Výsledky vyhledávání - "van Gilst, Merel"

Report

A generative foundation model for five-class sleep staging with arbitrary sensor input

Autor: van Gorp, Hans, van Gilst, Merel M., Fonseca, Pedro, van Meulen, Fokke B., van Dijk, Johannes P., Overeem, Sebastiaan, van Sloun, Ruud J. G.

Gold-standard sleep scoring as performed by human technicians is based on a subset of PSG signals, namely the EEG, EOG, and EMG. The PSG, however, consists of many more signal derivations that could potentially be used to perform sleep staging, inclu

Externí odkaz: http://arxiv.org/abs/2408.15253

Zobrazit plný text záznamu

Akademický článek

A Mobile App for Longterm Monitoring of Narcolepsy Symptoms: Design, Development, and Evaluation

Autor: Quaedackers, Laury, De Wit, Jan, Pillen, Sigrid, Van Gilst, Merel, Batalas, Nikolaos, Lammers, Gert Jan, Markopoulos, Panos, Overeem, Sebastiaan

Publikováno v: JMIR mHealth and uHealth, Vol 8, Iss 1, p e14939 (2020)

BackgroundNarcolepsy is a chronic sleep disorder with a broad variety of symptoms. Although narcolepsy is primarily characterized by excessive daytime sleepiness and cataplexy (loss of muscle control triggered by emotions), patients may suffer from h

Externí odkaz: https://doaj.org/article/8be3c57911b34671b798a2d46a5e5ce0

Zobrazit plný text záznamu

Report

SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series

Autor: Huijben, Iris A. M., Nijdam, Arthur A., Overeem, Sebastiaan, van Gilst, Merel M., van Sloun, Ruud J. G.

Publikováno v: International Conference on Machine Learning 2023

Continuous monitoring with an ever-increasing number of sensors has become ubiquitous across many application domains. However, acquired time series are typically high-dimensional and difficult to interpret. Expressive deep learning (DL) models have

Externí odkaz: http://arxiv.org/abs/2205.15875

Zobrazit plný text záznamu