Dementia Care Research and Psychosocial Factors.

Background: In the last decade, virtual reality has become a popular tool for rehabilitation. It is quite useful in spatial rehabilitation for Alzheimer's disease (AD) as it allows safe navigation in a virtual environment which looks realistic. However, a drawback of virtual reality is cybersickness.

Evaluation of a cognition-sensitive spatial virtual reality game for Alzheimer's disease.

Spatial impairment characterizes Alzheimer's disease (AD) from its earliest stages. We present the design and preliminary evaluation of "Barn Ruins," a serious virtual reality (VR) wayfinding game for early-stage AD. Barn Ruins is tailored to the cognitive abilities of this population, featuring simple controls and error-based scoring system.

Comprehensive prediction of outcomes in patients with ST elevation myocardial infarction (STEMI) using tree-based machine learning algorithms.

ST elevation myocardial infarction (STEMI), a subtype of acute coronary syndrome, is one of the leading causes of morbidity and mortality. Revascularization using primary percutaneous coronary intervention (PPCI) is the gold standard treatment. Despite the restoration of myocardial blood flow, some patients experience adverse outcomes.

Design and Analysis of a Contact Piezo Microphone for Recording Tracheal Breathing Sounds.

Analysis of tracheal breathing sounds (TBS) is a significant area of study in medical diagnostics and monitoring for respiratory diseases and obstructive sleep apnea (OSA). Recorded at the suprasternal notch, TBS can provide detailed insights into the respiratory system's functioning and health. This method has been particularly useful for non-invasive assessments and is used in various clinical settings, such as OSA, asthma, respiratory infectious diseases, lung function, and detection during either wakefulness or sleep.

Quantitative Analysis of Factors of Attrition in a Double-blind rTMS Study for Alzheimer Treatment.

Attrition is a particular concern in studies examining the efficacy of a treatment for Alzheimer disease. Analyzing reasons for withdrawal in Alzheimer studies is crucial to ruling out attrition bias, which can undermine a study's validity. In contrast, attrition in studies using repetitive transcranial magnetic stimulation (rTMS) has received much less attention.

Using principal component analysis to determine which vestibular stimuli provide best biomarkers for separating Alzheimer's from mixed Alzheimer's disease.

Alzheimer's disease (AD) is often mixed with cerebrovascular disease (AD-CVD). Heterogeneity of dementia etiology and the overlapping of neuropathological features of AD and AD-CVD make feature identification of the two challenging. Separation of AD from AD-CVD is important as the optimized treatment for each group may differ.

1-Year Mortality Prediction through Artificial Intelligence Using Hemodynamic Trace Analysis among Patients with ST Elevation Myocardial Infarction.

: Patients presenting with ST Elevation Myocardial Infarction (STEMI) due to occlusive coronary arteries remain at a higher risk of excess morbidity and mortality despite being treated with primary percutaneous coronary intervention (PPCI). Identifying high-risk patients is prudent so that close monitoring and timely interventions can improve outcomes. : A cohort of 605 STEMI patients [64.

iVR-fNIRS: studying brain functions in a fully immersive virtual environment.

Immersive virtual reality (iVR) employs head-mounted displays or cave-like environments to create a sensory-rich virtual experience that simulates the physical presence of a user in a digital space. The technology holds immense promise in neuroscience research and therapy. In particular, virtual reality (VR) technologies facilitate the development of diverse tasks and scenarios closely mirroring real-life situations to stimulate the brain within a controlled and secure setting.

Can Brain Volume-Driven Characteristic Features Predict the Response of Alzheimer's Patients to Repetitive Transcranial Magnetic Stimulation? A Pilot Study.

This study is a post-hoc examination of baseline MRI data from a clinical trial investigating the efficacy of repetitive transcranial magnetic stimulation (rTMS) as a treatment for patients with mild-moderate Alzheimer's disease (AD). Herein, we investigated whether the analysis of baseline MRI data could predict the response of patients to rTMS treatment. Whole-brain T1-weighted MRI scans of 75 participants collected at baseline were analyzed.

