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Towards a Gait Planning Training Strategy Using Lokomat

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Synergetic Cooperation between Robots and Humans (CLAWAR 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 811))

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Abstract

The main goal in this study was to investigate how strategies used to perform motor gait planning in an uncontrolled environment affects patterns of neural activity in healthy volunteers during task performance. Materials and Methods A 16-channel EEG system with electrodes and 2 channels of sEMG were used to acquire data from 10 healthy subjects. The data was processed to obtain for each foot the ERD for \(\mu \) and \(\beta \) rhythms; the spectrogram and continuous wavelet transform of the average 5 s segments and the STFT of the motor planning period. Results The results show significant differences in the ERD and FFT between feets that will be used in future works to develop an intervention using Lokomat to aid SCI individuals that cannot voluntarily initiate the gait. Conclusion This study is a preliminary study, it is still possible to draw some initial conclusions about the feasibility of using EEG signals to analyze gait motor planning.

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Acknowledgments

Authors would like to thank the CNPq scholarships from Brazil.

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Authors and Affiliations

  1. Postgraduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neurosciences, Santos Dumont Institute, Macaiba, Brazil

    Thayse Saraiva de Albuquerque, Lucas José da Costa, Ericka Raiane da Silva, Geovana Kelly Lima Rocha, André Felipe Oliveira de Azevedo Dantas, Caroline do Espírito Santo & Denis Delisle-Rodriguez

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  1. Thayse Saraiva de Albuquerque
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  2. Lucas José da Costa
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  3. Ericka Raiane da Silva
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  4. Geovana Kelly Lima Rocha
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  6. Caroline do Espírito Santo
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  7. Denis Delisle-Rodriguez
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Corresponding author

Correspondence to Thayse Saraiva de Albuquerque .

Editor information

Editors and Affiliations

  1. Universidade Federal de Santa Catarina, Blumenau, Santa Catarina, Brazil

    Ebrahim Samer El Youssef

  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. Universidade Federal de Santa Catarina, Blumenau, Santa Catarina, Brazil

    Leonardo Mejia Rincon

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© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

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de Albuquerque, T.S. et al. (2024). Towards a Gait Planning Training Strategy Using Lokomat. In: Youssef, E.S.E., Tokhi, M.O., Silva, M.F., Rincon, L.M. (eds) Synergetic Cooperation between Robots and Humans. CLAWAR 2023. Lecture Notes in Networks and Systems, vol 811. Springer, Cham. https://doi.org/10.1007/978-3-031-47272-5_30

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