Embodiment for Robotic Lower-Limb Exoskeletons: A Narrative Review
Research on embodiment of objects external to the human body has revealed important information about how the human nervous system interacts with robotic lower limb exoskeletons. Typical robotic exoskeleton control approaches view the controllers as an external agent intending to move in coordinatio...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
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| Online Access: | https://ieeexplore.ieee.org/document/9987531/ |
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| author | Rachel L. Hybart Daniel P. Ferris |
| author_facet | Rachel L. Hybart Daniel P. Ferris |
| author_sort | Rachel L. Hybart |
| collection | DOAJ |
| description | Research on embodiment of objects external to the human body has revealed important information about how the human nervous system interacts with robotic lower limb exoskeletons. Typical robotic exoskeleton control approaches view the controllers as an external agent intending to move in coordination with the human. However, principles of embodiment suggest that the exoskeleton controller should ideally coordinate with the human such that the nervous system can adequately model the input-output dynamics of the exoskeleton controller. Measuring embodiment of exoskeletons should be a necessary step in the exoskeleton development and prototyping process. Researchers need to establish high fidelity quantitative measures of embodiment, rather than relying on current qualitative survey measures. Mobile brain imaging techniques, such as high-density electroencephalography, is likely to provide a deeper understanding of embodiment during human-machine interactions and advance exoskeleton research and development. In this review we show why future exoskeleton research should include quantitative measures of embodiment as a metric of success. |
| format | Article |
| id | doaj-art-90c902dc659e4a17872a1dd27a13d82a |
| institution | DOAJ |
| issn | 1534-4320 1558-0210 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| spelling | doaj-art-90c902dc659e4a17872a1dd27a13d82a2025-08-20T03:05:29ZengIEEEIEEE Transactions on Neural Systems and Rehabilitation Engineering1534-43201558-02102023-01-013165766810.1109/TNSRE.2022.32295639987531Embodiment for Robotic Lower-Limb Exoskeletons: A Narrative ReviewRachel L. Hybart0https://orcid.org/0000-0003-1403-8002Daniel P. Ferris1https://orcid.org/0000-0001-6373-6021J. Crayton Pruitt Department of Biomedical Engineering, University of Florida, Gainesville, FL, USAJ. Crayton Pruitt Department of Biomedical Engineering, University of Florida, Gainesville, FL, USAResearch on embodiment of objects external to the human body has revealed important information about how the human nervous system interacts with robotic lower limb exoskeletons. Typical robotic exoskeleton control approaches view the controllers as an external agent intending to move in coordination with the human. However, principles of embodiment suggest that the exoskeleton controller should ideally coordinate with the human such that the nervous system can adequately model the input-output dynamics of the exoskeleton controller. Measuring embodiment of exoskeletons should be a necessary step in the exoskeleton development and prototyping process. Researchers need to establish high fidelity quantitative measures of embodiment, rather than relying on current qualitative survey measures. Mobile brain imaging techniques, such as high-density electroencephalography, is likely to provide a deeper understanding of embodiment during human-machine interactions and advance exoskeleton research and development. In this review we show why future exoskeleton research should include quantitative measures of embodiment as a metric of success.https://ieeexplore.ieee.org/document/9987531/Embodimentexoskeletonlower-limb |
| spellingShingle | Rachel L. Hybart Daniel P. Ferris Embodiment for Robotic Lower-Limb Exoskeletons: A Narrative Review IEEE Transactions on Neural Systems and Rehabilitation Engineering Embodiment exoskeleton lower-limb |
| title | Embodiment for Robotic Lower-Limb Exoskeletons: A Narrative Review |
| title_full | Embodiment for Robotic Lower-Limb Exoskeletons: A Narrative Review |
| title_fullStr | Embodiment for Robotic Lower-Limb Exoskeletons: A Narrative Review |
| title_full_unstemmed | Embodiment for Robotic Lower-Limb Exoskeletons: A Narrative Review |
| title_short | Embodiment for Robotic Lower-Limb Exoskeletons: A Narrative Review |
| title_sort | embodiment for robotic lower limb exoskeletons a narrative review |
| topic | Embodiment exoskeleton lower-limb |
| url | https://ieeexplore.ieee.org/document/9987531/ |
| work_keys_str_mv | AT rachellhybart embodimentforroboticlowerlimbexoskeletonsanarrativereview AT danielpferris embodimentforroboticlowerlimbexoskeletonsanarrativereview |