Common medical conditions are often associated with sleep abnormalities. Patients with medical disorders often suffer from poor sleep quality compared to healthy individuals, which in turn may worsen the symptoms of the disorder. Accurate detection of sleep/wake patterns is important in developing personalized digital markers, which can be used for objective measurements and efficient disease management. Big Data technologies and advanced analytics methods hold the promise to revolutionize clinical research processes, enabling the effective blending of digital data into clinical trials. Actigraphy, a non-invasive activity monitoring method is heavily used to detect and evaluate activities and movement disorders, and assess sleep/wake behavior. In order to study the connection between sleep/wake patterns and a cluster headache disorder, activity data was collected using a wearable device in the course of a clinical trial. This study presents two novel modeling schemes that utilize Deep Convolutional Neural Networks (CNN) to identify sleep/wake states. The proposed methods are a sequential CNN, reminiscent of the bi-directional CNN for slot filling, and a Multi-Task Learning (MTL) based model. Furthermore, we expand standard "Sleep" and "Wake" activity states space by adding the "Falling asleep" and "Siesta" states. We show that the proposed methods provide promising results in accurate detection of the expanded sleep/wake states. Finally, we explore the relations between the detected sleep/wake patterns and onset of cluster headache attacks, and present preliminary observations.
On Sleep-Wake Disorder Identification from Polysomnographic Representations
Faculty of Informatics, Università della Svizzera Italiana（瑞士意大利语区大学信息学院）；MeDiTech, SUPSI（瑞士应用科学与艺术大学医学技术学院）；Ente Ospedaliero Cantonale (EOC)（州立医院管理局）；University of Brescia（布雷西亚大学）；University of Bern（伯尔尼大学）
ActiTect: A Generalizable Machine Learning Pipeline for REM Sleep Behavior Disorder Screening through Standardized Actigraphy
Faculty of Mathematics and Natural Sciences, University of Cologne, Germany（科隆大学数学与自然科学学院，德国）；Institute for Biomedical Informatics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany（科隆大学医学院与科隆大学医院生物医学信息学研究所，德国）；Center for Molecular Medicine Cologne (CMMC), Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany（科隆分子医学中心（CMMC），科隆大学医学院与科隆大学医院，德国）；Medical Psychology | Neuropsychology and Gender Studies, Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany（科隆大学医学院与科隆大学医院医学心理学 | 神经心理学与性别研究，德国）；Cognitive Neuroscience, Insitute for Neuroscience and Medicine, INM-3, Research Center Juelich, Germany（认知神经科学，神经科学与医学研究所，Juelich研究中心，德国）；Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany（科隆大学医学院与科隆大学医院神经科，德国）；Center of Neurology, Department of Parkinson, Sleep and Movement Disorders, University Hospital Bonn, University of Bonn, Germany（神经科中心，帕金森、睡眠与运动障碍部门，波恩大学医院，德国）；German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany（德国神经退行性疾病研究中心（DZNE），波恩，德国）；Cluster of Excellence for Aging and Aging-Associated Diseases (CECAD), University of Cologne, Germany（老龄化与相关疾病卓越中心（CECAD），科隆大学，德国）；Department of Neurology, University Medical Center Schleswig-Holstein, Campus Kiel and Kiel University, Germany（神经科，施普伦德-霍斯特大学医院，基尔校区和基尔大学，德国）；Department of Informatics, Technical University of Munich, Germany（信息学院，慕尼黑技术大学，德国）；Institute for Digital Medicine, University Hospital Bonn, Germany（数字医学研究所，波恩大学医院，德国）；Lundbeck Foundation Parkinson’s Disease Research Center (PACE), Aarhus University, Denmark（路德维希基金会帕金森病研究中心（PACE），奥胡斯大学，丹麦）；Department of Nuclear Medicine, Aarhus University Hospital, Denmark（核医学部，奥胡斯大学医院，丹麦）；Department of Electrical and Computer Engineering, Aarhus University, Denmark（电气与计算机工程系，奥胡斯大学，丹麦）；Oxford Parkinson’s Disease Centre and Division of Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, UK（牛津帕金森病中心与神经科，牛津大学临床神经科学系，英国）
