Standardized low-resolution brain electromagnetic tomography does not improve EEG Alzheimer's disease assessment.

Quantitative EEG has been shown to reflect neurodegenerative processes in Alzheimer's disease (AD) and may provide non-invasive and widely available biomarkers to enhance the objectivization of disease assessment. To address EEG's major drawback - its low spatial resolution - many studies have employed 3D source localization. However, none have investigated whether this complex mapping into 3D space actually adds value over standard surface derivation.

Improved automatic identification of isolated rapid eye movement sleep behavior disorder with a 3D time-of-flight camera.

Background And Purpose: Automatic 3D video analysis of the lower body during rapid eye movement (REM) sleep has been recently proposed as a novel tool for identifying people with isolated REM sleep behavior disorder (iRBD), but, so far, it has not been validated on unseen subjects. This study aims at validating this technology in a large cohort and at improving its performances by also including an analysis of movements in the head, hands and upper body.

Methods: Fifty-three people with iRBD and 128 people without RBD (of whom 89 had sleep disorders considered RBD differential diagnoses) were included in the study.

TeaSpam: A Novel Method of TEmporal And SPAtial Movement Encoding during Sleep.

Movements during sleep characterize sleep disorders, which can disturb sleep or its onset, impacting sleep quantity and quality. Video-polysomnography is the current gold standard to assess movements during sleep, but its availability is limited. Using data recorded with a 3D time of flight sensor, we developed a novel method of encoding temporal and spatial information of automatically identified movements during sleep.

Automatic 3D Video Analysis of Upper and Lower Body Movements to Identify Isolated REM Sleep Behavior Disorder: A Pilot Study.

Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia characterized by dream enactment, abnormal jerks and movements during REM sleep. Isolated RBD (iRBD) is recognized as the early stage of alpha-synucleinopathies, i.e.

Functional (un-)Coupling: Impairment, Compensation, and Future Progression in Alzheimer's Disease.

Functional (un-)coupling (task-related change of functional connectivity) between different sites of the brain is a mechanism of general importance for cognitive processes. In Alzheimer's disease (AD), prior research identified diminished cortical connectivity as a hallmark of the disease. However, little is known about the relation between the amount of functional (un-)coupling and cognitive performance and decline in AD.

Fidgety Philip and the Suggested Clinical Immobilization Test: Annotation data for developing a machine learning algorithm.

The cartoon Fidgety Philip, the banner of Western-ADHD diagnosis, depicts a 'restless' child exhibiting hyperactive-behaviors with hyper-arousability and/or hypermotor-restlessness (H-behaviors) during sitting. To overcome the gaps between differential diagnostic considerations and modern computing methodologies, we have developed a non-interpretative, neutral pictogram-guided phenotyping language (PG-PL) for describing body-segment movements during sitting (). To develop the PG-PL, seven research assistants annotated three original Fidgety Philip cartoons.

Is Fidgety Philip's ground truth also ours? The creation and application of a machine learning algorithm.

Background: Behavioral observations support clinical in-depth phenotyping but phenotyping and pattern recognition are affected by training background. As Attention Deficit Hyperactivity Disorder, Restless Legs syndrome/Willis Ekbom disease and medication induced activation syndromes (including increased irritability and/or akathisia), present with hyperactive-behaviors with hyper-arousability and/or hypermotor-restlessness (H-behaviors), we first developed a non-interpretative, neutral pictogram-guided phenotyping language (PG-PL) for describing body-segment movements during sitting.

Methodology & Results: The PG-PL was applied for annotating 12 1-min sitting-videos (inter-observer agreements >85%->97%) and these manual annotations were used as a ground truth to develop an automated algorithm using OpenPose, which locates skeletal landmarks in 2D video.

Automated 3D video analysis of lower limb movements during REM sleep: a new diagnostic tool for isolated REM sleep behavior disorder.

Study Objectives: The differentiation of isolated rapid eye movement (REM) sleep behavior disorder (iRBD) or its prodromal phase (prodromal RBD) from other disorders with motor activity during sleep is critical for identifying α-synucleinopathy in an early stage. Currently, definite RBD diagnosis requires video polysomnography (vPSG). The aim of this study was to evaluate automated 3D video analysis of leg movements during REM sleep as objective diagnostic tool for iRBD.

3D Camera and Pulse Oximeter for Respiratory Events Detection.

Objective: The purpose of this study was to derive a respiratory movement signal from a 3D time-of-flight camera and to investigate if it can be used in combination with SpO to detect respiratory events comparable to polysomnography (PSG) based detection.

Methods: We derived a respiratory signal from a 3D camera and developed a new algorithm that detects reduced respiratory movement and SpO desaturation to score respiratory events. The method was tested on 61 patients' synchronized 3D video and PSG recordings.

Contactless detection of periodic leg movements during sleep: A 3D video pilot study.

In clinical practice, the quality of polysomnographic recordings in children and patients with neurodegenerative diseases may be affected by sensor displacement and diminished total sleep time due to stress during the recording. In the present study, we investigated if contactless three-dimensional (3D) detection of periodic leg movements during sleep was comparable to polysomnography. We prospectively studied a sleep laboratory cohort from two Austrian sleep laboratories.

A Novel Approach to Assess Sleep-Related Rhythmic Movement Disorder in Children Using Automatic 3D Analysis.

