A Computational Technique for Determining the Ground Reaction Forces in Human Bipedal Stance

2003 ◽  
Vol 19 (4) ◽  
pp. 361-371 ◽  
Author(s):  
Musa L. Audu ◽  
Robert F. Kirsch ◽  
Ronald J. Triolo
Keyword(s):  
Center Of Pressure ◽  
Optimization Technique ◽  
Reaction Force ◽  
Kinematic Chain ◽  
Optimization Procedure ◽  
Computational Technique ◽  
Inverse Dynamic ◽  
Open Chain ◽  
Reaction Forces

Our long-term goal is to use a musculoskeletal modeling approach for developing controller algorithms to restore standing balance to individuals with lower extremity paralysis using functional electrical stimulation. This paper describes a technique that facilitates this approach by avoiding the numerical problems associated with modeling the closed kinematic chain formed by the two lower extremities and the ground while standing. Specifically, we propose an optimization technique to estimate the magnitude and origin of the ground reaction force (GRF) vector on one of the feet, resulting in an equivalent open-chain formulation. Using this technique, we performed a series of inverse dynamic computations to determine the GRF and center of pressure (COP) values for five standing postures: neutral, neutral with forward lean, neutral with backward lean, wide, and tandem. The optimization procedure elicited force results that satisfy equilibrium and result in COP locations that are consistent and physically reasonable.

scholarly journals Active foot placement control ensures stable gait: Effect of constraints on foot placement and ankle moments

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0242215
Author(s):  
A. M. van Leeuwen ◽  
J. H. van Dieën ◽  
A. Daffertshofer ◽  
S. M. Bruijn
Keyword(s):  
Steady State ◽  
Center Of Pressure ◽  
Center Of Mass ◽  
Reaction Force ◽  
Stride Frequency ◽  
Tight Control ◽  
Foot Placement ◽  
Ankle Moment ◽  
Reaction Forces ◽  
Moment Control

Step-by-step foot placement control, relative to the center of mass (CoM) kinematic state, is generally considered a dominant mechanism for maintenance of gait stability. By adequate (mediolateral) positioning of the center of pressure with respect to the CoM, the ground reaction force generates a moment that prevents falling. In healthy individuals, foot placement is complemented mainly by ankle moment control ensuring stability. To evaluate possible compensatory relationships between step-by-step foot placement and complementary ankle moments, we investigated the degree of (active) foot placement control during steady-state walking, and under either foot placement-, or ankle moment constraints. Thirty healthy participants walked on a treadmill, while full-body kinematics, ground reaction forces and EMG activities were recorded. As a replication of earlier findings, we first showed step-by-step foot placement is associated with preceding CoM state and hip ab-/adductor activity during steady-state walking. Tight control of foot placement appears to be important at normal walking speed because there was a limited change in the degree of foot placement control despite the presence of a foot placement constraint. At slow speed, the degree of foot placement control decreased substantially, suggesting that tight control of foot placement is less essential when walking slowly. Step-by-step foot placement control was not tightened to compensate for constrained ankle moments. Instead compensation was achieved through increases in step width and stride frequency.

Prediction of Antagonistic Muscle Forces Using Inverse Dynamic Optimization During Flexion/Extension of the Knee

1999 ◽  
Vol 121 (3) ◽  
pp. 316-322 ◽  
Author(s):  
G. Li ◽  
K. R. Kaufman ◽  
E. Y. S. Chao ◽  
H. E. Rubash
Keyword(s):  
Dynamic Optimization ◽  
Optimization Procedure ◽  
Muscle Forces ◽  
Inverse Dynamic ◽  
Optimization Criteria ◽  
Flexion Extension ◽  
Antagonistic Muscle ◽  
Joint Reaction Forces ◽  
Reaction Forces ◽  
Joint Reaction

This paper examined the feasibility of using different optimization criteria in inverse dynamic optimization to predict antagonistic muscle forces and joint reaction forces during isokinetic flexion/extension and isometric extension exercises of the knee. Both quadriceps and hamstrings muscle groups were included in this study. The knee joint motion included flexion/extension, varus/valgus, and internal/external rotations. Four linear, nonlinear, and physiological optimization criteria were utilized in the optimization procedure. All optimization criteria adopted in this paper were shown to be able to predict antagonistic muscle contraction during flexion and extension of the knee. The predicted muscle forces were compared in temporal patterns with EMG activities (averaged data measured from five subjects). Joint reaction forces were predicted to be similar using all optimization criteria. In comparison with previous studies, these results suggested that the kinematic information involved in the inverse dynamic optimization plays an important role in prediction of the recruitment of antagonistic muscles rather than the selection of a particular optimization criterion. Therefore, it might be concluded that a properly formulated inverse dynamic optimization procedure should describe the knee joint rotation in three orthogonal planes.

