Education and Corporeality: Contributions from the Philosophy of Sport

2021 ◽  
Vol 25 (4) ◽  
pp. 602-612
Author(s):  
Ana Cristina Zimmermann
Keyword(s):  
Philosophy Of Education ◽  
Human Movement ◽  
Field Of Study ◽  
Human Movements ◽  
Philosophy Of Sport ◽  
Collective Experience ◽  
Constructing Knowledge

Corporeality is a subject strongly present in educational discussion nowadays. The purpose of this paper is to present an outline of issues we may address from the philosophy of sport that could foster a fruitful dialogue with the philosophy of education. It is understood that the philosophy of education can benefit from reflections on corporeality and human movement, namely from sports and games. Initially, the article introduces the philosophy of sport as a field of study that addresses reflections on human movement from sports and games. They highlight elements that are not specific to such practices and foster reflexions on different areas. Afterwards, it explores the experience of corporeality and the dialogical dimension of human movement based on Merleau-Ponty's phenomenology. Human movement indicates a unique way of being communicative. Finally, it presents some reflections on playing games as an experience that helps us think about our relationships with others and the environment. From this perspective it is possible to seek some critical features to understand education in the experience of human movement, namely from playing games, such as experience, dialogue, and expressiveness. Thoughts on human movements may reinforce the role corporeality plays in education as a collective experience and the recognition of the body's expressive potential in constructing knowledge.

scholarly journals Ensemble model for estimating continental-scale patterns of human movement: a case study of Australia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Karen McCulloch ◽  
Nick Golding ◽  
Jodie McVernon ◽  
Sarah Goodwin ◽  
Martin Tomko
Keyword(s):  
Spatial Scales ◽  
Predictive Ability ◽  
Movement Patterns ◽  
Human Movement ◽  
Continental Scale ◽  
Movement Characteristics ◽  
Human Movements ◽  
Movement Models ◽  
Epidemiology Data

AbstractUnderstanding human movement patterns at local, national and international scales is critical in a range of fields, including transportation, logistics and epidemiology. Data on human movement is increasingly available, and when combined with statistical models, enables predictions of movement patterns across broad regions. Movement characteristics, however, strongly depend on the scale and type of movement captured for a given study. The models that have so far been proposed for human movement are best suited to specific spatial scales and types of movement. Selecting both the scale of data collection, and the appropriate model for the data remains a key challenge in predicting human movements. We used two different data sources on human movement in Australia, at different spatial scales, to train a range of statistical movement models and evaluate their ability to predict movement patterns for each data type and scale. Whilst the five commonly-used movement models we evaluated varied markedly between datasets in their predictive ability, we show that an ensemble modelling approach that combines the predictions of these models consistently outperformed all individual models against hold-out data.

scholarly journals Postural Synergy-Based Exoskeleton Reproducing Natural Human Movements to Improve Upper Limb Motor Control after Stroke

2020 ◽  
Author(s):  
Chang He ◽  
Cai-Hua Xiong ◽  
Ze-Jian Chen ◽  
Wei Fan ◽  
Xiao-Lin Huang
Keyword(s):  
Motor Control ◽  
Upper Limb ◽  
Degrees Of Freedom ◽  
Response Rate ◽  
Human Movement ◽  
Interaction Force ◽  
Human Anatomy ◽  
Clinical Trial Registration ◽  
Upper Limb Exoskeleton ◽  
Human Movements

