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Dataset results
8 results for “functional gait assessment”
GSTRIDE: A database of frailty and functional assessments with inertial gait data from elderly fallers and non-fallers populations
<p>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/m<sup>2</sup> 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.</p> <p>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.</p> <p>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.</p> <p>The current version includes a new gait analysis processing conducted following the methodology described in [1].</p> <p>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). </p> <p>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.</p> <p>[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 <em>IEEE Transactions on Instrumentation and Measurement</em>, vol. 73, pp. 1-13, 2024, Art no. 4010513, doi: 10.1109/TIM.2024.3449951.</p>
MD-Vibe Dataset: Footstep-Induced Floor Vibration Data for Functional Gait Assessment of Individuals with Muscular Dystrophy
<p>The purpose of this dataset is to evaluate the performance of floor vibration sensing in tracking the progression of muscular dystrophy through individuals’ gait patterns. We recruited human subjects (N=36) and conducted experiments at Stanford University and Nationwide Children's Hospital in Columbus, Ohio, with healthy human subjects (N=21) and children with MD (N=15).</p> <p> </p> <p>The experiments consist of two phases - Phase 1 is a pilot study to test the feasibility of floor vibration sensing in capturing gait characteristics in lab settings; Phase 2 has two hospital studies to evaluate our sensing method in real life. This dataset consists of floor vibration data (vertical velocity of floor vibration) induced by 9 healthy subjects’ footsteps from these two phases, named <strong>lab data.zip</strong>, <strong>hospital data 1.zip</strong>, and <strong>hospital data 2.zip</strong>, respectively. The complete dataset requires a data-sharing agreement with Nationwide Children's Hospital.</p> <p> </p> <p>The custom coding scripts (in MATLAB and Python) to process the data are included in the <strong>code.zip</strong> file, which includes 3 processing steps: 1) Preprocessing and Footstep Detection, 2) Feature Extraction, and 3) Model Prediction, the scripts of each step are grouped into a folder with their corresponding names. Detailed function descriptions are included in the scripts.</p> <p> </p> <p>The footstep-induced structural vibration data is stored as both raw data and as individual footsteps. The raw data files start with “raw_”, each consisting of a series of consecutive footsteps (see the sample plot). The individual footstep data files start with “detected_steps_”, each consisting of one single footstep detected from the raw data. The dataset is stored in MAT file format that can be accessed through MATLAB.</p> <p> </p> <p>The sensing unit consists of 5 components: 1) the geophone (SM-24), 2) the amplification module, 3) the processor board, 4) the data acquisition module (NI-Daq), and 5) the power cables. The sensing unit converts the structural vibration velocity into voltage records. The sampling frequency is 500 Hz for the lab study and 25600 Hz for the hospital studies.</p> <p> </p> <p>The experiment setup, sample data plot, and code usage can be found in <strong>Dataset Description.pdf</strong>. For more details about the hospital studies, please refer to the MD-Vibe paper at the following link: <a href="https://doi.org/10.1145/3410530.3414610">https://doi.org/10.1145/3410530.3414610</a></p> <p> </p> <p>Please cite this dataset as:</p> <p>Yiwen Dong, Megan Iammarino, Jingxiao Liu, Jesse Codling, Jonathon Fagert, Mostafa Mirshekari, Linda Lowes, Pei Zhang, and Hae Young Noh. 2023. The MD-Vibe Dataset: Footstep-Induced Floor Vibration Data for Functional Gait Assessment of Individuals with Muscular Dystrophy. Zenodo, DOI: <a href="https://doi.org/10.5281/zenodo.8125704">https://doi.org/10.5281/zenodo.8125744</a></p> <p> </p> <p>Yiwen Dong, Joanna Jiaqi Zou, Jingxiao Liu, Jonathon Fagert, Mostafa Mirshekari, Linda Lowes, Megan Iammarino, Pei Zhang, and Hae Young Noh. 2020. MD-Vibe: physics-informed analysis of patient-induced structural vibration data for monitoring gait health in individuals with muscular dystrophy. In Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers (UbiComp-ISWC '20). Association for Computing Machinery, New York, NY, USA, 525–531. <a href="https://doi.org/10.1145/3410530.3414610">https://doi.org/10.1145/3410530.3414610</a></p>
Tele-Assessment and Face-to-Face Evaluation of Functional Gait Assessment in Multiple Sclerosis
ClinicalTrials.gov study NCT04932616. IPD Sharing: YES. Countries: 1. Publications: 12.
Dynamic Gait Index as a Functional Gait Assessment Measure in Children With JIA
ClinicalTrials.gov study NCT06870045. IPD Sharing: UNDECIDED. Countries: 1. Publications: 14.
Wearable Technology to Assess Gait Function in SMA and DMD
ClinicalTrials.gov study NCT04193085. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Association Between Gait Assessed by Intelligent System and Cognitive Function in Silent Cerebrovascular Disease
ClinicalTrials.gov study NCT04456348. IPD Sharing: NO. Countries: 0. Publications: 20.
Urdu Version of Functional Gait Assessment Scale: Reliability and Validity Study
ClinicalTrials.gov study NCT05431842. IPD Sharing: NO. Countries: 1. Publications: 0.
Effects of Therapeutic Intervention Through Selective Functional Movement Assessment on Pain, Function, Balance and Gait in Patients With Chronic Nonspecific Neck Pain
ClinicalTrials.gov study NCT05871775. IPD Sharing: NO. Countries: 1. Publications: 0.
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