Sleep research article
Dynamic Structural Causal Modeling for Sleep
Authors: Ranveer Singh , Saurabh Mathur , Pranuthi Tenali , Arun Badi , Sriraam Natarajan
One-line summary
A sleep science research article on Dynamic Structural Causal Modeling for Sleep.
Sleep health notes
Sleep health notes will be added by the Sleepatch editorial team.
中文解读
中文解读待补充：本站会优先为失眠研究、睡眠质量改善、昼夜节律等高价值睡眠研究添加中文说明。
Original abstract
The causal dynamics of sleep-disordered breathing are complex and vary across patient populations, hindering the development of targeted interventions. We learn dynamic causal graphs of sleep-disordered breathing from Home Sleep Apnea Test (HSAT) recordings, revealing systematic differences in causal structure across sex and age subcohorts. We do so using the PCMCI+ algorithm on windowed fractional variables derived from 105 HSAT recordings, exploiting domain knowledge via edge blacklisting and employing bootstrap aggregation to address small subcohort sizes. The learned graphs show that temporal self-dependencies and the apnea-desaturation relationship persist across all cohorts, while other relationships vary substantially.
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