Biomechanics of human walking and stability descriptive parameters

2016 ◽  
Vol 2 (1) ◽  
pp. 4
Author(s):  
Arturo Bertomeu-Motos
Keyword(s):  
Human Body ◽  
Center Of Pressure ◽  
Body Movement ◽  
Human Motion ◽  
Human Walking ◽  
Dynamic Motion ◽  
Mechanical Aspect ◽  
Zero Moment

From the time of Aristotle onward, there have been countless books written on the topic of movement in animals and humans. However, research of human motion, especially walking mechanisms, has increased over the last fifty years. The study of human body movement and its stability during locomotion involves both neuronal and mechanical aspect. The mechanical aspect, which is in the scope of this thesis, requires knowledge in the field of biomechanics. Walking is the most common maneuver of displacement for humans and it is performed by a stable dynamic motion. In this article it is introduced the bases of the human walking in biomechanical terms. Furthermore, two stability descriptive parameters during walking are also explained - Center of Pressure (CoP) and Zero-Moment Pint (ZMP).

scholarly journals Feasibility of Using Floor Vibration to Detect Human Falls

2020 ◽  
Vol 18 (1) ◽  
pp. 200
Author(s):  
Yu Shao ◽  
Xinyue Wang ◽  
Wenjie Song ◽  
Sobia Ilyas ◽  
Haibo Guo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Human Body ◽  
Nearest Neighbor ◽  
Body Movement ◽  
Modern Society ◽  
Recognition System ◽  
Machine Learning Algorithms ◽  
K Nearest Neighbor ◽  
Study Results ◽  
Floor Vibration

With the increasing aging population in modern society, falls as well as fall-induced injuries in elderly people become one of the major public health problems. This study proposes a classification framework that uses floor vibrations to detect fall events as well as distinguish different fall postures. A scaled 3D-printed model with twelve fully adjustable joints that can simulate human body movement was built to generate human fall data. The mass proportion of a human body takes was carefully studied and was reflected in the model. Object drops, human falling tests were carried out and the vibration signature generated in the floor was recorded for analyses. Machine learning algorithms including K-means algorithm and K nearest neighbor algorithm were introduced in the classification process. Three classifiers (human walking versus human fall, human fall versus object drop, human falls from different postures) were developed in this study. Results showed that the three proposed classifiers can achieve the accuracy of 100, 85, and 91%. This paper developed a framework of using floor vibration to build the pattern recognition system in detecting human falls based on a machine learning approach.

scholarly journals Acceleration Feature Extraction of Human Body Based on Wearable Devices

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 924
Author(s):  
Zhenzhen Huang ◽  
Qiang Niu ◽  
Ilsun You ◽  
Giovanni Pau
Keyword(s):  
Genetic Algorithm ◽  
Feature Extraction ◽  
Kalman Filter ◽  
Human Body ◽  
Wearable Devices ◽  
Human Motion ◽  
Data Set ◽  
Feature Extraction Method ◽  
Motion Data ◽  
Kalman Filter Algorithm

Wearable devices used for human body monitoring has broad applications in smart home, sports, security and other fields. Wearable devices provide an extremely convenient way to collect a large amount of human motion data. In this paper, the human body acceleration feature extraction method based on wearable devices is studied. Firstly, Butterworth filter is used to filter the data. Then, in order to ensure the extracted feature value more accurately, it is necessary to remove the abnormal data in the source. This paper combines Kalman filter algorithm with a genetic algorithm and use the genetic algorithm to code the parameters of the Kalman filter algorithm. We use Standard Deviation (SD), Interval of Peaks (IoP) and Difference between Adjacent Peaks and Troughs (DAPT) to analyze seven kinds of acceleration. At last, SisFall data set, which is a globally available data set for study and experiments, is used for experiments to verify the effectiveness of our method. Based on simulation results, we can conclude that our method can distinguish different activity clearly.

