scholarly journals Gutenberg Gait Database, a ground reaction force database of level overground walking in healthy individuals

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Fabian Horst ◽  
Djordje Slijepcevic ◽  
Marvin Simak ◽  
Wolfgang I. Schöllhorn
Keyword(s):  
Ground Reaction Force ◽  
Center Of Pressure ◽  
Reaction Force ◽  
Three Dimensional ◽  
Human Gait ◽  
Healthy Individuals ◽  
Overground Walking ◽  
Gait Patterns ◽  
Specific Factors ◽  
Gait Database

AbstractThe Gutenberg Gait Database comprises data of 350 healthy individuals recorded in our laboratory over the past seven years. The database contains ground reaction force (GRF) and center of pressure (COP) data of two consecutive steps measured - by two force plates embedded in the ground - during level overground walking at self-selected walking speed. The database includes participants of varying ages, from 11 to 64 years. For each participant, up to eight gait analysis sessions were recorded, with each session comprising at least eight gait trials. The database provides unprocessed (raw) and processed (ready-to-use) data, including three-dimensional GRF and two-dimensional COP signals during the stance phase. These data records offer new possibilities for future studies on human gait, e.g., the application as a reference set for the analysis of pathological gait patterns, or for automatic classification using machine learning. In the future, the database will be expanded continuously to obtain an even larger and well-balanced database with respect to age, sex, and other gait-specific factors.

scholarly journals Gait Disorders In Patients After Polytrauma

2015 ◽  
Vol 69 (1-2) ◽  
pp. 27-32
Author(s):  
Ruta Jakušonoka ◽  
Zane Pavāre ◽  
Andris Jumtiņš ◽  
Aleksejs Smolovs ◽  
Tatjana Anaņjeva
Keyword(s):  
Ground Reaction Force ◽  
Knee Flexion ◽  
Reaction Force ◽  
Three Dimensional ◽  
Step Length ◽  
Vertical Load ◽  
Lower Limb Injuries ◽  
Limb Injuries ◽  
Stance Time ◽  
Polytrauma Patients

Abstract Evaluation of the gait of patients after polytrauma is important, as it indicates the ability of patients to the previous activities and work. The aim of our study was to evaluate the gait of patients with lower limb injuries in the medium-term after polytrauma. Three-dimensional instrumental gait analysis was performed in 26 polytrauma patients (16 women and 10 men; mean age 38.6 years), 14 to 41 months after the trauma. Spatio-temporal parameters, motions in pelvis and lower extremities joints in sagittal plane and vertical load ground reaction force were analysed. Gait parameters in polytrauma patients were compared with a healthy control group. Polytrauma patients in the injured side had decreased step length, cadence, hip extension, maximum knee flexion, vertical load ground reaction force, and increased stance time and pelvic anterior tilt; in the uninjured side they had decreased step length, cadence, maximum knee flexion, vertical load ground reaction force and increased stance time (p < 0.05). The use of the three-dimensional instrumental gait analysis in the evaluation of polytrauma patients with lower limb injuries consequences makes it possible to identify the gait disorders not only in the injured, but also in the uninjured side.

Improvement of a Forward Dynamic MPC Based Human Gait Model

2016 ◽  
Author(s):  
Shaoli Wu ◽  
Philip A. Voglewede
Keyword(s):  
Predictive Control ◽  
Ground Reaction Force ◽  
Reaction Force ◽  
Human Gait ◽  
Mechanical Parameters ◽  
Anthropometric Parameters ◽  
Robust Controller ◽  
Central Tenet ◽  
Human Joints ◽  
Improved Model

This paper develops an improvement to an existing forward dynamic human gait model. A human gait model was developed previously to assist virtual testing prostheses and orthoses. The model consists of a plant model and a controller model. The central tenet to the model is the model predictive control (MPC) algorithm, which is a highly robust controller. In the previous model, however, there are several drawbacks. First, the anthropometric and mechanical parameters in the parts of the model are specific to one person. Second, the simulation result of ground reaction force (GRF) is not realistic. In this paper, the anthropometric parameters are calculated based on commonly used models that approximate an average person’s size. As for the mechanical parameters, the spring and damper coefficients in the human joints and ground reaction force (GRF) system are estimated by using the parameter estimation module in MATLAB based on the experimental subject data. The paper concludes with a simulation results between the new improved model and the previous developed model.

scholarly journals A data set with kinematic and ground reaction forces of human balance

