Articles de revues : « Human physical activity »

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Patel, Mayur A. « Combating Human Diseases through Physical Activity ». Indian Journal of Applied Research 3, n^o 2 (1 octobre 2011) : 312–13. http://dx.doi.org/10.15373/2249555x/feb2013/106.

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Wojciechowska, Paulina. « Physical activity and human health ». Medical Studies 4 (2014) : 254–60. http://dx.doi.org/10.5114/ms.2014.47924.

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Hill, M. J. « Physical activity and human cancer ». European Journal of Cancer Prevention 8, n^o 6 (décembre 1999) : 475–78. http://dx.doi.org/10.1097/00008469-199912000-00001.

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L, Latha, Cynthia J, G. Seetha Lakshmi, Raajshre B, Senthil J et Vikashini S. « Human Activity Recognition Using Smartphone Sensors ». Webology 18, n^o 04 (28 septembre 2021) : 1499–511. http://dx.doi.org/10.14704/web/v18si04/web18294.

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In today’s digitalized world, smartphones are the devices which have become a basic and fundamental part of our life. Since, these greatest technology’s appearance, an uprising has been created in the industry of mobile communication. These greatest inventions of mankind are not just constricted for calling these days. As the capabilities and the number of smartphone users increase day by day, smartphones are loaded with various types of sensors which captures each and every moment, activities of our daily life. Two of such sensors are Accelerometer and Gyroscope which measures the acceleration and angular velocity respectively. These could be used to identify the human activities performed. Basically, Human Activity Recognition is a classifying activity with so many use cases such as health care, medical, surveillance and anti-crime securities. Smartphones have wide variety of applications in various fields and can be used to excavate different kinds of data which provide accurate insights and knowledge about the user's lifestyle. Nowadays creating lifelogs that is a technology to capture and record a user's life through his or her mobile devices, are becoming very important task. An immense issue in creating a detailed lifelog is the accurate detection of activities performed by human based on the collected data from the sensors. The data in the lifelogs has strong association with physical health variables. These data are motivational and they identify any type of behavioral changes. These data provide us the overall measure of physical activity. In this project, we have analyzed the smartphone sensors produced data and used them to recognize the activities performed by the user.

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Gawędzka, Anna, Małgorzata Knapik-Czajka et Jagoda Drąg. « Statins and physical activity in human ». Farmacja Polska 74, n^o 11 (30 novembre 2018) : 645–50. http://dx.doi.org/10.32383/farmpol/118635.

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Westerterp, Klaas R., et Guy Plasqui. « Physical activity and human energy expenditure ». Current Opinion in Clinical Nutrition and Metabolic Care 7, n^o 6 (novembre 2004) : 607–13. http://dx.doi.org/10.1097/00075197-200411000-00004.

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Zhang, Kuan, Patricia Werner, Ming Sun, F. Xavier Pi-Sunyer et Carol N. Boozer. « Measurement of Human Daily Physical Activity ». Obesity Research 11, n^o 1 (janvier 2003) : 33–40. http://dx.doi.org/10.1038/oby.2003.7.

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Voicu, Robert-Andrei, Ciprian Dobre, Lidia Bajenaru et Radu-Ioan Ciobanu. « Human Physical Activity Recognition Using Smartphone Sensors ». Sensors 19, n^o 3 (23 janvier 2019) : 458. http://dx.doi.org/10.3390/s19030458.

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Because the number of elderly people is predicted to increase quickly in the upcoming years, “aging in place” (which refers to living at home regardless of age and other factors) is becoming an important topic in the area of ambient assisted living. Therefore, in this paper, we propose a human physical activity recognition system based on data collected from smartphone sensors. The proposed approach implies developing a classifier using three sensors available on a smartphone: accelerometer, gyroscope, and gravity sensor. We have chosen to implement our solution on mobile phones because they are ubiquitous and do not require the subjects to carry additional sensors that might impede their activities. For our proposal, we target walking, running, sitting, standing, ascending, and descending stairs. We evaluate the solution against two datasets (an internal one collected by us and an external one) with great effect. Results show good accuracy for recognizing all six activities, with especially good results obtained for walking, running, sitting, and standing. The system is fully implemented on a mobile device as an Android application.

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Attal, Ferhat, Samer Mohammed, Mariam Dedabrishvili, Faicel Chamroukhi, Latifa Oukhellou et Yacine Amirat. « Physical Human Activity Recognition Using Wearable Sensors ». Sensors 15, n^o 12 (11 décembre 2015) : 31314–38. http://dx.doi.org/10.3390/s151229858.

