A Survey of Alzheimer’s Disease Early Diagnosis Methods for Cognitive Assessment

Abstract

Dementia is a syndrome that is characterised by the decline of different cognitive abilities. A high rate of deaths and high cost for detection, treatments, and patients care count amongst its consequences. Although there is no cure for dementia, a timely diagnosis helps in obtaining necessary support, appropriate medication, and maintenance, as far as possible, of engagement in intellectual, social, and physical activities. The early detection of Alzheimer Disease (AD) is considered to be of high importance for improving the quality of life of patients and their families. In particular, Virtual Reality (VR) is an expanding tool that can be used in order to assess cognitive abilities while navigating through a Virtual Environment (VE). The paper summarises common AD screening and diagnosis techniques focusing on the latest approaches that are based on Virtual Environments, behaviour analysis, and emotions recognition, aiming to provide more reliable and non-invasive diagnostics at home or in a clinical environment. Furthermore, different AD diagnosis evaluation methods and metrics are presented and discussed together with an overview of the different datasets.

Inflammasome NLRP3 Potentially Links Obesity-Associated Low-Grade Systemic Inflammation and Insulin Resistance with Alzheimer’s Disease

“…The first, early symptoms of AD have been associated with the loss of episodic memory and difficulties in learning new information. When AD progresses, there is greater memory loss, cognitive impairment, and behavioral change, along with dysfunction of language and speech [ 16 , 17 ].…”

Epidemiology of Alzheimer’s disease in the Odesa region

“…Cognitive testing is useful not only to assist in diagnosing dementia, but also as an objective baseline for tracking changes over a period of time. Finally, cognitive test is also helpful in monitoring treatment response [1,2,5,[25][26][27][28][29][30].…”

Development and Validation of a Deep Learning Model for Earlier Detection of Cognitive Decline From Clinical Notes in Electronic Health Records

“… 2 , 3 , 4 Early detection of cognitive decline can facilitate enrollment in clinical trials and early interventions. 5 , 6 The US Food and Drug Administration recently approved aducanumab, a drug directed at the underlying pathologic characteristics of AD that clears amyloid plaques in the brain, to treat patients with AD. 7 However, detecting patients with cognitive decline is challenging.…”

“…Mild cognitive impairment (MCI) and subjective cognitive decline (SCD) represent precursor stages that can serve as targets for early treatment . Early detection of cognitive decline can facilitate enrollment in clinical trials and early interventions . The US Food and Drug Administration recently approved aducanumab, a drug directed at the underlying pathologic characteristics of AD that clears amyloid plaques in the brain, to treat patients with AD .…”