AIMC Topic: Sleep Initiation and Maintenance Disorders

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Staying Relevant in the Digital Age: Exploring the Evolving Frontier of Telehealth for Mental Health in the Military Health System and Veterans Health Administration.

Current psychiatry reports
PURPOSE OF REVIEW: This review examines recent evidence for the effectiveness of telehealth in treating Post-Traumatic Stress Disorder (PTSD), Major Depressive Disorder (MDD), alcohol use disorder, and insomnia in military veterans and active-duty se...

EEG based classification of sleep cyclic alternating patterns using frequency driven forward ternary encoding.

Sleep & breathing = Schlaf & Atmung
PURPOSE: Cyclic alternating patterns (CAP) of sleep can be observed through electroencephalogram (EEG) signals. Analyzing CAP can provide valuable insights into different abnormalities relating to sleep. CAP comprises of two phases: A and B, characte...

Prediction of suicidal ideation and depression in the general population with subthreshold insomnia using machine learning models.

BMC psychiatry
BACKGROUND: Insomnia is a significant independent risk factor for depression and suicidality. However, these conditions often go undetected, particularly in individuals presenting with sleep complaints. This study aimed to develop and validate machin...

Introduction of sub-band augmentation with machine learning to develop an insomnia classification model using single-channel EEG signals.

Physiological measurement
. Biological signals can be used to record sleep activities and can be used to identify sleep disorders. Insomnia is a sleep disorder that can be detected using supervised learning models developed using biological signal analysis. The baseline insom...

The effect of psychotherapy on the multivariate association between insomnia and depressive symptoms in late-life depression.

European psychiatry : the journal of the Association of European Psychiatrists
BACKGROUND: Late-life depression (LLD) is prevalent in older adults and linked to increased disability, mortality, and suicide risk. Insomnia symptoms are considered common remaining symptoms of LLD following treatment. However, the multivariate rela...

Exploration of common pathogenic genes between cerebral amyloid angiopathy and insomnia based on bioinformatics and experimental validation.

Scientific reports
Cerebral amyloid angiopathy (CAA) and insomnia are age-related neurological disorders increasingly recognized as being closely associated. However, research on the shared genes and their biological mechanisms remains limited. This study aims to ident...

Sleep disturbances and PTSD: identifying baseline predictors of insomnia response in an intensive treatment programme.

European journal of psychotraumatology
This study examined whether baseline demographic and clinical variables could predict clinically significant reductions in insomnia symptoms among veterans receiving a 2-week Cognitive Processing Therapy (CPT)-based intensive PTSD treatment programm...

Linear and nonlinear features of EEG microstate associated with insomnia.

Sleep medicine
BACKGROUND: Numerous studies have revealed abnormalities in EEG microstate in insomnia, primarily quantified using linear features, whereas nonlinear metrics remain underexplored. This study aimed to compare linear and nonlinear features and further ...

Deciphering Insomnia: Benchmarking Automated Sleep Staging Algorithms for Complex Sleep Disorders.

Journal of sleep research
Polysomnography (PSG) is essential for diagnosing sleep disorders, but its manual interpretation is labor-intensive. Automated sleep staging algorithms are promising, yet their utility in complex sleep disorders such as insomnia remains uncertain. Th...

Exploring predictors of insomnia severity in shift workers using machine learning model.

Frontiers in public health
INTRODUCTION: Insomnia in shift workers has distinctive features due to circadian rhythm disruption caused by reversed or unstable sleep-wake cycle work schedules. While previous studies have primarily focused on a limited number of predictors for in...