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Published July 22, 2022 | Version v0
Dataset Open

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

  • 1. Centro de Automática y Robótica (CAR). CSIC-UPM. Ctra. Campo Real km 0.2, 28500 Arganda del Rey, Spain.
  • 2. Department of Geriatrics,Foundation for Research and Biomedical Innovation of the Infanta Sofía Hospital (HUIS), 28702 Madrid, Spain
  • 3. Physical Therapy, Occupational Therapy, Rehabilitation and Physical Medicine Department, Rey Juan Carlos University, 28922 Madrid, Spain
  • 4. School of Experimental Sciences and Technology, Rey Juan Carlos University, 28933 Madrid, Spain

Description

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.

Notes

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.

Files

GSTRIDE_database.zip

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