Heart and Breathing Rate Variations as Biomarkers for Anxiety Detection

Abstract

With advances in portable and wearable devices, it should be possible to analyze and interpret the collected biosignals from those devices to tailor a psychological intervention to help patients. This study focuses on detecting anxiety by using a portable device that collects electrocardiogram (ECG) and respiration (RSP) signals. The feature extraction focused on heart-rate variability (HRV) and breathing-rate variability (BRV). We show that a significant change in these signals occurred between the non-anxiety-induced and anxiety-induced states. The HRV biomarkers were the mean heart rate (MHR; p¯ = 0.04), the standard deviation of the heart rate (SD; p¯ = 0.01), and the standard deviation of NN intervals (SDNN; p¯ = 0.03) for ECG signals, and the mean breath rate (MBR; p¯ = 0.002), the standard deviation of the breath rate (SD; p¯ < 0.0001), the root mean square of successive differences (RMSSD; p¯ < 0.0001) and SDNN (p¯ < 0.0001) for RSP signals. This work extends the existing literature on the relationship between stress and HRV/BRV by being the first to introduce a transitional phase. It contributes to systematically processing mental and emotional impulse data in humans measured via ECG and RSP signals. On the basis of these identified biomarkers, artificial-intelligence or machine-learning algorithms, and rule-based classification, the automated biosignal-based psychological assessment of patients could be within reach. This creates a broad basis for detecting and evaluating psychological abnormalities in individuals upon which future psychological treatment methods could be built using portable and wearable devices.

The Potential of Heart Rate Variability Monitoring for Mental Health Assessment in Top Wheel Gymnastics Athletes: A Single Case Design

“…In the present study, waking standing RMSSD had a moderate negative linear relationship with K6 and a moderate negative linear relationship with fatigue-Inertia of POMS2. Previous studies have reported that RMSSD decreases during transient anxiety induction (Ritsert et al, 2022). The moderate negative linear relationship between K6 and RMSSD in the present study aligns with previous studies.…”

Sex differences in heart rate variability measures that predict alcohol drinking in rats

“…However, several studies find that briefer analysis windows can provide meaningful findings, and 5 min is often used for a briefer baseline for humans 57 . During different challenges in humans, a 60‐s analysis window was as good as a 5‐min window for SDNN, RMSSD and HR, although with 2 min or more needed for frequency‐domain and more complex analyses 57–60 . Rodent studies have also validated the use of 1‐min HRV analysis windows, 61 including for anxiety‐like tests 54 .…”

“… 57 During different challenges in humans, a 60‐s analysis window was as good as a 5‐min window for SDNN, RMSSD and HR, although with 2 min or more needed for frequency‐domain and more complex analyses. 57 , 58 , 59 , 60 Rodent studies have also validated the use of 1‐min HRV analysis windows, 61 including for anxiety‐like tests. 54 Thus, determining HRV measures in the first minute of drinking (‘drinking onset’) reflected a compromise between having the rat already drinking and including sufficient data to allow robust HRV assessment.…”

Prediction of Impulsive Aggression Based on Video Images

“…Conversely, when individuals experience positive emotions, such as happiness, their RR intervals become longer, their heart rate slows down, and the low-frequency power (LF) of their heart rate variability power spectrum also decreases [ 9 ]. The regulation of heart rate variability is associated with the functional activities of the sympathetic and parasympathetic nervous systems, where the high-frequency component is mainly controlled by the parasympathetic nervous system, and the low-frequency component is regulated by the sympathetic nervous system [ 10 ]. Thus, by analyzing the time-domain and frequency-domain parameters of heart rate variability, it is possible to analyze an individual’s current autonomic nervous system state and further analyze their emotional state [ 11 ].…”