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A novel EMG-free prosthetic interface system using intra-socket force measurement and pinch gestures

Published: 01 July 2015 Publication History

Abstract

In this paper, we present a novel system to drive a robotic prosthetic hand through the measurement of intra-socket pressure, and gesture selection from the healthy hand. A prototype HRI interface was implemented and used to compare the proposed method with standard state of practice. Grip-selection was made using finger pinch-gestures, was shown to have adequate functionality to provide a user with on-the-fly grip determination and functionality consistent with commercial systems. A moving average filter acting as a signal classifier was created to determine "open" vs "close" patterns sensed by the socket mounted piezo-resistive sensors. Sample windows were user defined as were thresholds used to determine the subject's intent. The subject was able to successfully switch between three predetermined grip configurations of a Touch Bionics i-Limb robotic hand and choose appropriate opening and closing actions.

References

[1]
Artemiadis, P. K., and Kyriakopoulos, K. J. EMG-based teleoperation of a robot arm in planar catching movements using ARMAX model and trajectory monitoring techniques. Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on (2006), 3244--3249.
[2]
Asghari Oskoei, M., and Hu, H. Myoelectric control systems - A survey. Biomedical Signal Processing and Control 2, 4 (Oct. 2007), 275--294.
[3]
Assad, C., Wolf, M., Theodoridis, T., Glette, K., and Stoica, A. BioSleeve: A Natural EMG-based Interface for HRI. In Proceedings of the 8th ACM/IEEE International Conference on Human-robot Interaction (Piscataway, NJ, USA, 2013), HRI '13, IEEE Press, pp. 69--70.
[4]
Belter, J. T., Segil, J. L., Dollar, A. M., and Weir, R. F. Mechanical design and performance specifications of anthropomorphic prosthetic hands: a review. Journal of rehabilitation research and development 50, 5 (Jan. 2013), 599--618.
[5]
Chan, F. H. Y., Yang, Y.-S., Lam, F. K., Zhang, Y.-T., and Parker, P. A. Fuzzy EMG classification for prosthesis control, 2000.
[6]
Dalley, S. A., Member, S., Bennett, D. A., and Goldfarb, M. Functional Assessment of a Multigrasp Myoelectric Prosthesis : An Amputee Case Study. 2625--2629.
[7]
Dawson, M. R., Fahimi, F., and Carey, J. P. The development of a myoelectric training tool for above-elbow amputees. The open biomedical engineering journal 6 (Jan. 2012), 5--15.
[8]
Derry, M., and Argall, B. Extending Myoelectric Prosthesis Control with Shapable Automation: A First Assessment. In Proceedings of the 2014 ACM/IEEE International Conference on Human-robot Interaction (New York, NY, USA, 2014), HRI '14, ACM, pp. 455--462.
[9]
Dipietro, L., Sabatini, A. M., and Dario, P. No Title. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on 38, 4 (2008), 461--482.
[10]
Hargrove, L., Englehart, K., and Hudgins, B. The effect of electrode displacements on pattern recognition based myoelectric control. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 1 (Jan. 2006), 2203--6.
[11]
Hargrove, L. J., Englehart, K., and Hudgins, B. A comparison of surface and intramuscular myoelectric signal classification. IEEE transactions on bio-medical engineering 54, 5 (May 2007), 847--53.
[12]
Huang, Y., Englehart, K. B., Member, S., Hudgins, B., and Chan, A. D. C. Scheme for Myoelectric Control of Powered Upper Limb Prostheses. 1801--1811.
[13]
Kim, D., Hilliges, O., Izadi, S., Butler, A. D., Chen, J., Oikonomidis, I., and Olivier, P. Digits: Freehand 3D Interactions Anywhere Using a Wrist-worn Gloveless Sensor. In Proceedings of the 25th Annual ACM Symposium on User Interface Software and Technology (New York, NY, USA, 2012), UIST '12, ACM, pp. 167--176.
[14]
LaViola, J., and Zeleznik, R. Flex and Pinch: A Case Study of Whole-Hand Input Design for Virtual Environment Interaction. International Conference on Computer Graphics and Imaging'99 (1999), 221--225.
[15]
Mobasser, F., and Hashtrudi-zaad, K. Hand Force Estimation using Electromyography Signals. Proceedings of the 2005 IEEE International Conference on Robotics and Automation, April (2005), 31--36.
[16]
Oskoei, M. A., and Hu, H. Support vector machine-based classification scheme for myoelectric control applied to upper limb. IEEE transactions on bio-medical engineering 55, 8 (Aug. 2008), 1956--65.
[17]
Phillips, S. L., and Craelius, W. Residual kinetic imaging : a versatile interface for prosthetic control. 277--282.
[18]
Pilarski, P. M., Dawson, M. R., Degris, T., Carey, J. P., and Sutton, R. S. Dynamic switching and real-time machine learning for improved human control of assistive biomedical robots. 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) (June 2012), 296--302.
[19]
Radmand, A., Erik Scheme, and Kevin Englehart. On the Suitability of Integrating Accelerometry Data with Electromyography Signals for.pdf. Journal of prosthetics and orthotics: JPO 26 (2014).
[20]
Sanford, J., Patterson, R., and Popa, D. Surface EMG and Intra-socket Force Measurement to Control a Prosthetic Device. In Sensors for Next-Generation Robotics II (2015).
[21]
Scheme, E., Fougner, a., Stavdahl, O., Chan, a. C., and Englehart, K. Examining the adverse effects of limb position on pattern recognition based myoelectric control. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 2010 (Jan. 2010), 6337--40.
[22]
Tekscan. FlexiForce Sensors: Standard FlexiForce Sensors for Force Measurement, 2015.
[23]
V, M., G, V., N, K., and K., W. Mathiowetz (01985) Adult Norms for the Box and Block Test of Manual Dexterity.pdf. american journal of occupational therapy 39, 6 (1985), 6.
[24]
Wininger, M., Kim, N.-h., and Craelius, W. Pressure signature of forearm as predictor of grip force. Journal of Rehabilitation Research & Development 45, 6 (2008).
[25]
Wolf, M. T., Assad, C., Vernacchia, M. T., Fromm, J., and Jethani, H. L. Gesture-Based Robot Control with Variable Autonomy from the JPL BioSleeve.
[26]
Yetkin, O., Sanford, J., Mirza, F., Karulkar, R., Das, S. K., and Popa, D. O. DMD2015-8773 Control of a Powered Prosthetic Hand via a Tracked Glove. Journal of Medical Devices 9, 2 (2015).
[27]
Yetkin, O., Wallace, K., Sanford, J. D., and Popa, D. O. Control of a Powered Prosthetic Device via a Pinch Gesture Interface. In SPIE Sensors for Next-Generation Robotics II (2015).

