Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder of the brain that ultimately results in the death of neurons and dementia. The prevalence of the disease in the world is increasing rapidly. In recent years, many studies have been done to automatically detect this disease from brain signals. Method: In this paper, the Hjorth parameters are used along with other common features to improve the AD detection accuracy from EEG signals in early stages.
The use of advanced technological solutions (“neurotechnologies”) can improve the clinical outcomes of neurorehabilitation after stroke. Here, Micera et al. propose a paradigm shift that is based on a deep understanding of the basic mechanisms of natural stroke recovery and technology-assisted neurorehabilitation to improve the clinical effectiveness of neurotechnology.
