scholarly journals Effect of Common Pavements on Interjoint Coordination of Walking with and without Robotic Exoskeleton

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Jinlei Wang ◽  
Jing Qiu ◽  
Lei Hou ◽  
Xiaojuan Zheng ◽  
Suihuai Yu
Keyword(s):  
Gait Cycle ◽  
Sagittal Plane ◽  
Motor Recovery ◽  
Human Gait ◽  
Interjoint Coordination ◽  
Design And Optimization ◽  
Robotic Exoskeleton ◽  
The Common ◽  
Coordination Patterns ◽  
Healthy Participants

Background. The analysis and comprehension of the coordination control of a human gait on common grounds benefit the development of robotic exoskeleton for motor recovery. Objective. This study investigated whether the common grounds effect the interjoint coordination of healthy participants with/without exoskeletons in walking. Methods. The knee-ankle coordination and hip-knee coordination of 8 healthy participants in a sagittal plane were measured on five kinds of pavements (tiled, carpet, wooden, concrete, and pebbled) with/without exoskeletons, using the continuous relative phase (CRP). The root mean square of CRP (CRPRMS) over each phase of the gait cycle is used to analyze the magnitude of dephasing between joints, and the standard deviation of CRP (CRPSD) in the full gait cycle is used to assess the variability of coordination patterns between joints. Results. The CRPHip-Knee/RMS of the carpet pavement with exoskeleton is different from that of other pavements (except the tiled pavement) in the midstance phase. The CRPHip-Knee/RMS on the pebble pavement without exoskeleton is less than that on the other pavements in all phases. The CRPHip-Knee/SD of the pebble pavement without exoskeleton is smaller than that of other pavements. The CRPKnee-Ankle/SD with/without exoskeleton is similar across all pavements. Conclusion. The compressive capacity of the pavement and the unevenness of the pavement are important factors that influence interjoint coordination, which can be used as key control elements of gait to adapt different pavements for robotic exoskeleton. Novelty. We provide a basis of parameter change of kinematics on different common grounds for the design and optimization of robotic exoskeleton for motor recovery.

Modeling and Simulation of an Assistive Exoskeleton Leg System with Knee Osteoarthritis and Quadriceps Weakness

2022 ◽  
Author(s):  
Mehmet Iscan ◽  
Cuneyt Yilmaz ◽  
Berkem Vural ◽  
Huseyin Eken
Keyword(s):  
Knee Osteoarthritis ◽  
Feedback Linearization ◽  
Gait Cycle ◽  
Minimum Energy ◽  
Human Locomotion ◽  
Human Gait ◽  
Quadriceps Weakness ◽  
The Common ◽  
Adequate Data

Abstract The most common human locomotion problems such as quadriceps weakness, knee osteoarthritis can be healed up by using exoskeleton mechanisms with proper control systems. However, these kinds of abnormalities cannot be easily modeled in terms of engineering perspectives due to a lack of adequate data or unknown dynamics. Also, nature always seeks minimum energy as well as biology which means that the unknown dynamics can be built by using this phenomenon. In this study, a new system dynamic model had been involved in designing a simple single-legged exoskeleton robot mechanism and its control system to assist partially disabled individuals to improve their quality of locomotion. To determine the specific features of the human gait disorders to interpret their nature in the computer-aided simulation environment, knee osteoarthritis and quadriceps weakness, which are the common types of such problems, have been chosen as the main interests for this study. By using the lower limb model with anthropometric data, the simulations of disorders have been realized on MATLAB Simscape environment which enables us to model the entire exoskeleton system with the 3D parts of the human body. A model of a leg with the disorder was able to be obtained with the utilization of feedback linearization which is one of the examples of minimum principles in the control theory. A proper gait cycle is achieved with the exoskeleton application and separately for the leg, with approximately 10 deg deviation from the natural property in knee flexion. Finally, it can be seen that the system conversion into such problematic cases with or without an exoskeleton system is accomplished.

