ArticleSensors (Basel, Switzerland)2020
Age-Related Distinctions in EEG Signals during Execution of Motor Tasks Characterized in Terms of Long-Range Correlations.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 28 citations in OpenAlex.
- Long-range temporal correlations in resting state alpha oscillations in major depressive disorder and obsessive-compulsive disorder.Frontiers in neuroinformatics · 2024Article
- Characterization of Anesthesia in Rats from EEG in Terms of Long-Range Correlations.Diagnostics (Basel, Switzerland) · 2023Article
- Extended Detrended Fluctuation Analysis of Coarse-Grained Time Series.Diagnostics (Basel, Switzerland) · 2022Article
- Analysis of the Relationship Between Motor Imagery and Age-Related Fatigue for CNN Classification of the EEG Data.Frontiers in aging neuroscience · 2022Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
The problem of revealing age-related distinctions in multichannel electroencephalograms (EEGs) during the execution of motor tasks in young and elderly adults is addressed herein. Based on the detrended fluctuation analysis (DFA), differences in long-range correlations are considered, emphasizing changes in the scaling exponent α. Stronger responses in elderly subjects are confirmed, including the range and rate of increase in α. Unlike elderly subjects, young adults demonstrated about 2.5 times more pronounced differences between motor task responses with the dominant and non-dominant hand. Knowledge of age-related changes in brain electrical activity is important for understanding consequences of healthy aging and distinguishing them from pathological changes associated with brain diseases. Besides diagnosing age-related effects, the potential of DFA can also be used in the field of brain-computer interfaces.
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