DOI: 10.5281/zenodo.17052815
title: GSTRIDE: A database of frailty and functional assessments with inertial gait data from elderly fallers and non-fallers populations

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 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. Inertial data from foot-mounted IMUs (acceleration (m/s2), angular velocity (rad/s) and timestamps (s)) are included in the database in .csv files for each participant.

The current version includes a new gait analysis processing conducted following the methodology described in [1].

The complete gait analysis is included for each participant and trial in .csv files, including the gait parameters estimated for all individual steps and the gait segmentation events. The gait parameters included are: cycle duration (CD) (s), cadence (steps/min), stride length (SL) (m), path length 3D (%SL), path length 2D (%SL), stride velocity (m/s), percentage of swing (%CD), percentage of stance (%CD), percentage of stance subphases (loading, foot-flat, and pushing) (%stance), heel strike pitch (degrees), toe-off pitch (degrees), peak angle velocity (degrees/s), turning angle (degrees), and heel range of motion (ROM) (degrees). 

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.

[1] L. Ruiz-Ruiz, J. J. García-Domínguez and A. R. Jiménez, "A Novel Foot-Forward Segmentation Algorithm for Improving IMU-Based Gait Analysis," in IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-13, 2024, Art no. 4010513, doi: 10.1109/TIM.2024.3449951.
description: The current version (V3) includes a new gait analysis processing conducted following the methodology described in [1]. We strongly recommend using this version.

[1] L. Ruiz-Ruiz, J. J. García-Domínguez and A. R. Jiménez, "A Novel Foot-Forward Segmentation Algorithm for Improving IMU-Based Gait Analysis," in IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-13, 2024, Art no. 4010513, doi: 10.1109/TIM.2024.3449951.