Wearable artificial intelligence biosensor networks.

Artificial intelligence Biosensor network Machine learning Smartphone-based readout Wearable biosensors

Journal

Biosensors & bioelectronics
ISSN: 1873-4235
Titre abrégé: Biosens Bioelectron
Pays: England
ID NLM: 9001289

Informations de publication

Date de publication:
01 Jan 2023
Historique:
received: 20 05 2022
revised: 12 10 2022
accepted: 16 10 2022
pubmed: 29 10 2022
medline: 29 10 2022
entrez: 28 10 2022
Statut: ppublish

Résumé

The demand for high-quality healthcare and well-being services is remarkably increasing due to the ageing global population and modern lifestyles. Recently, the integration of wearables and artificial intelligence (AI) has attracted extensive academic and technological attention for its powerful high-dimensional data processing of wearable biosensing networks. This work reviews the recent developments in AI-assisted wearable biosensing devices in disease diagnostics and fatigue monitoring demonstrating the trend towards personalised medicine with highly efficient, cost-effective, and accurate point-of-care diagnosis by finding hidden patterns in biosensing data and detecting abnormalities. The reliability of adaptive learning and synthetic data and data privacy still need further investigation to realise personalised medicine in the next decade. Due to the worldwide popularity of smartphones, they have been utilised for sensor readout, wireless data transfer, data processing and storage, result display, and cloud server communication leading to the development of smartphone-based biosensing systems. The recent advances have demonstrated a promising future for the healthcare system because of the increasing data processing power, transfer efficiency and storage capacity and diversifying functionalities.

Identifiants

pubmed: 36306563
pii: S0956-5663(22)00865-X
doi: 10.1016/j.bios.2022.114825
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

114825

Informations de copyright

Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Yihan Zhang (Y)

Department of Chemical Engineering, Imperial College London, South Kensington, London, SW7 2BU, UK.

Yubing Hu (Y)

Department of Chemical Engineering, Imperial College London, South Kensington, London, SW7 2BU, UK. Electronic address: yubing.hu@imperial.ac.uk.

Nan Jiang (N)

West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, China; Jinfeng Laboratory, Chongqing, 401329, China. Electronic address: jiangnansophia@scu.edu.cn.

Ali K Yetisen (AK)

Department of Chemical Engineering, Imperial College London, South Kensington, London, SW7 2BU, UK.

Classifications MeSH