Abstract
Stroke has been considered the main cause of neuromuscular damages worldwide and one of the most common causes of walking disabilities, with approximately 60% of the individuals suffering from persistent problems in walking. These patients generally use technical aids for walking to achieve independent gait, however, when cognitive impairments are also present, conventional assistive devices such as walkers could be difficult to handle. By leveraging multimodal interfaces, smart walkers can offer natural and intuitive human-robot interaction. In this work, we present two multimodal interaction strategies for smart walkers focusing on guiding post-stroke patients through their environment. These strategies leverage different communication channels and provide distinct levels of guidance: one strategy uses haptic feedback and a visual interface to indicate the desired path to the user, while the other strategy uses haptic feedback and a virtual torque to maintain the user on path. We also present two case studies with post-stroke patients to preliminarily validate these interaction strategies with their target population and to collect valuable insight as to how multimodal strategies for smart walkers can be enhanced to deal with the characteristic asymmetries of post-stroke patients. Our results show that both strategies can guide the volunteers, however, the first one demands more effort from the volunteer and is more suited for patients with increased levels of independence. The second interaction strategy allows for higher linear velocity (Volunteer 1, \(\varvec{0.18}\) \(\varvec{\pm 0.026}\) \(\varvec{m/s}\); Volunteer 2, \(\varvec{0.22}\) \(\varvec{\pm 0.0283}\) \(\varvec{m/s}\)) than the first one (Volunteer 1, \(\varvec{0.10}\) \(\varvec{\pm 0.031}\) \(\varvec{m/s}\); Volunteer 2, \(\varvec{0.20}\) \(\varvec{\pm 0.012}\) \(\varvec{m/s}\)), suggesting improved guidance.
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Acknowledgements
The authors would like to acknowledge the valuable participation of the volunteers that took part in this study. It is also acknowledged the support given by the School of Engineering, Science and Technology at Universidad del Rosario, Colombia.
Funding
Open Access funding provided by Colombia Consortium. This research is supported by FAPES [grant number 2021-V4J3L, 2022-D48XB and 2022-C5K3H], CNPq [grant number 304049/2019-0, 403753/2021-0], H2020 European Research Council [grant number 688941] and Universidad del Rosario - Vice Provost of Research and Innovation - Competitive Funds - Medium Grants [grant number IV-FMI001].
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All authors (M.F.J., R.C.M., F.L., and A.F.) contributed to the study conception and design. M.F.J. and A.F. conceptualized the study. M.F.J. and R.C.M. designed the methodology. M.F.J. developed the feedback strategies. M.F.J. and R.C.M. conducted the experimental trials and performed data curation and processing. M.F.J. and R.C.M. wrote the original manuscript. M.F.J., R.C.M., and A.F. reviewed and edited the manuscript. A.F. supervised the study. A.F. managed the funding resources. All authors have read and agreed to the published version of the manuscript.
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The ethics committee of the Federal University of Epirito Santo approved the project with the number 2.264.127 to do tests with humans.
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Jimenez, M.F., Mello, R.C., Loterio, F. et al. Multimodal Interaction Strategies for Walker-Assisted Gait: A Case Study for Rehabilitation in Post-Stroke Patients. J Intell Robot Syst 110, 13 (2024). https://doi.org/10.1007/s10846-023-02031-w
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DOI: https://doi.org/10.1007/s10846-023-02031-w