30,806 research outputs found
3D Gait Abnormality Detection Employing Contactless IR-UWB Sensing Phenomenon
Gait disorder diagnosis and rehabilitation is one area where human perception and observation are highly integrated. Predominantly, gait evaluation, comprises technological devices for gait analysis such as, dedicated force sensors, cameras, and wearable sensor based solutions, however they are limited by insufficient gait parameter recognition, post processing, installation costs, mobility, and skin irritation issues. Thus, the proposed study concentrates on the creation of a widely deployable, noncontact and non-intrusive gait recognition method from impulse radio ultra wideband (IR-UWB) sensing phenomenon, where a standalone IR-UWB system can detect gait problems with less human intervention. A 3D human motion model for gait identification from IR-UWB has been proposed with embracing spherical trigonometry and vector algebra to determine knee angles. Subsequently, normal and abnormal walking subjects were involved in this study. Abnormal gait subjects belong to the spastic gait category only. The prototype has been tested in both the anechoic and multipath environments. The outcomes have been corroborated with a simultaneously deployed Kinect Xbox sensor and supported by statistical graphical approach Bland and Altman (B&A) analysis
Multi-segments kinematic model of the human spine during gait
The complex biomechanical structure of the human spine requires a deep investigation to properly describe its physiological function and its kinematic contribution during motion. The computational approach allows the segmentation of the human spine into several rigid bodies connected by 3D joints. Despite the numerous solutions proposed by previous literature studies based on both inertial and stereophotogrammetric systems, the modelling of the human spine is characterized by some limitations such as the lack of standardization. Accordingly, the present preliminary study focused on the development of a multi-segments kinematic model of the human spine and its validation during gait trials. Three-dimensional spinal angular patterns and ranges of motion of one healthy young subject were considered as outcomes of interest. They were obtained by applying the YXZ Euler angles convention to the custom model. First, results were compared with those of the standard Plug-in-Gait full-body model, which segments the human spine into pelvis and trunk segments. Then, outcomes of the multi-segments model were compared with those obtained using the Tilt-Twist method. Overall, results stressed the importance of the spine segmentation, the major angular contributions of spinal regions during gait (Medium-Lumbar segments for lateral bending and flexion-extension, Thoracic-Medium segments for axial rotation), and the reliability of the proposed custom model (differences between Euler angles method and Tilt-Twist method lower than 0.5° in most cases). Future analysis on a larger healthy population and in the clinical context might be implemented to optimize, standardize and validate the proposed human spine model
Predictive modelling of human walking over a complete gait cycle
An inverse dynamics multi-segment model of the body was combined with optimisation techniques to simulate normal walking in the sagittal plane on level ground. Walking is formulated as an optimal motor task subject to multiple constraints with minimisation of mechanical energy expenditure over a complete gait cycle being the performance criterion. All segmental motions and ground reactions were predicted from only three simple gait descriptors (inputs): walking velocity, cycle period and double stance duration. Quantitative comparisons of the model predictions with gait measurements show that the model reproduced the significant characteristics of normal gait in the sagittal plane. The simulation results suggest that minimising energy expenditure is a primary control objective in normal walking. However, there is also some evidence for the existence of multiple concurrent performance objectives.
