Evidence map›Paper›PMID 38005436›Full record

ReviewSensors (Basel, Switzerland)2023

Sensor-Based Wearable Systems for Monitoring Human Motion and Posture: A Review.

Xinxin Huang, Yunan Xue, Shuyun Ren, Fei Wang

Open access · goldAbstract readReview
In one paragraph

Review 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 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
28.7field-weighted citation impact, top 1% 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

36 citing papers in PubMed, 86 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

4 authors at 2 institutions in 1 country.

Xinxin HuangGuangdong Modern Apparel Technology & Engineering Center, Guangdong University of Technology, Guangzhou 510075, China.ORCID 0000-0001-7237-0316
Yunan XueGuangdong Modern Apparel Technology & Engineering Center, Guangdong University of Technology, Guangzhou 510075, China.
Shuyun RenGuangdong Modern Apparel Technology & Engineering Center, Guangdong University of Technology, Guangzhou 510075, China.
Fei WangSchool of Textile Materials and Engineering, Wuyi University, Jiangmen 529020, China.ORCID 0000-0002-6801-0470
Guangdong University of Technology · CNWuyi University · CN

Funding

High-level Talent Start-up Scheme of Wuyi University 2021AL034Natural Science Foundation of Guangdong Province 2022A15150115Regional Joint Fund of Guangdong Province 2021A1515110445Youth foundation for Humanities and Social Science Projects of the Ministry of Education of China 22YJCZH063
6 · The paper itself

Abstract

In recent years, marked progress has been made in wearable technology for human motion and posture recognition in the areas of assisted training, medical health, VR/AR, etc. This paper systematically reviews the status quo of wearable sensing systems for human motion capture and posture recognition from three aspects, which are monitoring indicators, sensors, and system design. In particular, it summarizes the monitoring indicators closely related to human posture changes, such as trunk, joints, and limbs, and analyzes in detail the types, numbers, locations, installation methods, and advantages and disadvantages of sensors in different monitoring systems. Finally, it is concluded that future research in this area will emphasize monitoring accuracy, data security, wearing comfort, and durability. This review provides a reference for the future development of wearable sensing systems for human motion capture.

Indexed as

PostureWearable Electronic DevicesHumansMonitoring, PhysiologicMotionMotion Capturemotion captureposture recognitionwearable sensorswearable systems

Identifiers

PMID38005436
PMCPMC10675437
OpenAlexW4388534647

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.