Key result
Ultra-short-term HRV analysis (under 5 min) achieved a classification accuracy of 90.5% for detecting acute mental stress, compared to 86.5% for short-term HRV analysis (5 min).
Why the study?
Mental stress is an increasing major health problem, and detecting and managing it is important to prevent stress-related diseases.
Can ultra-short-term HRV analysis accurately detect acute mental stress in young police officers?
Observational (n=74)
Can ultra-short-term HRV analysis accurately detect acute mental stress in young police officers?
Absolute Event Rate: 90.5% vs 86.5%
Ultra-short-term HRV analysis using empirical mode decomposition and SVM classification can accurately detect acute mental stress, suggesting potential applications for wearable devices.
New EMD-based HRV features may enable ultra-short stress detection; leaves open validation and clinical adoption.
Mental stress is on the rise as one of the major health problems in modern society. It is important to detect and manage mental stress to prevent various diseases caused by stress and to maintain a healthy life. The purpose of this paper is to present new heart rate variability (HRV) features based on empirical mode decomposition and to detect acute mental stress through short-term HRV (5 min) and ultra-short-term HRV (under 5 min) analysis. HRV signals were acquired from 74 young police officers using acute stressors, including the Trier Social Stress Test and horror movie viewing, and a total of 26 features, including the proposed IMF energy features and general HRV features, were extracted. A support vector machine (SVM) classification model is used to classify the stress and non-stress states through leave-one-subject-out cross-validation. The classification accuracies of short-term HRV and ultra-short-term HRV analysis are 86.5% and 90.5%, respectively. In the results of ultra-short-term HRV analysis using various time lengths, we suggest the optimal duration to detect mental stress, which can be applied to wearable devices or healthcare systems.
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Lee et al. (2022) conducted an observational in Acute mental stress (n=74). Ultra-short-term HRV analysis (under 5 min) vs. Short-term HRV analysis (5 min) was evaluated on Classification accuracy of stress and non-stress states using a support vector machine model. Ultra-short-term HRV analysis (under 5 min) achieved a classification accuracy of 90.5% for detecting acute mental stress, compared to 86.5% for short-term HRV analysis (5 min).
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