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A Novel Approach for Sleep Arousal Disorder Detection Based on the Interaction of Physiological Signals and Metaheuristic Learning. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2023; 2023:9379618. [PMID: 36688224 PMCID: PMC9859692 DOI: 10.1155/2023/9379618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 11/21/2022] [Accepted: 11/23/2022] [Indexed: 01/15/2023]
Abstract
The vast majority of sleep disturbances are caused by various types of sleep arousal. To diagnose sleep disorders and prevent health problems such as cardiovascular disease and cognitive impairment, sleep arousals must be accurately detected. Consequently, sleep specialists must spend considerable time and effort analyzing polysomnography (PSG) recordings to determine the level of arousal during sleep. The development of an automated sleep arousal detection system based on PSG would considerably benefit clinicians. We quantify the EEG-ECG by using Lyapunov exponents, fractals, and wavelet transforms to identify sleep stages and arousal disorders. In this paper, an efficient hybrid-learning method is introduced for the first time to detect and assess arousal incidents. Modified drone squadron optimization (mDSO) algorithm is used to optimize the support vector machine (SVM) with radial basis function (RBF) kernel. EEG-ECG signals are preprocessed samples from the SHHS sleep dataset and the PhysioBank challenge 2018. In comparison to other traditional methods for identifying sleep disorders, our physiological signals correlation innovation is much better than similar approaches. Based on the proposed model, the average error rate was less than 2%-7%, respectively, for two-class and four-class issues. Additionally, the proper classification of the five sleep stages is determined to be accurate 92.3% of the time. In clinical trials of sleep disorders, the hybrid-learning model technique based on EEG-ECG signal correlation features is effective in detecting arousals.
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Herrero Babiloni A, Beetz G, Dal Fabbro C, Martel MO, Huynh N, Masse JF, Sessle B, Lavigne GJ. Dental sleep medicine: Time to incorporate sleep apnoea education in the dental curriculum. EUROPEAN JOURNAL OF DENTAL EDUCATION : OFFICIAL JOURNAL OF THE ASSOCIATION FOR DENTAL EDUCATION IN EUROPE 2020; 24:605-610. [PMID: 32320121 DOI: 10.1111/eje.12533] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Revised: 02/10/2020] [Accepted: 04/17/2020] [Indexed: 06/11/2023]
Abstract
Dental sleep medicine is a discipline that includes conditions such as sleep breathing disorders (eg snoring and sleep apnoea), sleep bruxism, orofacial pain and sleep-related complaints, and to some extent gastro-oesophageal reflux disorder and/or insomnia. Obstructive sleep apnoea (OSA) is a life-threatening condition that dentists need to identify and manage when indicated in order to increase patient well-being and to be taken in consideration in the dental curriculum. The main objective of this paper is to highlight the relevance of dental sleep medicine in the context of dental education, and to discuss potential educational content for integration in the dental curriculum with a focus on OSA, a condition that is not yet integrated in many dental training curricula around the world.
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Affiliation(s)
- Alberto Herrero Babiloni
- Sacré-Coeur Hospital, University of Montreal, Montreal, QC, Canada
- Faculty of Dental Medicine, University of Montreal, Montreal, QC, Canada
- Division of Experimental Medicine, McGill University, Montreal, QC, Canada
| | - Gabrielle Beetz
- Sacré-Coeur Hospital, University of Montreal, Montreal, QC, Canada
| | | | - Marc O Martel
- Division of Experimental Medicine, McGill University, Montreal, QC, Canada
- Faculty of Dentistry & Department of Anesthesia, McGill University, Montreal, QC, Canada
| | - Nelly Huynh
- Faculty of Dental Medicine, University of Montreal, Montreal, QC, Canada
| | | | - Barry Sessle
- Faculty of Medicine, Faculty of Dentistry and Department of Physiology, University of Toronto, Toronto, ON, Canada
| | - Gilles J Lavigne
- Sacré-Coeur Hospital, University of Montreal, Montreal, QC, Canada
- Faculty of Dental Medicine, University of Montreal, Montreal, QC, Canada
- Division of Experimental Medicine, McGill University, Montreal, QC, Canada
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Carter SG, Carberry JC, Grunstein RR, Eckert DJ. Randomized Trial on the Effects of High-Dose Zopiclone on OSA Severity, Upper Airway Physiology, and Alertness. Chest 2020; 158:374-385. [DOI: 10.1016/j.chest.2020.02.057] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Revised: 02/13/2020] [Accepted: 02/22/2020] [Indexed: 12/22/2022] Open
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Rezaeitalab F, Mokhber N, Ravanshad Y, Saberi S, Rezaeetalab F. Response to a letter to the editor by Mohammad Rasoul Ghadami et al.: "Obstructive sleep apnea in veterans with post-traumatic stress disorder: looking beyond their complaint". Sleep Breath 2018; 23:295-296. [PMID: 30105584 DOI: 10.1007/s11325-018-1707-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2018] [Revised: 07/14/2018] [Accepted: 08/05/2018] [Indexed: 11/26/2022]
Affiliation(s)
- Fariborz Rezaeitalab
- Department of Neurology, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Naghmeh Mokhber
- Psychiatry and Behavioral Sciences Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Yalda Ravanshad
- Clinical Research Unit, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Soheila Saberi
- Department of Pathology, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- University of Sydney, Sydney, Australia
| | - Fariba Rezaeetalab
- Lung Disease Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
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