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Sun X, Sun X, Wang Q, Wang X, Feng L, Yang Y, Jing Y, Yang C, Zhang S. Biosensors toward behavior detection in diagnosis of alzheimer’s disease. Front Bioeng Biotechnol 2022; 10:1031833. [PMID: 36338126 PMCID: PMC9626796 DOI: 10.3389/fbioe.2022.1031833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 10/03/2022] [Indexed: 11/30/2022] Open
Abstract
In recent years, a huge number of individuals all over the world, elderly people, in particular, have been suffering from Alzheimer’s disease (AD), which has had a significant negative impact on their quality of life. To intervene early in the progression of the disease, accurate, convenient, and low-cost detection technologies are gaining increased attention. As a result of their multiple merits in the detection and assessment of AD, biosensors are being frequently utilized in this field. Behavioral detection is a prospective way to diagnose AD at an early stage, which is a more objective and quantitative approach than conventional neuropsychological scales. Furthermore, it provides a safer and more comfortable environment than those invasive methods (such as blood and cerebrospinal fluid tests) and is more economical than neuroimaging tests. Behavior detection is gaining increasing attention in AD diagnosis. In this review, cutting-edge biosensor-based devices for AD diagnosis together with their measurement parameters and diagnostic effectiveness have been discussed in four application subtopics: body movement behavior detection, eye movement behavior detection, speech behavior detection, and multi-behavior detection. Finally, the characteristics of behavior detection sensors in various application scenarios are summarized and the prospects of their application in AD diagnostics are presented as well.
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Affiliation(s)
- Xiaotong Sun
- Ningbo Innovation Center, School of Mechanical Engineering, Zhejiang University, Ningbo, China
- Faculty of Science and Engineering, University of Nottingham Ningbo, Ningbo, China
| | - Xu Sun
- Faculty of Science and Engineering, University of Nottingham Ningbo, Ningbo, China
- Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, University of Nottingham Ningbo, Ningbo, China
- *Correspondence: Sheng Zhang, ; Xu Sun,
| | - Qingfeng Wang
- Nottingham University Business School China, University of Nottingham Ningbo China, Ningbo, Zhejiang, China
| | - Xiang Wang
- Ningbo Innovation Center, School of Mechanical Engineering, Zhejiang University, Ningbo, China
- Faculty of Science and Engineering, University of Nottingham Ningbo, Ningbo, China
| | - Luying Feng
- Ningbo Innovation Center, School of Mechanical Engineering, Zhejiang University, Ningbo, China
| | - Yifan Yang
- Ningbo Innovation Center, School of Mechanical Engineering, Zhejiang University, Ningbo, China
- Faculty of Science and Engineering, University of Nottingham Ningbo, Ningbo, China
| | - Ying Jing
- Business School, NingboTech University, Ningbo, China
| | - Canjun Yang
- Ningbo Innovation Center, School of Mechanical Engineering, Zhejiang University, Ningbo, China
| | - Sheng Zhang
- Ningbo Innovation Center, School of Mechanical Engineering, Zhejiang University, Ningbo, China
- Faculty of Science and Engineering, University of Nottingham Ningbo, Ningbo, China
- *Correspondence: Sheng Zhang, ; Xu Sun,
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