Human-in-the-Loop Assessment of an Ultralight, Low-Cost Body Posture Tracking Device.

assistive robotics inertial measurement units low-cost sensors rehabilitation robotics space robotics teleoperation wearable sensors

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
07 Feb 2020
Historique:
received: 17 12 2019
revised: 29 01 2020
accepted: 04 02 2020
entrez: 13 2 2020
pubmed: 13 2 2020
medline: 11 11 2020
Statut: epublish

Résumé

In rehabilitation, assistive and space robotics, the capability to track the body posture of a user in real time is highly desirable. In more specific cases, such as teleoperated extra-vehicular activity, prosthetics and home service robotics, the ideal posture-tracking device must also be wearable, light and low-power, while still enforcing the best possible accuracy. Additionally, the device must be targeted at effective human-machine interaction. In this paper, we present and test such a device based upon commercial inertial measurement units: it weighs 575 grams in total, lasts up to 10.5 hours of continual operation, can be donned and doffed in under a minute and costs less than 290 EUR. We assess the attainable performance in terms of error in an online trajectory-tracking task in Virtual Reality using the device through an experiment involving 10 subjects, showing that an average user can attain a precision of 0.66 cm during a static precision task and 6.33 cm while tracking a moving trajectory, when tested in the full peri-personal space of a user.

Identifiants

pubmed: 32046129
pii: s20030890
doi: 10.3390/s20030890
pmc: PMC7039287
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Deutsche Forschungsgemeinschaft
ID : CA1389/1-1

Déclaration de conflit d'intérêts

Figure A2. Trajectory with error ellipsoids. The color shifts from red to green over time during target’s movement.

Références

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pubmed: 21846608
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pubmed: 28567271
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pubmed: 31304340
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pubmed: 11728329
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pubmed: 27014682
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pubmed: 22665514
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pubmed: 24235278
J Neural Eng. 2014 Oct;11(5):051001
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Sensors (Basel). 2019 Mar 12;19(5):
pubmed: 30870999

Auteurs

Marek Sierotowicz (M)

Institute of Robotics and Mechatronics, German Aerospace Center (DLR), 82234 Weßling, Germany.

Mathilde Connan (M)

Institute of Robotics and Mechatronics, German Aerospace Center (DLR), 82234 Weßling, Germany.

Claudio Castellini (C)

Institute of Robotics and Mechatronics, German Aerospace Center (DLR), 82234 Weßling, Germany.

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Classifications MeSH