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 Active foot placement control ensures stable gait: Effect of constraints on foot placement and ankle moments

2020 ◽  
Author(s):  
A.M. van Leeuwen ◽  
J.H. van Dieën ◽  
A. Daffertshofer ◽  
S.M. Bruijn
Keyword(s):  
Steady State ◽  
Center Of Pressure ◽  
Center Of Mass ◽  
Reaction Force ◽  
Stride Frequency ◽  
Tight Control ◽  
Foot Placement ◽  
Ankle Moment ◽  
Reaction Forces ◽  
Moment Control

AbstractStep-by-step foot placement control, relative to the center of mass (CoM) kinematic state, is generally considered a dominant mechanism for maintenance of gait stability. By adequate (mediolateral) positioning of the center of pressure with respect to the CoM, the ground reaction force generates a moment that prevents falling. In healthy individuals, foot placement is complemented mainly by ankle moment control ensuring stability. To evaluate possible compensatory relationships between step-by-step foot placement and complementary ankle moments, we investigated the degree of (active) foot placement control during steady-state walking, and under either foot placement-, or ankle moment constraints. Thirty healthy participants walked on a treadmill, while full-body kinematics, ground reaction forces and EMG activities were recorded. As a replication of earlier findings, we first showed step-by-step foot placement is associated with preceding CoM state and hip ab-/adductor activity during steady-state walking. Tight control of foot placement appears to be important at normal walking speed because there was a limited change in the degree of foot placement control despite the presence of a foot placement constraint. At slow speed, the degree of foot placement control decreased substantially, suggesting that tight control of foot placement is less essential when walking slowly. Step-by-step foot placement control was not tightened to compensate for constrained ankle moments. Instead compensation was achieved through increases in step width and stride frequency.

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.

Effects of Simulated Genu Valgum and Genu Varum on Ground Reaction Forces and Subtalar Joint Function During Gait

2005 ◽  
Vol 95 (6) ◽  
pp. 531-541 ◽  
Author(s):  
Bart Van Gheluwe ◽  
Kevin A. Kirby ◽  
Friso Hagman
Keyword(s):  
Subtalar Joint ◽  
Center Of Pressure ◽  
Reaction Force ◽  
Force Plate ◽  
Frontal Plane ◽  
Genu Valgum ◽  
Genu Varum ◽  
Contact Phase ◽  
Reaction Forces ◽  
Gait Study

The mechanical effects of genu valgum and varum deformities on the subtalar joint were investigated. First, a theoretical model of the forces within the foot and lower extremity during relaxed bipedal stance was developed predicting the rotational effect on the subtalar joint due to genu valgum and varum deformities. Second, a kinetic gait study was performed involving 15 subjects who walked with simulated genu valgum and genu varum over a force plate and a plantar pressure mat to determine the changes in the ground reaction force vector within the frontal plane and the changes in the center-of-pressure location on the plantar foot. These results predicted that a genu varum deformity would tend to cause a subtalar pronation moment to increase or a supination moment to decrease during the contact and propulsion phases of walking. With genu valgum, it was determined that during the contact phase a subtalar pronation moment would increase, whereas in the early propulsive phase, a subtalar supination moment would increase or a pronation moment would decrease. However, the current inability to track the spatial position of the subtalar joint axis makes it difficult to determine the absolute direction and magnitudes of the subtalar joint moments. (J Am Podiatr Med Assoc 95(6): 531–541, 2005)

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

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3626 ◽  
Author(s):  
Damiana A. dos Santos ◽  
Claudiane A. Fukuchi ◽  
Reginaldo K. Fukuchi ◽  
Marcos Duarte
Keyword(s):  
Center Of Pressure ◽  
Reaction Force ◽  
Three Dimensional ◽  
Force Platform ◽  
Ground Reaction Forces ◽  
Data Set ◽  
Public Data ◽  
Human Balance ◽  
Reaction Forces ◽  
Young Subjects

This article describes a public data set containing the three-dimensional kinematics of the whole human body and the ground reaction forces (with a dual force platform setup) of subjects who were standing still for 60 s in different conditions, in which the subjects’ 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 contain the three-dimensional positions of 42 markers that were placed on each subject’s body and 73 calculated joint 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 presents programming code to access the data set, generate analyses and other examples. The availability of a public data set on the Internet that contains these measurements and information about how to access and process this data can potentially boost the research on human postural control, increase the reproducibility of studies, and be used for training and education, among other applications.

scholarly journals Running ground reaction forces across footwear conditions are predicted from the motion of two body mass components

2019 ◽  
Vol 126 (5) ◽  
pp. 1315-1325 ◽  
Author(s):  
Andrew B. Udofa ◽  
Kenneth P. Clark ◽  
Laurence J. Ryan ◽  
Peter G. Weyand
Keyword(s):  
Ground Reaction Force ◽  
Lower Limb ◽  
Reaction Force ◽  
Ground Reaction Forces ◽  
Vertical Ground Reaction Force ◽  
Time Patterns ◽  
Foot Strike ◽  
Reaction Forces ◽  
Vertical Ground ◽  
Force Time