Assessing the Ergonomic Benefits of a New Adjustable Forklift Backrest

2020 ◽  
Vol 64 (1) ◽  
pp. 976-980
Author(s):  
Pranav Madhav Kuber ◽  
Ehsan Rashedi
Keyword(s):  
Comparative Study ◽  
Motion Capture ◽  
Center Of Pressure ◽  
Body Movement ◽  
Pressure Change ◽  
Motion Capture System ◽  
Design Features ◽  
Wide Range ◽  
Body Sizes ◽  
The Mean

A new forklift backrest has been developed by incorporating adjustability concepts into the design to facilitate comfort to a wide range of users. We have conducted a comparative study between the new and original backrests to assess the effectiveness of design features. Using the phenomenon of restlessness, discomfort of the user was associated with the amount of body movement, where we have used a motion- capture system and a force platform to quantify the individuals’ movement for a wide range of body sizes. Meanwhile, subjective comfort and design feedback were collected using a questionnaire. Our results showed a reduction in the mean torso movement and the maximum center of pressure change of location by 300 and 6 mm, respectively, for the new design. Taking advantage of adjustability feature, the new backrest design exhibited enhanced comfort for longer durations and reduced magnitude of discomfort for a wide range of participants’ body sizes.

scholarly journals Elastic Simulation of Joints with Particle-Based Fluid

2021 ◽  
Vol 11 (15) ◽  
pp. 6900
Author(s):  
Su-Kyung Sung ◽  
Sang-Won Han ◽  
Byeong-Seok Shin
Keyword(s):  
Principal Stress ◽  
Human Body ◽  
Yield Condition ◽  
Maximum Principal Stress ◽  
Human Motion ◽  
The Difference ◽  
The Moment ◽  
External Forces ◽  
Physical Changes ◽  
Elastic Simulation

Skinning, which is used in skeletal simulations to express the human body, has been weighted between bones to enable muscle-like motions. Weighting is not a form of calculating the pressure and density of muscle fibers in the human body. Therefore, it is not possible to express physical changes when external forces are applied. To express a similar behavior, an animator arbitrarily customizes the weight values. In this study, we apply the kernel and pressure-dependent density variations used in particle-based fluid simulations to skinning simulations. As a result, surface tension and elasticity between particles are applied to muscles, indicating realistic human motion. We also propose a tension yield condition that reflects Tresca’s yield condition, which can be easily approximated using the difference between the maximum and minimum values of the principal stress to simulate the tension limit of the muscle fiber. The density received by particles in the kernel is assumed to be the principal stress. The difference is calculated by approximating the moment of greatest force to the maximum principal stress and the moment of least force to the minimum principal stress. When the density of a particle increases beyond the yield condition, the object is no longer subjected to force. As a result, one can express realistic muscles.

Video-Based Human Motion Analysis

2011 ◽  
Vol 403-408 ◽  
pp. 2593-2597
Author(s):  
Hong Bao ◽  
Zhi Min Liu
Keyword(s):  
Motion Analysis ◽  
Human Body ◽  
Body Shape ◽  
Human Motion ◽  
Random Motion ◽  
Human Motion Analysis ◽  
Mass Center ◽  
Shape Features ◽  
Skeleton Model ◽  
Regular Motion

In the analysis of human motion, movement was divided into regular motion (such as walking and running) and random motion (such as falling down).Human skeleton model is used in this paper to do the video-based analysis. Key joints on human body were chosen to be traced instead of tracking the entire human body. Shape features like mass center trajectory were used to describe the movement, and to classify human motion. desired results achieved.

scholarly journals Sonifying the Shape of Human Body Motion using Motiongrams

2013 ◽  
Vol 8 (2) ◽  
pp. 73 ◽  
Author(s):  
Alexander Refsum Jensenius ◽  
Rolf Inge Godøy
Keyword(s):  
Human Body ◽  
Video Recording ◽  
Visual Display ◽  
Human Motion ◽  
Visual Similarity ◽  
Body Motion ◽  
Auditory Displays ◽  
Musical Sound ◽  
Starting Point ◽  
Spatial Shape

<p class="author">The paper presents sonomotiongram, a technique for the creation of auditory displays of human body motion based on motiongrams. A motiongram is a visual display of motion, based on frame differencing and reduction of a regular video recording. The resultant motiongram shows the spatial shape of the motion as it unfolds in time, somewhat similar to the way in which spectrograms visualise the shape of (musical) sound. The visual similarity of motiongrams and spectrograms is the conceptual starting point for the sonomotiongram technique, which explores how motiongrams can be turned into sound using &ldquo;inverse FFT&rdquo;. The paper presents the idea of shape-sonification, gives an overview of the sonomotiongram technique, and discusses sonification examples of both simple and complex human motion.</p>

Sign in / Sign up

Export Citation Format

Share Document