Evidence map›Paper›PMID 37420555›Full record

ArticleSensors (Basel, Switzerland)2023

Bluetooth-Based Healthcare Information and Medical Resource Management System.

Chao-Shu Chang, Tin-Hao Wu, Yu-Chi Wu, Chin-Chuan Han

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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

4 authors.

Chao-Shu ChangDepartment of Information Management, National United University, Miaoli 36003, Taiwan.
Tin-Hao WuDepartment of Information Management, National United University, Miaoli 36003, Taiwan.
Yu-Chi WuDepartment of Electrical Engineering, National United University, Miaoli 36003, Taiwan.ORCID 0000-0003-2821-2040
Chin-Chuan HanDepartment of Computer Science and Information Engineering, National United University, Miaoli 36003, Taiwan.

Funding

Ministry of Science and Technology, Taiwan MOST 109-2622-E-239-008
6 · The paper itself

Abstract

This paper presents a healthcare information and medical resource management platform utilizing wearable devices, physiological sensors, and an indoor positioning system (IPS). This platform provides medical healthcare information management based on the physiological information collected by wearable devices and Bluetooth data collectors. The Internet of Things (IoT) is constructed for this medical care purpose. The collected data are classified and used to monitor the status of patients in real time with a Secure MQTT mechanism. The measured physiological signals are also used for developing an IPS. When the patient is out of the safety zone, the IPS will send an alert message instantly by pushing the server to remind the caretaker, easing the caretaker's burden and offering extra protection for the patient. The presented system also provides medical resource management with the help of IPS. The medical equipment and devices can be tracked by IPS to tackle some equipment rental problems, such as lost and found. A platform for the medical staff work coordination information exchange and transmission is also developed to expedite the maintenance of medical equipment, providing the shared medical information to healthcare and management staff in a timely and transparent manner. The presented system in this paper will finally reduce the loading of medical staff during the COVID-19 pandemic period.

Indexed as

COVID-19Internet of ThingsWearable Electronic DevicesDelivery of Health CareHumansPandemicshealthcare informationindoor positioningInternet of Thingsmedical resource managementMQTTphysiological informationwearable devices

Identifiers

PMID37420555
PMCPMC10302901

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.