Hippocampal deep brain stimulation for drug-resistant epilepsy: Insights from bilateral temporal lobe and posterior epilepsy cases.

Purpose: This study evaluates the long-term efficacy of hippocampal deep brain stimulation (Hip-DBS) in patients with drug-resistant epilepsy (DRE), specifically focusing on bilateral temporal lobe epilepsy (BTLE) and posterior epilepsy (PE).

Methods: A retrospective analysis was conducted on 15 DRE patients (11 BTLE, 4 PE) who underwent bilateral Hip-DBS at Samsung Medical Center over an eight-year period. Medical records, seizure diaries, and neuropsychological assessments were reviewed.

Effect of closed-loop vibration stimulation on sleep quality for poor sleepers.

Introduction: Recent studies have investigated the autonomic modulation method using closed-loop vibration stimulation (CLVS) as a novel strategy for enhancing sleep quality. This study aimed to explore the effects of CLVS on sleep quality, autonomic regulation, and brain activity in individuals with poor sleep quality.

Methods: Twenty-seven participants with poor sleep quality (Pittsburgh sleep quality index >5) underwent two experimental sessions using polysomnography and a questionnaire, one with CLVS (STIM) and the other without (SHAM).

Validation of the Karolinska Sleepiness Scale in Korean.

Background And Purpose: The Karolinska Sleepiness Scale (KSS) is widely used for assessing current level of sleepiness, but it has not been validated in South Korea. This study aimed to validate the KSS using the Stanford Sleepiness Scale (SSS), polysomnography (PSG), and electroencephalography (EEG).

Methods: The sample consisted of 27 adult participants in this study aged 40.

Long-term night-shift work is associated with accelerates brain aging and worsens N3 sleep in female nurses.

Background: Shift work disrupts circadian rhythms and alters sleep patterns, resulting in various health problems. To quantitatively assess the impact of shift work on brain health, we evaluated the brain age index (BAI) derived from sleep electroencephalography (EEG) results in night-shift workers and compared it with that in daytime workers.

Methods: We studied 45 female night shift nurses (mean age: 28.

Are there effects of light exposure on daytime sleep for rotating shift nurses after night shift?: an EEG power analysis.

Introduction: Night-shift workers often face various health issues stemming from circadian rhythm shift and the consequent poor sleep quality. We aimed to study nurses working night shifts, evaluate the electroencephalogram (EEG) pattern of daytime sleep, and explore possible pattern changes due to ambient light exposure (30 lux) compared to dim conditions (<5 lux) during daytime sleep.

Moethods: The study involved 31 participants who worked night shifts and 24 healthy adults who had never worked night shifts.

Therapeutic Drug Monitoring of 6 New-Generation Antiseizure Medications Using a Mass Spectrometry Method: Analysis of 2-Year Experience in a Large Cohort of Korean Epilepsy Patients.

Context.—: New-generation antiseizure medications (ASMs) are increasingly prescribed, and therapeutic drug monitoring (TDM) has been proposed to improve clinical outcome. However, clinical TDM data on new-generation ASMs are scarce.

Predicting the impact of CPAP on brain health: A study using the sleep EEG-derived brain age index.

Objective: This longitudinal study investigated potential positive impact of CPAP treatment on brain health in individuals with obstructive sleep Apnea (OSA). To allow this, we aimed to employ sleep electroencephalogram (EEG)-derived brain age index (BAI) to quantify CPAP's impact on brain health and identify individually varying CPAP effects on brain aging using machine learning approaches.

Methods: We retrospectively analyzed CPAP-treated (n = 98) and untreated OSA patients (n = 88) with a minimum 12-month follow-up of polysomnography.

Deep learning of sleep apnea-hypopnea events for accurate classification of obstructive sleep apnea and determination of clinical severity.

Background: /Objective: Automatic apnea/hypopnea events classification, crucial for clinical applications, often faces challenges, particularly in hypopnea detection. This study aimed to evaluate the efficiency of a combined approach using nasal respiration flow (RF), peripheral oxygen saturation (SpO2), and ECG signals during polysomnography (PSG) for improved sleep apnea/hypopnea detection and obstructive sleep apnea (OSA) severity screening.

Methods: An Xception network was trained using main features from RF, SpO2, and ECG signals obtained during PSG.

Obstructive Sleep Apnea and Its Influence on Intracranial Aneurysm.

Obstructive sleep apnea syndrome (OSAS) is associated with cerebrovascular disease, which can lead to life-threatening outcomes. The purpose of the study was to investigate the relationship between OSAS and comorbid intracranial aneurysms. We retrospectively reviewed 564 patients who underwent a polysomnography and brain magnetic resonance angiography as part of their health checkup.

Gender differences in the upper airway, craniofacial morphological and polysomnographic parameters in patients with obstructive sleep apnoea.

Background: Obstructive sleep apnoea (OSA) is a common sleep disorder characterized by repetitive episodes of upper airway collapse during sleep associated with arousals with or without oxygen desaturation.

Objective: This study aims to assess and analyse the morphological and neurological factors associated with obstructive sleep apnoea using polysomnography study data and two-dimensional cephalometric analysis of airway and skeletal parameters and their correlation in the patients with varying severities of obstructive sleep apnoea.

Methods: This study included 892 patients who underwent a complete work up, including a thorough history, clinical examination, standard polysomnography study and 2D cephalometric analysis to diagnose obstructive sleep apnoea.

Sex-specific patterns of discomfort in patients with restless legs syndrome.