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Health Prospect, The. « Physical activity for human and planetary health ». Health Prospect 14, n^o 2 (31 décembre 2015) : 21. http://dx.doi.org/10.3126/hprospect.v14i2.14263.

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Żołądkiewicz, Katarzyna. « Impact of physical activity on the human body - the physiological basis of physical activity ». Quality in Sport 5, n^o 2 (13 août 2019) : 40. http://dx.doi.org/10.12775/qs.2019.010.

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Santiago, Jose A., James P. Quinn et Judith A. Potashkin. « Physical Activity Rewires the Human Brain against Neurodegeneration ». International Journal of Molecular Sciences 23, n^o 11 (2 juin 2022) : 6223. http://dx.doi.org/10.3390/ijms23116223.

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Physical activity may offset cognitive decline and dementia, but the molecular mechanisms by which it promotes neuroprotection remain elusive. In the absence of disease-modifying therapies, understanding the molecular effects of physical activity in the brain may be useful for identifying novel targets for disease management. Here we employed several bioinformatic methods to dissect the molecular underpinnings of physical activity in brain health. Network analysis identified ‘switch genes’ associated with drastic hippocampal transcriptional changes in aged cognitively intact individuals. Switch genes are key genes associated with dramatic transcriptional changes and thus may play a fundamental role in disease pathogenesis. Switch genes are associated with protein processing pathways and the metabolic control of glucose, lipids, and fatty acids. Correlation analysis showed that transcriptional patterns associated with physical activity significantly overlapped and negatively correlated with those of neurodegenerative diseases. Functional analysis revealed that physical activity might confer neuroprotection in Alzheimer’s (AD), Parkinson’s (PD), and Huntington’s (HD) diseases via the upregulation of synaptic signaling pathways. In contrast, in frontotemporal dementia (FTD) its effects are mediated by restoring mitochondrial function and energy precursors. Additionally, physical activity is associated with the downregulation of genes involved in inflammation in AD, neurogenesis in FTD, regulation of growth and transcriptional repression in PD, and glial cell differentiation in HD. Collectively, these findings suggest that physical activity directs transcriptional changes in the brain through different pathways across the broad spectrum of neurodegenerative diseases. These results provide new evidence on the unique and shared mechanisms between physical activity and neurodegenerative diseases.

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Bouchard, Claude. « The Human Genome, Physical Activity, Fitness, and Health ». Kinesiology Review 11, n^o 1 (1 février 2022) : 36–42. http://dx.doi.org/10.1123/kr.2021-0057.

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A summary of the evidence for a contribution of genetic variability to physical activity–related traits is presented. The availability of a reference human DNA sequence has made it possible to screen individuals and populations for the presence of genomic differences. Even though more than 100 million DNA variants have been identified, human beings share a genomic sequence, which is more than 99% identical. Four major lessons can be derived from ongoing genomic and genetic studies. First, the connection between a genotype and a phenotype is highly complex. Second, the expression of genes is regulated via multiple interacting mechanisms. Third, redundancy and compensatory mechanisms are ubiquitous. Fourth, complex, multifactorial traits are influenced by polygenic systems defined by hundreds and thousands of loci with most alleles characterized by very small effect sizes. The contribution of genetic variability is briefly summarized for human longevity, common chronic diseases, physical activity level, cardiorespiratory fitness in the sedentary state, and in response to exercise programs.

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ŚWITAŁA, KATARZYNA, et Agata Leońska-Duniec. « Physical activity and gene association with human obesity ». Baltic Journal of Health and Physical Activity 13, n^o 4 (31 décembre 2021) : 99–111. http://dx.doi.org/10.29359/bjhpa.13.4.10.

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The obesity is a leading cause of health problems all over the world. It is a comlex health abnormality that is influenced by developmental, behavioural, environmental, and genetic factors. Although the role of physical activity and diet in regulation of body weight is well described, the genetic variants potentially influencing the characteristics and range of the body’s adaptive response to physical activity in healthy individuals still remains mostly unknown. The main aim of this study is to review current evidence, through a literature review and the results of our studies, on the influence of selected molecular markers on the development of obesity, as well as the body composition changes in response to regular physical activity. We studied the most reliable candidate genes with a focus on catechol-O-methyltransferase gene (COMT), dopamine deceptor D2 gene (DRD2), fatty acid binding protein 2 gene (FABP2), fat mass and obesity-associated gene (FTO), and uncoupling protein 1 (UCP-1). This review provides information about recent genetic research progressions in adiposity, as well as molecular mechanisms, associated phenotypes, as well as their implications for human health, physical performance, and adaptive changes in response to physical activity.

