Evidence map›Paper›PMID 36338126›Full record

ReviewFrontiers in bioengineering and biotechnology2022

Biosensors toward behavior detection in diagnosis of alzheimer's disease.

Xiaotong Sun, Xu Sun, Qingfeng Wang, Xiang Wang, Luying Feng, Yifan Yang, Ying Jing, Canjun Yang, Sheng Zhang

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in bioengineering and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.

  1. Pooled it
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  4. Review
  5. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Xiaotong SunNingbo Innovation Center, School of Mechanical Engineering, Zhejiang University, Ningbo, China.
Xu SunFaculty of Science and Engineering, University of Nottingham Ningbo, Ningbo, China.
Qingfeng WangNottingham University Business School China, University of Nottingham Ningbo China, Ningbo, Zhejiang, China.
Xiang WangNingbo Innovation Center, School of Mechanical Engineering, Zhejiang University, Ningbo, China.
Luying FengNingbo Innovation Center, School of Mechanical Engineering, Zhejiang University, Ningbo, China.
Yifan YangNingbo Innovation Center, School of Mechanical Engineering, Zhejiang University, Ningbo, China.
Ying JingBusiness School, NingboTech University, Ningbo, China.
Canjun YangNingbo Innovation Center, School of Mechanical Engineering, Zhejiang University, Ningbo, China.
Sheng ZhangNingbo Innovation Center, School of Mechanical Engineering, Zhejiang University, Ningbo, China.
Ningbo University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

alzheimer’s diseasebehavior detectionbiosensorsdiagnosiselderly

Identifiers

PMID36338126
PMCPMC9626796
OpenAlexW4306843939

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.