Special Issue on Rehabilitation Robotics; Guest Editors: Loredana Zollo and Jung KimNo Access

Investigation of the Effect of Weighting between sEMG and Interaction Force in Intention Extraction for the Control of an Upper-Limb Assistive Device

Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea

E-mail Address: sangjoon.j.kim@kaist.ac.kr

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Hyosang Lee

Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea

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Jung Kim

Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea

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https://doi.org/10.1142/S2424905X17400050Cited by:0 (Source: Crossref)

Abstract

We investigated the effect of the weighting between surface electromyography (sEMG) and interaction force for user intention extraction for the control of an upper-limb assistive device. A point-to-point vertical arm lifting task was performed by two age-segregated cohorts including 10 young subjects and 10 elderly subjects. The performance in terms of muscular effort and repeatability was analyzed. The elderly and young group showed age-dependent differences in terms of muscular effort with distinct sEMG weights.

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References

1. M. Ory, M. K. Hoffman, M. Hawkins, B. Sanner and R. Mockenhaupt, Challenging aging stereotypes: Strategies for creating a more active society, Am. J. Prev. Med. 25 (3) (2003) 164–171. Crossref, Google Scholar
2. G. Anderson and J. Horvath, The growing burden of chronic disease in America, Public Health Rep. 119 (3) (2004) 263–270. Crossref, Google Scholar
3. S. Landsberger et al., Mobile arm supports: History, application, and work in progress, Top. Spinal Cord Inj. Rehabil. 11 (2) (2005) 74–94. Crossref, Google Scholar
4. A. A. Blank, J. A. French, A. U. Pehlivan and M. K. O’Malley, Current trends in robot-assisted upper-limb stroke rehabilitation: Promoting patient engagement in therapy, Curr. Phys. Med. Rehabil. Rep. 2 (3) (2014) 184–195. Crossref, Google Scholar
5. Y. Tomimatsu, J. Nan, M. Takashima, S. Moromugi, T. Ishimatsu and S. Eng, Assistive device for people with upper limb disability, ICROS-SICE Int. Joint Conf. (2009), pp. 781–784. Google Scholar
6. N. Saga and K. Kirihara, Design of upper limb assistive device using a pneumatic cylinder, J. Rehabil. Robot. 1 (2013) 9–18. Google Scholar
7. K. Kiguchi and Y. Hayashi, An EMG-based control for an upper-limb power-assist exoskeleton robot, IEEE Trans. Syst. Man. Cybern. 42 (4) (2012) 1064–1071. Crossref, Google Scholar
8. G. M. Gu, H. Lee, P. Heo, S. J. Kim and J. Kim, Upper-limb assistive device for the elderly at home, The 11th Int. Conf. Ubiquitous Robots and Ambient Intelligence (URAI2014) (2014), pp. 535–539. Google Scholar
9. R. A. R. C. Gopura, K. Kiguchi and Y. Yi, SUEFUL-7: A 7DOF upper-limb exoskeleton robot with muscle-model-oriented EMG-based control, 2009 IEEE/RSJ Int. Conf. Intelligent Robots and Systems, IROS 2009, November 2009, pp. 1126–1131. Google Scholar
10. R. A. R. C. Gopura, K. Kiguchi and E. Horikawa, A study on human upper-limb muscles activities during daily upper-limb motions, Int. J. Bioelectromagn. 12 (2) (2010) 54–61. Google Scholar
11. E. Ambrosini et al., Functional and usability assessment of a robotic exoskeleton arm to support activities of daily life, Robotica 32 (2014) 1213–1224. Crossref, Google Scholar
12. M. Baklouti, J. AbouSaleh, E. Monacelli and S. Couvet, Human machine interface in assistive robotics: Application to a force controlled upper limb powered exoskeleton, Robot. 2010 Curr. Futur. Challenges (2009), pp. 211–223. Google Scholar
13. L. Dipietro, M. Ferraro, J. J. Palazzolo, H. I. Krebs, B. T. Volpe and N. Hogan, Customized interactive robotic treatment for stroke: EMG-triggered therapy, IEEE Trans. Neural Syst. Rehabil. Eng. 13 (3) (2005) 325–334. Crossref, Google Scholar
14. C. K. Battye, A. Nightingale and J. Whillis, The use of myo-electric currents in the operation of prostheses, J. Bone Joint Surg. Br. 37-B (1955) 506–510. Crossref, Google Scholar
15. T. S. Buchanan, D. G. Lloyd, K. Manal and T. F. Besier, Neuromusculoskeletal modeling: Estimation of muscle forces and joint moments and movements from measurements of neural command, J. Appl. Biomech. 20 (4) (2004) 367–395. Crossref, Google Scholar
16. R. Song, K.-Y. Tong, X. Hu and L. Li, Assistive control system using continuous myoelectric signal in robot-aided arm training for patients after stroke, IEEE Trans. Neural Syst. Rehabil. Eng. 16 (4) (2008) 371–379. Crossref, Google Scholar
17. T. Lenzi, S. M. M. De Rossi, N. Vitiello and M. C. Carrozza, Intention-based EMG control for powered exoskeletons, IEEE Trans. Biomed. Eng. 59 (8) (2012) 2180–2190. Crossref, Google Scholar
18. J. Rosen, M. Brand, M. B. Fuchs and M. Arcan, A myosignal-based powered exoskeleton system, IEEE Trans. Syst. Man, Cybern. A, Syst. Hum. 31 (3) (2001) 210–222. Crossref, Google Scholar
19. M. S. Ju, C. C. K. Lin, J. R. Chen, H. S. Cheng and C. W. Lin, Performance of elbow tracking under constant torque disturbance in normotonic stroke patients and normal subjects, Clin. Biomech. (Bristol, Avon) 17 (9–10) (2002) 640–649. Crossref, Google Scholar
20. M. Santello and M. J. McDonagh, The control of timing and amplitude of EMG activity in landing movements in humans, Exp. Physiol. 83 (6) (1998) 857–874. Crossref, Google Scholar
21. C. J. De Luca, L. Donald Gilmore, M. Kuznetsov and S. H. Roy, Filtering the surface EMG signal: Movement artifact and baseline noise contamination, J. Biomech. 43 (8) (2010) 1573–1579. Crossref, Google Scholar
22. D. M. Connelly, C. L. Rice, M. R. Roos and A. A. Vandervoort, Motor unit firing rates and contractile properties in tibialis anterior of young and old men, J. Appl. Physiol. 87 (2) (1999) 843–852. Crossref, Google Scholar
23. C. Disselhorst-Klug, T. Schmitz-Rode and G. Rau, Surface electromyography and muscle force: Limits in sEMG-force relationship and new approaches for applications, Clin. Biomech. 24 (3) (2009) 225–235. Crossref, Google Scholar
24. X. Zhang and D. B. Chaffin, The effect of speed variation on joint kinematic during multisegment reaching movements, Hum. Mov. Sci. 18 (1999) 741–757. Crossref, Google Scholar
25. M. Roos, C. Rice, D. Connelly and A. Vandervoort, Quadriceps muscle strength, contractile properties, and motor unit firing rates in young and old men, Muscle Nerve 22 (1999) 1094–1103. Crossref, Google Scholar