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With the rapid development of wearable device technologies, accelerometers can record minute-by-minute physical activity for consecutive days, which provides important insight into a dynamic association between the intensity of physical…

Methodology · Statistics 2024-09-06 Cheng Cao , Jiguo Cao , Hao Pan , Yunting Zhang , Fan Jiang , Xinyue Li

Due to the sensitive nature of diabetes-related data, preventing them from being shared between studies, progress in the field of glucose prediction is hard to assess. To address this issue, we present GLYFE (GLYcemia Forecasting…

Signal Processing · Electrical Eng. & Systems 2020-06-30 Maxime De Bois , Mehdi Ammi , Mounîm A. El Yacoubi

With the improvement of medical data capturing, vast amount of continuous patient monitoring data, e.g., electrocardiogram (ECG), real-time vital signs and medications, become available for clinical decision support at intensive care units…

Machine Learning · Computer Science 2018-07-25 Yanbo Xu , Siddharth Biswal , Shriprasad R Deshpande , Kevin O Maher , Jimeng Sun

Accurately estimating parameters of physiological models is essential to achieving reliable digital twins. For Type 1 Diabetes, this is particularly challenging due to the complexity of glucose-insulin interactions. Traditional methods…

Effective management of Type 1 Diabetes requires continuous glucose monitoring and precise insulin adjustments to prevent hyperglycemia and hypoglycemia. With the growing adoption of wearable glucose monitors and mobile health applications,…

Machine Learning · Computer Science 2026-01-22 Giorgia Rigamonti , Mirko Paolo Barbato , Davide Marelli , Paolo Napoletano

Wearable devices, such as actigraphy monitors and continuous glucose monitors (CGMs), capture high-frequency data, which are often summarized by the percentages of time spent within fixed thresholds. For example, actigraphy data are…

Methodology · Statistics 2025-01-22 Junyoung Park , Neo Kok , Irina Gaynanova

We present a new method based on Functional Data Analysis (FDA) for detecting associations between one or more scalar covariates and a longitudinal response, while correcting for other variables. Our methods exploit the temporal structure…

Applications · Statistics 2014-04-30 Matthew Reimherr , Dan Nicolae

The human insulin-glucose metabolism is a time-varying process, which is partly caused by the changing insulin sensitivity of the body. This insulin sensitivity follows a circadian rhythm and its effects should be anticipated by any…

Systems and Control · Electrical Eng. & Systems 2021-01-29 Lukas Ortmann , Dawei Shi , Eyal Dassau , Francis J. Doyle , Berno J. E. Misgeld , Steffen Leonhardt

Gestational diabetes (GDM) poses a growing health risk to both pregnant women and their offspring. While telehealth interventions for GDM management have proven effective, they have traditionally relied on healthcare professionals for…

Human-Computer Interaction · Computer Science 2023-09-20 Mikko Kytö , Saila Koivusalo , Heli Tuomonen , Lisbeth Strömberg , Antti Ruonala , Pekka Marttinen , Seppo Heinonen , Giulio Jacucci

Advances of modern sensing and sequencing technologies generate a deluge of high dimensional space-temporal physiological and next-generation sequencing (NGS) data. Physiological traits are observed either as continuous random functions, or…

Genomics · Quantitative Biology 2014-10-28 D. Y. Lee , C. Hanis , G. I. Bell , D. A. Aguilar , S. Redline , J. Below , M. M. Xiong

Physical activity is crucial for human health. With the increasing availability of large-scale mobile health data, strong associations have been found between physical activity and various diseases. However, accurately capturing this…

Methodology · Statistics 2026-01-19 Xiaojing Sun , Bingxin Zhao , Fei Xue

A database of ten type 1 diabetes patients wearing a continuous glucose monitoring device has enabled to record their blood glucose continuous variations every minute all day long during fourteen consecutive days. These recordings…

We present a functional data analysis approach for studying time-dependent, continuous glucose monitoring data with repeated measures for each individual in an experiment. After scaling the glucose concentration curves to the interval [0,…

Methodology · Statistics 2025-11-04 Nihan Acar-Denizli , Pedro Delicado

Type 1 diabetes is a serious disease in which individuals are unable to regulate their blood glucose levels, leading to various medical complications. Artificial pancreas (AP) systems have been developed as a solution for type 1 diabetic…

Signal Processing · Electrical Eng. & Systems 2023-05-18 Ke Ma , Hongkai Chen , Shan Lin

In many clinical trials, outcomes of interest include binary-valued endpoints. It is not uncommon that a binary-valued outcome is dichotomized from a continuous outcome at a threshold of clinical interest. To reach the objective, common…

Applications · Statistics 2021-08-05 Chenchen Ma , Xin Shen , Yongming Qu , Yu Du

Diabetes is a chronic metabolic disorder characterized by persistently high blood glucose levels (BGLs), leading to severe complications such as cardiovascular disease, neuropathy, and retinopathy. Predicting BGLs enables patients to…

Personal health devices can enable continuous monitoring of health parameters. However, the benefit of these devices is often directly related to the frequency of use. Therefore, adherence to personal health devices is critical. This paper…

Computers and Society · Computer Science 2020-06-11 Sudip Vhaduri , Temiloluwa Prioleau

The availability of continuous glucose monitors as over-the-counter commodities have created a unique opportunity to monitor a person's blood glucose levels, forecast blood glucose trajectories and provide automated interventions to prevent…

Machine Learning · Computer Science 2026-04-16 Ebrahim Farahmand , Shovito Barua Soumma , Nooshin Taheri Chatrudi , Hassan Ghasemzadeh

Malignant ventricular arrhythmias (VT/VF) following acute myocardial infarction (AMI) are a major cause of in-hospital death, yet early identification remains a clinical challenge. While traditional risk scores have limited performance,…

Artificial Intelligence · Computer Science 2025-10-21 Shun Huang , Wenlu Xing , Shijia Geng , Hailong Wang , Guangkun Nie , Gongzheng Tang , Chenyang He , Shenda Hong

With our ability to record more neurons simultaneously, making sense of these data is a challenge. Functional connectivity is one popular way to study the relationship between multiple neural signals. Correlation-based methods are a set of…

Neurons and Cognition · Quantitative Biology 2017-06-09 Tiger W. Lin , Anup Das , Giri P. Krishnan , Maxim Bazhenov , Terrence J. Sejnowski
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