Department of Biomedical and Chemical Engineering and SciencesFlorida Institute of Technology Melbourne FL 32901 USA.
Department of Electrical and Computer EngineeringKing Abdulaziz University Jeddah 21589 Saudi Arabia.
IEEE J Transl Eng Health Med. 2021 Aug 23;9:2700607. doi: 10.1109/JTEHM.2021.3106803. eCollection 2021.
Stress is a significant risk factor for various diseases such as hypertension, heart attack, stroke, and even sudden death. Stress can also lead to psychological and behavioral disorders. Heart rate variability (HRV) can reflect changes in stress levels while other physiological factors, like blood pressure, are within acceptable ranges. Electroencephalogram (EEG) is a vital technique for studying brain activities and provides useful data regarding changes in mental status. This study incorporates EEG and a detailed HRV analysis to have a better understanding and analysis of stress. Investigating the correlation between EEG and HRV under stress conditions is valuable since they provide complementary information regarding stress.
Simultaneous electrocardiogram (ECG) and EEG recordings were obtained from fifteen subjects. HRV /EEG features were analyzed and compared in rest, stress, and meditation conditions. A one-way ANOVA and correlation coefficient were used for statistical analysis to explore the correlation between HRV features and features extracted from EEG.
The HRV features LF (low frequency), HF (high frequency), LF/HF, and rMSSD (root mean square of the successive differences) correlated with EEG features, including alpha power band in the left hemisphere and alpha band power asymmetry.
This study demonstrated five significant relationships between EEG and HRV features associated with stress. The ability to use stress-related EEG features in combination with correlated HRV features could help improve detecting stress and monitoring the progress of stress treatments/therapies. The outcomes of this study could enhance the efficiency of stress management technologies such as meditation studies and bio-feedback training.
压力是各种疾病的重要危险因素，如高血压、心脏病发作、中风，甚至猝死。压力还会导致心理和行为障碍。心率变异性（HRV）可以反映压力水平的变化，而其他生理因素，如血压，在可接受的范围内。脑电图（EEG）是研究大脑活动的重要技术，提供有关精神状态变化的有用数据。本研究结合 EEG 和详细的 HRV 分析，更好地理解和分析压力。研究应激条件下 EEG 和 HRV 之间的相关性很有价值，因为它们提供了有关压力的补充信息。
从 15 名受试者中同时获得心电图（ECG）和脑电图记录。在休息、应激和冥想条件下分析和比较 HRV/EEG 特征。使用单向方差分析和相关系数进行统计分析，以探讨 HRV 特征与从 EEG 中提取的特征之间的相关性。
HRV 特征 LF（低频）、HF（高频）、LF/HF 和 rMSSD（连续差异的均方根）与 EEG 特征相关，包括左半球的 alpha 功率带和 alpha 频带功率不对称。
本研究表明，与应激相关的 EEG 特征与 HRV 特征之间存在五种显著关系。利用与应激相关的 EEG 特征与相关 HRV 特征相结合的能力可以帮助提高检测应激和监测应激治疗/疗法进展的能力。本研究的结果可以提高冥想研究和生物反馈训练等应激管理技术的效率。