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Bailey, R. P., et R. M. Fernandez-Chung. « University students‘ physical activity : a human capital perspective ». International Journal of Physical Education 58, n^o 4 (2021) : 2–9. http://dx.doi.org/10.5771/2747-6073-2021-4-2.

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Physical activities often are overlooked at the university level. Young adults at this stage of their lives are focused on building their professional careers and expanding their social circles, often at the expense of physical activities. However, sufficient evidence supports the importance of continuing physical activities during university days. This article brings together evidence of this impact and highlights the lack of strategies, regulations, and policies surrounding the promotion of physical activities at universities. It spotlights some of the existing barriers, concluding that with existing facilities on most campuses today and the potential benefits of physical activity, its promotion seems to be an opportunity with minimal cost and considerable gains.

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Reilly, Thomas, et Benny Peiser. « Seasonal Variations in Health-Related Human Physical Activity ». Sports Medicine 36, n^o 6 (2006) : 473–85. http://dx.doi.org/10.2165/00007256-200636060-00002.

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Ravussin, E. « HUMAN PHYSIOLOGY:Beyond Sloth--Physical Activity and Weight Gain ». Science 283, n^o 5399 (8 janvier 1999) : 184–85. http://dx.doi.org/10.1126/science.283.5399.184.

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Bailey, Richard, Charles Hillman, Shawn Arent et Albert Petitpas. « Physical Activity : An Underestimated Investment in Human Capital ? » Journal of Physical Activity and Health 10, n^o 3 (mars 2013) : 289–308. http://dx.doi.org/10.1123/jpah.10.3.289.

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Despite the fact that physical activity is universally acknowledged to be an important part of healthy functioning and well-being, the full scope of its value is rarely appreciated. This article introduces a novel framework for understanding the relationships between physical activity (and specifically sport-related forms of physical activity) and different aspects of human development. It proposes that the outcomes of physical activity can be framed as differential ‘capitals’ that represent investments in domain-specific assets: Emotional, Financial, Individual, Intellectual, Physical, and Social. These investments, especially when made early in the life course, can yield significant rewards, both at that time and for years to come. The paper presents a new model—the Human Capital Model—that makes sense of these effects, outlines the different capitals, and briefly articulates the conditions necessary for the realization of Human Capital growth through physical activity.

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Shephard, R. J. « Seasonal Variations in Health-Related Human Physical Activity ». Yearbook of Sports Medicine 2007 (janvier 2007) : 115–16. http://dx.doi.org/10.1016/s0162-0908(08)70105-3.

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Atkinson, Greg, et Damien Davenne. « Relationships between sleep, physical activity and human health ». Physiology & ; Behavior 90, n^o 2-3 (février 2007) : 229–35. http://dx.doi.org/10.1016/j.physbeh.2006.09.015.

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Rankinen, Tuomo, et Claude Bouchard. « Gene-Physical Activity Interactions : Overview of Human Studies ». Obesity 16, S3 (décembre 2008) : S47—S50. http://dx.doi.org/10.1038/oby.2008.516.

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Sherrill, Duane L., Kimberly Kotchou et Stuart F. Quan. « Association of Physical Activity and Human Sleep Disorders ». Archives of Internal Medicine 158, n^o 17 (28 septembre 1998) : 1894. http://dx.doi.org/10.1001/archinte.158.17.1894.

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Keesling, Madison K., et Anne E. Mathews. « Guide to Tracking Physical Activity ». EDIS 2016, n^o 6 (15 août 2016) : 3. http://dx.doi.org/10.32473/edis-fs283-2016.

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Being physically active is fun, has many physical and mental health benefits, and can help maintain a healthy weight. The Physical Activity Guidelines for Americans recommend that adults be purposefully active for at least 150 minutes per week for overall health and wellness. One proven strategy to make sure you reach your activity goal is to track your energy expenditure. This 3-page fact sheet explains the different free and low cost cell phone apps, websites, and portable devices available for tracking physical activity. Written by Madison K. Keesling and Anne E. Mathews, and published by the Food Science and Human Nutrition Department, August 2016.

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Korzh, Nataliya, Liudmyla Shuba et Victoria Shuba. « Physical Activity as an Aspect of Students’ Social and Educational Life ». Bulletin of Luhansk Taras Shevchenko National University, n^o 3 (351) (2022) : 201–11. http://dx.doi.org/10.12958/2227-2844-2022-3(351)-201-211.

