scholarly journals Analysis and Research on Human Movement in Sports Scene

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yan Wang ◽  
Yuchen Zhang ◽  
LinJun Shen ◽  
ShuMing Wang
Keyword(s):  
Body Movement ◽  
Movement Analysis ◽  
Human Movement ◽  
Human Motion ◽  
Whole Body ◽  
Human Motion Analysis ◽  
Analysis Method ◽  
Multilabel Classification ◽  
Movement Process ◽  
Rope Skipping

As a whole-body sport, skipping rope plays an increasingly important role in daily life. In rope-skipping education, due to the lack of professional teachers, the training efficiency of students is low. The rope-skipping monitoring device is heavy and expensive, and the cost of labor statistics and energy consumption are high. In order to quickly analyze the movement process of students and provide correct guidance, this article implements the movement analysis method of the human body movement process. The problem of limb posture analysis in rope skipping is transformed into a multilabel classification problem, a real-time human motion analysis method based on mobile vision is proposed, and the algorithm model is verified in the rope-skipping scene. The experimental results prove that this paper proposes the improved algorithm, which achieved the expected effect. In the analysis of rope-skipping action, the choice of hyperparameters during the experiment is introduced, and it is verified that the proposed ALSTM-LSTM can solve the problem of multilabel classification in the rope-skipping process. The accuracy rate reaches 95.1%, and it can provide the best in all indicators and good performance. It is of great significance for movement analysis and movement quality evaluation during exercise.

scholarly journals A Dynamic Bayesian Approach to Computational Laban Shape Quality Analysis

2009 ◽  
Vol 2009 ◽  
pp. 1-17 ◽  
Author(s):  
Dilip Swaminathan ◽  
Harvey Thornburg ◽  
Jessica Mumford ◽  
Stjepan Rajko ◽  
Jodi James ◽  
...  
Keyword(s):  
Mixed Reality ◽  
Low Cost ◽  
Dynamic Bayesian Network ◽  
Movement Analysis ◽  
Human Movement ◽  
Physical World ◽  
The Body ◽  
Quality Analysis ◽  
Whole Body ◽  
Bayesian Fusion

Laban movement analysis (LMA) is a systematic framework for describing all forms of human movement and has been widely applied across animation, biomedicine, dance, and kinesiology. LMA (especially Effort/Shape) emphasizes how internal feelings and intentions govern the patterning of movement throughout the whole body. As we argue, a complex understanding of intention via LMA is necessary for human-computer interaction to becomeembodiedin ways that resemble interaction in the physical world. We thus introduce a novel, flexible Bayesian fusion approach for identifying LMA Shape qualities from raw motion capture data in real time. The method uses a dynamic Bayesian network (DBN) to fuse movement features across the body and across time and as we discuss can be readily adapted for low-cost video. It has delivered excellent performance in preliminary studies comprising improvisatory movements. Our approach has been incorporated inResponse, a mixed-reality environment where users interact via natural, full-body human movement and enhance their bodily-kinesthetic awareness through immersive sound and light feedback, with applications to kinesiology training, Parkinson's patient rehabilitation, interactive dance, and many other areas.

scholarly journals Motion-core assistive tools using pervasive embedded intelligence

2021 ◽  
Vol 2 (1) ◽  
pp. 10-21
Author(s):  
S. M. Namal Arosha Senanayake ◽  
Keyword(s):  
Performance Optimization ◽  
Movement Analysis ◽  
Human Movement ◽  
Decision Fusion ◽  
Human Motion ◽  
Test Subject ◽  
Data Mapping ◽  
Translation Techniques ◽  
And Performance ◽  
Embedded Intelligence