Abstract Background: Upper limb exoskeletons have drawn significant attention in neurorehabilitation because of anthropomorphic mechanical structure analogous to human anatomy. Whereas, the training movements are typically underorganized because most exoskeletons only control the movement of the hand in space, without considering rehabilitation of joint motion, particularly inter-joint postural synergy. The purposes of this study were to explore the application of a postural synergy-based exoskeleton (Armule) reproducing natural human movements for robot-assisted neurorehabilitation and to preliminarily assess its effect on patients' upper limb motor control after stroke. Methods: We developed a novel upper limb exoskeleton based on the concept of postural synergy, which provided five degrees of freedom (DOF) , natural human movements of the upper limb. Eight participants with hemiplegia due to a first-ever, unilateral stroke were recruited and included. They participated in exoskeleton therapy sessions 45 minutes/day, 5 days/week for 4 weeks, with passive/active training under anthropomorphic trajectories and postures. The primary outcome was the Fugl-Meyer Assessment for Upper Extremities (FMA-UE). The secondary outcomes were the Action Research Arm Test(ARAT), modified Barthel Index (mBI) , and exoskeleton kinematic as well as interaction force metrics: motion smoothness in the joint space, postural synergy error, interaction force smoothness, and the intent response rate. Results: After the 4-weeks intervention, all subjects showed significant improvements in the following clinical measures: the FMA-UE ( p =0.02), the ARAT ( p =0.003), and the mBI score ( p <0.001). Besides, all subjects showed significant improvements in motion smoothness ( p =0.004), postural synergy error ( p =0.014), interaction force smoothness ( p =0.004), and the intent response rate ( p =0.008). Conclusions: The subjects were well adapted to our device that assisted in completing functional movements with natural human movement characteristics. The results of the preliminary clinical intervention indicate that the Armule exoskeleton improves individuals’ motor control and activities of daily living (ADL) function after stroke, which might be associated with kinematic and interaction force optimization and postural synergy modification during functional tasks. Clinical trial registration: ChiCTR, ChiCTR1900026656; Date of registration: October 17, 2019. http://www.chictr.org.cn/showproj.aspx?proj=44420

Speed/accuracy trade-offs in target-directed movements

1997 ◽  
Vol 20 (2) ◽  
pp. 279-303 ◽  
Author(s):  
Réjean Plamondon ◽  
Adel M. Alimi
Keyword(s):  
Human Movement ◽  
Critical Survey ◽  
Kinematic Theory ◽  
Trade Offs ◽  
Human Movements ◽  
Target Article ◽  
Points Of View ◽  
High Degree ◽  
Speed Accuracy ◽  
Kinematic Properties

This target article presents a critical survey of the scientific literature dealing with the speed/accuracy trade-offs in rapid-aimed movements. It highlights the numerous mathematical and theoretical interpretations that have been proposed in recent decades. Although the variety of points of view reflects the richness of the field and the high degree of interest that such basic phenomena attract in the understanding of human movements, it calls into question the ability of many models to explain the basic observations consistently reported in the field. This target article summarizes the kinematic theory of rapid human movements, proposed recently by R. Plamondon (1993b; 1993c; 1995a; 1995b), and analyzes its predictions in the context of speed/accuracy trade-offs. Data from human movement literature are reanalyzed and reinterpreted in the context of the new theory. It is shown that the various aspects of speed/ accuracy trade-offs can be taken into account by considering the asymptotic behavior of a large number of coupled linear systems, from which a delta-lognormal law can be derived to describe the velocity profile of an end-effector driven by a neuromuscular synergy. This law not only describes velocity profiles almost perfectly, it also predicts the kinematic properties of simple rapid movements and provides a consistent framework for the analysis of different types of speed/accuracy trade-offs using a quadratic (or power) law that emerges from the model.

FRACTAL-BASED CLASSIFICATION OF ELECTROMYOGRAPHY (EMG) SIGNAL BETWEEN FINGERS AND HAND’S BASIC MOVEMENTS, FUNCTIONAL MOVEMENTS, AND FORCE PATTERNS

Fractals ◽  
2019 ◽  
Vol 27 (04) ◽  
pp. 1950050 ◽  
Author(s):  
HAMIDREZA NAMAZI
Keyword(s):  
Linear Structure ◽  
Human Movement ◽  
The Body ◽  
Emg Signal ◽  
Human Movements ◽  
Main Indicator ◽  
Human Ability ◽  
Rehabilitation Science ◽  
Functional Movements

