An Automatic Sleep Scoring Toolbox : Multi-modality of Polysomnography Signals’ Processing
Yan, R., Li, F., Wang, X., Ristaniemi, T., & Cong, F. (2019). An Automatic Sleep Scoring Toolbox : Multi-modality of Polysomnography Signals’ Processing. In M. Obaidat, C. Callegari, M. van Sinderen, P. Novais, P. Sarigiannidis, S. Battiato, Á. Serrano Sánchez de León, P. Lorenz, & F. Davoli (Eds.), ICETE 2019 : Proceedings of the 16th International Joint Conference on e-Business and Telecommunications, Volume 1: DCNET, ICE-B, OPTICS, SIGMAP and WINSYS (pp. 301-309). SCITEPRESS Science And Technology Publications. https://doi.org/10.5220/0007925503010309
© 2019 by SCITEPRESS
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. ...
PublisherSCITEPRESS Science And Technology Publications
Parent publication ISBN978-989-758-378-0
ConferenceInternational Conference on Signal Processing and Multimedia Applications
Is part of publicationICETE 2019 : Proceedings of the 16th International Joint Conference on e-Business and Telecommunications, Volume 1: DCNET, ICE-B, OPTICS, SIGMAP and WINSYS
Publication in research information system
MetadataShow full item record
Additional information about fundingThis work was supported by the scholarships from China Scholarship Council (Nos. 201606060227).
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Yan, Rui; Li, Fan; Zhou, Dong Dong; Ristaniemi, Tapani; Cong, Fengyu (Elsevier, 2021)Background: Sleep scoring is an essential but time-consuming process, and therefore automatic sleep scoring is crucial and urgent to help address the growing unmet needs for sleep research. This ...
Yan, Rui; Li, Fan; Zhou, DongDong; Ristaniemi, Tapani; Cong, Fengyu (IEEE, 2020)Sleep scoring is a fundamental but time-consuming process in any sleep laboratory. Automatic sleep scoring is crucial and urgent to help address the increasing unmet need for sleep research. Therefore, this paper aims to ...
Yan, Rui; Zhang, Chi; Spruyt, Karen; Wei, Lai; Wang, Zhiqiang; Tian, Lili; Li, Xueqiao; Ristaniemi, Tapani; Zhang, Jihui; Cong, Fengyu (Elsevier BV, 2019)Objective: The study aims to develop an automatic sleep scoring method by fusing different polysomnography (PSG) signals and further to investigate PSG signals’ contribution to the scoring result. Methods: Eight combinations ...
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