Unlike other episodic sleep disorders in childhood, there are no agreed severity indices for rhythmic movement disorder. While movements can be characterized in detail by polysomnography, in our experience most children inhibit rhythmic movement during polysomnography. Actigraphy and home video allow assessment in the child's own environment, but both have limitations.

Neuroimaging markers of global cognition in early Alzheimer's disease: A magnetic resonance imaging-electroencephalography study.

Introduction: Magnetic resonance imaging (MRI) and electroencephalography (EEG) are a promising means to an objectified assessment of cognitive impairment in Alzheimer's disease (AD). Individually, however, these modalities tend to lack precision in both AD diagnosis and AD staging. A joint MRI-EEG approach that combines structural with functional information has the potential to overcome these limitations.

Associations of event-related brain potentials and Alzheimer's disease severity: A longitudinal study.

Background: So far, no cost-efficient, widely-used biomarkers have been established to facilitate the objectivization of Alzheimer's disease (AD) diagnosis and monitoring. Research suggests that event-related potentials (ERPs) reflect neurodegenerative processes in AD and might qualify as neurophysiological AD markers.

Objectives: First, to examine which ERP component correlates the most with AD severity, as measured by the Mini-Mental State Examination (MMSE).

A Blind Source-Based Method for Automated Artifact-Correction in Standard Sleep EEG.

Electroencephalogram (EEG) is a common tool in sleep medicine, but it is often compromised by non-neural artifacts. Excluding visually identified artifacts is time-consuming and removes relevant EEG information. Blind source separation (BSS) techniques, on the other hand, are capable of separating "brain" from "artifact source components".

Functional cortical source connectivity of resting state electroencephalographic alpha rhythms shows similar abnormalities in patients with mild cognitive impairment due to Alzheimer's and Parkinson's diseases.

Objective: This study tested the hypothesis that markers of functional cortical source connectivity of resting state eyes-closed electroencephalographic (rsEEG) rhythms may be abnormal in subjects with mild cognitive impairment due to Alzheimer's (ADMCI) and Parkinson's (PDMCI) diseases compared to healthy elderly subjects (Nold).

Methods: rsEEG data had been collected in ADMCI, PDMCI, and Nold subjects (N = 75 for any group). eLORETA freeware estimated functional lagged linear connectivity (LLC) from rsEEG cortical sources.

Abnormalities of Resting State Cortical EEG Rhythms in Subjects with Mild Cognitive Impairment Due to Alzheimer's and Lewy Body Diseases.

The present study tested the hypothesis that cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms reveal different abnormalities in cortical neural synchronization in groups of patients with mild cognitive impairment due to Alzheimer's disease (ADMCI) and dementia with Lewy bodies (DLBMCI) as compared to cognitively normal elderly (Nold) subjects. Clinical and rsEEG data in 30 ADMCI, 23 DLBMCI, and 30 Nold subjects were available in an international archive. Age, gender, and education were carefully matched in the three groups.

A flexible method for the automated offline-detection of artifacts in multi-channel electroencephalogram recordings.

Electroencephalogram (EEG) signal quality is often compromised by artifacts that corrupt quantitative EEG measurements used in clinical applications and EEG-related studies. Techniques such as filtering, regression analysis and blind source separation are often used to remove these artifacts. However, these preprocessing steps do not allow for complete artifact correction.

Predicting rapid cognitive decline in Alzheimer's disease patients using quantitative EEG markers and neuropsychological test scores.

Alzheimer's Disease (AD) can take different courses: some patients remain relatively stable while others decline rapidly within a given period of time. Losing more than 3 Mini-Mental State Examination (MMSE) points in one year is classified as rapid cognitive decline (RCD). This study used neuropsychological test scores and quantitative EEG (QEEG) markers obtained at a baseline examination to identify if an AD patient will be suffering from RCD.

3D detection of periodic limb movements in sleep.

The standard polysomnographic method for detecting periodic limb movements in sleep (PLMS) includes measuring the electromyography (EMG) signals from electrodes at the left and right tibialis anterior muscles. This procedure has disadvantages as the cabling affects the patients quality of sleep and the electrodes tend to come off during the night, deteriorating data quality. We used contactless monitoring of body movements by a 3D time-of-flight camera mounted above the bed.

Differential diagnosis between patients with probable Alzheimer's disease, Parkinson's disease dementia, or dementia with Lewy bodies and frontotemporal dementia, behavioral variant, using quantitative electroencephalographic features.

The objective of this work was to develop and evaluate a classifier for differentiating probable Alzheimer's disease (AD) from Parkinson's disease dementia (PDD) or dementia with Lewy bodies (DLB) and from frontotemporal dementia, behavioral variant (bvFTD) based on quantitative electroencephalography (QEEG). We compared 25 QEEG features in 61 dementia patients (20 patients with probable AD, 20 patients with PDD or probable DLB (DLBPD), and 21 patients with bvFTD). Support vector machine classifiers were trained to distinguish among the three groups.

Quantifying synchrony patterns in the EEG of Alzheimer's patients with linear and non-linear connectivity markers.

We analyzed the relation of several synchrony markers in the electroencephalogram (EEG) and Alzheimer's disease (AD) severity as measured by Mini-Mental State Examination (MMSE) scores. The study sample consisted of 79 subjects diagnosed with probable AD. All subjects were participants in the PRODEM-Austria study.