An Automatic Sleep Scoring Toolbox: Multi-modality of Polysomnography Signals’ Processing

Rui Yan, Fan Li, Xiaoyu Wang, Tapani Ristaniemi, Fengyu Cong

Abstract

Sleep scoring is a fundamental but time-consuming process in any sleep laboratory. To speed up the process of sleep scoring without compromising accuracy, this paper develops an automatic sleep scoring toolbox with the capability of multi-signal processing. It allows the user to choose signal types and the number of target classes. Then, an automatic process containing signal pre-processing, feature extraction, classifier training (or prediction) and result correction will be performed. Finally, the application interface displays predicted sleep structure, related sleep parameters and the sleep quality index for reference. To improve the identification accuracy of minority stages, a layer-wise classification strategy is proposed according to the signal characteristics of sleep stages. The context of the current stage is taken into consideration in the correction phase by employing a Hidden Markov Model to study the transition rules of sleep stages in the training dataset. These transition rules will be used for logic classification results. The performance of proposed toolbox has been tested on 100 subjects with an average accuracy of 85.76%. The proposed automatic scoring toolbox would alleviate the burden of the physicians, speed up sleep scoring, and expedite sleep research.

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Paper Citation


in Harvard Style

Yan R., Li F., Wang X., Ristaniemi T. and Cong F. (2019). An Automatic Sleep Scoring Toolbox: Multi-modality of Polysomnography Signals’ Processing.In Proceedings of the 16th International Joint Conference on e-Business and Telecommunications - Volume 1: SIGMAP, ISBN 978-989-758-378-0, pages 301-309. DOI: 10.5220/0007925503010309


in Bibtex Style

@conference{sigmap19,
author={Rui Yan and Fan Li and Xiaoyu Wang and Tapani Ristaniemi and Fengyu Cong},
title={An Automatic Sleep Scoring Toolbox: Multi-modality of Polysomnography Signals’ Processing},
booktitle={Proceedings of the 16th International Joint Conference on e-Business and Telecommunications - Volume 1: SIGMAP,},
year={2019},
pages={301-309},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007925503010309},
isbn={978-989-758-378-0},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on e-Business and Telecommunications - Volume 1: SIGMAP,
TI - An Automatic Sleep Scoring Toolbox: Multi-modality of Polysomnography Signals’ Processing
SN - 978-989-758-378-0
AU - Yan R.
AU - Li F.
AU - Wang X.
AU - Ristaniemi T.
AU - Cong F.
PY - 2019
SP - 301
EP - 309
DO - 10.5220/0007925503010309