scholarly journals Applying adversarial auto-encoder for estimating human walking gait abnormality index

2019 ◽  
Vol 22 (4) ◽  
pp. 1597-1608 ◽  
Author(s):  
Trong-Nguyen Nguyen ◽  
Jean Meunier
Keyword(s):  
Human Walking ◽  
Walking Gait ◽  
Gait Abnormality ◽  
Abnormality Index

A dynamic analysis of Middle Pleistocene human walking gait adjustment and control

2019 ◽  
Vol 138 (2) ◽  
pp. 231-238
Author(s):  
Gerard Saborit ◽  
Alessandro Mondanaro ◽  
Marina Melchionna ◽  
Carmela Serio ◽  
Francesco Carotenuto ◽  
...  
Keyword(s):  
Dynamic Analysis ◽  
Human Walking ◽  
Middle Pleistocene ◽  
Walking Gait ◽  
And Control

DEVELOPMENT OF MOTION CAPTURE SYSTEM USING DUAL VIDEO CAMERAS FOR THE GAIT DESIGN OF A BIPED ROBOT

2011 ◽  
Vol 08 (02) ◽  
pp. 275-299 ◽  
Author(s):  
JUNG-YUP KIM ◽  
YOUNG-SEOG KIM
Keyword(s):  
Motion Capture ◽  
Human Walking ◽  
Human Gait ◽  
Motion Capture System ◽  
System Calibration ◽  
Walking Gait ◽  
Video Cameras ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Motion Capture Systems

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.

A mechatronic analysis and synthesis of human walking gait

2009 ◽  
Author(s):  
Luis I. Lugo-Villeda ◽  
Antonio Frisoli ◽  
Oscar O. Sandoval Gonzalez ◽  
Massimo Bergamasco ◽  
Vicente Parra-Vega
Keyword(s):  
Human Walking ◽  
Walking Gait ◽  
Analysis And Synthesis

scholarly journals A-GAS: a Probabilistic Approach for Generating Automated Gait Assessment Score for Cerebral Palsy Children

2021 ◽  
Author(s):  
Rishabh Bajpai ◽  
Deepak Joshi
Keyword(s):  
Cerebral Palsy ◽  
Gait Cycle ◽  
Joint Angle ◽  
Gait Disorders ◽  
Weighted Sum ◽  
Assessment Score ◽  
Gait Assessment ◽  
Gait Abnormality ◽  
Abnormality Index ◽  
Set Up

Gait disorders in children with cerebral palsy (CP) affect their mental, physical, economic, and social lives. Gait assessment is one of the essential steps of gait management. It has been widely used for clinical decision making and evaluation of different treatment outcomes. However, most of the present methods of gait assessment are subjective, less sensitive to small pathological changes, time-taking and need a great effort of an expert. This study proposes an automated, comprehensive gait assessment score (A-GAS) for gait disorders in CP. Kinematic data of 356 CP and 41 typically developing subjects is used to validate the performance of A-GAS. For the computation of A-GAS, instance abnormality index (AII) and abnormality index (AI) are computed. AII quantifies gait abnormality of a gait cycle instance, while AI quantifies gait abnormality of a joint angle profile. AII is calculated for all gait cycle instances by performing probabilistically and statistical tests. Abnormality index (AI) is a weighted sum of AII, computed for each joint angle profile. A-GAS is a weighted sum of AI, calculated for a lower limb. Moreover, a graphical representation of the gait assessment report, including AII, AI, and A-GAS is generated to understand the results better. Furthermore, the study compares A-GAS with a present rating-based gait assessment scores to understand fundamental differences between them. Finally, AGAS’s performance is verified for a high-cost multicamera set-up using nine joint angle profiles and a low-cost single camera set-up using three joint angle profiles. Results show no significant differences in performance of A-GAS for both the set-ups. Therefore, A-GAS for both the set-ups can be used interchangeably.

scholarly journals A novel ex vivo protocol to mimic human walking gait: implications for Duchenne muscular dystrophy

2020 ◽  
Vol 129 (4) ◽  
pp. 779-791
Author(s):  
Katherine E. Bukovec ◽  
Xiao Hu ◽  
Matthew Borkowski ◽  
Duane Jeffery ◽  
Silvia S. Blemker ◽  
...  
Keyword(s):  
Ex Vivo ◽  
Human Movement ◽  
Length Change ◽  
Human Walking ◽  
Eccentric Contractions ◽  
Muscle Stimulation ◽  
Mouse Muscle ◽  
Walking Gait ◽  
Excitation Pattern ◽  
Stimulation Technique

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.

Stabilization of a Dynamic Walking Gait Simulation

2006 ◽  
Vol 2 (1) ◽  
pp. 65-72 ◽  
Author(s):  
Mike Peasgood ◽  
Eric Kubica ◽  
John McPhee
Keyword(s):  
Feedback Control ◽  
Controller Design ◽  
Balance Control ◽  
Single Step ◽  
Dynamics Simulation ◽  
Human Walking ◽  
Linear Feedback ◽  
Dynamic Simulations ◽  
Arbitrary Length ◽  
Walking Gait

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.

scholarly journals Human-Inspired Algebraic Curves for Wearable Robot Control

2018 ◽  
Author(s):  
Alireza Mohammadi ◽  
Robert D. Gregg
Keyword(s):  
Robot Control ◽  
Gait Cycle ◽  
Algebraic Curves ◽  
Controller Design ◽  
Rehabilitation Robotics ◽  
Relative Degree ◽  
Human Walking ◽  
Wearable Robot ◽  
Walking Gait ◽  
Robot Controller

Having unified representations of human walking gait data is of paramount importance for wearable robot control. In the rehabilitation robotics literature, control approaches that unify the gait cycle of wearable robots are more appealing than the conventional approaches that rely on dividing the gait cycle into several periods, each with their own distinct controllers. In this article we propose employing algebraic curves to represent human walking data for wearable robot controller design. In order to generate algebraic curves from human walking data, we employ the 3L fitting algorithm, a tool developed in the pattern recognition literature for fitting implicit polynomial curves to given datasets. For an impedance model of the knee joint motion driven by the hip angle signal, we provide conditions by which the generated algebraic curves satisfy a robust relative degree condition throughout the entire walking gait cycle. The robust relative degree property makes the algebraic curve representation of walking gaits amenable to various nonlinear output tracking controller design techniques.

Sign in / Sign up

Export Citation Format

Share Document