Literature DB >> 34205793

Intelligent Sensing Technologies for the Diagnosis, Monitoring and Therapy of Alzheimer's Disease: A Systematic Review.

Nazia Gillani1, Tughrul Arslan1.   

Abstract

Alzheimer's disease is a lifelong progressive neurological disorder. It is associated with high disease management and caregiver costs. Intelligent sensing systems have the capability to provide context-aware adaptive feedback. These can assist Alzheimer's patients with, continuous monitoring, functional support and timely therapeutic interventions for whom these are of paramount importance. This review aims to present a summary of such systems reported in the extant literature for the management of Alzheimer's disease. Four databases were searched, and 253 English language articles were identified published between the years 2015 to 2020. Through a series of filtering mechanisms, 20 articles were found suitable to be included in this review. This study gives an overview of the depth and breadth of the efficacy as well as the limitations of these intelligent systems proposed for Alzheimer's. Results indicate two broad categories of intelligent technologies, distributed systems and self-contained devices. Distributed systems base their outcomes mostly on long-term monitoring activity patterns of individuals whereas handheld devices give quick assessments through touch, vision and voice. The review concludes by discussing the potential of these intelligent technologies for clinical practice while highlighting future considerations for improvements in the design of these solutions for Alzheimer's disease.

Entities:  

Keywords:  Alzheimer’s disease; activity monitoring; intelligent sensors; remote health monitoring; robots; smart devices; smart homes; smart sensors; user-centred design

Year:  2021        PMID: 34205793     DOI: 10.3390/s21124249

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  1 in total

Review 1.  A Novel Explainability Approach for Technology-Driven Translational Research on Brain Aging.

Authors:  Adam Turnbull; Robert M Kaplan; Ehsan Adeli; Feng V Lin
Journal:  J Alzheimers Dis       Date:  2022       Impact factor: 4.160

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.