A Single Channel-Based Neonatal Sleep-Wake Classification using Hjorth Parameters and Improved Gradient Boosting
Department of Computer Science, Loyola University（洛约拉大学计算机科学系）；Department of Computer Science, University of People（人民大学计算机科学系）；Department of Electronic, Electrical and Systems Engineering, University of Birmingham（伯明翰大学电子、电气与系统工程系）；School of Computing, Engineering and the Built Environment, Edinburgh Napier University（爱丁堡纳皮尔大学计算、工程与环境科学学院）；RIOTU Lab, Prince Sultan University（普森大学RIOTU实验室）
Institute for Data Science Foundations, Hamburg University of Technology（汉堡工业大学数据科学基础研究所）；Transylvanian Institute of Neuroscience（特兰西瓦尼亚神经科学研究所）；Quaesta AI（奎斯塔人工智能公司）
DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning
MIT（麻省理工学院）；CSAIL（麻省理工学院计算机科学与人工智能实验室）；NeuroSpin（神经自旋中心）；Center for Brains, Minds, and Machines（大脑、心智与机器中心）；Department of Brain and Cognitive Sciences（脑与认知科学系）；Department of Electrical Engineering and Computer Science（电气工程与计算机科学系）
A persistent homology approach to heart rate variability analysis with an application to sleep-wake classification
University of North Carolina at Greensboro（北卡罗来纳大学格林斯伯勒分校）；National Taiwan Normal University（台湾师范大学）；Chang Gung Memorial Hospital（长庚纪念医院）；Chang Gung University（长庚大学）；Duke University（杜克大学）；National Center for Theoretical Sciences（国家理论科学研究中心）
Using Legacy Polysomnography Data to Train a Radar System to Quantify Sleep in Older Adults and People living with Dementia
Department of Electrical and Electronic Engineering and UK Dementia Research Institute (Care Research & Technology Centre), Imperial College London（电气与电子工程系和英国痴呆症研究机构（护理与技术研究中心）、帝国理工学院伦敦分校）；Department of Informatics, University of Oslo（信息系，奥斯陆大学）；School of Biosciences, University of Surrey（生物科学学院，萨里大学）
The Breakthrough of Sleep: A Contactless Approach for Accurate Sleep Stage Detection Using the Sleepal AI Lamp
Hong Kong Xsmart Century Technology Co., Ltd.（香港Xsmart世纪科技有限公司）；Urban Mobility Lab, Massachusetts Institute of Technology（城市移动实验室，麻省理工学院）；Singapore-MIT Alliance for Research and Technology (SMART) Centre（新加坡-麻省理工联盟研究技术中心）；Department of Respiratory and Critical Care Medicine, Binzhou Medical University Hospital（呼吸与危重症医学科，滨州医学院医院）；Interdisciplinary Center of Sleep Medicine, Charité – Universitätsmedizin Berlin（睡眠医学跨学科中心，夏里特-柏林大学医学中心）
Automated Classification of Sleep Stages and EEG Artifacts in Mice with Deep Learning
Emory University（埃默里大学）；University Hospital Tübingen（图宾根大学医院）；University of Tübingen（图宾根大学）；Technische Universität Dresden（德累斯顿工业大学）；German Center for Neurodegenerative Diseases (DZNE)（德国神经退行性疾病中心）；FH Aachen University of Applied Sciences（亚琛应用技术大学）
A Foundation Model for Wearable Movement Data in Mental Health Research
Dartmouth College（达特茅斯学院）；National Institute of Diabetes and Digestive and Kidney Diseases（国家糖尿病、消化系统疾病和肾病研究所）；National Institutes of Health（美国国立卫生研究院）；Department of Computer Science at Dartmouth College（达特茅斯学院计算机科学系）