2017 ◽  
Author(s):  
Damiana A dos Santos ◽  
Claudiane A Fukuchi ◽  
Reginaldo K Fukuchi ◽  
Marcos Duarte
Keyword(s):  
Center Of Pressure ◽  
Reaction Force ◽  
Kinematic Model ◽  
Three Dimensional ◽  
Force Platform ◽  
Whole Body ◽  
Ground Reaction Forces ◽  
Data Set ◽  
Public Data ◽  
Reaction Forces

This article describes a public data set with the three-dimensional kinematics of the whole body and the ground reaction forces (with a dual force platform setup) of subjects standing still for 60 s in different conditions, in which the vision and the standing surface were manipulated. Twenty-seven young subjects and 22 old subjects were evaluated. The data set comprises a file with metadata plus 1,813 files with the ground reaction force (GRF) and kinematics data for the 49 subjects (three files for each of the 12 trials plus one file for each subject). The file with metadata has information about each subject’s sociocultural, demographic, and health characteristics. The files with the GRF have the data from each force platform and from the resultant GRF (including the center of pressure data). The files with the kinematics have the three-dimensional position of the 42 markers used for the kinematic model of the whole body and the 73 calculated angles. In this text, we illustrate how to access, analyze, and visualize the data set. All the data is available at Figshare (DOI: 10.6084/m9.figshare.4525082 ), and a companion Jupyter Notebook (available at https://github.com/demotu/datasets ) presents the programming code to generate analyses and other examples.

scholarly journals Humanoid standing control: learning from human demonstration

2002 ◽  
Vol 12 (1) ◽  
pp. 16-22 ◽  
Author(s):  
Andreas Hofmann ◽  
Marko Popovic ◽  
Hugh Herr
Keyword(s):  
Ground Reaction Force ◽  
Center Of Pressure ◽  
Human Subjects ◽  
Reaction Force ◽  
Morphological Data ◽  
Human Model ◽  
Joint Torques ◽  
Double Support ◽  
High Level ◽  
Force Data

A three-dimensional numerical model of human standing is presented that reproduces the dynamics of simple swaying motions while in double-support. The human model is structurally realistic, having both trunk and two legs with segment lengths and mass distributions defined using human morphological data from the literature. In this investigation, model stability in standing is achieved through the application of a high-level reduced-order control system where stabilizing forces are applied to the model's trunk by virtual spring- damper elements. To achieve biologically realistic model dynamics, torso position and ground reaction force data measured on human subjects are used as demonstration data in a supervised learning strategy. Using Powell's method, the error between simulation data and measured human data is minimized by varying the virtual high-level force field. Once optimized, the model is shown to track torso position and ground reaction force data from human demonstrations. With only these limited demonstration data, the humanoid model sways in a biologically realistic manner. The model also reproduces the center-of-pressure trajectory beneath the foot, even though no error term for this is included in the optimization algorithm. This indicates that the error terms used (the ones for torso position and ground reaction force) are sufficient to compute the correct joint torques such that independent metrics, like center-of-pressure trajectory, are correct.

scholarly journals A data set with kinematic and ground reaction forces of human balance

2017 ◽  
Author(s):  
Damiana A dos Santos ◽  
Claudiane A Fukuchi ◽  
Reginaldo K Fukuchi ◽  
Marcos Duarte
Keyword(s):  
Center Of Pressure ◽  
Reaction Force ◽  
Kinematic Model ◽  
Three Dimensional ◽  
Force Platform ◽  
Whole Body ◽  
Ground Reaction Forces ◽  
Data Set ◽  
Public Data ◽  
Reaction Forces

This article describes a public data set with the three-dimensional kinematics of the whole body and the ground reaction forces (with a dual force platform setup) of subjects standing still for 60 s in different conditions, in which the vision and the standing surface were manipulated. Twenty-seven young subjects and 22 old subjects were evaluated. The data set comprises a file with metadata plus 1,813 files with the ground reaction force (GRF) and kinematics data for the 49 subjects (three files for each of the 12 trials plus one file for each subject). The file with metadata has information about each subject’s sociocultural, demographic, and health characteristics. The files with the GRF have the data from each force platform and from the resultant GRF (including the center of pressure data). The files with the kinematics have the three-dimensional position of the 42 markers used for the kinematic model of the whole body and the 73 calculated angles. In this text, we illustrate how to access, analyze, and visualize the data set. All the data is available at Figshare (DOI: 10.6084/m9.figshare.4525082 ), and a companion Jupyter Notebook (available at https://github.com/demotu/datasets ) presents the programming code to generate analyses and other examples.

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