Separating Acute Psychological Stress from Physical Exertion in Biometric Signals
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arXiv
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866918503458537472 |
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| author | Bosch, Esther |
| author_facet | Bosch, Esther |
| contents | Acute psychological stress occurs in a wide range of everyday contexts, including transportation, occupational settings, and physical activity, where its reliable detection could enable adaptive system responses and support human well-being. A persistent challenge in automated stress recognition is disentangling the biometric signatures of acute psychological stress from those of concurrent physical exertion. This study examined how five physiological signals (tonic electrodermal activity, trapezius electromyography, heart rate, heart rate variability, and respiration rate) respond to cognitive stress and physical activity, independently and in combination. Nineteen participants completed a 2x3 within-subjects design in which acute psychological stress was induced via an n-back arithmetic task combined with social pressure and financial reward, across three activity conditions: idle sitting, walking, and stationary cycling. Multilevel linear mixed models and repeated-measures ANOVA were used to decompose main effects and interactions for each sensor. Tonic electrodermal activity showed a robust, additive response to both cognitive stress (r=0.48) and physical exertion (r=0.67), with no interaction, making it the most promising candidate for stress detection during physical activity. Heart rate and trapezius electromyography were driven almost exclusively by physical exertion, with no reliable sensitivity to the stress task. RMSSD was strongly suppressed by physical activity and showed only marginal sensitivity to cognitive load. Respiration rate was dominated by physical activity, with no reliable stress effect in the primary analysis. These findings provide a sensor-specific hierarchy for real-world stress detection and highlight tonic electrodermal activity as the most informative channel when cognitive stress must be identified in physically active populations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_15756 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Separating Acute Psychological Stress from Physical Exertion in Biometric Signals Bosch, Esther Human-Computer Interaction Applications Acute psychological stress occurs in a wide range of everyday contexts, including transportation, occupational settings, and physical activity, where its reliable detection could enable adaptive system responses and support human well-being. A persistent challenge in automated stress recognition is disentangling the biometric signatures of acute psychological stress from those of concurrent physical exertion. This study examined how five physiological signals (tonic electrodermal activity, trapezius electromyography, heart rate, heart rate variability, and respiration rate) respond to cognitive stress and physical activity, independently and in combination. Nineteen participants completed a 2x3 within-subjects design in which acute psychological stress was induced via an n-back arithmetic task combined with social pressure and financial reward, across three activity conditions: idle sitting, walking, and stationary cycling. Multilevel linear mixed models and repeated-measures ANOVA were used to decompose main effects and interactions for each sensor. Tonic electrodermal activity showed a robust, additive response to both cognitive stress (r=0.48) and physical exertion (r=0.67), with no interaction, making it the most promising candidate for stress detection during physical activity. Heart rate and trapezius electromyography were driven almost exclusively by physical exertion, with no reliable sensitivity to the stress task. RMSSD was strongly suppressed by physical activity and showed only marginal sensitivity to cognitive load. Respiration rate was dominated by physical activity, with no reliable stress effect in the primary analysis. These findings provide a sensor-specific hierarchy for real-world stress detection and highlight tonic electrodermal activity as the most informative channel when cognitive stress must be identified in physically active populations. |
| title | Separating Acute Psychological Stress from Physical Exertion in Biometric Signals |
| topic | Human-Computer Interaction Applications |
| url | https://arxiv.org/abs/2605.15756 |