PDF(Pubmed)
Abstract：
(1) Background: This study aims to investigate the correlation between heart rate variability (HRV) during exercise and recovery periods and the levels of anxiety and depression among college students. Additionally, the study assesses the accuracy of a multilayer perceptron-based HRV analysis in predicting these emotional states. (2) Methods: A total of 845 healthy college students, aged between 18 and 22, participated in the study. Participants completed self-assessment scales for anxiety and depression (SAS and PHQ-9). HRV data were collected during exercise and for a 5-min period post-exercise. The multilayer perceptron neural network model, which included several branches with identical configurations, was employed for data processing. (3) Results: Through a 5-fold cross-validation approach, the average accuracy of HRV in predicting anxiety levels was 89.3% for no anxiety, 83.6% for mild anxiety, and 74.9% for moderate to severe anxiety. For depression levels, the average accuracy was 90.1% for no depression, 84.2% for mild depression, and 82.1% for moderate to severe depression. The predictive R-squared values for anxiety and depression scores were 0.62 and 0.41, respectively. (4) Conclusions: The study demonstrated that HRV during exercise and recovery in college students can effectively predict levels of anxiety and depression. However, the accuracy of score prediction requires further improvement. HRV related to exercise can serve as a non-invasive biomarker for assessing psychological health.
摘要：
（1）背景：本研究旨在调查运动和恢复期心率变异性（HRV）与大学生焦虑和抑郁水平之间的相关性。此外,该研究评估了基于多层感知器的HRV分析预测这些情绪状态的准确性.(2)方法:845名健康大学生,年龄在18至22岁之间，参与了这项研究。参与者完成了焦虑和抑郁自评量表（SAS和PHQ-9）。在运动期间和运动后5分钟内收集HRV数据。多层感知器神经网络模型,其中包括几个具有相同配置的分支，用于数据处理。(3)结果：通过5倍交叉验证方法，HRV预测焦虑水平的平均准确率为89.3%，83.6%为轻度焦虑，中度至重度焦虑为74.9%。对于抑郁水平，没有抑郁的平均准确率为90.1%，84.2%为轻度抑郁症，中度至重度抑郁症为82.1%。焦虑和抑郁评分的R平方预测值分别为0.62和0.41。(4)结论:研究表明,大学生运动和恢复过程中的HRV能有效预测焦虑和抑郁水平。然而,分数预测的准确性需要进一步提高。与运动相关的HRV可以作为评估心理健康的非侵入性生物标志物。
