scholarly journals Use of the Human Walking Gait Cycle for Assistive Torque Generation for the Hip Joint Exoskeleton

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Riska Analia ◽  
Jan Hong ◽  
Joshua Mangkey ◽  
Susanto ◽  
Daniel Pamungkas ◽  
...  
Keyword(s):  
Hip Joint ◽  
Initial Phase ◽  
Gait Cycle ◽  
Reference Signal ◽  
Human Gait ◽  
Human Beings ◽  
Walking Gait ◽  
Lower Limb Exoskeleton ◽  
Inertial Moment ◽  
Decision Tree Method

The development of an assistive robot to assist human beings in walking normally is a difficult task. One of the main challenges lies in understanding the intention to walk, as an initial phase before walking commences. In this work, we classify the human gait cycle based on data from an inertial moment unit sensor and information on the angle of the hip joint and use the results as initial signals to produce a suitable assistive torque for a lower limb exoskeleton. A neural network module is used as a prediction module to identify the intention to walk based on the gait cycle. A decision tree method is implemented in our system to generate the assistive torque, and a prediction of the human gait cycle is used as a reference signal. Real-time experiments are carried out to verify the performance of the proposed method, which can differentiate between various types of walking. The results show that the proposed method is able to predict the intention to walk as an initial phase and is also able to provide an assistive torque based on the information predicted for this phase.

scholarly journals Characterization of walking gait features using Kinect

2021 ◽  
Author(s):  
Peter Müller ◽  
Ádam Schiffer
Keyword(s):  
Gait Cycle ◽  
Movement Analysis ◽  
Body Motion ◽  
Human Gait ◽  
Physiotherapy Treatment ◽  
Walking Gait ◽  
Gait Features ◽  
Analysis System ◽  
Reduced Mobility

AbstractThe examination of the human gait cycle can be useful for physiotherapists for identifying and/or predicting body motion disorders and it provides important data about the patient's condition in many ways. In this paper, the progress of a special TheraSuit physiotherapy treatment of a child, who has reduced mobility due to cerebral palsy, has been investigated. Generally, this type of disorder is classified into strict levels and the effectiveness of the therapy is expressed by changing between distinct levels. On the other hand paper describes a new markerless self-developed movement analysis system, which is able to show the effectiveness of the treatment with quantitative parameters. These parameters are determined by statistical methods.

Topology Optimization of the Hip Bone for Walking Using Multi-Load Approach

2020 ◽  
Author(s):  
Kandula Eswara Sai Kumar ◽  
Sourav Rakshit
Keyword(s):  
Topology Optimization ◽  
Optimal Design ◽  
Hip Joint ◽  
Gait Cycle ◽  
Procrustes Analysis ◽  
Optimal Designs ◽  
Shape Similarity ◽  
Joint Force ◽  
Walking Gait ◽  
Case Based

Abstract In this work, we use structural topology optimization to design the hip bone with multi-load conditions of walking gait cycle. Previous research works on optimal bone design primarily aimed to design the micro-structure of the femur bone using a multi-load approach with global geometry fixed. To the best of authors’ knowledge, no optimal design research literature is available on the hip bone. This work uses the concept of multiload conditions, since it considers the effect of entire gait cycle while applying loading conditions. We consider three cases for the weights. Those are (i) equi-weight case, (ii) non-equi weight case based on the fraction of the phase in the gait cycle and (iii) non-equi weight case based on the ratio of magnitude of the hip joint force in respective phases to the total hip joint force of the entire walking gait cycle. The optimal designs are compared with natural hip bone by measuring shape similarity using Procrustes Analysis. Results show that the compliance is less for the optimal designs compared with natural hip bone. The shape similarity values for the three cases are found to be 64%, 78% and 73% respectively. Optimal design obtained from the non-equi weight case based on the duration of phase has highest shape similarity value due to creation of a hole similar to obturator foramen in lower portion of the hip bone. The maximum stress and maximum displacement values are lower in optimal designs compared with natural hip bone. From the shape similarity results, the optimal design from the non-equi weight based on duration of the phase may be more suitable for prosthesis applications.

Research on Characteristics of Human Gait by Electrostatic Detection

2012 ◽  
Vol 241-244 ◽  
pp. 587-590
Author(s):  
Peng Fei Li
Keyword(s):  
Correlation Coefficient ◽  
Human Activity ◽  
Gait Cycle ◽  
Human Walking ◽  
Human Gait ◽  
Phase Point ◽  
Human Beings ◽  
Physical Conditions ◽  
Recurrence Property ◽  
Object Based

Electrostatic detection is remarkably developed and has been employed to detect human activity for years. In this paper, an induction electrostatic detector is designed, and used to measure human walking signals. The gait signals of totally six segments of the same object are measured in the experiment. An algorithm is proposed to obtain accurate gait cycle. The original signals are transformed to correlation coefficient series. Peaks of correlation coefficient series is picked out as the same phase point instead of peaks of walking signal. The time between very second peaks is defined as gait cycle of object. Based on the gait cycle, we discussed the recurrence property as the characteristics of human beings. It is expected that the slope of the recurrence line can be used as an index, and will indicate the personal particularity of objects in detection and their physical conditions.

scholarly journals Real-Time Identification of Knee Joint Walking Gait as Preliminary Signal for Developing Lower Limb Exoskeleton

