Fit‐for‐purpose biometric monitoring technologies: leveraging the laboratory biomarker experience
Biometric monitoring technologies (BioMeTs) are becoming increasingly common to aid
data collection in clinical trials and practice. The state of BioMeTs, and associated digitally …
data collection in clinical trials and practice. The state of BioMeTs, and associated digitally …
An efficient and unified statistical monitoring framework for multivariate autocorrelated processes
K Wang, W Xu, J Li - Computers & Industrial Engineering, 2024 - Elsevier
In current manufacturing and service systems, product quality or process status is typically
characterized by multiple variables. The rapid advances of information technologies further …
characterized by multiple variables. The rapid advances of information technologies further …
Distributional data analysis via quantile functions and its application to modeling digital biomarkers of gait in Alzheimer's Disease
With the advent of continuous health monitoring with wearable devices, users now generate
their unique streams of continuous data such as minute-level step counts or heartbeats …
their unique streams of continuous data such as minute-level step counts or heartbeats …
Parsimonious hidden Markov models for matrix-variate longitudinal data
Abstract Hidden Markov models (HMMs) have been extensively used in the univariate and
multivariate literature. However, there has been an increased interest in the analysis of …
multivariate literature. However, there has been an increased interest in the analysis of …
Empirical likelihood-based inference for functional means with application to wearable device data
This paper develops a nonparametric inference framework that is applicable to occupation
time curves derived from wearable device data. These curves consider all activity levels …
time curves derived from wearable device data. These curves consider all activity levels …
Doubly-online changepoint detection for monitoring health status during sports activities
Doubly-online changepoint detection for monitoring health status during sports activities Page
1 The Annals of Applied Statistics 2023, Vol. 17, No. 3, 2387–2409 https://doi.org/10.1214/22-AOAS1724 …
1 The Annals of Applied Statistics 2023, Vol. 17, No. 3, 2387–2409 https://doi.org/10.1214/22-AOAS1724 …
Mixture of hidden Markov models for accelerometer data
Mixture of hidden Markov models for accelerometer data Page 1 The Annals of Applied
Statistics 2020, Vol. 14, No. 4, 1834–1855 https://doi.org/10.1214/20-AOAS1375 © Institute …
Statistics 2020, Vol. 14, No. 4, 1834–1855 https://doi.org/10.1214/20-AOAS1375 © Institute …
[PDF][PDF] Contributions to Model-Based Clustering
M Marbac - 2022 - hal.science
1.1 Summary of my contributions...................... 7 1.1. 1 Presentation................................ 7 1.1. 2
Research Interests............................. 8 1.1. 3 Publications................................. 9 1.2 Outline of …
Research Interests............................. 8 1.1. 3 Publications................................. 9 1.2 Outline of …
Analisi delle performance sportive con i modelli state space
M Stival - 2022 - research.unipd.it
The study of sports performances is a topic of paramount importance in sports sciences, in
which the role of data have been always fundamental. The evaluation of athletes' …
which the role of data have been always fundamental. The evaluation of athletes' …
[PDF][PDF] Fit-for-Purpose Biometric Monitoring Technologies (BioMeT): Leveraging the Laboratory Biomarker Experience. nd
Abstract Biometric Monitoring Technologies (BioMeTs) are becoming increasingly common
to aid data collection in clinical trials and practice. The state of BioMeTs, and associated …
to aid data collection in clinical trials and practice. The state of BioMeTs, and associated …