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37. Effects of 3‐month Qigong exercise on heart rate variability and respiration in anxious college students.

Author

Sun, Jingyu, Zhuo, Jiatong, Chu, Hang, Wang, Jing, Chen, Tao, Li, Bin, Lu, Tianfeng, Zheng, Hao, Xu, Yaning, Dong, Jingmei, and Cicchella, Antonio

Subjects
ANXIETY prevention, PSYCHOLOGY of college students, QI gong, TREATMENT effectiveness, RANDOMIZED controlled trials, HEART beat, DESCRIPTIVE statistics, RESEARCH funding, QUESTIONNAIRES, RESPIRATION, STATISTICAL sampling, MIND & body therapies, LONGITUDINAL method, EVALUATION
Abstract

Objective: This longitudinal study aimed to investigate the effects of Qigong on the anxiety state, heart rate variability (HRV), and breathing of anxious college students. Methods: A total of 37 individuals (18–25 years old) were randomly allocated to the control (n = 19) and intervention (n = 18) groups. Qigong interventions were conducted five times weekly for 12 weeks, with each session lasting 60 min. Hamilton Anxiety Scale, Fatigue Scale 14, Pittsburgh Sleep Quality Index, and 36‐item Short Form Survey, HRV, and respiration data were collected before and after the 3‐month intervention. Results: Individuals who participated in the three‐month Qigong exercise intervention showed a significant reduction in anxiety, particularly mental anxiety (p < 0.05). Subjects in the intervention group presented a decrease in skin temperature (p < 0.05) and an increase in blood volume pulsation (p < 0.05). Meanwhile, HRV exhibited a significant increase in the standard deviation of interbeat interval before and after comparisons (p < 0.05) and between the two groups (p = 0.039) and a reduction in the normalized low‐frequency power after the intervention. Moreover, the intervention group experienced increased abdominal breathing depth and abdominal breathing per minute (p < 0.05). Conclusion: These findings indicate that Qigong is an effective mind–body exercise strategy for relieving anxiety. HRV and breathing were improved accordingly among college students after the completion of the 3‐month Qigong program. [ABSTRACT FROM AUTHOR]

Published
2024
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46. Toward Unified and Quantitative Cinematic Shot Attribute Analysis.

Author

Li, Yuzhi, Tian, Feng, Xu, Haojun, and Lu, Tianfeng

Subjects
TRANSFORMER models, OPTICAL flow, ARCHITECTURAL design, TASK analysis, DEEP learning
Abstract

Cinematic Shot Attribute Analysis aims to analyze the intrinsic attributes of movie shots, such as movement and scale. In previous methods, specialized architectures were designed for each specific task and relied on the use of optical flow maps. In this paper, we consider shot attribute analysis as a unified task of motion–static weight allocation, and propose a motion–static dual-path architecture for recognizing various shot attributes. In this architecture, we design a new action cue generation module for adapting the end-to-end training process instead of a pre-trained optical flow network; and, to address the issue of limited samples in movie shot datasets, we design a fixed-size adjustment strategy to enable the network to directly utilize pre-trained vision transformer models while adapting to shot data inputs at arbitrary sample rates. In addition, we quantitatively analyze the sensitivity of different shot attributes to motion and static features for the first time. Subsequent experimental results on two datasets, MovieShots and AVE, demonstrate that our proposed method outperforms all previous approaches without increasing computational cost. [ABSTRACT FROM AUTHOR]

Published
2023
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