Electronics ◽  
2021 ◽  
Vol 10 (17) ◽  
pp. 2117
Author(s):  
Susanto Susanto ◽  
Ipensius Tua Simorangkir ◽  
Riska Analia ◽  
Daniel Sutopo Pamungkas ◽  
Hendawan Soebhakti ◽  
...  
Keyword(s):  
Knee Joint ◽  
Real Time ◽  
Gait Cycle ◽  
Initial Step ◽  
Knee Joints ◽  
Walking Gait ◽  
Lower Limb Exoskeleton ◽  
Walking Rehabilitation ◽  
Research Experiment ◽  
Real Time Identification

An exoskeleton is a device used for walking rehabilitation. In order to develop a proper rehabilitation exoskeleton, a user’s walking intention needs to be captured as the initial step of work. Moreover, every human has a unique walking gait style. This work introduced a wearable sensor, which aimed to recognize the walking gait phase, as the fundamental step before applying it into the rehabilitation exoskeleton. The sensor used in this work was the IMU sensor, used to recognize the pitch angle generated from the knee joint while the user walks, as information about the walking gait cycle, before doing the investigation on how to identify the walking gait cycle. In order to identify the walking gait cycle, Neural Network has been proposed as a method. The gait cycle identification was generated to recognize the gait cycle on the knee joint. To verify the performance of the proposed method, experiments have been done in real-time application. The experiments were carried out with different processes such as walking on a flat floor, climbing up, and walking down stairs. Five subjects were trained and tested using the system. The experiments showed that the proposed method was able to recognize each gait cycle for all users as they wore the sensor on their knee joints. This study has the potential to be applied on an exoskeleton rehabilitation robot as a further research experiment.

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

Discrete element and finite element methods provide similar estimations for hip joint contact mechanics during walking gait

2021 ◽  
Vol 115 ◽  
pp. 110163
Author(s):  
Mao Li ◽  
Mikko S. Venäläinen ◽  
Shekhar S. Chandra ◽  
Rushabh Patel ◽  
Jurgen Fripp ◽  
...  
Keyword(s):  
Finite Element ◽  
Contact Mechanics ◽  
Hip Joint ◽  
Finite Element Methods ◽  
Discrete Element ◽  
Walking Gait ◽  
Joint Contact

AN ALGORITHM TO CALCULATE THE COMPONENTS OF ALL MUSCLE FORCES DURING EACH PHASES OF THE GAIT CYCLE, FOR THE PELVIC-FEMUR COMPLEX

2005 ◽  
Vol 05 (04) ◽  
pp. 539-548 ◽  
Author(s):  
SANTANU MAJUMDER ◽  
AMIT ROYCHOWDHURY ◽  
SUBRATA PAL
Keyword(s):  
Finite Element ◽  
Hip Joint ◽  
Computational Models ◽  
Gait Cycle ◽  
Muscle Force ◽  
Fe Analysis ◽  
Muscle Forces ◽  
Force Magnitude ◽  
Flexion Extension ◽  
Force Components

With the help of finite element (FE) computational models of femur, pelvis or hip joint to perform quasi-static stress analysis during the entire gait cycle, muscle force components (X, Y, Z) acting on the hip joint and pelvis are to be known. Most of the investigators have presented only the net muscle force magnitude during gait. However, for the FE software, either muscle force components (X, Y, Z) or three angles for the muscle line of action are required as input. No published algorithm (with flowchart) is readily available to calculate the required muscle force components for FE analysis. As the femur rotates about the hip center during gait, the lines of action for 27 muscle forces are also variable. To find out the variable lines of action and muscle force components (X, Y, Z) with directions, an algorithm was developed and presented here with detailed flowchart. We considered the varying angles of adduction/abduction, flexion/extension during gait. This computer program, obtainable from the first author, is able to calculate the muscle force components (X, Y, Z) as output, if the net magnitude of muscle force, hip joint orientations during gait and muscle origin and insertion coordinates are provided as input.

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 Kinect-based human gait identifcation under different covariate factors

2018 ◽  
Vol 6 (2) ◽  
pp. 1-11
Author(s):  
Azhin T. Sabir
Keyword(s):  
Human Body ◽  
Gait Recognition ◽  
Video Quality ◽  
Microsoft Kinect ◽  
Human Gait ◽  
Human Beings ◽  
Linear Discriminant ◽  
Gait Biometrics ◽  
Gait Identification ◽  
Microsoft Kinect Sensor

Introduction: Nowadays human gait identification/recognition is available in a variety of applications due to rapid advances in biometrics technology. This makes them easier to use for security and surveillance. Due to the rise in terrorist attacks during the last ten years research has focused on the biometric traits in these applications and they are now capable of recognising human beings from a distance. The main reason for my research interest in Gait biometrics is because it is unobtrusive and requires lower image/video quality compared to other biometric traits. Materials and Methods: In this paper we propose investigating Kinect-based gait recognition using non-standard gait sequences. This study examines different scenarios to highlight the challenges of non-standard gait sequences. Gait signatures are extracted from the 20 joint points of the human body using a Microsoft Kinect sensor. Results and Discussion: This feature is constructed by calculating the distances between each two joint points from the 20 joint points of the human body provided which is known as the Euclidean Distance Feature (EDF). The experiments are based on five scenarios, and a Linear Discriminant Classifier (LDC) is used to test the performance of the proposed method. Conclusions: The results of the experiments indicate that the proposed method outperforms previous work in all scenarios.

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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