Bayesian Covariate-Dependent Circadian Modeling of Rest-Activity Rhythms
We propose a Bayesian covariate-dependent anti-logistic circadian model for analyzing activity data collected via wrist-worn wearable devices. The proposed approach integrates covariates into the modeling of the amplitude and phase parameters, facilitating cohort-level analysis with enhanced flexibi...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Data Science in Science |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/26941899.2025.2474943 |
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| author | Beniamino Hadj-Amar Vaishnav Krishnan Marina Vannucci |
| author_facet | Beniamino Hadj-Amar Vaishnav Krishnan Marina Vannucci |
| author_sort | Beniamino Hadj-Amar |
| collection | DOAJ |
| description | We propose a Bayesian covariate-dependent anti-logistic circadian model for analyzing activity data collected via wrist-worn wearable devices. The proposed approach integrates covariates into the modeling of the amplitude and phase parameters, facilitating cohort-level analysis with enhanced flexibility and interpretability. To promote model sparsity, we employ an [Formula: see text]-ball projection prior, enabling precise control over complexity while identifying significant predictors. We assess performances on simulated data and then apply the method to real-world actigraphy data from people with epilepsy. Our results demonstrate the model’s effectiveness in uncovering complex relationships among demographic, psychological, and medical factors influencing rest-activity rhythms, offering insights for personalized clinical assessments and healthcare interventions. |
| format | Article |
| id | doaj-art-9e3c58dfcdc446d99bde09f9a2b6be56 |
| institution | DOAJ |
| issn | 2694-1899 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Data Science in Science |
| spelling | doaj-art-9e3c58dfcdc446d99bde09f9a2b6be562025-08-20T03:05:42ZengTaylor & Francis GroupData Science in Science2694-18992025-12-014110.1080/26941899.2025.2474943Bayesian Covariate-Dependent Circadian Modeling of Rest-Activity RhythmsBeniamino Hadj-Amar0Vaishnav Krishnan1Marina Vannucci2Department of Statistics, Rice University, Houston, TX, USANeurology, Neuroscience, and Psychiatry & Behavioral Sciences, Baylor College of Medicine, Houston, TX, USADepartment of Statistics, Rice University, Houston, TX, USAWe propose a Bayesian covariate-dependent anti-logistic circadian model for analyzing activity data collected via wrist-worn wearable devices. The proposed approach integrates covariates into the modeling of the amplitude and phase parameters, facilitating cohort-level analysis with enhanced flexibility and interpretability. To promote model sparsity, we employ an [Formula: see text]-ball projection prior, enabling precise control over complexity while identifying significant predictors. We assess performances on simulated data and then apply the method to real-world actigraphy data from people with epilepsy. Our results demonstrate the model’s effectiveness in uncovering complex relationships among demographic, psychological, and medical factors influencing rest-activity rhythms, offering insights for personalized clinical assessments and healthcare interventions.https://www.tandfonline.com/doi/10.1080/26941899.2025.2474943Anti-logistic Circadian modelrest-activity rhythmsl1-ball projection priormulti-subject modelingwereable devices |
| spellingShingle | Beniamino Hadj-Amar Vaishnav Krishnan Marina Vannucci Bayesian Covariate-Dependent Circadian Modeling of Rest-Activity Rhythms Data Science in Science Anti-logistic Circadian model rest-activity rhythms l1-ball projection prior multi-subject modeling wereable devices |
| title | Bayesian Covariate-Dependent Circadian Modeling of Rest-Activity Rhythms |
| title_full | Bayesian Covariate-Dependent Circadian Modeling of Rest-Activity Rhythms |
| title_fullStr | Bayesian Covariate-Dependent Circadian Modeling of Rest-Activity Rhythms |
| title_full_unstemmed | Bayesian Covariate-Dependent Circadian Modeling of Rest-Activity Rhythms |
| title_short | Bayesian Covariate-Dependent Circadian Modeling of Rest-Activity Rhythms |
| title_sort | bayesian covariate dependent circadian modeling of rest activity rhythms |
| topic | Anti-logistic Circadian model rest-activity rhythms l1-ball projection prior multi-subject modeling wereable devices |
| url | https://www.tandfonline.com/doi/10.1080/26941899.2025.2474943 |
| work_keys_str_mv | AT beniaminohadjamar bayesiancovariatedependentcircadianmodelingofrestactivityrhythms AT vaishnavkrishnan bayesiancovariatedependentcircadianmodelingofrestactivityrhythms AT marinavannucci bayesiancovariatedependentcircadianmodelingofrestactivityrhythms |