Perceived mental stress and reactions in heart rate variability--a pilot study among employees of an electronics company.

In this study perceived mental stress during occupational work was compared to heart rate variability (HRV) using a traditional questionnaire and a novel wristop heart rate monitor with related software. The aim was to find HRV parameters useful for mental stress detection. We found the highest correlation between perceived mental stress with the differences between the values of triangular interpolation of rhythm-to-rhythm (RR) interval histogram (TINN) and the root mean square of differences of successive RR intervals (RMSSD) obtained in the morning and during the workday (r=-.73 and r=-.60, respectively). The analysis shows that as the RMSSD and TINN value differences increase from night to morning, the stress decreases.

Heart rate variability derived from exercise ECG in the detection of coronary artery disease.

The diagnostic performance of heart rate variability (HRV) analysis from exercise ECG in the detection of coronary artery disease (CAD) is unknown. Bicycle exercise ECG recordings from The Finnish Cardiovascular Study (FINCAVAS) of angiography-proofed CAD patients (n = 112) and a patient group with a low likelihood of CAD (n = 114) were analyzed. HRV parameters (SDNN, RMSSD, Poincaré SD1 and SD2) were calculated from 1 min segments before exercise, during exercise and after exercise. All the parameters were in addition calculated from heart rate (HR)-corrected RR-interval segments. The ST-segment depressions in each stage were also determined. The diagnostic performance of the parameters was evaluated with the area under the receiver operating characteristic (ROC) curve method. The uncorrected HRV parameters showed the best diagnostic performance in the recovery segments but the correlation with HR was also high (SDNN: 0.758/-0.64, RMSSD: 0.747/-0.60; area under the ROC/correlation coefficient). The HR correction decreased the correlation and the diagnostic performance in recovery segments (SDNN: 0.515/-0.12, RMSSD: 0.609/0.20). The diagnostic performance of ST-level at its best was higher than any of HRV parameters (ST-level: 0.795/0.36). According to the results, the HR correction decreased the diagnostic performance of the recovery phase. The HRV parameters calculated from 1 min segments of exercise test ECG were not as capable as traditional ST-segment analysis. In conclusion, the HRV analysis from exercise or recovery phase seems to be inadequate in the detection of CAD.