Repetitive transcranial magnetic stimulation as a treatment for Alzheimer's disease: A randomized placebo-controlled double-blind clinical trial.

We report results of a large multisite double-blind randomized trial investigating the short and long-term efficacy of repetitive transcranial magnetic stimulation (rTMS) applied to patients with Alzheimer's disease (AD) at mild to moderate stages, in doses of either 2 or 4 weeks of treatment (5 days/week), whilst compared with 4 weeks of sham rTMS. Randomization to treatment group was stratified based on age and severity. The objectives of this study were to: 1) investigate the efficacy of active rTMS versus sham, 2) investigate the effect of dose of treatment (2 or 4 weeks), and 3) investigate the length of benefits from treatment.

How accurate are coordinate systems being used for transcranial magnetic stimulation?

When applying transcranial magnetic stimulation (TMS) to the brain, it is desired to be as precise as possible to reach a target area in the brain. For that, neuronavigational system using individuals' MRI scans were developed to guide TMS pulses delivery. All neuronavigational systems need coordinates of the target area to guide the TMS coil.

Gray and White Matter Voxel-Based Morphometry of Alzheimer's Disease With and Without Significant Cerebrovascular Pathologies.

Alzheimer's disease (AD) is the most common type of dementia, and AD individuals often present significant cerebrovascular disease (CVD) symptomology. AD with significant levels of CVD is frequently labeled mixed dementia (or sometimes AD-CVD), and the differentiation of these two neuropathologies (AD, AD-CVD) from each other is challenging, especially at early stages. In this study, we compared the gray matter (GM) and white matter (WM) volumes in AD (n = 83) and AD-CVD (n = 37) individuals compared with those of cognitively healthy controls (n = 85) using voxel-based morphometry (VBM) of their MRI scans.

Measuring anxiety disorder in bipolar disorder using EVestG: broad impact of medication groups.

Objectives: Anxiety disorder is present in approximately half of all bipolar disorder (BD) patients. There are neurologic bases for the comorbidity of balance (vestibular) disorders and anxiety. Our objective is to use electrovestibulography (EVestG), which is predominantly a measure of vestibular neural activity to not only quantitatively detect and measure comorbid anxiety disorder but also to quantitatively measure the impacts of anti-depressant, anti-psychotic, and mood stabilizer medication groups on anxiety measures in BD patients.

Obstructive sleep apnea detection during wakefulness: a comprehensive methodological review.

Obstructive sleep apnea (OSA) is a chronic condition affecting up to 1 billion people, globally. Despite this spread, OSA is still thought to be underdiagnosed. Lack of diagnosis is largely attributed to the high cost, resource-intensive, and time-consuming nature of existing diagnostic technologies during sleep.

Evaluating the Diagnostic Value of Electrovestibulography (EVestG) in Alzheimer's Patients with Mixed Pathology: A Pilot Study.

: Diagnosis of dementia subtypes caused by different brain pathophysiologies, particularly Alzheimer's disease (AD) from AD mixed with levels of cerebrovascular disease (CVD) symptomology (AD-CVD), is challenging due to overlapping symptoms. In this pilot study, the potential of Electrovestibulography (EVestG) for identifying AD, AD-CVD, and healthy control populations was investigated. : A novel hierarchical multiclass diagnostic algorithm based on the outcomes of its lower levels of binary classifications was developed using data of 16 patients with AD, 13 with AD-CVD, and 24 healthy age-matched controls, and then evaluated on a blind testing dataset made up of a new population of 12 patients diagnosed with AD, 9 with AD-CVD, and 8 healthy controls.

Developing cognitive workload and performance evaluation models using functional brain network analysis.

