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Dataset . 2022
License: CC BY
Data sources: Datacite
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Dataset . 2022
License: CC BY
Data sources: Datacite
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DIGITAL.CSIC
Dataset . 2024 . Peer-reviewed
Data sources: DIGITAL.CSIC
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https://doi.org/10.5281/zenodo...
Dataset . 2022
License: CC BY
Data sources: Sygma
DIGITAL.CSIC
Dataset . 2022
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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GSTRIDE: A database of frailty and functional assessments with inertial gait data from elderly fallers and non-fallers populations

Authors: García-Villamil Neira, Guillermo; Neira Álvarez, Marta; Huertas Hoyas, Elisabet; Ruiz Ruiz, Luisa; García-de-Villa, Sara; del-Ama, Antonio J.; Rodríguez Sánchez, María Cristina; +1 Authors

GSTRIDE: A database of frailty and functional assessments with inertial gait data from elderly fallers and non-fallers populations

Abstract

The GSTRIDE database contains relevant metrics and motion data of elder people for the assessment of their health status. The data correspond to 163 patients, 45 men and 118 women, between 70 and 98 years old with an average Body Mass Index (BMI) of 26.1±5.0 kg/m2 and a cognitive deterioration status index between 1 and 7, according to the Global Deterioration Scale (GDS) scale. In this way, we ensure variability among the volunteers in terms of socio-demographic and anatomic parameters and their functional and cognitive capacities. The database files are stored in TXT and CSV format to ease their usability with common data processing software. We provide socio-demographic data, anatomical, functional and cognitive variables, and the outcome measurements from test commonly performed for the evaluation of elder people. The evaluation tests carried out to obtain these data are the Gait Speed Test (4-metre), the Hand Grip Strength, the Short Physical Performance Battery (SPPB), the Timed up and go (TUG) and the Short Falls Efficacy Scale International (FES-I). We also include the outcomes of the GDS questionnaire, the Frailty assessment and the information about falls during the last year prior to the tests. These data are complemented with the gait parameters of a walking test recorded by an Inertial Measurement Unit (IMU) placed on the foot. The walking tests have an average duration of 21.4±7.1 minutes, which are analyzed in order to estimate the total walking distance, the number of strides and the gait spatio-temporal parameters. The results of this analysis include the following metrics: stride time duration, stride length, step speed, percentage of the gait phases (toe off, swing, heel strike, foot flat) over the strides, foot angle during the toe off and heel strike phases, cadence, step speed, 3D and 2D paths and clearance. We provide these metrics for the steps detected, as well as their average and variance values in the database record. The raw and calibrated signals from the IMUs using the calibration parameters (bias vector, misalignment and scaling matrix and the sampling rate correction factor) are included in the database in order to allow the researchers to perform other approaches for the gait analysis. These signals consist in the linear acceleration and the turn rate. The files also contain the calibration parameters and the specifications of the inertial sensors used in this work. Furthermore, these data are accompanied with the gait analysis code, which is used to obtain the metrics given in the database, that provides also visualization tools to study the distribution of these metrics. GSTRIDE is specially focused on, but not limited to, the study of faller and non-faller elder people. The main aim of this dataset is the availability of study these different populations. By including the results of the health evaluation tests and questionnaires and the inertial and spatio-temporal data, researchers can analyze different techniques for the identification of fallers. Moreover, this database allows the analysis of cognitive deterioration and frailty parameters of patients by the research community.

This dataset creation was supported by a grant from the FUNDACION MAPFRE "Ayudas a la investigación de Ignacio H. de Larramendi, 2020" and the contributions from other complementary resources: Spanish Ministry of Science, Grant No. MICROCEBUS RTI2018-095168-B-C55 (MCIU/AEI/FEDER, UE) and European Union, NEXTPERCEPTION project, Grant No. ECSEL-2019-2-RIA, Ref. 876487.

Country
Spain
Keywords

elderly people, inertial measurement unit, falls, frailty, functional assessment, IMU, gait

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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4
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