A multi-sensor human gait dataset captured through an optical system and inertial measurement units
dc.contributor.author | Santos, Geise | |
dc.contributor.author | Wanderley, Marcelo | |
dc.contributor.author | TIAGO FERNANDES TAVARES | |
dc.contributor.author | Rocha, Anderson | |
dc.creator | Santos, Geise | |
dc.creator | Wanderley, Marcelo | |
dc.creator | Rocha, Anderson | |
dc.date.accessioned | 2025-01-23T22:58:37Z | |
dc.date.available | 2025-01-23T22:58:37Z | |
dc.date.issued | 2022 | |
dc.description.abstract | Diferent technologies can acquire data for gait analysis, such as optical systems and inertial measurement units (IMUs). Each technology has its drawbacks and advantages, ftting best to particular applications. The presented multi-sensor human gait dataset comprises synchronized inertial and optical motion data from 25 participants free of lower-limb injuries, aged between 18 and 47 years. A smartphone and a custom micro-controlled device with an IMU were attached to one of the participant’s legs to capture accelerometer and gyroscope data, and 42 refexive markers were taped over the whole body to record three-dimensional trajectories. The trajectories and inertial measurements were simultaneously recorded and synchronized. Participants were instructed to walk on a straight-level walkway at their normal pace. Ten trials for each participant were recorded and pre processed in each of two sessions, performed on diferent days. This dataset supports the comparison of gait parameters and properties of inertial and optical capture systems, whereas allows the study of gait characteristics specifc for each system. | en |
dc.format | Digital | |
dc.format.extent | 10 p. | |
dc.identifier.doi | 10.1038/s41597-022-01638-2 | |
dc.identifier.issn | 2052-4463 | |
dc.identifier.uri | https://repositorio.insper.edu.br/handle/11224/7275 | |
dc.language.iso | Inglês | |
dc.relation.ispartof | Scientific Data | |
dc.title | A multi-sensor human gait dataset captured through an optical system and inertial measurement units | |
dc.type | journal article | |
dspace.entity.type | Publication | |
local.identifier.sourceUri | https://www.nature.com/articles/s41597-022-01638-2 | |
local.publisher.country | Não Informado | |
local.subject.cnpq | CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO | |
local.subject.cnpq | ENGENHARIAS::ENGENHARIA BIOMEDICA | |
local.subject.cnpq | CIENCIAS BIOLOGICAS::BIOLOGIA GERAL | |
local.type | Artigo Científico | |
publicationvolume.volumeNumber | 9 | |
relation.isAuthorOfPublication | b94cce1d-a49e-40dc-becd-051f9254fab8 | |
relation.isAuthorOfPublication.latestForDiscovery | b94cce1d-a49e-40dc-becd-051f9254fab8 |
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