Development of a Lower Limb Orthosis to Form Neuromuscular Patterning

2014 ◽  
Author(s):  
Karla A. Camarillo–Gómez ◽  
Gerardo I. Pérez-Soto ◽  
Luis A. Torres-Rico
Keyword(s):  
Quality Of Life ◽  
Control System ◽  
Lower Limb ◽  
Gait Cycle ◽  
Lower Cost ◽  
Sagittal Plane ◽  
Lower Limbs ◽  
Human Gait

In this paper, a lower limb orthosis is proposed to form the human gait neuromuscular patterns in patients with myelomeningocele. The orthosis has two lower limbs of 2–DOF each which reduces the motion of the hip and knee to the sagittal plane. The orthosis are assembled in a back support which also supports the patients weight. The control system for the orthosis allows to reproduce in a repetitive, controlled and autonomous way the human gait cycle at different velocities according to the patient requirements; so that, the neuromuscular patterning can be supervised by a therapist. The development of these orthosis seeks to improve the quality of life of those infants with myelomenigocele and to introduce a lower cost Mexican technology with Mexican anthropometric dimensions.

Liquid State Machine to Generate the Movement Profiles for the Gait Cycle of a Six Degrees-of-Freedom Bipedal Robot in a Sagittal Plane

2019 ◽  
Vol 142 (1) ◽  
Author(s):  
Jesús Franco-Robles ◽  
Alejandro De Lucio-Rangel ◽  
Karla A. Camarillo-Gómez ◽  
Gerardo I. Pérez-Soto ◽  
Miguel A. Martínez-Prado
Keyword(s):  
Time Series ◽  
Liquid State ◽  
Degrees Of Freedom ◽  
Gait Cycle ◽  
Sagittal Plane ◽  
State Machine ◽  
Supervised Machine Learning ◽  
Human Gait ◽  
Bipedal Robot ◽  
Six Degrees Of Freedom

Abstract In this paper, an approach based on a liquid state machine (LSM) to compute the movement profiles to achieve a gait pattern subject to different variations in its trajectory is presented. At the same time, the position of the zero moment point (ZMP) to determine the stability of the six degrees-of-freedom (6DOF) bipedal robot in the sagittal plane during the gait cycle is calculated. The system is constructed as a supervised machine learning model. The time series of the oscillating foot trajectory obtained by direct kinematics with a multilayer perceptron neural network (MLP), to strengthen the kinematic model, is considered as input values for training. The target movement profiles are acquired of a human gait cycle analysis in three different scenarios: normal gait, climbing stairs, and descending stairs. In training, this model also gets the trajectories of the ZMP position during the gait cycle, as target time series. The LSM formed by spiking neurons, considered as third-generation neural networks, is compared in the accuracy of prediction, by the dynamic time warping (DTW) technique and correlation analysis, against the human gait analysis database. With this neuronal system, the joint positions to generate a trajectory of the oscillating foot and the ZMP position of the bipedal in the sagittal plane in different scenarios are obtained, proving the robustness of the LSM.

USING EMG PATTERNS FOR HUMAN GAIT CYCLE RECOGNITION1

2016 ◽  
Vol 35 (3) ◽  
pp. 21-28
Author(s):  
Anatoly S. Bobe ◽  
◽  
Dmitry V. Konyshev ◽  
Sergey A. Vorotnikov ◽  
◽  
...  
Keyword(s):  
Gait Cycle ◽  
Human Gait ◽  
Emg Patterns

Kinematic Coordination in Human Gait: Relation to Mechanical Energy Cost

1998 ◽  
Vol 79 (4) ◽  
pp. 2155-2170 ◽  
Author(s):  
L. Bianchi ◽  
D. Angelini ◽  
G. P. Orani ◽  
F. Lacquaniti
Keyword(s):  
Energy Expenditure ◽  
Energy Cost ◽  
Time Course ◽  
Sagittal Plane ◽  
Dimensional Space ◽  
Mechanical Energy ◽  
Direction Cosine ◽  
Lower Limbs ◽  
Human Gait ◽  
Plane Orientation

