Monitoring and Health Evaluation of Fitness Qigong Training Effect Based on Embedded System

This study analyzes the biomechanical and physiological responses to Qigong training. It uses an embedded real-time monitoring system. High-resolution motion analysis, real-time data processing, and performance indices were employed to evaluate training effects. Three custom metrics — Motion Consistency Score (MCS), Energy Efficiency Index (EEI), and Joint Stability Coefficient (JSC) — were proposed. This was to assess movement precision, energy efficiency, and joint control. Advanced statistical methods; Canonical Correlation Analysis (CCA), Dynamic Time Warping (DTW), and Granger Causality Analysis, were applied, majorly to explore the relationships between physical movements and physiological responses like heart rate variability and muscle activation. Results demonstrate consistent improvements in motion patterns, energy expenditure, and joint kinematics across training sessions. These findings suggest that Fitness Qigong not only enhances athletic performance but also provides long-term benefits to cardiovascular, neuromuscular, and overall health. The study presents a robust, evidence-based framework for evaluating Qigong’s therapeutic potential in modern health paradigms.

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Publication Details

Journal
International Journal of High Speed Electronics and Systems
Published
2025-07-19
DOI
https://doi.org/10.1142/s0129156425500107
Citations
2
Primary Topic
Biofield Effects and Biophysics
Type
article
Field-Weighted Citation Impact
2.33
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article

Monitoring and Health Evaluation of Fitness Qigong Training Effect Based on Embedded System

Chun-Yu He
2 citations
International Journal of High Speed Electronics and Systems
Biofield Effects and Biophysics
2.33
article

Monitoring and Health Evaluation of Fitness Qigong Training Effect Based on Embedded System

Chun-Yu He
article en
2 citations

Abstract

This study analyzes the biomechanical and physiological responses to Qigong training. It uses an embedded real-time monitoring system. High-resolution motion analysis, real-time data processing, and performance indices were employed to evaluate training effects. Three custom metrics — Motion Consistency Score (MCS), Energy Efficiency Index (EEI), and Joint Stability Coefficient (JSC) — were proposed. This was to assess movement precision, energy efficiency, and joint control. Advanced statistical methods; Canonical Correlation Analysis (CCA), Dynamic Time Warping (DTW), and Granger Causality Analysis, were applied, majorly to explore the relationships between physical movements and physiological responses like heart rate variability and muscle activation. Results demonstrate consistent improvements in motion patterns, energy expenditure, and joint kinematics across training sessions. These findings suggest that Fitness Qigong not only enhances athletic performance but also provides long-term benefits to cardiovascular, neuromuscular, and overall health. The study presents a robust, evidence-based framework for evaluating Qigong’s therapeutic potential in modern health paradigms.

International Journal of High Speed Electronics and SystemsVol. 35(02)
Pingdingshan University (CN)
Openalex Percentile: Top 11%
Biofield Effects and Biophysics
2.33
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