Versatile and non-versatile occupational back-support exoskeletons: A comparison in laboratory and field studies
Assistive strategies for occupational back-support exoskeletons have focused, mostly, on lifting tasks. However, in occupational scenarios, it is important to account not only for lifting but also for other activities. This can be done exploiting human activity recognition algorithms that can identi...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2021-01-01
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| Series: | Wearable Technologies |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S2631717621000098/type/journal_article |
| _version_ | 1797319225656737792 |
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| author | Tommaso Poliero Matteo Sposito Stefano Toxiri Christian Di Natali Matteo Iurato Vittorio Sanguineti Darwin G. Caldwell Jesús Ortiz |
| author_facet | Tommaso Poliero Matteo Sposito Stefano Toxiri Christian Di Natali Matteo Iurato Vittorio Sanguineti Darwin G. Caldwell Jesús Ortiz |
| author_sort | Tommaso Poliero |
| collection | DOAJ |
| description | Assistive strategies for occupational back-support exoskeletons have focused, mostly, on lifting tasks. However, in occupational scenarios, it is important to account not only for lifting but also for other activities. This can be done exploiting human activity recognition algorithms that can identify which task the user is performing and trigger the appropriate assistive strategy. We refer to this ability as exoskeleton versatility. To evaluate versatility, we propose to focus both on the ability of the device to reduce muscle activation (efficacy) and on its interaction with the user (dynamic fit). To this end, we performed an experimental study involving
$ 10 $
healthy subjects replicating the working activities of a manufacturing plant. To compare versatile and non-versatile exoskeletons, our device, XoTrunk, was controlled with two different strategies. Correspondingly, we collected muscle activity, kinematic variables and users’ subjective feedbacks. Also, we evaluated the task recognition performance of the device. The results show that XoTrunk is capable of reducing muscle activation by up to
$ 40\% $
in lifting and
$ 30\% $
in carrying. However, the non-versatile control strategy hindered the users’ natural gait (e.g.,
$ -24\% $
reduction of hip flexion), which could potentially lower the exoskeleton acceptance. Detecting carrying activities and adapting the control strategy, resulted in a more natural gait (e.g.,
$ +9\% $
increase of hip flexion). The classifier analyzed in this work, showed promising performance (online accuracy > 91%). Finally, we conducted 9 hours of field testing, involving four users. Initial subjective feedbacks on the exoskeleton versatility, are presented at the end of this work. |
| first_indexed | 2024-03-08T04:03:45Z |
| format | Article |
| id | doaj.art-8987658f330b4314ae0c6773c55a048e |
| institution | Directory Open Access Journal |
| issn | 2631-7176 |
| language | English |
| last_indexed | 2024-03-08T04:03:45Z |
| publishDate | 2021-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Wearable Technologies |
| spelling | doaj.art-8987658f330b4314ae0c6773c55a048e2024-02-09T08:58:17ZengCambridge University PressWearable Technologies2631-71762021-01-01210.1017/wtc.2021.9Versatile and non-versatile occupational back-support exoskeletons: A comparison in laboratory and field studiesTommaso Poliero0https://orcid.org/0000-0002-3901-8983Matteo Sposito1https://orcid.org/0000-0002-7442-1399Stefano Toxiri2Christian Di Natali3https://orcid.org/0000-0001-7399-7399Matteo Iurato4Vittorio Sanguineti5Darwin G. Caldwell6Jesús Ortiz7Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genova, ItalyDepartment of Advanced Robotics, Istituto Italiano di Tecnologia, Genova, Italy Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, Milan, ItalyDepartment of Advanced Robotics, Istituto Italiano di Tecnologia, Genova, ItalyDepartment of Advanced Robotics, Istituto Italiano di Tecnologia, Genova, ItalyDepartment of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genova, ItalyDepartment of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genova, ItalyDepartment of Advanced Robotics, Istituto Italiano di Tecnologia, Genova, ItalyDepartment of Advanced Robotics, Istituto Italiano di Tecnologia, Genova, ItalyAssistive strategies for occupational back-support exoskeletons have focused, mostly, on lifting tasks. However, in occupational scenarios, it is important to account not only for lifting but also for other activities. This can be done exploiting human activity recognition algorithms that can identify which task the user is performing and trigger the appropriate assistive strategy. We refer to this ability as exoskeleton versatility. To evaluate versatility, we propose to focus both on the ability of the device to reduce muscle activation (efficacy) and on its interaction with the user (dynamic fit). To this end, we performed an experimental study involving $ 10 $ healthy subjects replicating the working activities of a manufacturing plant. To compare versatile and non-versatile exoskeletons, our device, XoTrunk, was controlled with two different strategies. Correspondingly, we collected muscle activity, kinematic variables and users’ subjective feedbacks. Also, we evaluated the task recognition performance of the device. The results show that XoTrunk is capable of reducing muscle activation by up to $ 40\% $ in lifting and $ 30\% $ in carrying. However, the non-versatile control strategy hindered the users’ natural gait (e.g., $ -24\% $ reduction of hip flexion), which could potentially lower the exoskeleton acceptance. Detecting carrying activities and adapting the control strategy, resulted in a more natural gait (e.g., $ +9\% $ increase of hip flexion). The classifier analyzed in this work, showed promising performance (online accuracy > 91%). Finally, we conducted 9 hours of field testing, involving four users. Initial subjective feedbacks on the exoskeleton versatility, are presented at the end of this work.https://www.cambridge.org/core/product/identifier/S2631717621000098/type/journal_articlecarryinghuman activity recognitionliftingmanual material handlingoccupational exoskeletons |
| spellingShingle | Tommaso Poliero Matteo Sposito Stefano Toxiri Christian Di Natali Matteo Iurato Vittorio Sanguineti Darwin G. Caldwell Jesús Ortiz Versatile and non-versatile occupational back-support exoskeletons: A comparison in laboratory and field studies Wearable Technologies carrying human activity recognition lifting manual material handling occupational exoskeletons |
| title | Versatile and non-versatile occupational back-support exoskeletons: A comparison in laboratory and field studies |
| title_full | Versatile and non-versatile occupational back-support exoskeletons: A comparison in laboratory and field studies |
| title_fullStr | Versatile and non-versatile occupational back-support exoskeletons: A comparison in laboratory and field studies |
| title_full_unstemmed | Versatile and non-versatile occupational back-support exoskeletons: A comparison in laboratory and field studies |
| title_short | Versatile and non-versatile occupational back-support exoskeletons: A comparison in laboratory and field studies |
| title_sort | versatile and non versatile occupational back support exoskeletons a comparison in laboratory and field studies |
| topic | carrying human activity recognition lifting manual material handling occupational exoskeletons |
| url | https://www.cambridge.org/core/product/identifier/S2631717621000098/type/journal_article |
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