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Cited by 438Muscle activation and electromyography studiesProsthetics and Rehabilitation RoboticsEEG and Brain-Computer Interfaces

The optimal controller delay for myoelectric prostheses

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Farrell, Todd R., Weir, Richard F.·2007·IEEE Transactions on Neural Systems and Rehabilitation Engineering
DOI 10.1109/tnsre.2007.891391PMC PMC8173529
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Abstract

A tradeoff exists when considering the delay created by multifunctional prosthesis controllers. Large controller delays maximize the amount of time available for EMG signal collection and analysis (and thus maximize classification accuracy); however, large delays also degrade prosthesis performance by decreasing the responsiveness of the prosthesis. To elucidate an "optimal controller delay" twenty able-bodied subjects performed the Box and Block Test using a device called PHABS (prosthetic hand for able bodied subjects). Tests were conducted with seven different levels of controller delay ranging from nearly 0-300 ms and with two different artificial hand speeds. Based on repeted measures ANOVA analysis and a linear mixed effects model, the optimal controller delay was found to range between approximately 100 ms for fast prehensors and 125 ms for slower prehensors. Furthermore, the linear mixed effects model shows that there is a linear degradation in performance with increasing delay.

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  1. [1][1].Englehart K, Hudgins B, and Parker PA, “A wavelet-based continuous classification scheme for multifunction myoelectric control,” IEEE Trans. Biomed. Eng, vol. 48, no. 3, pp. 302–311, March. 2001. [DOI] [PubMed] [Google Scholar]
  2. [2][2].Du S and Vuskovic MI, “Temporal vs. spectral approach to feature extraction from prehensile EMG signals,” in Proc. IEEE Int. Conf. Inf. Reuse Integration, November. 8-10, 2004, pp. 344–350. [Google Scholar]
  3. [3][3].Yamada M, Niwa N, and Uchiyama A, “Evaluation of a multifunctional hand prosthesis system using EMG controlled animation,” IEEE Trans. Biomed. Eng, vol. 30, pp. 759–763, 1983. [DOI] [PubMed] [Google Scholar]
  4. [4][4].Hogan N, “A review of the methods of processing EMG for use as a proportional control signal,” Biomed. Eng, vol. 11, pp. 81–86, 1976. [PubMed] [Google Scholar]
  5. [5][5].Kyberd PJ, Holland OE, Chappell PH, Smith S, Tregidgo R, Bagwell PJ, and Snaith M, “MARCUS: A two degree of freedom hand prosthesis with hierarchical grip control,” IEEE Trans. Rehabil. Eng, vol. 3, no. 1, pp. 70–76, March. 1995. [Google Scholar]
  6. [6][6].Conklin JE, “Linearity of the tracking performance function,” Perceptual Motor Skills, vol. 9, pp. 387–391, 1959. [Google Scholar]
  7. [7][7].Ferrell WR, “Remote manipulation with transmission delay,” IEEE Trans. Human Factors Electronics, vol. HFE6, pp. 24–32, 1965. [Google Scholar]
  8. [8][8].Ferrell WR and Sheridan TB, “Supervisory Control of Remote Manipulation,” IEEE Spectrum, vol. 4, pp. 81–88, 1967. [Google Scholar]
  9. [9][9].MacKenzie I and Ware C, “Lag as a determinant of human performance in interactive systems,” in Proc. ACM Conf. Human Factors Comput. Syst.—INTERCHI ’ 93, 1993, pp. 488–493. [Google Scholar]
  10. [10][10].Sheridan TB and Ferrell WR, “Remote manipulative control with transmission delay,” IEEE Trans. Human Factors Eng, vol. HFE4, pp. 25–29, September. 1963. [Google Scholar]
  11. [11][11].Smith KU, Smith WM, and Smith MF, Delayed Sensory Feedback and Behavior. Philadelphia, PA: W.B. Saunders and Company, 1962. [Google Scholar]
  12. [12][12].Smith WM, “Feedback: Real-time delayed vision of one’s own tracking behavior,” Science, vol. 176, pp. 939–940, 1972. [DOI] [PubMed] [Google Scholar]
  13. [13][13].Smith WM and Bowen KF, “The effects of delayed and displaced visual feedback on motor control,” J. Mot. Behav, vol. 12, pp. 91–101, 1980. [DOI] [PubMed] [Google Scholar]
  14. [14][14].Held R, Efstathiou A, and Greene M, “Adaptation to displaced and delayed visual feedback from the hand,” J. Exp. Psychol, vol. 72, pp. 887–891, 1966. [Google Scholar]
  15. [15][15].Paciga JE, Richard PD, and Scott RN, “Error rate in five-state myoelectric control systems,” Med. Biol. Eng. Comput, vol. 18, pp. 287–290, 1980. [DOI] [PubMed] [Google Scholar]
