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Approaches for Exploiting Neural Networks for Semi-supervised Myoelectric Control of Robot Hands

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European Robotics Forum 2024 (ERF 2024)

Part of the book series: Springer Proceedings in Advanced Robotics ((SPAR,volume 32))

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Abstract

Human-In-The-Loop (HITL) control strategies using surface electromyography (sEMG) face challenges with labeling in supervised learning. Unsupervised regression methods for sEMG signals have limitations in controlling multiple grasp motions. This paper presents two semi-supervised regression approaches using neural networks (NN) for sEMG-based robot hand control. The first approach uses soft-DTW divergence as a loss function for minimally supervised NN training. The second combines Non-Negative Matrix Factorization (NMF) with self-supervised NN regression. Offline tests show the soft-DTW NN performs similarly to a standard MSE-based NN, and the self-supervised regression outperforms traditional unsupervised methods, enabling multiple grasp actions.

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References

  1. C. Melchiorri, Robot Teleoperation. London: Springer London, 2013, pp. 1–14

    Google Scholar 

  2. Ameri, A., Kamavuako, E.N., Scheme, E.J., Englehart, K.B., Parker, P.A.: Support vector regression for improved real-time, simultaneous myoelectric control. IEEE Trans. Neural Syst. Rehabil. Eng. 22(6), 1198–1209 (2014)

    Article  Google Scholar 

  3. M. Blondel, A. Mensch, and J.-P. Vert, “Differentiable divergences between time series,” in International Conference on Artificial Intelligence and Statistics. PMLR, 2021, pp. 3853–3861

    Google Scholar 

  4. Jiang, N., Englehart, K.B., Parker, P.A.: Extracting simultaneous and proportional neural control information for multiple-dof prostheses from the surface electromyographic signal. IEEE Trans. Biomed. Eng. 56(4), 1070–1080 (2008)

    Article  MATH  Google Scholar 

  5. Meattini, R., Benatti, S., Scarcia, U., De Gregorio, D., Benini, L., Melchiorri, C.: An semg-based human-robot interface for robotic hands using machine learning and synergies. IEEE Transactions on Components, Packaging and Manufacturing Technology 8(7), 1149–1158 (2018)

    Article  Google Scholar 

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Acknowledgement

This work was partially supported by European Commission’s Horizon Europe Framework Programme with the project IntelliMan under Grant 101070136, by MUR with the project “Sustainable Mobility Center” under Grant CN00000023-CUP J33C22001120001, and by MICS (Made in Italy – Circular and Sustainable) Extended Partnership and received funding from the European Union Next-GenerationEU (PIANO NAZIONALE DI RIPRESA E RESILIENZA (PNRR) – MISSIONE 4 COMPONENTE 2, INVESTIMENTO 1.3 – D.D. 1551.11-10-2022, PE00000004).

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Correspondence to Roberto Meattini .

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Meattini, R., Bernardini, A., Caporali, A., Palli, G., Melchiorri, C. (2024). Approaches for Exploiting Neural Networks for Semi-supervised Myoelectric Control of Robot Hands. In: Secchi, C., Marconi, L. (eds) European Robotics Forum 2024. ERF 2024. Springer Proceedings in Advanced Robotics, vol 32. Springer, Cham. https://doi.org/10.1007/978-3-031-76424-0_58

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