Bianchi, L., D. Angelini, G. P. Orani, and F. Lacquaniti. Kinematic coordination in human gait: relation to mechanical energy cost. J. Neurophysiol. 79: 2155–2170, 1998. Twenty-four subjects walked at different, freely chosen speeds ( V) ranging from 0.4 to 2.6 m s−1, while the motion and the ground reaction forces were recorded in three-dimensional space. We considered the time course of the changes of the angles of elevation of the trunk, pelvis, thigh, shank, and foot in the sagittal plane. These angles specify the orientation of each segment with respect to the vertical and to the direction of forward progression. The changes of the trunk and pelvis angles are of limited amplitude and reflect the dynamics of both right and left lower limbs. The changes of the thigh, shank, and foot elevation are ample, and they are coupled tightly among each other. When these angles are plotted one versus the others, they describe regular loops constrained on a plane. The plane of angular covariation rotates, slightly but systematically, along the long axis of the gait loop with increasing V. The rotation, quantified by the change of the direction cosine of the normal to the plane with the thigh axis ( u 3 t ), is related to a progressive phase shift between the foot elevation and the shank elevation with increasing V. As a next step in the analysis, we computed the mass-specific mean absolute power ( P u ) to obtain a global estimate of the rate at which mechanical work is performed during the gait cycle. When plotted on logarithmic coordinates, P u increases linearly with V. The slope of this relationship varies considerably across subjects, spanning a threefold range. We found that, at any given V > 1 m s−1, the value of the plane orientation ( u 3 t ) is correlated with the corresponding value of the net mechanical power ( P u ). On the average, the progressive rotation of the plane with increasing V is associated with a reduction of the increment of P u that would occur if u 3 t remained constant at the value characteristic of low V. The specific orientation of the plane at any given speed is not the same in all subjects, but there is an orderly shift of the plane orientation that correlates with the net power expended by each subject. In general, smaller values of u 3 t tend to be associated with smaller values of P u and vice versa. We conclude that the parametric tuning of the plane of angular covariation is a reliable predictor of the mechanical energy expenditure of each subject and could be used by the nervous system for limiting the overall energy expenditure.

Functional Data Analyses for the Assessment of Joint Power Profiles During Gait of Stroke Subjects

2014 ◽  
Vol 30 (2) ◽  
pp. 348-352 ◽  
Author(s):  
André G. P. Andrade ◽  
Janaine C. Polese ◽  
Leopoldo A. Paolucci ◽  
Hans-Joachim K. Menzel ◽  
Luci F. Teixeira-Salmela
Keyword(s):  
Power Generation ◽  
Gait Cycle ◽  
Sagittal Plane ◽  
Plantar Flexion ◽  
Knee Extension ◽  
Mathematical Function ◽  
Joint Power ◽  
Gait Biomechanics ◽  
Isolated Points ◽  
Parametric Analyses

Lower extremity kinetic data during walking of 12 people with chronic poststroke were reanalyzed, using functional analysis of variance (FANOVA). To perform the FANOVA, the whole curve is represented by a mathematical function, which spans the whole gait cycle and avoids the need to identify isolated points, as required for traditional parametric analyses of variance (ANOVA). The power variables at the ankle, knee, and hip joints, in the sagittal plane, were compared between two conditions: With and without walking sticks at comfortable and fast speeds. For the ankle joint, FANOVA demonstrated increases in plantar flexion power generation during 60–80% of the gait cycle between fast and comfortable speeds with the use of walking sticks. For the knee joint, the use of walking sticks resulted in increases in the knee extension power generation during 10–30% of the gait cycle. During both speeds, the use of walking sticks resulted in increased power generation by the hip extensors and flexors during 10–30% and 40–70% of the gait cycle, respectively. These findings demonstrated the benefits of applying the FANOVA approach to improve the knowledge regarding the effects of walking sticks on gait biomechanics and encourage its use within other clinical contexts.

