Abstract

Age-related changes in the brain’s electrical activity can be caused by healthy aging and brain disorders. The ability to detect such phenomena from an electroencephalogram (EEG) is important to identify diseases’ latent stages. These changes appear in the brain’s background electrical activity, but the performance of cognitive or motor tasks can cause more significant signs of impairments in brain dynamics. Here, we analyze the features of multichannel EEGs in groups of healthy elderly and younger adults during hand clenching and apply two wavelet-based methods to reveal distinctions that arise with age, namely multiresolution analysis using the discrete wavelet transform, and multifractal formalism, which involves extracting the skeleton of the continuous wavelet transform. With the first method, we demonstrate that inter-group differences are established at rest and during the performance of motor tasks. With the second method, we also find similar distinctions, although the number of suitable channels and their distribution can differ. We conclude that characterization of age-related differences depends on the wavelet-based method used for EEG processing.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call