Cited By

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  • (2017)Concurrent surface electromyography and force myography classification during times of prosthetic socket shift and user fatigueJournal of Rehabilitation and Assistive Technologies Engineering10.1177/20556683177087314Online publication date: 1-Aug-2017

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cover image ACM Other conferences
PETRA '15: Proceedings of the 8th ACM International Conference on PErvasive Technologies Related to Assistive Environments
July 2015
526 pages
ISBN:9781450334525
DOI:10.1145/2769493
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

  • NSF: National Science Foundation
  • University of Texas at Austin: University of Texas at Austin
  • Univ. of Piraeus: University of Piraeus
  • NCRS: Demokritos National Center for Scientific Research
  • Ionian: Ionian University, GREECE

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 July 2015

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Author Tags

  1. human machine interface
  2. myoelectric prosthetic control
  3. physical human robot interaction

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  • Research-article

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  • National Science Foundation

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PETRA '15
Sponsor:
  • NSF
  • University of Texas at Austin
  • Univ. of Piraeus
  • NCRS
  • Ionian

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Cited By

View all
  • (2017)Concurrent surface electromyography and force myography classification during times of prosthetic socket shift and user fatigueJournal of Rehabilitation and Assistive Technologies Engineering10.1177/20556683177087314Online publication date: 1-Aug-2017

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