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Education – education and upbringing – is the most noble and responsible sphere of human activity precisely because here a person is formed as a person, his/her world outlook and culture are intertwined, the foundations of future profession, career, life success are laid. The rapid development of the modern world, of course, influences the character of the mental work of the individual and requires constant improvement of mental abilities, skills and skills aimed at productive work of the human brain in order to create innovative ideas, projects. But at the same time, a decrease in physical activity has a negative impact on mental activity, attitudes towards personal and social life position, and reduces the quality of life, both social and personal. Material and methods. The purpose of the study – to analyze the impact of exercising on the social and educational activity of life of modern student youth. The study involved 337 students of different sexes from the National University of Zaporizhia Polytechnic who were divided into two groups: the first group Physically Passive Group – 153 students who never visited fitness centers and did not exercise independently for the purpose of additional physical education; second Physical Activity Group – 184 students who regularly exercise independently or regularly visit fitness centers and other sports sections. Conclusion: Based on the above, we draw attention to the fact that students in both the physically active and the physically passive groups have a strong desire for material support and good health. But at the same time, students belonging to Physically Passive Group have little motivation to make any effort to achieve their goals.

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Zhang, Mei Heng, Hai Peng Wang et Qin You Yang. « Physical Classroom System "Human - Human" Interactive Equipment Design ». Advanced Materials Research 664 (février 2013) : 1133–38. http://dx.doi.org/10.4028/www.scientific.net/amr.664.1133.

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Physics classroom teaching "human-human" interactive technology is research to realize participate in the teaching activity of teachers and students and students and students interaction between feedback system and how to use the feedback system realize effective interaction method, research and development based on the WiFi technology suitable for physical science classroom feedback system, this paper discusses the use of the feedback system realize effective interaction method.

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Harridge, Stephen D. R., et Norman R. Lazarus. « Physical Activity, Aging, and Physiological Function ». Physiology 32, n^o 2 (mars 2017) : 152–61. http://dx.doi.org/10.1152/physiol.00029.2016.

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Human evolution suggests that the default position for health is to be physically active. Inactivity, by contrast, has serious negative effects on health across the lifespan. Therefore, only in physically active people can the inherent aging process proceed unaffected by disuse complications. In such individuals, although the relationship between age and physiological function remains complex, function is generally superior with health, well being, and the aging process optimized.

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Kurita, Koichi. « Human Physical Activity Measurement Method Based on Electrostatic Induction ». Journal of Sensor Technology 04, n^o 03 (2014) : 139–47. http://dx.doi.org/10.4236/jst.2014.43013.

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Paraschiv-Ionescu, Anisoara, Christophe Perruchoud, Eric Buchser et Kamiar Aminian. « Barcoding Human Physical Activity to Assess Chronic Pain Conditions ». PLoS ONE 7, n^o 2 (23 février 2012) : e32239. http://dx.doi.org/10.1371/journal.pone.0032239.

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Miller, Benjamin F. « Human Muscle Protein Synthesis After Physical Activity and Feeding ». Exercise and Sport Sciences Reviews 35, n^o 2 (avril 2007) : 50–55. http://dx.doi.org/10.1097/jes.0b013e31803eac78.

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Fried, Linda P. « Interventions for Human Frailty : Physical Activity as a Model ». Cold Spring Harbor Perspectives in Medicine 6, n^o 6 (3 mai 2016) : a025916. http://dx.doi.org/10.1101/cshperspect.a025916.

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Sherar, Lauren B., et Sean P. Cumming. « Human biology of physical activity in the growing child ». Annals of Human Biology 47, n^o 4 (18 mai 2020) : 313–15. http://dx.doi.org/10.1080/03014460.2020.1816934.

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Martin, Alan D., et Enid Brown. « The effects of physical activity on the human skeleton ». Topics in Geriatric Rehabilitation 4, n^o 2 (janvier 1989) : 25–36. http://dx.doi.org/10.1097/00013614-198901000-00006.

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Doppelmayr, M., P. Sauseng et H. Doppelmayr. « Modifications in the human EEG during extralong physical activity ». Neurophysiology 39, n^o 1 (janvier 2007) : 76–81. http://dx.doi.org/10.1007/s11062-007-0011-z.

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POSASHKOVA, Oksana Yurievna, et Yulia Ivanovna SAVINA. « THE EFFECT OF PHYSICAL EXERCISE ON HUMAN BRAIN ACTIVITY ». Актуальные исследования, n^o 42 (2022) : 152–54. http://dx.doi.org/10.51635/27131513_2022_42_152.