Although running shoes alter foot-ground reaction forces, particularly during impact, how they do so is incompletely understood. Here, we hypothesized that footwear effects on running ground reaction force-time patterns can be accurately predicted from the motion of two components of the body’s mass (mb): the contacting lower-limb (m1 = 0.08mb) and the remainder (m2 = 0.92mb). Simultaneous motion and vertical ground reaction force-time data were acquired at 1,000 Hz from eight uninstructed subjects running on a force-instrumented treadmill at 4.0 and 7.0 m/s under four footwear conditions: barefoot, minimal sole, thin sole, and thick sole. Vertical ground reaction force-time patterns were generated from the two-mass model using body mass and footfall-specific measures of contact time, aerial time, and lower-limb impact deceleration. Model force-time patterns generated using the empirical inputs acquired for each footfall matched the measured patterns closely across the four footwear conditions at both protocol speeds ( r2 = 0.96 ± 0.004; root mean squared error  = 0.17 ± 0.01 body-weight units; n = 275 total footfalls). Foot landing angles (θF) were inversely related to footwear thickness; more positive or plantar-flexed landing angles coincided with longer-impact durations and force-time patterns lacking distinct rising-edge force peaks. Our results support three conclusions: 1) running ground reaction force-time patterns across footwear conditions can be accurately predicted using our two-mass, two-impulse model, 2) impact forces, regardless of foot strike mechanics, can be accurately quantified from lower-limb motion and a fixed anatomical mass (0.08mb), and 3) runners maintain similar loading rates (ΔFvertical/Δtime) across footwear conditions by altering foot strike angle to regulate the duration of impact. NEW & NOTEWORTHY Here, we validate a two-mass, two-impulse model of running vertical ground reaction forces across four footwear thickness conditions (barefoot, minimal, thin, thick). Our model allows the impact portion of the impulse to be extracted from measured total ground reaction force-time patterns using motion data from the ankle. The gait adjustments observed across footwear conditions revealed that runners maintained similar loading rates across footwear conditions by altering foot strike angles to regulate the duration of impact.

scholarly journals The Design and Simulation of a 16-Sensors Plantar Pressure Insole Layout for Different Applications: From Sports to Clinics, a Pilot Study

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1450
Author(s):  
Alfredo Ciniglio ◽  
Annamaria Guiotto ◽  
Fabiola Spolaor ◽  
Zimi Sawacha
Keyword(s):  
Pressure Distribution ◽  
Plantar Pressure ◽  
Center Of Pressure ◽  
Reaction Force ◽  
Weight Lifting ◽  
Lower Limbs ◽  
Plantar Pressure Distribution ◽  
Drop Landing ◽  
Mean Pressure ◽  
Footwear Design

The quantification of plantar pressure distribution is widely done in the diagnosis of lower limbs deformities, gait analysis, footwear design, and sport applications. To date, a number of pressure insole layouts have been proposed, with different configurations according to their applications. The goal of this study is to assess the validity of a 16-sensors (1.5 × 1.5 cm) pressure insole to detect plantar pressure distribution during different tasks in the clinic and sport domains. The data of 39 healthy adults, acquired with a Pedar-X® system (Novel GmbH, Munich, Germany) during walking, weight lifting, and drop landing, were used to simulate the insole. The sensors were distributed by considering the location of the peak pressure on all trials: 4 on the hindfoot, 3 on the midfoot, and 9 on the forefoot. The following variables were computed with both systems and compared by estimating the Root Mean Square Error (RMSE): Peak/Mean Pressure, Ground Reaction Force (GRF), Center of Pressure (COP), the distance between COP and the origin, the Contact Area. The lowest (0.61%) and highest (82.4%) RMSE values were detected during gait on the medial-lateral COP and the GRF, respectively. This approach could be used for testing different layouts on various applications prior to production.

scholarly journals Postural Control Disturbances Induced by Virtual Reality in Stroke Patients

2021 ◽  
Vol 11 (4) ◽  
pp. 1510
Author(s):  
Charles Morizio ◽  
Maxime Billot ◽  
Jean-Christophe Daviet ◽  
Stéphane Baudry ◽  
Christophe Barbanchon ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Postural Control ◽  
Virtual Environments ◽  
Center Of Pressure ◽  
Dynamic Condition ◽  
Static Condition ◽  
Stroke Patients ◽  
Post Stroke ◽  
Subacute Stroke

People who survive a stroke are often left with long-term neurologic deficits that induce, among other impairments, balance disorders. While virtual reality (VR) is growing in popularity for postural control rehabilitation in post-stroke patients, studies on the effect of challenging virtual environments, simulating common daily situations on postural control in post-stroke patients, are scarce. This study is a first step to document the postural response of stroke patients to different challenging virtual environments. Five subacute stroke patients and fifteen age-matched healthy adults were included. All participants underwent posturographic tests in control conditions (open and closed eyes) and virtual environment without (one static condition) and with avatars (four dynamic conditions) using a head-mounted device for VR. In dynamic environments, we modulated the density of the virtual crowd (dense and light crowd) and the avoidance space with the avatars (near or far). Center of pressure velocity was collected by trial throughout randomized 30-s periods. Results showed that more challenging conditions (dynamic condition) induced greater postural disturbances in stroke patients than in healthy counterparts. Our study suggests that virtual reality environments should be adjusted in light of obtaining more or less challenging conditions.

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