Changes in ST, QT and RR ECG intervals during acute stress in firefighters: A pilot study

Abstract

Firefighting is a stressful occupation. The monitoring of psychophysiological measures in those professionals can be a way to prevent and early detect cardiac diseases and other stress-related problems. The current study aimed to assess morphological changes in the ECG signal induced by acute stress. A laboratory protocol was conducted among 6 firefighters, including a laboratory stress-inducer task - the Trier Social Stress Task (TSST) - and a 2-choice reaction time task (CRTT) that was performed before (CRTT1) and after (CRTT2) the stress condition. ECG signals were continuously acquired using the VitalJacket®, a wearable t-shirt that acts as a medical certified ECG monitor. Results showed that ECG morphological features such as QT and ST intervals are able to differentiate stressful from non stressful events in first responders. Group mean Visual Analogue Scale (VAS) for stress assessment significantly increased after the stress task (TSST), relatively to the end of CRTT2 (after TSST: 4.67±1.63; after CRTT2: 3.17±0.75), a change that was accompanied by a significant increase in group mean QT and ST segments corrected for heart rate during TSST. These encouraging results will be followed by larger studies in order to explore those measures and its physiological impact under realistic environments in a higher scalability.

Beat-to-beat ECG features for time resolution improvements in stress detection

“…The applied laboratory protocol (figure 1) was conducted in a previous study by our laboratory and proved to be a suitable protocol to induce acute stress in FFs [4]. ECG signals were continuously acquired throughout the duration of the experiment (≈ 1 hour) using the VitalJacket [9] (VJ) at 500 Hz from a single lead.…”

“…In this way, simultaneously analyzing subject's perceived stress levels and physiological signals such as electrocardiogram (ECG) in firefighters, is the first step towards a general stress sensing solution, applicable to all contexts [2], [4]. Since acute stress events induce physiological responses by our cardiovascular and neuroendocrine systems, ECGderived features both in time and frequency domains have been widely used for stress monitoring and are highly correlated with subject's stress and arousal state changes [4], [5]. Indeed, numerous authors have been exploring the use of ECG features in a human affect context.…”

“…Recently, we have shown that specific HeartBeat Morphology (HBM) features based on temporal distances between ECG fiducial points are able to differentiate "stressful" from "non stressful" events in Firefighters (FFs), using a laboratory protocol [4] composed by a stress inducer task -the Trier Social Stress Test (TSST [8]). Considering the drawbacks associated to W-HRV features, we decided to compare performance outcomes using W-HRV versus HBM features.…”

“…Based on knowledge of the HBM extraction process, we hypothesized that the use of this method as opposed to the W-HRV method could mitigate some of the drawbacks of W-HRV outlined above. In this paper we therefore examined the extent to which these HBM features are useful in stress event sensing, by conducting the same laboratory protocol used in our past study [4] among 13 firefighters. In order to evaluate these two methods, we utilized automatic algorithms for stress event detection based on Machine Learning techniques.…”

“…Such metrics could be of high importance, since stressful events have been linked to abnormalities in cardiovascular functions (e.g. arrhythmias, cardiomyopathy, etc) in healthy and nonhealthy persons [4], making prompt stress detection very desirable.…”