚ‬Δӡಈ‫ي‬ಓΛ༻͍ͯ EMG ৴߸ͷଌఆ࣮‫ݧ‬Λߦͬͨ. ඃ‫ऀݧ‬͸ࠨ࿹Λ 2 ϦϯΫΞʔϜʹԊ͏Α͏ʹ৐ͤ, ਫฏํ޲ʹྗΛൃ‫ش‬͢ΔΑ͏࣮‫ݧ‬Λߦ͏. ࣮‫ݧ‬ͷࡍ͸, ӡಈ‫ي‬ಓͷଟ߲ۙࣅ‫ۂ‬ઢΛϞχλʹදࣔ͠, खઌҐஔΛࣔ͢ϚʔΧʔ͕දࣔ͞Εͨ‫ي‬ಓΛͳͧΔΑ͏ʹಈ࡞ͤ͞Δ.
࣮‫݁ݧ‬ՌΛ Fig. 10ʙ14 ʹࣔ͢. ॎ࣠͸‫׆ے‬ಈϨϕϧ,ԣ࣠͸֤‫͋Ͱے‬Δ. ൺֱͷͨΊ, ‫׆ے‬ಈϨϕϧ͸֤࣮‫ݧ‬ʹ͓͚Δ࠷େ஋Ͱਖ਼‫ن‬Խͨ͠. Fig. 10ʙ14 ͸ͦΕͧΕ,M1 ∼M5 ΛτϨʔχϯάର৅‫͍ͯ͠ͱے‬Δ.
Fig. 10ʙ13 ʹ͓͍ͯ͸, ࠓճઃ‫ͨ͠ܭ‬ӡಈ‫ي‬ಓΛ༻͍ͨํ͕, ର৅‫ے‬Ҏ֎ͷ‫׆ے‬ಈΛ཈͑ΒΕ͍ͯΔ. M3 Λର৅‫ ͨ͠ͱے‬Fig. 12 Ͱ͸, ৽‫ي‬ಓΛ༻͍Δͱ M3 ͷ‫׆‬ಈ͕௿͘ͳΔ΋ͷͷ, ଞͷ‫ے‬ͷ‫׆‬ಈ͕େ෯ʹ཈͑ΒΕ͍ͯΔ.
M1 ∼M4 ͸Ұؔઅ‫͋Ͱے‬Γ, ͜ΕΒͷ‫ʹے‬ରͯ͠͸, ຊ‫ݚ‬‫ڀ‬ͷ໨తΛ֓Ͷୡ੒ͨ͠ͱ͍͑Δ.
Ұํ, Fig. 14 ʹࣔ͢௨Γ, ೋؔઅ‫͋Ͱے‬Δ M5 ΛτϨʔχϯάର৅ͱ͢Δͱ, ଞͷ‫ے‬΋ಉ࣌ʹ‫׆‬ಈ͍ͯ͠Δ. ೋؔઅ‫ے‬ͷτϨʔχϯάʹؔͯ͠͸վળͷ༨஍͕͋Δ.
1

M1

M2

M3

M40.9

M5

˳

Proposal Path
Previous Path

0.8

Rate of Muscle Activation

0.7
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˳

M1

M2

M3

M4

M5

Fig. 13 Experiment Result(M4)1˳Proposal Path
Previous Path

0.9

Rate of Muscle Activation

0.8
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0.3
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˳

Proposal Path
Previous Path0.9

˳Fig. 12 Experiment Result(M3)

5.

0.1
00.8
Rate of Muscle Activation

˳Proposal Path
Previous Path˳

M1

M2

M3

M4

M5

Fig. 14 Experiment Result(M5)

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6.

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0M1

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Fig. 10 Experiment Result(M1)1˳Proposal Path
PreviousPath0.9݁‫ݴ‬ࠓճ, ‫׆ے‬ಈਪఆ๏ͱͯ͠৽ͨʹχϡʔϥϧωοτϫʔΫΛ༻͍Δ͜ͱͰ, ಛఆ‫ڧ૿ྗے‬ͷͨΊͷӡಈ‫ي‬ಓઃ‫ܭ‬Λߦͬͨ. ͦͷ݁Ռ, ैདྷख๏Ͱઃ‫͞ܭ‬Εͨ‫ي‬ಓΛ༻͍ͨ৔߹ͱൺֱͯ͠, Ұؔઅ‫ͯؔ͠ʹے‬͸վળ͕‫ݟ‬ΒΕͨ. Ұํ,ೋؔઅ‫ͯؔ͠ʹے‬͸ଞͷ‫ے‬ͷ‫׆‬ಈ͕͋Γ, ՝୊͕࢒͞Εͯ
͍Δ.
‫ࡏݱ‬, શͯͷӡಈ‫ي‬ಓͷॳ‫࢟ظ‬੎Λ‫ݻ‬ఆ͍ͯ͠Δ͕, ͜ΕΛ֤‫ے‬ຖʹม͑Δ͜ͱͰ, ӡಈ‫ي‬ಓͷࣗ༝౓͕޲্͠, ݁Ռ͕վળ͞ΕΔՄೳੑ͕͋Δ. ·ͨ, ࠓ‫ޙ‬, ຊख๏ͷԼࢶʹର͢Δద༻΍, 3 ࣍‫ݩ‬ӡಈ΁ͷ֦ு౳΋ߦ͏.

Rate of Muscle Activation

0.8ࢀߟจ‫ݙ‬

0.7
0.6(1) T. Okada, T. Imamura, T. Miyoshi, K. Terashima,Y. Yasuda, T. Suzuki, Muscle Strength Estimation
Using Musculo-Skeletal Model for Upper Limb Rehabilitation, Journal of Robotics and Mechatronics,
vol. 20, no. 6, pp. 863-871, 2008.
(2) ࢳ਺, ࡾ޷, ࣉౢ, ಛఆ‫ے‬τϨʔχϯάΛ໨తͱ͢Δ፰߅‫ے‬Λߟྀͨ͠ӡಈ‫ي‬ಓͷઃ‫ͱܭ‬ධՁ, ೔ຊ‫ػ‬ցֶձ౦ւࢧ෦ ୈ 61 ‫ظ‬૯ձɾߨԋձ, pp. 126-127, 2012.

0.5
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0.10˳M1M2M3M4

M5Fig. 11 Experiment Result(M2)−3−