Abstract: Bipartite medial cuneiforms are relatively rare but may play a significant role in biomechanical and gait abnormalities. It is believed that a bipartite medial cuneiform may alter the available range of motion due to its larger morphological variant, thus limiting the metatarsal plantarflexion needed to achieve adequate hallux dorsiflexion for normal gait. Radiographic and clinical assessment were performed on two patients who reported with foot pain along the first ray. Both patients had visible bipartite medial cuneiforms on MRI. Using gait plate and Metascan ™ analysis, both were noted to have four measurements far beyond the expected range. Medial and lateral heel peak pressure, hallux peak pressure, and 1st metatarsal peak pressure were all noted to be increased. These measurements are believed to be increased due to the hindrance placed on the available ROM of the first ray by the increased size of the medial cuneiform. A larger patient population would be needed to fully understand this developmental anomaly.
Abstract: Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.
Abstract: This study presents new gait representations for improving gait recognition accuracy on cross gait appearances, such as normal walking, wearing a coat and carrying a bag. Based on the Gait Energy Image (GEI), two ideas are implemented to generate new gait representations. One is to append lower knee regions to the original GEI, and the other is to apply convolutional operations to the GEI and its variants. A set of new gait representations are created and used for training multi-class Support Vector Machines (SVMs). Tests are conducted on the CASIA dataset B. Various combinations of the gait representations with different convolutional kernel size and different numbers of kernels used in the convolutional processes are examined. Both the entire images as features and reduced dimensional features by Principal Component Analysis (PCA) are tested in gait recognition. Interestingly, both new techniques, appending the lower knee regions to the original GEI and convolutional GEI, can significantly contribute to the performance improvement in the gait recognition. The experimental results have shown that the average recognition rate can be improved from 75.65% to 87.50%.
Abstract: The purpose of this research is to analyze the gait
strategy between the normal and loaded gait. To this end, five male
participants satisfied two conditions: the normal and loaded gait
(backpack load 25.2 kg). As expected, results showed that additional
loads elicited not a proportional increase in vertical and shear ground
reaction force (GRF) parameters but also increase of the impulse,
momentum and mechanical work. However, in case of the loaded gait,
the time duration of the double support phase was increased
unexpectedly. It is because the double support phase which is more
stable than the single support phase can reduce instability of the
loaded gait. Also, the directions of the pre-collision and after-collision
were moved upward and downward compared to the normal gait. As a
result, regardless of the additional backpack load, the
impulse-momentum diagram during the step-to-step transition was
maintained such as the normal gait. It means that human walk
efficiently to keep stability and minimize total net works in case of the
loaded gait.
Abstract: Underactuated biped robots control is one of the interesting topics in robotics. The main difficulties are its highly nonlinear dynamics, open-loop instability, and discrete event at the end of the gait. One of the methods to control underactuated systems is the partial feedback linearization, but it is not robust against uncertainties and disturbances that restrict its performance to control biped walking and running. In this paper, fuzzy partial feedback linearization is presented to overcome its drawback. Numerical simulations verify the effectiveness of the proposed method to generate stable and robust biped walking and running gaits.
Abstract: Precise capture of plantar 3D surface of the foot at the
loading gait phases on rigid substrates was found to be valuable for
the assessment of the physiology, health and problems of the feet.
Photogrammetry, a precision 3D spatial data capture technique is
suitable for this type of dynamic application. In this research, the
technique is utilised to study the plantar deformation as a result of
having a strip of kinesiology tape on the plantar surface during the
loading phase of gait. For this pilot study, one healthy adult male
subject was recruited under the University’s human research ethics
guidelines for this preliminary study. The 3D plantar deformation
data with and without applying the tape were analysed. The results
and analyses are presented together with detailed findings.
Abstract: The aim of this paper is to present the kinematic
analysis and mechanism design of an assistive robotic leg for
hemiplegic and hemiparetic patients. In this work, the priority is to
design and develop the lightweight, effective and single driver
mechanism on the basis of experimental hip and knee angles- data for
walking speed of 1 km/h. A mechanism of cam-follower with three
links is suggested for this purpose. The kinematic analysis is carried
out and analysed using commercialized MATLAB software based on
the prototype-s links sizes and kinematic relationships. In order to
verify the kinematic analysis of the prototype, kinematic analysis data
are compared with the experimental data. A good agreement between
them proves that the anthropomorphic design of the lower extremity
exoskeleton follows the human walking gait.
Abstract: The purpose of this study is to find natural gait of
biped robot such as human being by analyzing the COG (Center Of
Gravity) trajectory of human being's gait. It is discovered that human
beings gait naturally maintain the stability and use the minimum
energy. This paper intends to find the natural gait pattern of biped
robot using the minimum energy as well as maintaining the stability by
analyzing the human's gait pattern that is measured from gait image on
the sagittal plane and COG trajectory on the frontal plane. It is not
possible to apply the torques of human's articulation to those of biped
robot's because they have different degrees of freedom. Nonetheless,
human and 5-link biped robots are similar in kinematics. For this, we
generate gait pattern of the 5-link biped robot by using the GA
algorithm of adaptation gait pattern which utilize the human's ZMP
(Zero Moment Point) and torque of all articulation that are measured
from human's gait pattern. The algorithm proposed creates biped
robot's fluent gait pattern as that of human being's and to minimize
energy consumption because the gait pattern of the 5-link biped robot
model is modeled after consideration about the torque of human's each
articulation on the sagittal plane and ZMP trajectory on the frontal
plane. This paper demonstrate that the algorithm proposed is superior
by evaluating 2 kinds of the 5-link biped robot applied to each gait
patterns generated both in the general way using inverse kinematics
and in the special way in which by considering visuality and
efficiency.
Abstract: Children with hemiplgic cerebral palsy often walk
with diminished reciprocal arm swing so the purpose of this study
was to describe kinematic characteristics in children with hemiplegic
cerebral palsy (CP) during the gait suphases, and find if there is a
correlation between upper(shoulder and elbow) and lower(hip, knee,
and ankle) limb joints either in involved or uninvolved.48 children
with hemiplegic cerebral palsy (18boys, 30girls) with an average age
of (5.1±0.87) years were selected randomly to evaluate joint angles
during gait by 3D motion analysis system with 6 pro reflex cameras
in a sagittal plane for both sides of the body. The results showed
increased shoulder and elbow flexion, increased hip angular
displacement, decreased knee and ankle arcs during gait cycle, also
there is correlation between shoulder and elbow to hip, knee, and
ankle joints during various subphases of gait.
Abstract: Biometrics methods include recognition techniques
such as fingerprint, iris, hand geometry, voice, face, ears and gait. The gait recognition approach has some advantages, for example it
does not need the prior concern of the observed subject and it can
record many biometric features in order to make deeper analysis, but
most of the research proposals use high computational cost. This
paper shows a gait recognition system with feature subtraction on a
bundle rectangle drawn over the observed person. Statistical results
within a database of 500 videos are shown.