Evidence map›Paper›PMID 35323409›Full record

ArticleBiosensors2022

A Flexible, Wearable, and Wireless Biosensor Patch with Internet of Medical Things Applications.

Duc Tri Phan, Cong Hoan Nguyen, Thuy Dung Pham Nguyen, Le Hai Tran, Sumin Park, Jaeyeop Choi, Byeong-Il Lee, Junghwan Oh

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 pooled it
5.8field-weighted citation impact, top 3% 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

26 citing papers in PubMed, 2 syntheses or guidelines pooled it, 80 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Duc Tri PhanIndustry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan 48513, Korea.
Cong Hoan NguyenIndustry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan 48513, Korea.
Thuy Dung Pham NguyenIndustry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan 48513, Korea.ORCID 0000-0003-2396-9474
Le Hai TranIndustry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan 48513, Korea.
Sumin ParkIndustry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan 48513, Korea.
Jaeyeop ChoiIndustry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan 48513, Korea.
Byeong-Il LeeDepartment of Smart Healthcare, Pukyong National University, Busan 48513, Korea.
Junghwan OhIndustry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan 48513, Korea.ORCID 0000-0002-5837-0958
Pukyong National University · KR

Funding

Pukyong National University Development Project Research Fund(Philosopher of Next Generation) 2021
6 · The paper itself

Abstract

Monitoring the vital signs and physiological responses of the human body in daily activities is particularly useful for the early diagnosis and prevention of cardiovascular diseases. Here, we proposed a wireless and flexible biosensor patch for continuous and longitudinal monitoring of different physiological signals, including body temperature, blood pressure (BP), and electrocardiography. Moreover, these modalities for tracking body movement and GPS locations for emergency rescue have been included in biosensor devices. We optimized the flexible patch design with high mechanical stretchability and compatibility that can provide reliable and long-term attachment to the curved skin surface. Regarding smart healthcare applications, this research presents an Internet of Things-connected healthcare platform consisting of a smartphone application, website service, database server, and mobile gateway. The IoT platform has the potential to reduce the demand for medical resources and enhance the quality of healthcare services. To further address the advances in non-invasive continuous BP monitoring, an optimized deep learning architecture with one-channel electrocardiogram signals is introduced. The performance of the BP estimation model was verified using an independent dataset; this experimental result satisfied the Association for the Advancement of Medical Instrumentation, and the British Hypertension Society standards for BP monitoring devices. The experimental results demonstrated the practical application of the wireless and flexible biosensor patch for continuous physiological signal monitoring with Internet of Medical Things-connected healthcare applications.

Indexed as

Biosensing TechniquesWearable Electronic DevicesBlood PressureHumansInternetMonitoring, Physiologicartificial neural network (ANN)biosensorsInternet of Medical Things (IoMT)physiological signals

Identifiers

PMID35323409
PMCPMC8945966
OpenAlexW4213418584

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.