  16. [16][16].Childress DS and Weir RF, “Control of limb prostheses,” in Atlas of Amputations and Limb Deficiencies: Surgical, Prosthetic, and Rehabilitation Principles, Smith DG, Michael JW, and B. J. H., Eds., 3rd ed. Rosemont, IL: J. H. Bowker, 2004, pp. 173–195. [Google Scholar]
  17. [18][18].Englehart K, Hudgins B, and Chan A, “Continuous multifunction myoelectric control using pattern recognition,” Technol. Disability, vol. 15, pp. 95–103, 2003. [Google Scholar]
  18. [20][20].Graupe D, Salahi J, and Zhang DS, “Stochastic analysis of myoelectric temporal signatures for multifunctional single-site activation of prostheses and orthoses,” J. Biomed. Eng, vol. 7, pp. 18–29, 1985. [DOI] [PubMed] [Google Scholar]
  19. [21][21].Hefftner G, Zucchini W, and Jaros GG, “The electromyogram (EMG) as a control signal for functional neuromuscular stimulation—Part I: Autoregressive modeling as a means of EMG signature discrimination,” IEEE Trans. Biomed. Eng, vol. 35, no. 4, pp. 230–237, April. 1988. [DOI] [PubMed] [Google Scholar]
  20. [22][22].Chu JK, Moon I, and Mun M, “A real-time EMG pattern recognition based on linear-nonlinear feature projection for multifunction myoelectric hand,” presented at the IEEE 9th Int. Conf. Rehabilitation Robotics (ICORR), Chicago, IL, 2005. [Google Scholar]
  21. [23][23].Myobock Arm Components Catalog. Duderstadt, Germany: Otto Bock Healthcare, 2004/2005. [Google Scholar]
  22. [24][24].Heckathorne CW, “Components for electric-powered systems,” in Atlas of Amputations and Limb Deficiencies, Smith DG, Michael JW, and Bowker JH, Eds., 3rd ed. Rosemont, IL: American Academy of Orthopaedic Surgeons, 2004, pp. 145–171. [Google Scholar]
  23. [25][25].Childress DS, “An approach to powered grasp,” in Advances in External Control of Human ExtremitiesFourth International Symposium on External Control of Human Extremities, Gavrilovic MM and Wilson AB Jr., Eds., Belgrade, Yugoslavia, 1973, pp. 159–167. [Google Scholar]
  24. [26][26].Weir RF, “Design of artificial arms and hands for prosthetic applications,” in Standard Handbook of Biomedical Engineering and Design, Kutz M, Ed. New York: McGraw–Hill, 2003, ch. 32, pp. 32.1–32.61. [Google Scholar]
  25. [28][28].Goodkin DE, Hertsgaard D, and Seminary J, “Upper extremity function in multiple sclerosis: Improving assessment sensitivity with box- and-block and nine-hole peg tests,” Arch. Phys. Med. Rehabil, vol. 69, pp. 850–854, 1988. [PubMed] [Google Scholar]
  26. [29][29].Desrosiers J, Bravo G, Hebert R, Dutil E, and Mercier L, “Validation of the Box and Block Test as a measure of dexterity of elderly people: Reliability, validity, and norms studies,” Arch. Phys. Med. Rehabil, vol. 75, pp. 751–755, 1994. [PubMed] [Google Scholar]
  27. [30][30].Mathiowetz V, Volland G, Kashman N, and Weber K, “Adult norms for the Box and Block Test of manual dexterity,” Am. J. Occup. Ther, vol. 39, pp. 386–391, 1985. [DOI] [PubMed] [Google Scholar]
  28. [31][31].Goodman G and Bazyk S, “The effects of a short thumb opponens splint on hand function in cerebral palsy: A single-subject study,” Am. J. Occup. Ther, vol. 45, pp. 726–731, 1991. [DOI] [PubMed] [Google Scholar]
  29. [32][32].Goodkin DE, Rudick RA, VanderBrug Medendorp S, Daughtry MM, Schwetz KM, Fischer J, and Van Dyke C, “Low-dose (7.5 mg) oral methotrexate reduces the rate of progression in chronic progressive multiple sclerosis,” Ann. Neurol, vol. 37, pp. 30–40, 1995. [DOI] [PubMed] [Google Scholar]
  30. [33][33].Cauraugh JH and Kim SB, “Chronic stroke motor recovery: Duration of active neuromuscular stimulation,” J. Neurol. Sci, vol. 215, pp. 13–19, 2003. [DOI] [PubMed] [Google Scholar]
  31. [34][34].Carey JR, Kimberley TJ, Lewis SM, Auerbach EJ, Dorsey L, Rundquist P, and Ugurbil K, “Analysis of fMRI and finger tracking training in subjects with chronic stroke,” Brain, vol. 125, pp. 773–788, 2002. [DOI] [PubMed] [Google Scholar]
  32. [35][35].Cauraugh J, Light K, Kim S, Thigpen M, and Behrman A, “Chronic motor dysfunction after stroke: Recovering wrist and finger extension by electromyography-triggered neuromuscular stimulation,” Stroke, vol. 31, pp. 1360–1364, 2000. [DOI] [PubMed] [Google Scholar]
  33. [36][36].Park E and Meek SG, “Adaptive filtering of the electromyographic signal for prosthetic control and force estimation,” IEEE Trans. Biomed. Eng, vol. 42, no. 10, pp. 1048–1052, October. 1995. [DOI] [PubMed] [Google Scholar]

