Heart and Breathing Rate Variations as Biomarkers for Anxiety Detection
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Date
2022-11
Publication Type
Journal Article
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yes
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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 over bar = 0.04), the standard deviation of the heart rate (SD; (p) over bar = 0.01), and the standard deviation of NN intervals (SDNN; (p) over bar = 0.03) for ECG signals, and the mean breath rate (MBR; p over bar = 0.002), the standard deviation of the breath rate (SD; p over bar < 0.0001), the root mean square of successive differences (RMSSD; p over bar < 0.0001) and SDNN ((p) over bar < 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.
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published
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Journal / series
Volume
9 (11)
Pages / Article No.
711
Publisher
MDPI
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Subject
digital health; wearable technology; heart rate variability; respiration rate variability; breathing rate variability; anxiety assessment; mental health monitoring; real-time anxiety detection
Organisational unit
09715 - Menon, Carlo / Menon, Carlo