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Dustman, Robert E., Rita Emmerson et Donald Shearer. « Physical Activity, Age, and Cognitive-Neuropsychological Function ». Journal of Aging and Physical Activity 2, n^o 2 (avril 1994) : 143–81. http://dx.doi.org/10.1123/japa.2.2.143.

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Findings from three research paradigms that employed aerobic exercise as an independent variable were used to test the hypothesis that aerobic exercise improves cognitive-neuropsychological functioning. The research paradigms were animal intervention studies, cross-sectional human studies, and human intervention studies. Results from studies of animals, usually rodents, provide consistent evidence that aerobic fitness is associated with improved neurobiological and behavioral functioning. Cross-sectional studies with humans indicate a strong positive association between physical activity level and cognitive-neuropsychological performance. However, results from these studies must be interpreted cautiously, as individuals who elect to exercise or not exercise may differ on other variables that could influence cognitive-neuropsychological performance. To date, human intervention studies have not consistently demonstrated cognitive-neuropsychological improvements following exercise training. To satisfactorily test the exercise/cognition hypothesis with humans, carefully controlled intervention studies that last longer than those previously employed are needed.

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Bhardwaj, Rashmi, et Aashima Bangia. « Dynamical Indicator of Human Body’s Physical Endurance ». Nepal Journal of Mathematical Sciences 2, n^o 1 (30 avril 2021) : 25–34. http://dx.doi.org/10.3126/njmathsci.v2i1.36561.

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Physical endurance is the time span between the beginning of physical activity by an individual and the termination because of exhaustion. Physical endurance involves a multifaceted behaviour which can be understood by complexities. Everyone performs physical activity in order to sustain-life. However, the number of activities done are largely subject to personal choice and varies from person to person as well as for a given person over time. Physical activity like meditation/exercises are positively related to physical fitness. One needs to understand relation between physical activity, exercise, physical fitness and health. These activities can be partitioned mutually exclusively into many different ways. This paper categorizes daily physical activity into three broad subdivisions based on amount of body movements taking place are: (i) light, (ii) moderate and (iii) high intensity. These three characterizations are considered to be mutually exclusive and sum up to total energy spent by an individual. The behavior of the three factors physical activity, heart and energy generated is analyzed with the help of Fast Lyapunov indicator (FLI), Dynamic Lyapunov indicator (DLI), Small alignment index (SALI). FLI’s increase for chaotic orbits for values of R=20, Q=70 for the case of high intensity exercises and to linearly regular orbits for values of R=5, Q=8 and R=10, Q=12 in the cases of light and moderate exercises respectively. SALI’s alters through non-zero value for R=20, Q=70 while it tends to zero for values of R=5, Q=8 and R=10, Q=12. DLI’s the largest Eigen values form a definite pattern/curve for n=2000 for values of R=5, Q=8 and n=100 for R=10, Q=12 respectively as the motion stays regular plus dispersed randomly as the motion is chaotic for n=60 and for R=20, Q=70.

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Guieu, Régis, Olivier Blin, Jean Pouget et Georges Serratrice. « Nociceptive Threshold and Physical Activity ». Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 19, n^o 1 (février 1992) : 69–71. http://dx.doi.org/10.1017/s0317167100042566.

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ABSTRACT:Previous studies using subjective tools to measure pain have shown that muscle exercise can have analgesic effects in man. The nociceptive leg flexion reflex (or RIII reflex) is a useful objective tool for assessing human pain. In this study, the pain threshold was assessed using the nociceptive flexion reflex in six high-level athletes 1) at rest in comparison with 8 control subjects and 2) after exercise requiring the production of a 200-Watt force over a period of 20 minutes. The nociceptive flexion reflex threshold at rest was found to be spontaneously higher in the athletes than in the controls. Physical activity resulted in a significant increase (+53%) in the threshold of the nociceptive reflex in the athletes. The role of stress-induced analgesia, the reduction in perceived intensity of stimuli during movement, and the release of opioids are discussed.

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KOZACHUK, Irina V. « PHYSICAL ACTIVITY AND HEALTHY LIFESTYLE ». Medicine and Physical Education : Science and Practice, n^o 8 (2020) : 52–58. http://dx.doi.org/10.20310/2658-7688-2020-2-4(8)-52-58.

