Evidence map›Paper›PMID 38573175›Full record

ReviewAdvanced healthcare materials2024

Recent Trends of Bioanalytical Sensors with Smart Health Monitoring Systems: From Materials to Applications.

Thi Sinh Vo, Trung Hoang, Tran Thi Bich Chau Vo, Byounghyun Jeon, Vu Hoang Nguyen, Kyunghoon Kim

Abstract readReview
In one paragraph

Review in Advanced healthcare materials, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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. Article
  2. Article
  3. Review
  4. Article
  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

6 authors.

Thi Sinh VoSchool of Mechanical Engineering, Sungkyunkwan University, Suwon, 16419, South Korea.ORCID 0000-0003-3830-0474
Trung HoangDepartment of Biophysics, Sungkyunkwan University, Suwon, 16419, South Korea.ORCID 0000-0003-2158-0641
Tran Thi Bich Chau VoFaculty of Industrial Management, College of Engineering, Can Tho University, Can Tho, 900000, Vietnam.ORCID 0000-0002-3049-2080
Byounghyun JeonSchool of Mechanical Engineering, Sungkyunkwan University, Suwon, 16419, South Korea.ORCID 0009-0002-8257-0156
Vu Hoang NguyenDepartment of Mechanical and Aerospace Engineering, Monash University, Clayton, VIC, 3800, Australia.ORCID 0009-0002-6539-0751
Kyunghoon KimSchool of Mechanical Engineering, Sungkyunkwan University, Suwon, 16419, South Korea.ORCID 0000-0001-8034-947X

Funding

National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) NRF-2023R1A2C2005617
6 · The paper itself

Abstract

Smart biosensors attract significant interest due to real-time monitoring of user health status, where bioanalytical electronic devices designed to detect various activities and biomarkers in the human body have potential applications in physical sign monitoring and health care. Bioelectronics can be well integrated by output signals with wireless communication modules for transferring data to portable devices used as smart biosensors in performing real-time diagnosis and analysis. In this review, the scientific keys of biosensing devices and the current trends in the field of smart biosensors, (functional materials, technological approaches, sensing mechanisms, main roles, potential applications and challenges in health monitoring) will be summarized. Recent advances in the design and manufacturing of bioanalytical sensors with smarter capabilities and enhanced reliability indicate a forthcoming expansion of these smart devices from laboratory to clinical analysis. Therefore, a general description of functional materials and technological approaches used in bioelectronics will be presented after the sections of scientific keys to bioanalytical sensors. A careful introduction to the established systems of smart monitoring and prediction analysis using bioelectronics, regarding the integration of machine-learning-based basic algorithms, will be discussed. Afterward, applications and challenges in development using these smart bioelectronics in biological, clinical, and medical diagnostics will also be analyzed. Finally, the review will conclude with outlooks of smart biosensing devices assisted by machine learning algorithms, wireless communications, or smartphone-based systems on current trends and challenges for future works in wearable health monitoring.

Indexed as

Biosensing TechniquesHumansMachine LearningMonitoring, PhysiologicWearable Electronic DevicesWireless Technologybioanalytical sensorhealth monitoringmachine learningsmart biosensor

Identifiers

PMID38573175
PMCPMC11468404

What OpenQuestion holds

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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.