Detail publikace

Automatic Segmentation of Actigraphy Data Utilising Gradient Boosting Algorithm

MIKULEC, M. MEKYSKA, J. SIGMUND, J. GALÁŽ, Z. BRABENEC, L. MORÁVKOVÁ, I. REKTOROVÁ, I.

Originální název

Automatic Segmentation of Actigraphy Data Utilising Gradient Boosting Algorithm

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

As the popularity of decentralised clinical trials increases, there is a need to have a tool enabling remote assessment of sleep, while having good consistency with the golden standard, i.e. with polysomnography (PSG). This study aims to introduce a new approach to sleep assessment that utilises the modelling of actigraphy data by a gradient boosting algorithm. The method is compared to a conventional baseline technique in terms of sleep/wake stages detection accuracy in a dataset containing 55 recordings of actigraphy and PSG (acquired from 28 subjects). In addition, we explored how well the outputs of the new method agree with data acquired via sleep diaries in another dataset including 150 recordings (22 subjects). With 97% sensitivity and 73 %specificity, the new method significantly outperformed the baseline one in modelling the PSG ground truth. On the other hand, it had a lower agreement with the patient-reported outcomes. The results suggest that a combination of both approaches could be a good alternative to the golden standard in remote sleep assessment studies.

Klíčová slova

actigraphy; machine learning; polysomnography; sleep; sleep diary

Autoři

MIKULEC, M.; MEKYSKA, J.; SIGMUND, J.; GALÁŽ, Z.; BRABENEC, L.; MORÁVKOVÁ, I.; REKTOROVÁ, I.

Vydáno

26. 7. 2021

Nakladatel

IEEE

Místo

Brno, Czech Republic

ISBN

978-1-6654-2933-7

Kniha

2021 44th International Conference on Telecommunications and Signal Processing

Strany od

399

Strany do

402

Strany počet

4

URL

BibTex

@inproceedings{BUT172297,
  author="MIKULEC, M. and MEKYSKA, J. and SIGMUND, J. and GALÁŽ, Z. and BRABENEC, L. and MORÁVKOVÁ, I. and REKTOROVÁ, I.",
  title="Automatic Segmentation of Actigraphy Data Utilising Gradient Boosting Algorithm",
  booktitle="2021 44th International Conference on Telecommunications and Signal Processing",
  year="2021",
  pages="399--402",
  publisher="IEEE",
  address="Brno, Czech Republic",
  doi="10.1109/TSP52935.2021.9522650",
  isbn="978-1-6654-2933-7",
  url="https://doi.org/10.1109/TSP52935.2021.9522650"
}