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Wearable Lower Limb Neuroprosthesis: System Architecture and Control Tuning

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Robotics in Natural Settings (CLAWAR 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 530))

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Abstract

The use of functional electrical stimulation (FES) through neuroprosthesis is becoming a promising solution in lower limb neurorehabilitation. However, the wearability constraints and time-consuming tuning of stimulation parameters still limit the daily use of neuroprostheses. This work proposes two major contributions, namely: (i) a conceptual design and technical architecture of a fully wearable lower limb neuroprosthesis; and (ii) a Matlab-OpenSim framework that enables fast subject-and muscle-specific tuning of FES controllers based on OpenSim musculoskeletal models. The validation procedures for this study were divided into three phases: (i) Verification of the system architecture real-time requirements; (ii) evaluation of the reliability of the MATLAB-OpenSim framework for tuning PID controller; and (iii) its subsequent use in the neuroprosthesis control with a healthy subject. The obtained results demonstrated that the neuroprosthesis system was able to meet the real-time requirements, with control and data acquisition call periods below 10 ms. Further findings indicated reliable and stable behavior of the simulation-tuned PID controller with an overshoot of 9.82% and a rise time of 0.063 s. The trajectory tracking control results with the neuroprosthesis corroborated the robustness of the tuned PID controller in tracking the desired ankle trajectory (RMSE = 17.23 ± 2.97º and time delay = 0.21 ± 0.070 s).

This work has been supported by the Fundação para a Ciência e Tecnologia (FCT) through the Reference Scholarship under Grant SFRH/BD/147878/2019, the Stimulus of Scientific Employment under Grant 2020.03393.CEECIND, and in part by the FEDER Funds through the Programa Operacional Regional do Norte and national funds from FCT with the SmartOs project under Grant NORTE-01-0145-FEDER-030386. It is also supported under the national support to R & D units grant, through the reference project UIDB/04436/2020 and UIDP/04436/2020.

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Authors and Affiliations

  1. Center for MicroElectroMechanical Systems (CMEMS), University of Minho, Braga, Portugal

    Simão P. Carvalho, Joana Figueiredo & Cristina P. Santos

  2. LABBELS – Associate Laboratory, Braga/Guimarães, Portugal

    Simão P. Carvalho, Joana Figueiredo & Cristina P. Santos

Authors
  1. Simão P. Carvalho
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  2. Joana Figueiredo
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  3. Cristina P. Santos
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Corresponding author

Correspondence to Joana Figueiredo .

Editor information

Editors and Affiliations

  1. Faculty of Sciences and Technology, University of the Azores, Ponta Delgada, Portugal

    José M. Cascalho

  2. School of Engineering, London South Bank University, London, UK

    Mohammad Osman Tokhi

  3. School of Engineering, Polytechnic Institute of Porto, Porto, Portugal

    Manuel F. Silva

  4. Faculty of Sciences and Technology, University of the Azores, Ponta Delgada, Portugal

    Armando Mendes

  5. Mechanical, Materials and Manufacturing Engineering (M3), Faculty of Engineering, University of Nottingham, Nottingham, UK

    Khaled Goher

  6. Faculty of Sciences and Technology, University of the Azores, Ponta Delgada, Portugal

    Matthias Funk

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Carvalho, S.P., Figueiredo, J., Santos, C.P. (2023). Wearable Lower Limb Neuroprosthesis: System Architecture and Control Tuning. In: Cascalho, J.M., Tokhi, M.O., Silva, M.F., Mendes, A., Goher, K., Funk, M. (eds) Robotics in Natural Settings. CLAWAR 2022. Lecture Notes in Networks and Systems, vol 530. Springer, Cham. https://doi.org/10.1007/978-3-031-15226-9_52

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