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We justified the need to understand the significance of physical education and sport for a person. Every person wants to live his life happily ever after. Therefore, everything must be done to maintain health until it is too late. Usually, due to the wrong lifestyle, a person has poor health, nervous disorders, diseases. Does a person do everything possible to maintain his health? Many diseases can be avoided if you properly build your lifestyle. Sport and physical education are not only a healthy lifestyle, but in general a normal and healthy life, which opens up more and more opportunities for the realization of forces and talents. We considered the issue of the importance of physical activity in human life, preservation and promotion of health. We discussed the problems of a sedentary lifestyle. We analyzed the need to preserve and promote health through physical activity.

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Gravina, Raffaele, Congcong Ma, Pasquale Pace, Gianluca Aloi, Wilma Russo, Wenfeng Li et Giancarlo Fortino. « Cloud-based Activity-aaService cyber–physical framework for human activity monitoring in mobility ». Future Generation Computer Systems 75 (octobre 2017) : 158–71. http://dx.doi.org/10.1016/j.future.2016.09.006.

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Pyataeva, Anna V., Mikhail A. Merko, Vladislava A. Zhukovskaya et Alena A. Kazakevich. « RECOGNITION OF HUMAN ACTIVITY BY VIDEO DATA ». International Journal of Advanced Studies 12, n^o 4 (29 décembre 2022) : 96–110. http://dx.doi.org/10.12731/2227-930x-2022-12-4-96-110.

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The paper considers the problem solution of classifying the type of physical activity of a person according to visual data. The authors propose using of deep neural networks to determine the type of activity. The recognizing human activity from video data or a single image systems are currently actively used in various areas of human activity. As the example we can take the system for monitoring the effectiveness of enterprise employees. So solving the problem of recognizing human actions from visual data is an actual task. The authors developed an algorithm for determining the physical activity type by visual data based on the DenseNet121 and MobileNetV2 models. Then the deep neural network model was built and hyperparameters were selected, because pre-trained networks did not provide the required accuracy of detecting the type of physical activity. The software implementation of the model is made in the IDLE environment in the Python programming language. Experimental studies performed on a specialized UCF50 dataset containing 50 different types of human actions confirm the effectiveness of using the proposed approach to solve the problem. Additionally, the representativeness of the test data set was increased with the help of video sequences obtained from YouTube. Purpose – development of an algorithm for determining a person’s physical activity based on visual data. Methodology: in the work the methods of computer vision, deep learning methods and object-oriented programming methods were used. Results: an algorithm for tracking a person’s physical activity based on visual data using deep learning technologies has been developed. Practical implications: the obtained results can be used in human activity monitoring systems, for example, in tracking criminal activity, in medical diagnostics, in tracking the activity of office employees, etc.

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Światowy, Witold Józef, Hanna Drzewiecka, Michalina Kliber, Maria Sąsiadek, Paweł Karpiński, Andrzej Pławski et Paweł Piotr Jagodziński. « Physical Activity and DNA Methylation in Humans ». International Journal of Molecular Sciences 22, n^o 23 (30 novembre 2021) : 12989. http://dx.doi.org/10.3390/ijms222312989.

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Physical activity is a strong stimulus influencing the overall physiology of the human body. Exercises lead to biochemical changes in various tissues and exert an impact on gene expression. Exercise-induced changes in gene expression may be mediated by epigenetic modifications, which rearrange the chromatin structure and therefore modulate its accessibility for transcription factors. One of such epigenetic mark is DNA methylation that involves an attachment of a methyl group to the fifth carbon of cytosine residue present in CG dinucleotides (CpG). DNA methylation is catalyzed by a family of DNA methyltransferases. This reversible DNA modification results in the recruitment of proteins containing methyl binding domain and further transcriptional co-repressors leading to the silencing of gene expression. The accumulation of CpG dinucleotides, referred as CpG islands, occurs at the promoter regions in a great majority of human genes. Therefore, changes in DNA methylation profile affect the transcription of multiple genes. A growing body of evidence indicates that exercise training modulates DNA methylation in muscles and adipose tissue. Some of these epigenetic markers were associated with a reduced risk of chronic diseases. This review summarizes the current knowledge about the influence of physical activity on the DNA methylation status in humans.

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Siahaan, Paulus Parholong, Bambang Purwanto, Raden Mohammad Budiarto et Irfiansyah Irwadi. « Physical Activity Level and Resting Heart Rate ». Jurnal Ilmiah Kesehatan 3, n^o 1 (30 avril 2021) : 181–87. http://dx.doi.org/10.36590/jika.v3i1.103.