Liquid State Machine to Generate the Movement Profiles for the Gait Cycle of a 6 DOF Bipedal Robot in a Sagittal Plane

2018 ◽  
Author(s):  
Jesús Franco-Robles ◽  
Alejandro De Lucio-Rangel ◽  
Karla A. Camarillo-Gómez ◽  
Gerardo I. Pérez-Soto ◽  
Jesús Rivera-Guillén
Keyword(s):  
Time Series ◽  
Multilayer Perceptron ◽  
Liquid State ◽  
Gait Cycle ◽  
Sagittal Plane ◽  
Experimental Result ◽  
Forward Kinematics ◽  
Neuronal System ◽  
Bipedal Robot ◽  
Input Time

In this paper, a neuronal system with the ability to generate motion profiles and profiles of the ZMP in a 6DoF bipedal robot in the sagittal plane, is presented. The input time series for LSM training are movement profiles of the oscillating foot trajectory obtained by forward kinematics performed by a previously trained ANN multilayer perceptron. The profiles of objective movement for training are acquired from the analysis of the human walk. Based on a previous simulation of the bipedal robot, a profile of the objective ZMP will be generated for the y–axis and another for the z–axis to know its behavior during the training walk. As an experimental result, the LSM generates new motion profiles and ZMP, given a different trajectory with which it was trained. With the LSM it will be possible to propose new trajectories of the oscillating foot, where it will be known if this trajectory will be stable, by the ZMP, and what movement profile for each articulation will be required to reach this trajectory.

scholarly journals Gait Analysis Using Accelerometry Data from a Single Smartphone: Agreement and Consistency between a Smartphone Application and Gold-Standard Gait Analysis System

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7497
Author(s):  
Roy T. Shahar ◽  
Maayan Agmon
Keyword(s):  
Gait Analysis ◽  
Gold Standard ◽  
Concurrent Validity ◽  
Gait Cycle ◽  
Intraclass Correlation ◽  
Smartphone Application ◽  
Healthy Adults ◽  
Community Dwelling ◽  
Human Gait ◽  
Spatio Temporal

Spatio-temporal parameters of human gait, currently measured using different methods, provide valuable information on health. Inertial Measurement Units (IMUs) are one such method of gait analysis, with smartphone IMUs serving as a good substitute for current gold-standard techniques. Here we investigate the concurrent validity of a smartphone placed in a front-facing pocket to perform gait analysis. Sixty community-dwelling healthy adults equipped with a smartphone and an application for gait analysis completed a 2-min walk on a marked path. Concurrent validity was assessed against an APDM mobility lab (APDM Inc.; Portland, OR, USA). Bland–Altman plots and intraclass correlation coefficients (agreement and consistency) for gait speed, cadence, and step length indicate good to excellent agreement (ICC2,1 > 0.8). For right leg stance and swing % of gait cycle and double support % of gait cycle, results were moderate (0.52 < ICC2,1 < 0.62). For left leg stance and swing % of gait cycle left results show poor agreement (ICC2,1 < 0.5). Consistency of results was good to excellent for all tested parameters (ICC3,1 > 0.8). Thus we have a valid and reliable instrument for measuring healthy adults’ spatio-temporal gait parameters in a controlled walking environment.

scholarly journals Human Gait Cycle Analysis Using Kinect V2 Sensor

2020 ◽  
Vol 15 (3) ◽  
pp. 3-14
Author(s):  
Péter Müller ◽  
Ádám Schiffer
Keyword(s):  
Gait Cycle ◽  
Medical Condition ◽  
Measurement Data ◽  
Human Movement ◽  
Gait Pattern ◽  
Lower Limbs ◽  
Human Gait ◽  
Skeleton Model ◽  
Kinect V2 ◽  
Reduced Mobility

Examining a human movement can provide a wealth of information about a patient’s medical condition. The examination process can be used to diagnose abnormal changes (lesions), ability development and monitor the rehabilitation process of people with reduced mobility. There are several approaches to monitor people, among other things with sensors and various imaging and processing devices. In this case a Kinect V2 sensor and a self-developed LabView based application was used, to examine the movement of the lower limbs. The ideal gait pattern was recorded in the RoboGait training machine and the measured data was used to identify the phases of the human gait. During the evaluation, the position of the skeleton model, the associated body joints and angles can be calculated. The pre-recorded ideal and natural gait cycle can be compared.With the self-developed method the pre-recorded ideal and natural gait cycle can be compared and processed for further evaluation. The evaluated measurement data confirm that a reliable and mobile solution for gait analysis has been created.

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