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1 - - A New Control Method for Power-assisted Wheelchair based on the Surface Myoelectric Signal 2024 : 66427
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5 % % % 5 1 [1] % : 1.1 [2] - 3 -
![8% 5 1 [1] 50 40.](/docs-images/50/20164902/images/page_5.jpg "5% 5 2 65 2025 680 1.")
6 (%) () : The world health report 2006( WHO ) 2000 [4] [3] % 17.7% 1.3%
7 : - 5 -
8
9 : KAL-40B - 7 -
10 NEO-P : JWII - 8 -
11 YAMAHA JWII DSP : DSP AD PWMCAN Texas Instruments ezdsp2808 ezdsp2808 RAM 36KB TAC SH3 SH7706LAN 2.4: 24V90W DC DSP 40[µs] PWM 20[µs] DSP - 9 -
12 2.2 AD 0[V] 3[V] 0[V ] 5[V ] DSP 16chAD 160[ns] 12bit DSP DSP SH3 16 SH3 SD SH3 DSP 1[ms] DSP 1[ms] AD Duty SH3 2.1 YAMAHA JWII DSP Texas Instruments ezdsp2808 TAC SH7706LAN MES-01 RE20F STL Japan HS-EG : 26[kg] 2.2, [kg] 1[kg]([%]) 1[kg]([%]) 11[kg]([%]) 13[kg]([%]) 16[kg]([%]) 18[kg]([%]) 25[kg]([%]) 27[kg]([%]) 2.2: 2.3: 24[V]4.5[Ah]
13 τ assist = ɛ P A 1 + τs τ human (3.1) : τ human τ assist ɛ P A τ
14 3.2 (3.1) (3.2) τ = { τ1 = 0.1[s] τ human > 0 τ 2 = 0.5[s] τ human < 0 (3.2) : 3.3: 3.4: 3.5:
![5[s] τ human < 0 (3.2) 3.2 3.2 3.3 3.](/docs-images/50/20164902/images/page_14.jpg "4 3.5 3.2: 3.3: 3.4: 3.5: 3.4 3.2 1.")
15 3.2 τ : τ 1 = 0.01[s], τ 2 = 0.5[s] 3.7: τ 1 = 0.5[s], τ 2 = 0.5[s] τ : τ 1 = 0.1[s], τ 2 = 0.05[s] 3.9: τ 1 = 0.1[s], τ 2 = 2[s]
![5[s], τ 2 = 0.5[s] 3.6 3.7 τ 2 3.8 3.9 3.](/docs-images/50/20164902/images/page_15.jpg "8: τ 1 = 0.1[s], τ 2 = 0.05[s] 3.")
16
17 [9] 10[µV ] 20[mV ] [Hz] : 4.1 SH
![] 20[mV ] 2](/docs-images/50/20164902/images/page_17.jpg "1000[Hz] 4.1.2 4.")
18 4.2 [11] [12] 4.1 EMOS PX 4.1 CYBERDYNE HAL [13] ON OFF : EMG 4.2 [21] 4.2 MES
![1 CYBERDYNE HAL [13] ON](/docs-images/50/20164902/images/page_18.jpg "OFF 4.2 4.1 4.1: EMG 4.")
19 : EMG 4.2: semg V bit AD 1 khz AD 2.5[V] : 4.4:
20 : 4.6: 4.7: [V] [V] 2.5[V] [V] [V] 4.7 0[V] 5[V] electoromechanical delay:emd [ms] [10]
![2344[V] 4.7 0[V] 5[V] 4.2.2 1.](/docs-images/50/20164902/images/page_20.jpg "2. 3. 1.")
21
22 : [ms] FFT [Hz] 300[Hz] STFT
23 : (5.1) [6] X(b, ω) = w(t b)e jωt x(t)dt (5.1) w : [Hz]
24 iemg [5] 5.4 () 10[Hz] [7]iEMG 5.4: 10[Hz] 3[Hz] iemg 5.5, : 10[Hz] 5.6: 3[Hz]
25 : 100Hz ms : 5.9: 5.10: 5.11:
26 , [Hz] [Hz] 5.12: 100[Hz] 5.13: 10[Hz] [Hz] : 5.14 demg 5.7 τ (5.2) { τ1 = 0.1[s] v > 0 τ = (5.2) τ 2 = 0.5[s] v <
27 , 5.16 ɛ = , 5.18 ɛ = : 5.16: 5.17: 5.18:
28
29 6 [8] J n, B n T a LPF 6.1 J n (s) (6.1) T a = 0.01, B n = 0.2 J n = { 0.5 v > v < 0 (6.1) 6.1:
30 : DisturbanceObserver 6.1 K 6.4, :
31 : 6.5: ( ) [s]
32 : 7.1 FuzzyController 7.2 F 1 F v α F 1 F 2 K1, τ 1 K1 τ
33 : F 1, F 2 7.2: 7.4: v β F 1 F 2 K2, τ 2 K2 τ 2 v α v β F 2 F 1 v α v β τ 1 = τ 2 = 0.5[s]
34 ,7.6 v α = 0.3, v beta = 0.8, K 1 : K 2 = 4 : 1τ 7.1 τ = { τ1fast = τ 2fast = 0.1[s] v > 0 τ 1slow = τ 2slow = 0.5[s] v < 0 (7.1) 7.5: 7.6: [ms]
35 7.2 K 1, K 2 K 1, K 2 7.7, 7.8 K 1 : K 2 = 7 : 1 7.9, 7.10 K 1 : K 2 = 1 : 1 7.7: (K1:K2=7:1) 7.8: (K1:K2=7:1) 7.9: (K1:K2=1:1) 7.10: (K1:K2=1:1) K 1 7.7, 7.8 K 2 K
36 7.2 K 1 7.9, 7.10 K 2 K 1 v α, v beta v α, v beta??,?? v α = 0.1, v beta = 1.5??,?? v α = 1.0, v beta = : (v α = 0.1, v beta = 1.5) 7.12: (v α = 0.1, v beta = 1.5) 7.14: 7.13: (v α = (v α = 1.0, v beta = 1.05) 1.0, v beta = 1.05)
37 7.2 v α v β 7.13, 7.14 v α v β v α v α v β 7.11, 7.12 τ 1, τ 2 τ 1, τ , , τ = { τ1fast = τ 2fast = 0.05[s] v > 0 τ 1slow = τ 2slow = 0.2[s] v < 0 (7.2) τ = { τ1fast = τ 2fast = 0.5[s] v > 0 τ 1slow = τ 2slow = 1.125[s] v < 0 (7.3) 7.15: (7.2) 7.16: ( 7.2) , ,