Cited by

Sorted by citations

Authors
Farrell, T. R., & Weir, R. F.
Affiliations
Northwestern University (US)
ORCID
Venue
IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2007-03
Volume
15
Issue
1
Pages
111-118
ISSN
  • 1534-4320 (ISSN-L)
  • 1558-0210
DOI
10.1109/tnsre.2007.891391
PMC
PMC8173529
OpenAlex
W2125585124
Cited by
438
References
4
Citations by year
2026: 27 · 2025: 26 · 2024: 30 · 2023: 33 · 2022: 30 · 2021: 40 · 2020: 32 · 2019: 35 · 2018: 32 · 2017: 31 · 2016: 14 · 2015: 19 · 2014: 29 · 2013: 10 · 2012: 11
FWCI
5.74
Type
journal article
Language
en
Open access
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
Locations
  • IEEE Transactions on Neural Systems and Rehabilitation Engineering (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
National Institute of Biomedical Imaging and Bioengineering (R01EB001672, 1 R01EB01672-01)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Muscle activation and electromyography studies
  • Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
Keywords
myoelectric prosthesis, EMG signal processing, Box and Block Test, phaB, EMG signal classification
MeSH terms
Artificial Limbs, Electric Stimulation Therapy, Feedback, Hand, Humans, Prosthesis Design, Therapy, Computer-Assisted, Muscle, Skeletal, Hand Strength, Equipment Failure Analysis

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