Cognition, defined as the ability to learn, remember, sustain attention, make decisions, and solve problems, is essential in daily activities and in learning new skills. The purpose of this study was to develop cognitive workload and performance evaluation models using features that were extracted from Electroencephalogram (EEG) data through functional brain network and spectral analyses. The EEG data were recorded from 124 brain areas of 26 healthy participants conducting two cognitive tasks on a robot simulator.

Does Resting Motor Threshold correlate with severity of Alzheimer's disease?

Conflicting results have emerged from studies examining the potential of resting motor threshold (RMT) as a neurophysiological marker for Alzheimer's disease (AD) diagnosis and progression. In this study, we estimated the strength of the association between RMT measurements and severity of cognitive impairment in a relatively large sample (N=128) of clinical trial participants with mild (Clinical Dementia Rating - CDR=1) to moderate (CDR=2) AD. RMT for each participant was determined by applying single-pulse transcranial magnetic stimulation repeated at varying intensities over left and right sides of the primary motor cortex.

Verification EVestG recordings are vestibuloacoustic signals.

Introduction: Neural dysfunction is associated with aberrant nerve firing; thus, electrodiagnosis has the potential for objective diagnosis and quantification of neural dysfunction. Electrical stimulation alters nerve firing and may also have treatment potential. This article outlines some findings related to electrodiagnosis and electrical stimulation of the ear.

Fluid-structure interaction modelling of the upper airway with and without obstructive sleep apnea: a review.

Obstructive sleep apnea (OSA) is a common respiratory disorder associated with the collapse of the upper airway during sleep. OSA may cause oxygen desaturation, arousals from sleep, and daytime sleepiness, in turn affecting quality of life. There is low success rate in existing OSA surgical treatments mainly due to heterogeneity of the OSA population and poor understanding of the mechanism of the upper airway collapse in each individual.

The Effect of Transcranial Alternating Current Stimulation With Cognitive Training on Executive Brain Function in Individuals With Dementia: Protocol for a Crossover Randomized Controlled Trial.

Background: Although memory and cognitive declines are associated with normal brain aging, they may also be precursors to dementia.

Objective: We aim to offer a novel approach to prevent or slow the progress of neurodegenerative dementia, or plausibly, improve the cognitive functions of individuals with dementia.

Methods: We will recruit and enroll 75 participants (older than 50 years old with either mild cognitive impairment or probable early or moderate dementia) for this double-blind randomized controlled study to estimate the efficacy of active transcranial alternating current stimulation with cognitive treatment (in comparison with sham transcranial alternating current stimulation).

Comparing Vestibular Responses to Linear and Angular Whole-Body Accelerations in Real and Immersive Environments.

The vestibular end organs differ in terms of anatomical and physiological characteristics. Sensory modalities' stimuli including visual stimuli and vestibular sensation can influence these organs differently. This paper explores differences between vestibular responses to axial tilts in physical and virtual environments.

Sleep-wake states change the interictal localization of candidate epileptic source generators.

Study Objectives: To compare estimated epileptic source localizations from 5 sleep-wake states (SWS): wakefulness (W), rapid eye movement sleep (REM), and non-REM 1-3.

Methods: Electrical source localization (sLORETA) of interictal spikes from different SWS on surface EEG from the epilepsy monitoring unit at spike peak and take-off, with results mapped to individual brain models for 75% of patients. Concordance was defined as source localization voxels shared between 2 and 5 SWS, and discordance as those unique to 1 SWS against 1-4 other SWS.

An unbiased algorithm for objective separation of Alzheimer's, Alzheimer's mixed with cerebrovascular symptomology, and healthy controls from one another using electrovestibulography (EVestG).

Diagnosis of Alzheimer's disease (AD) from AD with cerebrovascular disease pathology (AD-CVD) is a rising challenge. Using electrovestibulography (EVestG) measured signals, we develop an automated feature extraction and selection algorithm for an unbiased identification of AD and AD-CVD from healthy controls as well as their separation from each other. EVestG signals of 24 healthy controls, 16 individuals with AD, and 13 with AD-CVD were analyzed within two separate groupings: One-versus-One and One-versus-All.