Evidence map›Paper›PMID 34677328›Full record

ReviewBiosensors2021

Recent Advances on IoT-Assisted Wearable Sensor Systems for Healthcare Monitoring.

Shwetank Dattatraya Mamdiwar, Akshith R, Zainab Shakruwala, Utkarsh Chadha, Kathiravan Srinivasan, Chuan-Yu Chang

Abstract readReview
In one paragraph

Review in Biosensors, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 2 pooled it
–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

44 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

6 authors.

Shwetank Dattatraya MamdiwarSchool of Electronics Engineering, Vellore Institute of Technology (VIT), Vellore 632014, India.
Akshith RSchool of Electronics Engineering, Vellore Institute of Technology (VIT), Vellore 632014, India.
Zainab ShakruwalaSchool of Electronics Engineering, Vellore Institute of Technology (VIT), Vellore 632014, India.
Utkarsh ChadhaDepartment of Manufacturing Engineering, School of Mechanical Engineering, Vellore Institute of Technology (VIT), Vellore 632014, India.ORCID 0000-0002-5044-3761
Kathiravan SrinivasanSchool of Computer Science and Engineering, Vellore Institute of Technology (VIT), Vellore 632014, India.ORCID 0000-0002-9352-0237
Chuan-Yu ChangDepartment of Computer Science and Information Engineering, National Yunlin University of Science and Technology, Yunlin 64002, Taiwan.ORCID 0000-0001-9476-8130

Funding

Ministry of Education Higher Education Sprout ProjectMinistry of Science and Technology, Taiwan MOST109-2221-E-224-048- MY2
6 · The paper itself

Abstract

IoT has played an essential role in many industries over the last few decades. Recent advancements in the healthcare industry have made it possible to make healthcare accessible to more people and improve their overall health. The next step in healthcare is to integrate it with IoT-assisted wearable sensor systems seamlessly. This review rigorously discusses the various IoT architectures, different methods of data processing, transfer, and computing paradigms. It compiles various communication technologies and the devices commonly used in IoT-assisted wearable sensor systems and deals with its various applications in healthcare and their advantages to the world. A comparative analysis of all the wearable technology in healthcare is also discussed with tabulation of various research and technology. This review also analyses all the problems commonly faced in IoT-assisted wearable sensor systems and the specific issues that need to be tackled to optimize these systems in healthcare and describes the various future implementations that can be made to the architecture and the technology to improve the healthcare industry.

Indexed as

Wearable Electronic DevicesDelivery of Health CareHumanscloud systemsdata processinghealthcarehealthcare monitoringInternet of Thingssensorswearable devices

Identifiers

PMID34677328
PMCPMC8534204

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.