Real-time human movement monitoring anywhere at any time is time critical depending on core human motion activities, in particular nation’s valuable asserts; athletes and soldiers considered as reference standard of any society. Light weight wearable technologies are the key measurements and instruments system integrated to develop human motion-core assistive tools (MAT) using pervasive embedded intelligence. Unlike many existing motion analysis models, motion-core models are based on domain specific data service architectures beyond cloud technologies using inner data structures and data models created. Four layered micro system architecture that consists of sensing, networking, service and Motion-core IoT (MIoT) is proposed. Knowledge base was designed as a distributed and networked data center based on transient and resident data addressing modes in order to guarantee the secure data accessing, propagating, visualizing and control between these two modes of operations. While transient data change and avail in relevant clouds storages, corresponding resident data and processed data retain inside local servers or/and private clouds. Data mapping and translation techniques are applied for the formation of complete motion-core data packet related to the test subject under consideration. Thus, hybrid MIoT system is developed using 3D decision fusion models which are the internationally quantifiable standards for assessing human motion set by trainers, coachers, physiotherapists and orthopedics. MIoT built as motion-core assistive tools have been tested for rehabilitation monitoring, injury prevention and performance optimization of athletes, soldiers, and general public. The hybrid system introduced in this work is novel and proves lower down the latency and connectivity independence by allowing human movement analysis during daily active lifestyle.

Video-Based Motion Capture for Measuring Human Movement

2011 ◽  
pp. 81-100 ◽  
Author(s):  
Chee Kwang Quah ◽  
Michael Koh ◽  
Alex Ong ◽  
Hock Soon Seah ◽  
Andre Gagalowicz
Keyword(s):  
Computer Vision ◽  
Digital Media ◽  
Motion Capture ◽  
Human Movement ◽  
Human Motion ◽  
The Body ◽  
Optical Systems ◽  
Human Motion Analysis ◽  
Capture Method ◽  
The Subject

Through the advancement of electronics technologies, human motion analysis applications span many domains. Existing commercially available magnetic, mechanical and optical systems for motion capture and analyses are far from being able to operate in natural scenarios and environments. The current shortcoming of requiring the subject to wear sensors and markers on the body has prompted development directed towards a marker-less setup using computer vision approaches. However, there are still many challenges and problems in computer vision methods such as inconsistency of illumination, occlusion and lack of understanding and representation of its operating scenario. The authors present a videobased marker-less motion capture method that has the potential to operate in natural scenarios such as occlusive and cluttered scenes. In specific applications in sports biomechanics and education, which are stimulated by the usage of interactive digital media and augmented reality, accurate and reliable capture of human motion are essential.

Development of Flexible Sensors for Measuring Human Motion and Displacement of Novel Flexible Pneumatic Actuator

2011 ◽  
Vol 5 (5) ◽  
pp. 621-628 ◽  
Author(s):  
Tetsuya Akagi ◽  
◽  
Shujiro Dohta ◽  
Hiroaki Kuno ◽  
Akimasa Fukuhara ◽  
...  
Keyword(s):  
Body Movement ◽  
Human Movement ◽  
Human Motion ◽  
The Body ◽  
Displacement Sensor ◽  
Pneumatic Cylinder ◽  
Flexible Sensors ◽  
Sensing System ◽  
Linear Encoder ◽  
Bending Sensor

The importance of wearable devices in nursing care and rehabilitation has been strongly recognized. The purpose of our study is to develop a flexible displacement and bending sensor which can measure human movement and the movement of a flexible actuator. In this paper, a skin displacement sensing system using a flexible string-like flexible displacement sensor to measure the body movement, i.e., measuring the displacement of the skin, was proposed and tested. A flexible linear encoder that can measure the displacement of the flexible pneumatic cylinder using four photoreflectors was also developed. In addition, the measurement using both sensors was done to measure the human motion and the flexible actuator.

A Robust Real-Time Control Algorithm for Whole-Body Running

2011 ◽  
Author(s):  
Xianlian Zhou ◽  
Andrzej Przekwas
Keyword(s):  
Computer Animation ◽  
High Mobility ◽  
Human Movement ◽  
Human Motion ◽  
Whole Body ◽  
Real Time Control ◽  
Dynamic Simulations ◽  
Time Control ◽  
Military Applications ◽  
Experimental Approaches

Dynamic simulations of human movement are becoming increasingly important in biomechanics, computer animation, clinical and military applications. It complements experimental approaches by providing capabilities not generally offered by the experimental approaches. Nonetheless, the dynamic simulation of human movement remains one of great challenges in biomechanics due to the high-mobility of the human body and the redundancy of body control. Over past decades, various methods have been developed to simulate human motion.

