The role of EEG signal processing in detection of neurocognitive disorders

Abstract

Early diagnosis of neurocognitive disorders (NCD) has become vital because the number of patients with NCD has increased rapidly with the ageing population worldwide. Dementia (major NCD) is one of the factors that cause disability in late-life. Due to various neurological conditions, types and cognitive factors, the diagnosis of any NCD has become a difficult and complex task to achieve. Thus, diagnoses of NCD require a combination of an extensive cognitive assessment and the screening of the possible causes along with EEG analysis which provides promising complete neurological examination. EEG based diagnosis approach is economical, portable and can be used to diagnose mass population. Apart from this, EEG analysis also helps to investigate the brain activation during the cognitive task performance. This paper reviews several linear and non-linear signal processing methods for the diagnosis of NCD and their cause like Alzheimer's disease (AD), frontotemporal disease and vascular dementia (VaD) etc.