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Correlation of Spatiotemporal and EMG Measures with Lower Extremity Fugl-Meyer Assessment Score in Post-Stroke Walking

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Robot 2023: Sixth Iberian Robotics Conference (ROBOT 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 978))

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Abstract

Lower Extremity Fugl-Meyer Assessment (FMA-LE) is recommended as the primary outcome for assessing motor function in post-stroke population. However, the subjectivity, dependency on professional experience, and time-consuming visual inspection by healthcare professionals limit the use of FMA-LE in clinical practice. Contrarily to clinical scales, sensor-based assessments can automatically provide objective measurements of motor function. This work advances literature by evaluating the Spearman correlation between the FMA-LE clinical scores and both spatiotemporal and electromyographic (EMG) measures, acquired during different mobility walking tasks (self-selected speed, maximum speed, maximum cadence, maximum step length, and maximum step height). Data were extracted from ARRA dataset, including 27 post-stroke participants. The results showed that step length (0.44 ≤ r ≤ 0.60), stride time (−0.48 ≤ r ≤ −0.40), and cadence (0.40 ≤ r ≤ 0.46) spatiotemporal measures, and peak power frequency (PKF) EMG measure of gluteus medius (r = 0.42), lateral hamstring (0.40 ≤ r ≤ 0.46), and vastus medialis (0.42 ≤ r ≤ 0.45) muscles revealed significant strong correlations in multiple walking tasks. Overall, spatiotemporal measures presented higher correlations with FMA-LE than EMG measures. These findings are promising for future research to develop artificial intelligence methods to estimate the Lower FMA clinical scores for motor assessment, maximizing its use in clinical practice.

This work was funded by the Fundação para a Ciência e Tecnologia under the scholarship reference 2020.05709.BD, under the Stimulus of Scientific Employment with the grant 2020.03393. CEECIND, under the national support to R&D units grant through the reference project UIDB/04436/2020 and UIDP/04436/2020.

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Acknowledgments

The results published here are based on data obtained from Steven A. Kautz and Richard R. Neptune’s Dataset [21]: Medical University of South Carolina Stroke Data (ARRA) (ICPSR 37122).

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Authors and Affiliations

  1. Center for MicroElectroMechanical Systems (CMEMS), University of Minho, 4800-058, Guimarães, Portugal

    Cristiana Pinheiro, Luís Abreu, Joana Figueiredo & Cristina P. Santos

  2. LABBELS Associative Laboratory, University of Minho, Braga/Guimarães, Portugal

    Joana Figueiredo & Cristina P. Santos

Authors
  1. Cristiana Pinheiro
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  2. Luís Abreu
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  3. Joana Figueiredo
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  4. Cristina P. Santos
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Corresponding author

Correspondence to Joana Figueiredo .

Editor information

Editors and Affiliations

  1. Dep. de Eng. Electrotecnica e de Computadores, University of Coimbra, Coimbra, Portugal

    Lino Marques

  2. Department of Electrónica Industrial, University of Minho, Escola de Engenharia, Guimarães, Portugal

    Cristina Santos

  3. Department of Electrical Engineering, ESTIG, Polytechnic Institute of Bragança, Bragança, Portugal

    José Luís Lima

  4. Centro Universitario de la Defensa, Zaragoza, Spain

    Danilo Tardioli

  5. Centre for Automation and Robotics UPM-CSIC, Universidad Politécnica de Madrid, Madrid, Spain

    Manuel Ferre

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Pinheiro, C., Abreu, L., Figueiredo, J., Santos, C.P. (2024). Correlation of Spatiotemporal and EMG Measures with Lower Extremity Fugl-Meyer Assessment Score in Post-Stroke Walking. In: Marques, L., Santos, C., Lima, J.L., Tardioli, D., Ferre, M. (eds) Robot 2023: Sixth Iberian Robotics Conference. ROBOT 2023. Lecture Notes in Networks and Systems, vol 978. Springer, Cham. https://doi.org/10.1007/978-3-031-59167-9_35

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