Acute mental stress assessment via short term HRV analysis in healthy adults : a systematic review with meta-analysis

TLDR: HRV resulted significantly depressed during mental stress, showing a reduced variability and less chaotic behaviour, and the method proposed to transform and then meta-analyze the HRV measures can be applied to other fields where HRV proved to be clinically significant.

About: This article is published in Biomedical Signal Processing and Control.The article was published on 2015-04-01 and is currently open access. It has received 296 citations till now. The article focuses on the topics: Heart rate variability & Population.

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Table 6: Pooled HRV measures

Table 1: Characteristics of studies.

Table 5: Non-linear features

Table 2: Description of study design

Table 3: Time domain features

Frequently asked questions

Q1. What was the task for naming the colour words on a screed?

The task required naming the ink colour in which colours’ names were printed on a screed being either congruent or incongruent with respect to the colour words. 

Q2. How many studies used NPST to investigate how HRV measures changed before and after the stress?

Nine studies [1, 6, 12-14, 16, 17, 19, 20] used ANOVA, ANCOVA or t-student test to investigate how HRV measures changed before and after the stress section. 

Q3. How did the proposed model achieve accuracy, sensitivity and specificity?

The proposed model achieved accuracy, sensitivity and specificity respectively of 90%, 86% and 95% in automatically detecting subjects under stress. 

Q4. What are the main criteria for the analysis of HRV measures?

2.4. HRV measuresRegarding linear HRV measures in time and frequency domains, the recommendations of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology guidelines [9]were followed. 

Q5. How many studies used NPST to investigate how the frequency domain HRV measures changed?

Of these, Traina et al., Papousek et al., and Lackener et al. [12, 13, 15] converted frequencies domain HRV features with a log transform, while the remaining applied directly standard statistical significance tests to frequency domain measures, which are not normally distributed, being asymmetric distributions of positive numbers [21, 22]. 

Q6. What is the reason for the p-value difference?

Since the p-value is strongly dependent by the sample size, a possible explanation is that the number of volunteers enrolled in each of those 6 studies was too small compared with the LF/HF mean differences measured, which, in turn, were too small compared with the standard deviations measured in each group during stress and rest [24]. 

Q7. How many measures of the LF and HF were pooled during stress?

the results of the pooling of the HRV measures, provided pivot values for at least 7 HRV measures that changed significantly during stressing sections. 

Q8. What percentage of the study heterogeneity is considered low, medium, and high?

Percentages of around 25% (I2 = 25), 50% (I2 = 50), and 75% (I2 = 75) may be interpreted as low, medium, and high heterogeneity, respectively [25]. 

Q9. How many subjects were enrolled in this study?

The 12 studies enrolled from 12 to 399 subject each, for a cumulative population of 785 subjects, which was finally pooled in this review. 

Q10. What is the result of the pooled values of HRV frequency measures?

This is consistently confirmed by pooled values of HRV frequency measures, among which HF was proved to decrease significantly, reflecting a decreased HRV variability.