scholarly journals PSYCHOLOGICAL SKILLS OF TALANTED ATHLETES IN INDIVIDUAL SPORTS IN LATVIA

2019 ◽  
Author(s):  
Dace Eikena ◽  
Keyword(s):  
Psychological Skills ◽  
Individual Sports

scholarly journals Karakteristik psikologis atlet Sea Games Indonesia ditinjau dari jenis cabang olahraga dan jenis kelamin

2018 ◽  
Vol 6 (1) ◽  
pp. 69-76
Author(s):  
Yahya Eko Nopiyanto ◽  
Dimyati Dimyati
Keyword(s):  
Team Sports ◽  
T Test ◽  
Psychological Characteristics ◽  
Survey Method ◽  
Psychological Skills ◽  
Psychological Characteristic ◽  
High Category ◽  
Ex Post ◽  
Ex Post Facto ◽  
Individual Sports

Penelitian ini bertujuan untuk mengungkapkan: (1) karakteristik psikologis atlet SEA Games Indonesia ditinjau dari cabang olahraga individu, (2) ditinjau dari cabang olahraga tim, (3) perbedaan karakteristik psikologis atlet SEA Games Indonesia ditinjau dari cabang olahraga individu berdasarkan jenis kelamin, dan (4) olahraga tim berdasarkan jenis kelamin. Pendekatan penelitian ini adalah ex-post facto. Penelitian ini merupakan penelitian populasi. Semua subjek dalam populasi diikutsertakan dalam penelitian dengan jumlah 273 atlet. Pengumpulan data menggunakan kuesioner The Psychological Skills Inventory for Sports. Teknik analisis data menggunakan independent sample t-test. Hasil penelitian ini menunjukkan bahwa: (1) karakteristik psikologis atlet SEA Games Indonesia ditinjau dari cabang olahraga individu dalam kategori tinggi (2) ditinjau dari cabang olahraga tim dalam kategori tinggi (3) tidak ada perbedaan yang signifikan karakteristik psikologis atlet SEA Games Indonesia ditinjau dari cabang olahraga individu berdasarkan jenis kelamin dengan nilai sig. = 0,092  > 0,05; dan (4) ada perbedaan yang signifikan karakteristik psikologis atlet SEA Games Indonesia ditinjau dari cabang olahraga tim berdasarkan jenis kelamin dengan nilai nilai sig. = 0,000 < 0,05. The psychological characteristics of Indonesian Sea Games athletes in terms of sports and sex AbstractThis research was aimed to investigate : (1) the psychological characteristics of  Indonesian SEA Games athletes in terms of individual sports, (2) in terms of team sports, (3) the psychological characteristic differences of Indonesian SEA Games athletes in terms of individual sports based on sex, and (4) the psychological characteristic differences of  Indonesian SEA Games athletes in terms of team sports based on sex. This research employed the quantitative approach using the survey method with a restrospective causal-comparative design. This research was population research. All subjects in the population were included in this research with a total of 273 athletes. The data were collected using the Psychological Skills Inventory for Sports questionnaire and analyzed using the independent sample t test at. The research findings revealed that: (1) the psychological characteristics of  Indonesian SEA Games athletes in terms of individual sports were in a high category, (2) the psychological characteristics of  Indonesian SEA Games athletes in terms of team sports are in high category, (3) there were no significant differences in the psychological characteristics of  Indonesian SEA Games athletes in terms of individual sports based on sex sig. values = 0.092  > 0.05, and (4) there were significant differences in the psychological characteristics of Indonesian SEA Games athletes in terms of team sports based on sex with sig. values = 0.000 < 0.05.

Internet of things-based smart wearable system to monitor sports person health

2021 ◽  
pp. 1-14
Author(s):  
Fen Li ◽  
Oscar Sanjuán Martínez ◽  
R.S. Aiswarya
Keyword(s):  
Internet Of Things ◽  
Experimental Result ◽  
Wearable System ◽  
Wearable Systems ◽  
Trading Decisions ◽  
Time Basis ◽  
And Performance ◽  
Individual Sports ◽  
Smart Wearable ◽  
The Internet Of Things

BACKGROUND: The modern Internet of Things (IoT) makes small devices that can sense, process, interact, connect devices, and other sensors ready to understand the environment. IoT technologies and intelligent health apps have multiplied. The main challenges in the sports environment are playing without injuries and healthily. OBJECTIVE: In this paper the Internet of Things-based Smart Wearable System (IoT-SWS) is introduced for monitoring sports person activity to improve sports person health and performance in a healthy way. METHOD: Wearable systems are commonly used to capture individual sports details on a real-time basis. Collecting data from wearable devices and IoT technologies can help organizations learn how to optimize in-game strategies, identify opponents’ vulnerabilities, and make smarter draft choices and trading decisions for a sportsperson. RESULTS: The experimental result shows that IoT-SWS achieve the highest accuracy of 98.22% and efficient in predicting the sports person’s health to improve sports person performance reliably.

Psychological behavior signal analysis for sports person during their activity session

2021 ◽  
pp. 1-10
Author(s):  
Guochun Liu ◽  
Jian Zheng ◽  
Lin Jiang ◽  
Karthik Chandran ◽  
Beenu Mago
Keyword(s):  
Heart Rate ◽  
Signal Detection ◽  
Signal Analysis ◽  
Well Being ◽  
Machine Learning Algorithms ◽  
Psychological Skills ◽  
Social Dimensions ◽  
Useful Knowledge ◽  
Structural Problems ◽  
Psychological Behavior

The signal analysis helps us derive useful knowledge from biological processes to analyze, describe, and understand their origin mechanisms. However, biomedical signals are not immune and have time-consuming statistics. The major challenges of signal analysis of sportsperson are reliability and accuracy. Sports psychology uses psychological skills to discuss the optimum success and well-being of sports athletes, the developmental and social dimensions of the sport and sports facilities, and structural problems. The signal detection tool is used to detect the best combination of long-term practice predictors for active, sedentary adults’ signal. This paper proposed the wearable assisted signal detection method (WASDM) to find the sportspersons’ behavior signal analysis. This method performs an IoT based heart rate monitoring using a wearable device named intelligent bracelet mounted on the sportsperson to track the variations in his/her human heart rate. The wearable signal detector method analysis the heart rate abnormality and predicts health status, followed by an alarm to the physician and the respective personnel while performing activity session. In this research, various machine learning algorithms have been tried to perform signal analysis and prediction and compared their results to suggest the best in this application scenario. Finally, the experimental analysis shows better outcomes for the sportspersons’ psychological behavior signal analysis than the conventional methods.

Sign in / Sign up

Export Citation Format

Share Document