UMATBrush Traces.

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dc.centroE.T.S.I. Telecomunicaciónes_ES
dc.contributor.authorGonzález-Cañete, Francisco Javier
dc.contributor.authorCasilari-Pérez, Eduardo
dc.date.accessioned2025-12-04T13:25:27Z
dc.date.available2025-12-04T13:25:27Z
dc.date.issued2025-05-16
dc.departamentoTecnología Electrónicaes_ES
dc.descriptionThe database (UMATBrush Dataset [15]) has a main folder and two subfolders named: Traces (with the sensed data traces measured) and Scripts. The first one contains the collected accelerometer data while the second one includes two scripts that automatically download, unzip and process the dataset. The Traces subfolder in turn consists of four subfolders, each corresponding to one of the experimental subjects. These are named with the word Subject, followed by an underscore (_) and the subject’s identifier (a number from 1 to 4). The names of the monitored data files with the acceleration measurements are presented according to the layout Subject_X_Watch_WWW_Date_YYYYMMDD_Time_HHMMSS.csv, where: • X is the subject identification number (1 to 4). • WWW is the smartwatch model name used to capture the acceleration signals. It can take one of the following values: LEO-DLXX, TicWatch-Pro or TicWatch-Pro-3-GPS, as indicated in the next section. • YYYYMMDD is the year (YYYY), month (MM) and day (DD) when the trace was collected. • HHMMSS is the hour (HH), minute (MM) and second (SS) of the instant when the gathering of the samples was initiated. Data files are plain text files in CSV (Comma Separated Values) format without headers. Every line in each data file contains a single measurement of the triaxial accelerometer of the IMU embedded in the smartwatch. The values of each line are arranged as it follows: • Timestamp, Ax, Ay, Az, Class Label where: Timestamp is the time (in μs) elapsed from the starting time of the recording to the instant in which the sample was captured. Accordingly, the first sample has a zero value and the rest of samples have a timestamp relative to this first sample. Ax, Ay, Az are the measurements of the three axes of the triaxial accelerometer (expressed in g units). Class Label is a binary value that indicates whether the sample corresponds to a toothbrush activity (1) or not (0).es_ES
dc.description.abstractThe UMATBrush dataset provides accelerometer measurements captured by three different commercial smartwatches and from four participants during the execution of toothbrushing activities and other daily life activities in real-life conditions. The dataset can be used to characterize the dynamics of the toothbrushing movements as well as a dataset to train, validate and test AI-based HAR (Human Activity Recognition) systems.es_ES
dc.description.sponsorshipSpanish Ministry of Science, Innovation, and Universitieses_ES
dc.description.sponsorshipNextGenerationEU/PRTR Fundses_ES
dc.description.sponsorshipCampus de Excelencia Internacional Andalucia Teches_ES
dc.description.sponsorshipED2021-130456B-I00es_ES
dc.description.sponsorshipB4-2023-12es_ES
dc.grupoDIANA (Diseño de Interfaces AvaNzAdos)es_ES
dc.identifier.doi10.6084/m9.figshare.28955756
dc.identifier.doi10.24310/riuma.40999
dc.identifier.urihttps://hdl.handle.net/10630/40999
dc.identifier.urlhttps://figshare.com/articles/dataset/UMATBrush_Traces/28955756es_ES
dc.language.isoenges_ES
dc.publication.year2025
dc.publisherRepositorio Figsharees_ES
dc.rightsAttribution-NonCommercial 4.0 Internacional*
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectInteracción hombre-ordenadores_ES
dc.subject.otherHuman activity recognitiones_ES
dc.subject.otherHand Gestureses_ES
dc.subject.otherSmartwatcheses_ES
dc.subject.otherWearableses_ES
dc.subject.otherInertial Sensor Monitoringes_ES
dc.subject.otherAccelerometeres_ES
dc.titleUMATBrush Traces.es_ES
dc.title.alternativeA dataset of inertial signals of toothbrushing activities.es_ES
dc.typedatasetes_ES
dc.version2es_ES
dspace.entity.typePublication
relation.isAuthorOfPublication0da4355e-2b08-4279-8857-3b9697a431e9
relation.isAuthorOfPublicationb00113ce-90f4-46b3-a2ba-507489e804c7
relation.isAuthorOfPublication.latestForDiscovery0da4355e-2b08-4279-8857-3b9697a431e9

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