Passive Measurement of Autonomic Arousal in Real-World Settings
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arXiv
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| Autori principali: | , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866915267050733568 |
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| author | Abdel-Ghaffar, Samy Galatzer-Levy, Isaac Heneghan, Conor Liu, Xin Kernasovskiy, Sarah Garrett, Brennan Barakat, Andrew McDuff, Daniel |
| author_facet | Abdel-Ghaffar, Samy Galatzer-Levy, Isaac Heneghan, Conor Liu, Xin Kernasovskiy, Sarah Garrett, Brennan Barakat, Andrew McDuff, Daniel |
| contents | The autonomic nervous system (ANS) is activated during stress, which can have negative effects on cardiovascular health, sleep, the immune system, and mental health. While there are ways to quantify ANS activity in laboratories, there is a paucity of methods that have been validated in real-world contexts. We present the Fitbit Body Response Algorithm, an approach to continuous remote measurement of ANS activation through widely available remote wrist-based sensors. The design was validated via two experiments, a Trier Social Stress Test (n = 45) and ecological momentary assessments (EMA) of perceived stress (n=87), providing both controlled and ecologically valid test data. Model performance predicting perceived stress when using all available sensor modalities was consistent with expectations (accuracy=0.85) and outperformed models with access to only a subset of the signals. We discuss and address challenges to sensing that arise in real world settings that do not present in conventional lab environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_21242 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Passive Measurement of Autonomic Arousal in Real-World Settings Abdel-Ghaffar, Samy Galatzer-Levy, Isaac Heneghan, Conor Liu, Xin Kernasovskiy, Sarah Garrett, Brennan Barakat, Andrew McDuff, Daniel Human-Computer Interaction Machine Learning The autonomic nervous system (ANS) is activated during stress, which can have negative effects on cardiovascular health, sleep, the immune system, and mental health. While there are ways to quantify ANS activity in laboratories, there is a paucity of methods that have been validated in real-world contexts. We present the Fitbit Body Response Algorithm, an approach to continuous remote measurement of ANS activation through widely available remote wrist-based sensors. The design was validated via two experiments, a Trier Social Stress Test (n = 45) and ecological momentary assessments (EMA) of perceived stress (n=87), providing both controlled and ecologically valid test data. Model performance predicting perceived stress when using all available sensor modalities was consistent with expectations (accuracy=0.85) and outperformed models with access to only a subset of the signals. We discuss and address challenges to sensing that arise in real world settings that do not present in conventional lab environments. |
| title | Passive Measurement of Autonomic Arousal in Real-World Settings |
| topic | Human-Computer Interaction Machine Learning |
| url | https://arxiv.org/abs/2504.21242 |