Evidence map›Paper›PMID 37456720›Full record

ReviewFrontiers in bioengineering and biotechnology2023

Current development of biosensing technologies towards diagnosis of mental diseases.

Yuhan Zheng, Chen Liu, Nai Yeen Gavin Lai, Qingfeng Wang, Qinghua Xia, Xu Sun, Sheng Zhang

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in bioengineering and biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 14% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Review
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

7 authors at 2 institutions in 1 country.

Yuhan ZhengFaculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo, China.
Chen LiuFaculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo, China.
Nai Yeen Gavin LaiFaculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo, China.
Qingfeng WangNottingham Ningbo China Beacons of Excellence Research and Innovation Institute, University of Nottingham Ningbo China, Ningbo, China.
Qinghua XiaNingbo Research Center, Ningbo Innovation Center, Zhejiang University, Ningbo, China.
Xu SunFaculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo, China.
Sheng ZhangFaculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo, China.
University of Nottingham Ningbo China · CNNingbo University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The biosensor is an instrument that converts the concentration of biomarkers into electrical signals for detection. Biosensing technology is non-invasive, lightweight, automated, and biocompatible in nature. These features have significantly advanced medical diagnosis, particularly in the diagnosis of mental disorder in recent years. The traditional method of diagnosing mental disorders is time-intensive, expensive, and subject to individual interpretation. It involves a combination of the clinical experience by the psychiatrist and the physical symptoms and self-reported scales provided by the patient. Biosensors on the other hand can objectively and continually detect disease states by monitoring abnormal data in biomarkers. Hence, this paper reviews the application of biosensors in the detection of mental diseases, and the diagnostic methods are divided into five sub-themes of biosensors based on vision, EEG signal, EOG signal, and multi-signal. A prospective application in clinical diagnosis is also discussed.

Indexed as

biosensorsdiagnosis methodEEG signalsEOG signalseye-trackingmental diseasesvirtual reality

Identifiers

PMID37456720
PMCPMC10342212
OpenAlexW4382600573

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.