Key result
Earbud PPG features match reference ECG for stress detection with a ~0.88 F1 score.
Why the study?
Although photoplethysmography-based heart rate variability features from earbud sensors can detect stress, morphological photoplethysmography features from earbuds had not been evaluated for stress detection.
Do morphological PPG features from earbud sensors improve stress detection compared to PPG HRV features or reference ECG HRV features?
Observational (n=97)
Do morphological PPG features from earbud sensors improve stress detection compared to PPG HRV features or reference ECG HRV features?
Effect estimate: ∆F1% = 0.798%
Absolute Event Rate: 0.88% vs 0.887%
Earbud-based PPG morphological and HRV features can detect stress with similar fidelity to reference ECG, offering a user-friendly alternative for physiological monitoring.
Supports earbud PPG stress detection comparable to ECG; leaves open clinical adoption pending prospective validation.
Stress monitoring has become a focal interest in health sensing due to the mental and physical effects of long-term stress. Recent work demonstrated the feasibility of photoplethysmography (PPG)-based heart rate variability (HRV) features from earbud sensors to detect stress. However, morphological PPG features from earbuds have not been evaluated for stress detection. We analyzed physiological data from periods of stress and non-stress for 97 subjects. We trained machine learning models on PPG morphological features and HRV features from the earbuds, as well as ECG HRV features from a reference device. The morphological features (F1 score: 0.879) outperformed PPG HRV features (F1 score: 0.773) in stress classification. The combination of PPG morphological features and HRV features (F1 score: 0.880) performed similarly to ECG HRV features (F1 score: 0.887; ∆<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F1%</inf> = 0.798%). The results suggest earbud PPG morphological and HRV features can detect stress with similar fidelity to ECG, despite the smaller form factor and limited sampling rate. Thus, earbud sensors may be a strong candidate for stress monitoring in physiology due to their user-friendly and comfortable nature.
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Zhang et al. (2024) conducted an observational in Stress (n=97). Earbud PPG morphological and HRV features vs. ECG HRV features was evaluated on Stress classification (∆F1% = 0.798%). Earbud PPG morphological and HRV features detected stress with an F1 score of 0.880, performing similarly to reference ECG HRV features (F1 score 0.887).
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