Assessment of the Impact of Positive Heels (Plantarflexion) and Negative Heels (Dorsiflexion) Shoes on Human Walking Gait

Author(s):  
E. X. Ng ◽  
C. Monkhouse ◽  
P. Wong ◽  
G. Meyer ◽  
Y. Aloni ◽  
...  
2019 ◽  
Vol 138 (2) ◽  
pp. 231-238
Author(s):  
Gerard Saborit ◽  
Alessandro Mondanaro ◽  
Marina Melchionna ◽  
Carmela Serio ◽  
Francesco Carotenuto ◽  
...  

2011 ◽  
Vol 08 (02) ◽  
pp. 275-299 ◽  
Author(s):  
JUNG-YUP KIM ◽  
YOUNG-SEOG KIM

This paper, describes the development of a motion capture system with novel features for biped robots. In general, motion capture is effectively utilized in the field of computer animation. In the field of humanoid robotics, the number of studies attempting to design human-like gaits by using expensive optical motion capture systems is increasing. The optical motion capture systems used in these studies have involved a large number of cameras because such systems use small-sized ball markers; hence the position accuracy of the markers and the system calibration are very significant. However, since the human walking gait is a simple periodic motion rather than a complex motion, we have developed a specialized motion capture system for this study using dual video cameras and large band-type markers without high-level system calibration in order to capture the human walking gait. In addition to its lower complexity, the proposed capture method requires only a low-cost system and has high space efficiency. An image processing algorithm is also proposed for deriving the human gait data. Finally, we verify the reliability and accuracy of our system by comparing a zero moment point (ZMP) trajectory calculated by the motion captured data with a ZMP trajectory measured by foot force sensors.


Author(s):  
Luis I. Lugo-Villeda ◽  
Antonio Frisoli ◽  
Oscar O. Sandoval Gonzalez ◽  
Massimo Bergamasco ◽  
Vicente Parra-Vega

Author(s):  
Wankun Sirichotiyakul ◽  
Aykut C. Satici ◽  
Eric S. Sanchez ◽  
Pranav A. Bhounsule

Abstract In this work, we discuss the modeling, control, and implementation of a rimless wheel with torso. We derive and compare two control methodologies: a discrete-time controller (DT) that updates the controls once-per-step and a continuous-time controller (CT) that updates gains continuously. For the discrete controller, we use least-squares estimation method to approximate the Poincaré map on a certain section and use discrete-linear-quadratic-regulator (DQLR) to stabilize a (closed-form) linearization of this map. For the continuous controller, we introduce moving Poincaré sections and stabilize the transverse dynamics along these moving sections. For both controllers, we estimate the region of attraction of the closed-loop system using sum-of-squares methods. Analysis of the impact map yields a refinement of the controller that stabilizes a steady-state walking gait with minimal energy loss. We present both simulation and experimental results that support the validity of the proposed approaches. We find that the CT controller has a larger region of attraction and smoother stabilization as compared with the DT controller.


2020 ◽  
Vol 129 (4) ◽  
pp. 779-791
Author(s):  
Katherine E. Bukovec ◽  
Xiao Hu ◽  
Matthew Borkowski ◽  
Duane Jeffery ◽  
Silvia S. Blemker ◽  
...  

A novel ex vivo mouse soleus protocol that mimics scaled length change and excitation profiles predicted by a mathematical model of human soleus during gait is presented. A custom stimulator was developed that enabled an innovative muscle stimulation technique to modulate voltage to closely match the excitation pattern of human soleus during gait. This ex vivo protocol provides assessment of simulated human movement in mouse muscle, including components of eccentric contractions.


2006 ◽  
Vol 2 (1) ◽  
pp. 65-72 ◽  
Author(s):  
Mike Peasgood ◽  
Eric Kubica ◽  
John McPhee

Forward dynamic simulations of human walking gait have typically simulated and analyzed a single step of the walking cycle, assuming symmetric and periodic gait. To enable simulations over many steps, a stabilizer is required to maintain the balance of the walking model, ideally mimicking the human balance control mechanism. This paper presents a feedback control system that stabilizes the torso orientation during a human walking gait dynamic simulation, enabling arbitrarily long simulations. The model is a two-dimensional mechanical simulation, in which the desired joint trajectories are defined as functions of time; the only external forces on the model are gravitational and ground reaction forces. Orientation or postural control is achieved by modulation of the rate at which lower limb joints move through angular trajectories. The controller design is based on a sequence of simple linear feedback controllers, each based on an intuitive control law. Controller parameters were determined iteratively using an optimization algorithm and repeated executions of the forward dynamics simulation to minimize control term errors. Results show the use of feedback control and joint speed modulation to be effective in maintaining balance for walking simulations of arbitrary length, allowing for analysis of steady-state walking.


2008 ◽  
Vol 130 (5) ◽  
Author(s):  
S. Srinivasan ◽  
I. A. Raptis ◽  
E. R. Westervelt

This paper applies a robotics-inspired approach to derive a low-dimensional forward-dynamic hybrid model of human walking in the sagittal plane. The low-dimensional model is derived as a subdynamic of a higher-dimensional anthropomorphic hybrid model. The hybrid model is composed of models for single support (SS) and double support (DS), with the transition from SS to DS modeled by a rigid impact to account for the impact at heel-contact. The transition from DS to SS occurs in a continuous manner. Existing gait data are used to specify, via parametrization, the low-dimensional model that is developed. The primary result is a one-degree-of-freedom model that is an exact subdynamic of the higher-dimensional anthropomorphic model and describes the dynamics of walking. The stability properties of the model are evaluated using the method of Poincaré. The low-dimensional model is validated using the measured human gait data. The validation demonstrates the observed stability of the measured gait.


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