Keywords: Gait prediction; Inverse dynamics; Optimisation; Optimal motor tas
Automated design of robust discriminant analysis classifier for foot pressure lesions using kinematic data
In the recent years, the use of motion tracking systems for acquisition of functional biomechanical gait data, has received increasing interest due to the richness and accuracy of the measured kinematic information. However, costs frequently restrict the number of subjects employed, and this makes the dimensionality of the collected data far higher than the available samples. This paper applies discriminant analysis algorithms to the classification of patients with different types of foot lesions, in order to establish an association between foot motion and lesion formation. With primary attention to small sample size situations, we compare different types of Bayesian classifiers and evaluate their performance with various dimensionality reduction techniques for feature extraction, as well as search methods for selection of raw kinematic variables. Finally, we propose a novel integrated method which fine-tunes the classifier parameters and selects the most relevant kinematic variables simultaneously. Performance comparisons are using robust resampling techniques such as Bootstrapand k-fold cross-validation. Results from experimentations with lesion subjects suffering from pathological plantar hyperkeratosis, show that the proposed method can lead tocorrect classification rates with less than 10% of the original features
Virtual Constraints and Hybrid Zero Dynamics for Realizing Underactuated Bipedal Locomotion
Underactuation is ubiquitous in human locomotion and should be ubiquitous in
bipedal robotic locomotion as well. This chapter presents a coherent theory for
the design of feedback controllers that achieve stable walking gaits in
underactuated bipedal robots. Two fundamental tools are introduced, virtual
constraints and hybrid zero dynamics. Virtual constraints are relations on the
state variables of a mechanical model that are imposed through a time-invariant
feedback controller. One of their roles is to synchronize the robot's joints to
an internal gait phasing variable. A second role is to induce a low dimensional
system, the zero dynamics, that captures the underactuated aspects of a robot's
model, without any approximations. To enhance intuition, the relation between
physical constraints and virtual constraints is first established. From here,
the hybrid zero dynamics of an underactuated bipedal model is developed, and
its fundamental role in the design of asymptotically stable walking motions is
established. The chapter includes numerous references to robots on which the
highlighted techniques have been implemented.Comment: 17 pages, 4 figures, bookchapte
3LP: a linear 3D-walking model including torso and swing dynamics
In this paper, we present a new model of biped locomotion which is composed
of three linear pendulums (one per leg and one for the whole upper body) to
describe stance, swing and torso dynamics. In addition to double support, this
model has different actuation possibilities in the swing hip and stance ankle
which could be widely used to produce different walking gaits. Without the need
for numerical time-integration, closed-form solutions help finding periodic
gaits which could be simply scaled in certain dimensions to modulate the motion
online. Thanks to linearity properties, the proposed model can provide a
computationally fast platform for model predictive controllers to predict the
future and consider meaningful inequality constraints to ensure feasibility of
the motion. Such property is coming from describing dynamics with joint torques
directly and therefore, reflecting hardware limitations more precisely, even in
the very abstract high level template space. The proposed model produces
human-like torque and ground reaction force profiles and thus, compared to
point-mass models, it is more promising for precise control of humanoid robots.
Despite being linear and lacking many other features of human walking like CoM
excursion, knee flexion and ground clearance, we show that the proposed model
can predict one of the main optimality trends in human walking, i.e. nonlinear
speed-frequency relationship. In this paper, we mainly focus on describing the
model and its capabilities, comparing it with human data and calculating
optimal human gait variables. Setting up control problems and advanced
biomechanical analysis still remain for future works.Comment: Journal paper under revie
Feedback Control of an Exoskeleton for Paraplegics: Toward Robustly Stable Hands-free Dynamic Walking
This manuscript presents control of a high-DOF fully actuated lower-limb
exoskeleton for paraplegic individuals. The key novelty is the ability for the
user to walk without the use of crutches or other external means of
stabilization. We harness the power of modern optimization techniques and
supervised machine learning to develop a smooth feedback control policy that
provides robust velocity regulation and perturbation rejection. Preliminary
evaluation of the stability and robustness of the proposed approach is
demonstrated through the Gazebo simulation environment. In addition,
preliminary experimental results with (complete) paraplegic individuals are
included for the previous version of the controller.Comment: Submitted to IEEE Control System Magazine. This version addresses
reviewers' concerns about the robustness of the algorithm and the motivation
for using such exoskeleton
Review of Person Re-identification Techniques
Person re-identification across different surveillance cameras with disjoint
fields of view has become one of the most interesting and challenging subjects
in the area of intelligent video surveillance. Although several methods have
been developed and proposed, certain limitations and unresolved issues remain.
In all of the existing re-identification approaches, feature vectors are
extracted from segmented still images or video frames. Different similarity or
dissimilarity measures have been applied to these vectors. Some methods have
used simple constant metrics, whereas others have utilised models to obtain
optimised metrics. Some have created models based on local colour or texture
information, and others have built models based on the gait of people. In
general, the main objective of all these approaches is to achieve a
higher-accuracy rate and lowercomputational costs. This study summarises
several developments in recent literature and discusses the various available
methods used in person re-identification. Specifically, their advantages and
disadvantages are mentioned and compared.Comment: Published 201
- âŠ