38 : 7.17: ( (7.3) 7.3) 7.18 τ
39 : 8.2:
40 : 8.4:
41 : direction direction + direction
42 : : 8.8:
43 :
44 : : :
45 [ms] 0.5[Nm] 8.1 demg τ assist = τ stop exp β demgmax t (8.1) τ stop demg demg max demg max demg β?? : 8.14:
46 : 8.16: [s] [s]
47 : 8.18:
48
49
50 LotfiMostefai WuEric
51 [1], [2] WHO The world health report 2006, [3], 2005,, [4] WAM NET,,, [5],,, :, C,Vol.124, No.2, pp , [6] Du, S., Vuskovic, M.: Temporal vs. Spectral approach to Feature Extraction from Pre-hensile EMG Signals, The IEEE Int. Conf. on Information Reuse and Integration (IEEE IRI-2004), Las Vegas, Nevada pp (2004). [7] M. Yoshida, M.Terao : Suitable Cutoff Frequency of Low-pass Filter for Estimating Muscle Force by Surface Eectromyogram, Proceedings of 25th Annual International Conference of the IEEE EMBS pp ,2003 [8] Y. Kaida and T. Murakami: Power-Assist Motion of an Electric Wheelchair for a Caregiver, Proceedings of the 9th International Workshop on Advanced Motion Control, AMC 06, pp , 2006 [9] Peter Konrad: The ABC of EMG : A Practical Introduction to Kinesiological Electromyography Version 1.0 April [10] L. Li, B. Baum: Electromechanical delay estimated by using electromyography during cycling at different pedaling frequencies. Journal of Electromyography and Kinesiology, Volume 14, Issue 6, Pages ,2004 [11] Gordon K.E., Ferris D.P.: Proportional myoelectric control of a virtual object to investigate human efferent control Experimental Brain Research, Vol.159, pp ,2004. [12],,, : EMG, Vol.29, No.10, pp ,
52 [13] H. Kawamoto, S. Lee, S. Kanbe, Y. Sankai: Power assist method for HAL-3 using EMG-based feedback controller, IEEE International Conference on Systems, Man and Cybernetics 2003, vol. 2, pp , [14] Sehoon Oh, Naoki Hata, Yoichi Hori: Integrated motion control of a wheelchair in the longitudinal, lateral and pitch directions, Proc. of AMC-2006, , Istanbul [15] Takeaki Sugimoto, Hirokazu Seki, Susumu Tadakuma: Rectilinear Driving Improvement of Power Assisted Wheelchair Based on Disturbance Estimation of Right and Left Wheels, Japan Industry Applications Society Conference 2004, Y-35, [16] : ( 2): D [17] :,,40,5,pp , [18] Yuichi Kurita, Mitsunori Tada, Yoshio Matsumoto, Tsukasa Ogasawara: Simultaneous Measurement of the Grip/Load Force and the Finger EMG :Effects of the Object Weight, Proceedings of IEEE International Conference on Systems, Man and Cybernetics (SMC2002), TP1B6, Tunisia, [19] Kyuwan Choi, Makoto Sato, Yasuharu Koike: A new, human-centered wheelchair system controlled by the EMG signal, WCCI2006, [20] T.Saitoh, T.C. Hwa, Y. Hori: Realtime generation of smart speed pattern for EVs taking driver s command change into account, Proc.of The IEEE International Workshop on Advanced Motion Control, 2004 [21] :,, WIT , pp.71-76,
53 [1] :, IIC-07-72, ,7, [2] :, 19, , [3] :,,Vol.59,No.6,pp.32-35,2007 [4] :, IIC-08-72, ,11, () [5]Yuusuke Oonishi, Sehoon Oh and Yoichi Hori: A New Control Method for Powerassisted Wheelchair based on the Surface Myoelectric Signal, IECON 2007, , Taipei [6]Yuusuke Oonishi, Sehoon Oh and Yoichi Hori: New Control Method for Power-assisted Wheelchair Based on Upper Extremity Movement Using Surface Myoelectric Signal, AMC 2008, , Torrent()
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