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Human life quality is related to the density of daily physical activity. Human diseases are related to how many steps to take within a day. The level of human physical activity can be measured using the IPAQ scoring protocol, created by WHO in 1988. The relationship between IPAQ score and health problems show to be correlated. Nevertheless, the relationship between the level of physical activity using the IPAQ score instrument and resting heart rate is not known yet. This researcher conducted this study to determine the relationship between physical activity level using the IPAQ scoring protocol and rest heart rate. This study is an observative analytic with a cross-sectional study design using a simple random sampling technique. This study was conducted in Surabaya from November 2019 until March 2020 using primary data in the form of the IPAQ scoring method and resting heart rate examination using the Polar Heart Rate tool, which is then processed using IBM SPSS Statistics 22. The IPAQ score and resting heart rate measurement results using polar heart rate tools showed that the most college student has a high degree of physical activity level (72%) and a normal level of resting heart rate (90%). When measured with the Pearson correlation test, the correlation of those two components has a negative and weak correlation (r= -0,337, p<0,05). Overall, the correlation of physical activity level and resting heart rate are inverted and weak. For further research can be done to assess other things like one’s external stressors and lifestyle.

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Pišot, Rado. « Physical inactivity – The human health’s greatest enemy ». Slovenian Journal of Public Health 61, n^o 1 (27 décembre 2021) : 1–5. http://dx.doi.org/10.2478/sjph-2022-0002.

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Abstract For decades, research has been highlighting the positive impact of physical activity on health. Despite the immense efforts made by many professional and scientific organizations to raise individual and societal awareness about the role of a sufficient quantity and intensity of physical activity in everyday life and to increase the level of adherence, the situation is still very worrying. Even more worrying is the fact that increasingly prolonged periods of physical inactivity are insidiously and aggressively taking over modern people’s lives – at school, at work, at home, even at leisure. It is probably incomprehensible and difficult for many to accept, but physical inactivity is becoming the first and worst enemy of health in today’s society.

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Turk, James R., et M. Harold Laughlin. « Physical Activity and Atherosclerosis : Which Animal Model ? » Canadian Journal of Applied Physiology 29, n^o 5 (1 octobre 2004) : 657–83. http://dx.doi.org/10.1139/h04-042.

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Atherosclerosis is a progressive disease that is the most important single contributor to human cardiovascular morbidity and mortality. Epidemiologic studies show that physical activity, or routine exercise, reduces the risk of developing cardiovascular disease. The mechanisms through which exercise may function in primary or secondary prevention of atherosclerosis remain largely to be established. Most studies in humans are performed after the onset of clinical signs when disease is well advanced and the prescription of exercise is based on empirical evidence of benefit in secondary prevention. Animal models permit the study of the initiation and progression of preclinical stages of atherosclerosis. In order to provide information relevant to treatment and prevention, these models should mimic human disease and interactions of physical activity with disease processes as closely as possible. The purpose of this review is to compare animal models of atherosclerosis and to summarize the available data in those models in regard to the effects of exercise. Key words: hypercholesterolemia, exercise, pathology, porcine

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Lensu, Sanna, et Satu Pekkala. « Gut Microbiota, Microbial Metabolites and Human Physical Performance ». Metabolites 11, n^o 11 (21 octobre 2021) : 716. http://dx.doi.org/10.3390/metabo11110716.

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Trillions of microbes inhabiting the gut modulate the metabolism of the host. Cross-sectional studies have reported associations between physical performance and the gut microbiota (GM). Physical activity seems to increase GM diversity and the abundance of certain health-beneficial microbes. We reviewed the evidence from longitudinal studies on the connection between physically active lifestyle or long-term exercise interventions and the GM. We made literature searches using databases of Web of Science and PubMed Medline to collect human studies showing or not the associations between the GM and exercise. Many controversies exist in the studies. However, the longitudinal studies show that frequently, medium-intensity endurance exercise has yielded most beneficial effects on the GM, but the results vary depending on the study population and exercise protocol. In addition, the literature shows that certain microbes own the potency to increase physical activity and performance. Generally, a physically active lifestyle and exercise associate with a “healthy” GM. However, in previously sedentary subjects, the exercise-induced improvements in the GM seem to disappear unless the active lifestyle is continued. Unfortunately, several studies are not controlled for the diet. Thus, in the future, more longitudinal studies on the GM and physical performance are needed, with detailed dietary information.

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Sato, Takeshi, Masami Miyazaki et Kazuyoshi Seki. « Analysis of physical activity and human movement on GPS receiver. » Japanese journal of ergonomics 34, Supplement (1998) : 306–7. http://dx.doi.org/10.5100/jje.34.supplement_306.

