Reliability of quantitative EEG features.

Clin Neurophysiol

Department of Computer Science, University of Iceland, Reykjavik, Iceland.

Published: October 2007

Objective: To investigate the reliability of several well-known quantitative EEG (qEEG) features in the elderly in the resting, eyes closed condition and study the effects of epoch length and channel derivations on reliability.

Methods: Fifteen healthy adults, over 50 years of age, underwent 10 EEG recordings over a 2-month period. Various qEEG features derived from power spectral, coherence, entropy and complexity analysis of the EEG were computed. Reliability was quantified using an intraclass correlation coefficient.

Results: The highest reliability was obtained with the average montage, reliability increased with epoch length up to 40s, longer epochs gave only marginal improvement. The reliability of the qEEG features was highest for power spectral parameters, followed by regularity measures based on entropy and complexity, coherence being least reliable.

Conclusions: Montage and epoch length had considerable effects on reliability. Several apparently unrelated regularity measures had similar stability. Reliability of coherence measures was strongly dependent on channel location and frequency bands.

Significance: The reliability of regularity measures has until now received limited attention. Low reliability of coherence measures in general may limit their usefulness in the clinical setting.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.clinph.2007.06.018DOI Listing

Publication Analysis

Top Keywords

qeeg features
12
epoch length
12
regularity measures
12
reliability
10
quantitative eeg
8
power spectral
8
entropy complexity
8
reliability coherence
8
coherence measures
8
measures
5

Similar Publications

Complex childhood trauma (CCT) involves prolonged exposure to severe interpersonal stressors, leading to deficits in executive functioning and self-regulation during adolescence, a critical period for neurodevelopment. While qEEG parameters, particularly alpha oscillations, have been proposed as potential biomarkers for trauma, empirical documentation in developmental samples is limited. .

View Article and Find Full Text PDF

Quantitative electroencephalography predicts postoperative delirium in adult cardiac surgical patients from a prospective observational study.

Sci Rep

December 2024

State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing, 210009, China.

The diagnostic and prognostic value of quantitative electroencephalogram (qEEG) in the the onset of postoperative delirium (POD) remains an area of inquiry. We aim to determine whether qEEG could assist in the diagnosis of early POD in cardiac surgery patients. We prospectively studied a cohort of cardiac surgery patients undergoing qEEG for evaluation of altered mental status.

View Article and Find Full Text PDF

Objective: to conduct a clinical and neurophysiological study of Chornobyl clean-up workers and military personnelof the Armed Forces of Ukraine (AFU) with previous coronavirus disease (COVID-19) and individuals of the comparison groups to study the impact of long-term effects of ionizing radiation, psychoemotional stress and previouscoronavirus infection on cerebral functioning.

Materials And Methods: A prospective clinical study of Chornobyl clean-up workers and servicemen of the ArmedForces of Ukraine (AFU) who had coronavirus disease (COVID-19) and individuals of the comparison groups. Themain group - 30 males participated in liquidating the consequences of the Chornobyl Nuclear Power Plant (ChNPP)accident with previously verified COVID-19 (Chornobyl clean-up workers).

View Article and Find Full Text PDF

Persistent motor deficits are highly prevalent among post-stroke survivors, contributing significantly to disability. Despite the prevalence of these deficits, the precise mechanisms underlying motor recovery after stroke remain largely elusive. The exploration of motor system reorganization using functional neuroimaging techniques represents a compelling yet challenging avenue of research.

View Article and Find Full Text PDF

Purpose: This study aims to investigate using eyes-open (EO) and eyes-closed (EC) resting-state EEG data to diagnose cognitive impairment using machine learning methods, enhancing timely intervention and cost-effectiveness in dementia research.

Participants And Methods: A total of 890 participants aged 40-90 were included in the study, comprising 269 healthy controls (HC), 356 individuals with mild cognitive impairment (MCI), and 265 with Alzheimer's disease (AD) from a cohort study. Resting-state EEG (rEEG) signals were recorded and transformed into relative power spectral density (PSD) data for analysis.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!