Advertisement

Fast Online Decoding of Motor Tasks with Single sEMG Electrode in Lower Limb Amputees

  • Federica Barberi
  • Federica Aprigliano
  • Emanuele Gruppioni
  • Angelo Davalli
  • Rinaldo Sacchetti
  • Alberto Mazzoni
  • Silvestro Micera
Conference paper
Part of the Biosystems & Biorobotics book series (BIOSYSROB, volume 22)

Abstract

The quality of life of lower limb amputees strongly depends on the performance of their prosthesis. Active prostheses controlled by prosthesis sensors can participate to the movement and improve the walking performance of the amputees. However, a promising control mechanism involves the use of electromyography (EMG) to decode motor intentions. This approach could timely inform the prosthesis about the steps that the patient is going to perform much earlier compared to the feedback given by sensors. Here, we investigate whether an EMG-based algorithm is able to detect the motor intentions of transfemoral amputees. Subjects with a transfemoral amputation performed different motor tasks (e.g., ground level walking, climbing up/down stairs), while we recorded the EMG signals from surface electrodes placed on the subject’s stump. Our decoding algorithm achieved 100% motion intention discrimination. Such perfect decoding was achieved usually after less than 100 ms from the onset of the movement, thus ensuring that the information about the next step could be transmitted to the active prostheses with a sufficient advance to achieve its proper control. These results showed not only the feasibility of EMG-based online decoding of motor intentions, but also that perfect decoding can be achieved online with as little as one recording site, ensuring a minimum discomfort and encumbrance of the whole system.

References

  1. 1.
    Crea, S., Cipriani, C., Donati, M., Carrozza, M.C., Vitiello, N.: Providing time-discrete gait information by wearable feedback apparatus for lower-limb amputees: usability and functional validation. IEEE Trans. Neural Syst. Rehabil. Eng. 23(2), 250–257 (2015)CrossRefGoogle Scholar
  2. 2.
    Ehde, D.M., Czerniecki, J.M., Smith, D.G., Campbell, K.M., Edwards, W.T., Jensen, M.P., Robinson, L.R.: Chronic phantom sensations, phantom pain, residual limb pain, and other regional pain after lower limb amputation. Arch. Phys. Med. Rehabil. 81(8), 1039–1044 (2000)CrossRefGoogle Scholar
  3. 3.
    Martinez-Villalpando, E.C.: Design and evaluation of a biomimetic agonist-antagonist active knee prosthesis, pp. 1–102 (2012)Google Scholar
  4. 4.
    Windrich, M., Grimmer, M., Christ, O., Rinderknecht, S., Beckerle, P.: Active lower limb prosthetics: a systematic review of design issues and solutions. Biomed. Eng. Online 15(3), 5–19 (2016)Google Scholar
  5. 5.
    Micera, S., Raspopovic, S.: Control of hand prostheses using peripheral information, pp. 48–68 (2010)CrossRefGoogle Scholar
  6. 6.
    Au, S.K., Bonato, P., Herr, H.: An EMG-position controlled system for an active ankle-foot prosthesis: an initial experimental study. Sig. Process. 375–379 (2005)Google Scholar
  7. 7.
    Wu, S., Waycaster, G., Shen, X.: Electromyography-based control of active above-knee prostheses. Control Eng. Pract. 19(8), 875–882 (2011)CrossRefGoogle Scholar
  8. 8.
    Hargrove, L.J., Simon, A.M., Young, A.J., Lipschutz, R.D., Finucane, S.B., Smith, D.G., Kuiken, T.A.: Robotic leg control with EMG decoding in an amputee with nerve transfers, pp. 1237–1242 (2013)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Federica Barberi
    • 1
  • Federica Aprigliano
    • 1
  • Emanuele Gruppioni
    • 2
  • Angelo Davalli
    • 2
  • Rinaldo Sacchetti
    • 2
  • Alberto Mazzoni
    • 1
  • Silvestro Micera
    • 1
    • 3
  1. 1.The BioRobotics Institute, Scuola Superiore Sant’AnnaPisaItaly
  2. 2.INAIL Prosthesis Center Vigorso di Budrio (BO)BolognaItaly
  3. 3.Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics and Institute of Bioengineering, School of EngineeringÉcole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland

Personalised recommendations