Study Objectives: Sex differences in the prevalence of restless legs syndrome (RLS) have been reported, with a higher prevalence in women than in men. However, sex differences in clinical presentation remain unclear. We aimed to investigate the phenotypic differences in patients with RLS between sexes by comparing clinical presentations, iron status, polysomnographic parameters, and treatment.

White matter microstructure and connectivity changes after surgery in male adults with obstructive sleep apnea: recovery or reorganization?

Study Objectives: Obstructive sleep apnea (OSA) is a prevalent clinical problem significantly affecting cognitive functions. Surgical treatment is recommended for those unable to use continuous positive airway pressure. We aimed to investigate the therapeutic effect of upper airway surgery on the white matter (WM) microstructure and brain connectivity in patients with OSA.

Imputing missing sleep data from wearables with neural networks in real-world settings.

Sleep is a critical component of health and well-being but collecting and analyzing accurate longitudinal sleep data can be challenging, especially outside of laboratory settings. We propose a simple neural network model titled SOMNI (Sleep data restOration using Machine learning and Non-negative matrix factorIzation [NMF]) for imputing missing rest-activity data from actigraphy, which can enable clinicians to better handle missing data and monitor sleep-wake cycles of individuals with highly irregular sleep-wake patterns. The model consists of two hidden layers and uses NMF to capture hidden longitudinal sleep-wake patterns of individuals with disturbed sleep-wake cycles.

Validating a Consumer Smartwatch for Nocturnal Respiratory Rate Measurements in Sleep Monitoring.

Wrist-based respiratory rate (RR) measurement during sleep faces accuracy limitations. This study aimed to assess the accuracy of the RR estimation function during sleep based on the severity of obstructive sleep apnea (OSA) using the Samsung Galaxy Watch (GW) series. These watches are equipped with accelerometers and photoplethysmography sensors for RR estimation.

Predicting the Risk of Sleep Disorders Using a Machine Learning-Based Simple Questionnaire: Development and Validation Study.

Background: Sleep disorders, such as obstructive sleep apnea (OSA), comorbid insomnia and sleep apnea (COMISA), and insomnia are common and can have serious health consequences. However, accurately diagnosing these conditions can be challenging as a result of the underrecognition of these diseases, the time-intensive nature of sleep monitoring necessary for a proper diagnosis, and patients' hesitancy to undergo demanding and costly overnight polysomnography tests.

Objective: We aim to develop a machine learning algorithm that can accurately predict the risk of OSA, COMISA, and insomnia with a simple set of questions, without the need for a polysomnography test.

A real-time, personalized sleep intervention using mathematical modeling and wearable devices.

The prevalence of artificial light exposure has enabled us to be active any time of the day or night, leading to the need for high alertness outside of traditional daytime hours. To address this need, we developed a personalized sleep intervention framework that analyzes real-world sleep-wake patterns obtained from wearable devices to maximize alertness during specific target periods. Our framework utilizes a mathematical model that tracks the dynamic sleep pressure and circadian rhythm based on the user's sleep history.

Automatic stridor detection using small training set via patch-wise few-shot learning for diagnosis of multiple system atrophy.

Stridor is a rare but important non-motor symptom that can support the diagnosis and prediction of worse prognosis in multiple system atrophy. Recording sounds generated during sleep by video-polysomnography is recommended for detecting stridor, but the analysis is labor intensive and time consuming. A method for automatic stridor detection should be developed using technologies such as artificial intelligence (AI) or machine learning.

Identifying important factors for successful surgery in patients with lateral temporal lobe epilepsy.

Objective: Lateral temporal lobe epilepsy (LTLE) has been diagnosed in only a small number of patients; therefore, its surgical outcome is not as well-known as that of mesial temporal lobe epilepsy. We aimed to evaluate the long-term (5 years) and short-term (2 years) surgical outcomes and identify possible prognostic factors in patients with LTLE.

Methods: This retrospective cohort study was conducted between January 1995 and December 2018 among patients who underwent resective surgery in a university-affiliated hospital.

More extensive white matter disruptions present in untreated obstructive sleep apnea than we thought: A large sample diffusion imaging study.

Obstructive sleep apnea (OSA) may lead to white mater (WM) disruptions and cognitive deficits. However, no studies have investigated the full extent of the brain WM, and its associations with cognitive deficits in OSA remain unclear. We thus applied diffusion tensor imaging (DTI) tractography with multi-fiber models and used atlas-based bundle-specific approach to investigate the WM abnormalities for various tracts of the cerebral cortex, thalamus, brainstem, and cerebellum in patients with untreated OSA.

Novel neuroelectrophysiological age index associated with imaging features of brain aging and sleep disorders.

Sleep architecture and microstructures alter with aging and sleep disorder-led accelerated aging. We proposed a sleep EEG based brain age prediction model using convolutional neural networks. We then associated the estimated brain age index with brain structural aging features, sleep disorders and various sleep parameters.

Depression is a main determinant of health-related quality of life in patients with diabetic kidney disease.

Low health-related quality of life (HRQOL) is associated with adverse outcomes in diabetic kidney disease (DKD) patients. We examined the modifiable factors associated with low HRQOL in these patients. We enrolled 141 DKD patients.

Performance evaluation of a wrist-worn reflectance pulse oximeter during sleep.

Objectives: To characterize and evaluate the estimation of oxygen saturation measured by a wrist-worn reflectance pulse oximeter during sleep.

Methods: Ninety-seven adults with sleep disturbances were enrolled. Oxygen saturation was simultaneously measured using a reflectance pulse oximeter (Galaxy Watch 4 [GW4], Samsung, South Korea) and a transmittance pulse oximeter (polysomnography) as a reference.