Analysis of human ability to move the body (hand, feet, etc.) is one of the major issues in rehabilitation science. For this purpose, scientists analyze different signals govern from human body. Electromyography (EMG) signal is the main indicator of human movement that can be analyzed using different techniques in order to classify different movements. In this paper, we analyze the complex non-linear structure of EMG signal from subjects while they underwent three exercises that include basic movements of the fingers and of the wrist, grasping and functional movements, and force patterns. For this purpose, we employ fractal dimension as indicator of complexity. The result of our analysis showed that the EMG signal experiences the greatest complexity when subjects think to press combinations of fingers with an increasing force (force pattern). The method of analysis employed in this research can be widely applied to analyze and classify different types of human movements.

scholarly journals SPATIAL AND TEMPORAL ANALYSIS OF HUMAN MOVEMENTS AND APPLICATIONS FOR DISASTER RESPONSE MANAGEMENT UTILIZING CELL PHONE USAGE DATA

2015 ◽  
Vol II-4/W2 ◽  
pp. 217-224 ◽  
Author(s):  
M. Yasumiishi ◽  
C. S. Renschler ◽  
T. E. Bittner
Keyword(s):  
Disaster Response ◽  
Cell Phone ◽  
Extreme Event ◽  
Human Movement ◽  
Temporal Analysis ◽  
Communication Link ◽  
Human Movements ◽  
Major Disaster ◽  
Disaster Response Management ◽  
Usage Data

As cell phone usage becomes a norm in our daily lives, analysis and application of the data has become part of various research fields. This study focuses on the application of cell phone usage data to disaster response management. Cell phones work as a communication link between emergency responders and victims during and after a major disaster. This study recognizes that there are two kinds of disasters, one with an advance warning, and one without an advance warning. Different movement distance between a day with a blizzard (advanced warning) and a normal weather day was identified. In the scenario of a day with an extreme event without advanced warning (earthquake), factors that alter the phone users' movements were analyzed. Lastly, combining both cases, a conceptual model of human movement factors is proposed. Human movements consist of four factors that are push factors, movement-altering factors, derived attributes and constraint factors. Considering each category of factors in case of emergency, it should be necessary that we prepare different kinds of emergency response plans depending on the characteristics of a disaster.

scholarly journals Real Life Human Movement Realization in Multimodal Group Communication Using Depth Map Information and Machine Learning

2020 ◽  
Vol 2 (2) ◽  
pp. 93-101
Author(s):  
Dr. Ranganathan G.
Keyword(s):  
Data Gathering ◽  
Real Life ◽  
Depth Map ◽  
Human Movement ◽  
Recognition System ◽  
Research Field ◽  
Movement Detection ◽  
The Real ◽  
Human Movements ◽  
Almost All

The latest advancements in the evolution of depth map information’s has paved way for interesting works like object recognition sign detection and human movement detection etc. The real life human movement detection or their activity identification is very challenging and tiresome. Since the real life activities of the humans could be of much interest in almost all areas, the subject of identifying the human activities has gained significance and has become a most popular research field. Identifying the human movements /activities in the public places like airport, railways stations, hospital, home for aged become very essential due to the several benefits incurred form the human movement recognition system such as surveillance camera, monitoring devices etc. since the changes in the space and the time parameters can provide an effective way of presenting the movements, yet in the case of natural color vision, as the flatness is depicted in almost all portions of images. So the work laid out in the paper in order to identify the human movement in the real life employs the space and the time depth particulars (Spatial-Temporal depth details –STDD) and the random forest in the final stage for movement classification. The technology put forth utilize the Kinect sensors to collecting the information’s in the data gathering stage. The mechanism laid out to identify the human movements is test with the MATLAB using the Berkley and the Cornell datasets. The mechanism proposed through the acquired results proves to deliver a better performance compared to the human movements captured using the normal video frames.

scholarly journals The Use of Exergames in Motor Education Processes for School-Aged Children: A Systematic Review and Epistemic Diagnosis

2021 ◽  
Author(s):  
Dirceu Ribeiro Nogueira da Gama ◽  
Andressa Oliveira Barros dos Santos ◽  
João Gabriel Miranda de Oliveira ◽  
Juliana Brandão Pinto de Castro ◽  
Rodrigo Gomes de Souza Vale
Keyword(s):  
Systematic Review ◽  
Sports Medicine ◽  
Human Movement ◽  
Experimental Investigations ◽  
School Aged Children ◽  
Sport Pedagogy ◽  
Philosophy Of Sport ◽  
And Performance ◽  
And Control ◽  
Sports Sciences