Human motion analysis and action scoring technology for sports training based on computer vision features

2021 ◽  
pp. 1-9
Author(s):  
Yong Bai ◽  
Yinggang Chen
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Digital Image Processing ◽  
Human Body ◽  
Median Filter ◽  
Human Movement ◽  
Human Motion ◽  
Human Motion Analysis ◽  
Recognition Model ◽  
Frame Difference

With the advent of the information age, computer-related application research has become more and more extensive, human motion analysis and action scoring based on computer vision have gradually become the focus of attention. In order to adapt to the development of the times and solve the problems related to the analysis of human motion, the experiment analyzed the similarity of eight common human movement behaviors, analyze the movement speed of men and women under sports training, and analyzed the accuracy of the human body motion recognition model in the two cases of the original gray data and the frame difference channel, finally, the denoising performance of four different algorithms of SMF, EMF, RAMF and median filter algorithm in digital image processing is analyzed. The final result shows that there is a big similarity between the same kind of human movement behavior, the accuracy rate of the frame difference channel human body recognition model is higher than that of the original gray data recognition model, and digital image processing median filter algorithm has good image denoising performance.

Video-Based Motion Capture for Measuring Human Movement

2011 ◽  
pp. 209-228
Author(s):  
Chee Kwang Quah ◽  
Michael Koh ◽  
Alex Ong ◽  
Hock Soon Seah ◽  
Andre Gagalowicz
Keyword(s):  
Computer Vision ◽  
Digital Media ◽  
Motion Capture ◽  
Human Movement ◽  
Human Motion ◽  
The Body ◽  
Optical Systems ◽  
Human Motion Analysis ◽  
Capture Method ◽  
The Subject

Through the advancement of electronics technologies, human motion analysis applications span many domains. Existing commercially available magnetic, mechanical and optical systems for motion capture and analyses are far from being able to operate in natural scenarios and environments. The current shortcoming of requiring the subject to wear sensors and markers on the body has prompted development directed towards a marker-less setup using computer vision approaches. However, there are still many challenges and problems in computer vision methods such as inconsistency of illumination, occlusion and lack of understanding and representation of its operating scenario. The authors present a videobased marker-less motion capture method that has the potential to operate in natural scenarios such as occlusive and cluttered scenes. In specific applications in sports biomechanics and education, which are stimulated by the usage of interactive digital media and augmented reality, accurate and reliable capture of human motion are essential.

Error and Data Coding in the Multi-Dimensional Analysis of Human Movement Signals

1993 ◽  
Vol 207 (2) ◽  
pp. 103-110 ◽  
Author(s):  
P Loslever
Keyword(s):  
Time Windows ◽  
Three Dimensional ◽  
Human Movement ◽  
Human Motion ◽  
Analysis Method ◽  
Joint Angles ◽  
Sitting Posture ◽  
Motion Data ◽  
Data Coding ◽  
Correspondence Factor Analysis

This paper discusses two main problems of human motion data: their uncertainty and analysis. Considering the first point, a simulating method is proposed to assess the error. This approach is applied to a joint angle, computed from the positions of points obtained through a three-dimensional video-computer system. Considering the second point, a multi-variate methodology based on appropriate data coding and the correspondence factor analysis method is proposed. The outcomes of this allow the relations within the time windows of the variable set, the distances within the observation set and the correspondences between these two sets to be shown graphically. To illustrate this approach, two examples are considered: the analysis of the low back-pelvis angle in an ergonomical study about the sitting posture and the analysis of joint angles in the gait.

Case study: CAREN (computer assisted rehabilitation environment): A novel way to improve shoe efficacy

2003 ◽  
Vol 27 (2) ◽  
pp. 158-162 ◽  
Author(s):  
I.J.M. De Groot ◽  
O. Even Zohar ◽  
R. Haspels ◽  
H. Van Keeken ◽  
E. Otten
Keyword(s):  
Virtual Environment ◽  
Natural Environment ◽  
Body Movement ◽  
Movement Analysis ◽  
Technical System ◽  
Whole Body ◽  
Computer Assisted ◽  
Total Body ◽  
Made In

A new technical system, CAREN (computer assisted rehabilitation environment), is described, which makes it possible to do a total body movement analysis in a virtual environment. The virtual environment is reproducible and as close to natural environment as possible. In a case study it proved possible with this system to test different shoes and get insight in the movement problems. The importance of whole body analysis is demonstrated in this case study. The adjustments made in the shoes could be tested for their efficacy.

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