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Henderson, Karla A., et Barbara E. Ainsworth. « Physical Activity and Human Development among Older Native American Women ». Journal of Aging and Physical Activity 9, n^o 3 (juillet 2001) : 285–99. http://dx.doi.org/10.1123/japa.9.3.285.

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Physical activity involvement often changes as an individual gets older. The purpose of this cross-sectional study was to explore the involvement in and meanings of physical activity from childhood to the present among a selected group of Native American women. The results showed that perceived meanings of physical activity remained relatively stable over the lives of these women. Two patterns of involvement emerged among the women: decliners and rejuvenators. The results suggested that physical activity as women aged was a result not of choice as often as of a life situation. Furthermore, the changes occurring in physical activity over the life course reflected social and cultural influences, as well as individual self-determination. The findings indicated that a variety of perspectives are needed if researchers are to understand the changes that occur in physical activity patterns and how both women and men of all ethnic groups might remain involved in physical activity throughout their lives.

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Wright, Stephen P., Tyish S. Hall Brown, Scott R. Collier et Kathryn Sandberg. « How consumer physical activity monitors could transform human physiology research ». American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 312, n^o 3 (1 mars 2017) : R358—R367. http://dx.doi.org/10.1152/ajpregu.00349.2016.

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A sedentary lifestyle and lack of physical activity are well-established risk factors for chronic disease and adverse health outcomes. Thus, there is enormous interest in measuring physical activity in biomedical research. Many consumer physical activity monitors, including Basis Health Tracker, BodyMedia Fit, DirectLife, Fitbit Flex, Fitbit One, Fitbit Zip, Garmin Vivofit, Jawbone UP, MisFit Shine, Nike FuelBand, Polar Loop, Withings Pulse O2, and others have accuracies similar to that of research-grade physical activity monitors for measuring steps. This review focuses on the unprecedented opportunities that consumer physical activity monitors offer for human physiology and pathophysiology research because of their ability to measure activity continuously under real-life conditions and because they are already widely used by consumers. We examine current and potential uses of consumer physical activity monitors as a measuring or monitoring device, or as an intervention in strategies to change behavior and predict health outcomes. The accuracy, reliability, reproducibility, and validity of consumer physical activity monitors are reviewed, as are limitations and challenges associated with using these devices in research. Other topics covered include how smartphone apps and platforms, such as the Apple ResearchKit, can be used in conjunction with consumer physical activity monitors for research. Lastly, the future of consumer physical activity monitors and related technology is considered: pattern recognition, integration of sleep monitors, and other biosensors in combination with new forms of information processing.

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Smallwood, Nicola, Meg J. Spriggs, Christopher S. Thompson, Carolyn C. Wu, Jeff P. Hamm, David Moreau et Ian J. Kirk. « Influence of Physical Activity on Human Sensory Long-Term Potentiation ». Journal of the International Neuropsychological Society 21, n^o 10 (novembre 2015) : 831–40. http://dx.doi.org/10.1017/s1355617715001095.

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AbstractA growing body of literature has explored the influence of physical activity on brain structure and function. While the mechanisms of this relationship remain largely speculative, recent research suggests that one of the effects of physical exercise is an increase in synaptic long-term potentiation (LTP). This has not yet been explored directly in humans due to the difficulty of measuring LTP non-invasively. However, we have previously established that LTP-like changes in visual-evoked potentials (VEPs) can be measured in humans. Here, we investigated whether physical fitness status affects the degree of visual sensory LTP. Using a self-report measure of physical activity, participants were split into two groups: a high-activity group, and a low-activity group. LTP was measured and compared between the two groups using the previously established electroencephalography-LTP paradigm, which assesses the degree to which the N1b component of the VEP elicited by a sine grating is potentiated (enhanced) following a rapid “tetanic” presentation of that grating. Both groups demonstrated increased negativity in the amplitude of the N1b component of the VEP immediately after presentation of the visual “tetanus,” indicating potentiation. However, after a 30-min rest period, the N1b for the high-activity group remained potentiated while the N1b for the low-activity group returned to baseline. This study presents the first evidence for the impact of self-reported levels of physical activity on LTP in humans, and sheds light on potential neurological mechanisms underlying the relationship between physical fitness and cognition. (JINS, 2015, 21, 831–840)

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Eaton, S. Boyd, et Stanley B. Eaton. « An evolutionary perspective on human physical activity : implications for health ». Comparative Biochemistry and Physiology Part A : Molecular & ; Integrative Physiology 136, n^o 1 (septembre 2003) : 153–59. http://dx.doi.org/10.1016/s1095-6433(03)00208-3.

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