This study aimed to diagnose the current state of knowledge about the use of exergames in the motor education processes of school-aged children. We conducted a systematic review following the PRISMA recommendations. Web of Science, MedLine (via PubMed), ScienceDirect, and Scopus databases were searched in December 2020 with the terms “exergames”, “motor education”, and “children”. We used the Jadad scale and the Systematization for Research Approaches in Sports Sciences instrument to evaluate the surveyed material. Seventeen articles met the inclusion criteria. We observed that: 1) the use of exergames by children can increase the motor skills of locomotion and control of objects, in addition to the levels of physical fitness, but the magnitude and duration of these increments remain inconclusive; 2) the articles exhibited theoretical and methodological weaknesses; 3) empirical-experimental investigations centered on intervention studies are hegemonic; 4) the theories of Sports Training, Didactics, and Human Movement underlie the studies, referring to an interdisciplinary crossing between Sport Psychology, Sport Pedagogy, Sport and Performance, and Sport and Health; 4) researches with alternative designs are necessary; 5) we recommend to approach this issue according to other perspectives, such as Biomechanics applied to Sport, Sports Medicine, Sociology of Sport, and Philosophy of Sport.

scholarly journals VI-Net—View-Invariant Quality of Human Movement Assessment

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5258
Author(s):  
Faegheh Sardari ◽  
Adeline Paiement ◽  
Sion Hannuna ◽  
Majid Mirmehdi
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Rank Correlation ◽  
Human Movement ◽  
Body Parts ◽  
Single View ◽  
Human Movements ◽  
Movement Assessment ◽  
Two Stages

We propose a view-invariant method towards the assessment of the quality of human movements which does not rely on skeleton data. Our end-to-end convolutional neural network consists of two stages, where at first a view-invariant trajectory descriptor for each body joint is generated from RGB images, and then the collection of trajectories for all joints are processed by an adapted, pre-trained 2D convolutional neural network (CNN) (e.g., VGG-19 or ResNeXt-50) to learn the relationship amongst the different body parts and deliver a score for the movement quality. We release the only publicly-available, multi-view, non-skeleton, non-mocap, rehabilitation movement dataset (QMAR), and provide results for both cross-subject and cross-view scenarios on this dataset. We show that VI-Net achieves average rank correlation of 0.66 on cross-subject and 0.65 on unseen views when trained on only two views. We also evaluate the proposed method on the single-view rehabilitation dataset KIMORE and obtain 0.66 rank correlation against a baseline of 0.62.

scholarly journals Generative Model for Skeletal Human Movements Based on Conditional DC-GAN Applied to Pseudo-Images

Algorithms ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 319
Author(s):  
Wang Xi ◽  
Guillaume Devineau ◽  
Fabien Moutarde ◽  
Jie Yang
Keyword(s):  
Data Augmentation ◽  
Human Movement ◽  
Generative Models ◽  
Generative Model ◽  
Great Success ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Human Movements ◽  
Action Type ◽  
Skeleton Image

Generative models for images, audio, text, and other low-dimension data have achieved great success in recent years. Generating artificial human movements can also be useful for many applications, including improvement of data augmentation methods for human gesture recognition. The objective of this research is to develop a generative model for skeletal human movement, allowing to control the action type of generated motion while keeping the authenticity of the result and the natural style variability of gesture execution. We propose to use a conditional Deep Convolutional Generative Adversarial Network (DC-GAN) applied to pseudo-images representing skeletal pose sequences using tree structure skeleton image format. We evaluate our approach on the 3D skeletal data provided in the large NTU_RGB+D public dataset. Our generative model can output qualitatively correct skeletal human movements for any of the 60 action classes. We also quantitatively evaluate the performance of our model by computing Fréchet inception distances, which shows strong correlation to human judgement. To the best of our knowledge, our work is the first successful class-conditioned generative model for human skeletal motions based on pseudo-image representation of skeletal pose sequences.

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