Evidence map›Paper›PMID 32182928›Full record

ArticleSensors (Basel, Switzerland)2020

Electronic Skin Wearable Sensors for Detecting Lumbar-Pelvic Movements.

Yuxin Zhang, Pari Delir Haghighi, Frada Burstein, Lim Wei Yap, Wenlong Cheng, Lina Yao, Flavia Cicuttini

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.8field-weighted citation impact, top 16% 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

16 citing papers in PubMed, 41 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

7 authors at 2 institutions in 1 country.

Yuxin ZhangFaculty of Information Technology, Monash University, Melbourne, VIC 3145, Australia.ORCID 0000-0002-7636-4084
Pari Delir HaghighiFaculty of Information Technology, Monash University, Melbourne, VIC 3145, Australia.ORCID 0000-0001-9922-1214
Frada BursteinFaculty of Information Technology, Monash University, Melbourne, VIC 3145, Australia.ORCID 0000-0001-8258-0878
Lim Wei YapDepartment of Chemical Engineering, Monash University, Melbourne, VIC 3800, Australia.ORCID 0000-0003-3072-6307
Wenlong ChengDepartment of Chemical Engineering, Monash University, Melbourne, VIC 3800, Australia.
Lina YaoSchool of Computer Science and Engineering, The University of New South Wales, Sydney, NSW 2052, Australia.
Flavia CicuttiniDepartment of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia.
Monash University · AUUNSW Sydney · AU

Funding

Monash University Institute for Medical engineering (MIME) Funding 2920684
6 · The paper itself

Abstract

backgroundA nanomaterial-based electronic-skin (E-Skin) wearable sensor has been successfully used for detecting and measuring body movements such as finger movement and foot pressure. The ultrathin and highly sensitive characteristics of E-Skin sensor make it a suitable alternative for continuously out-of-hospital lumbar-pelvic movement (LPM) monitoring. Monitoring these movements can help medical experts better understand individuals' low back pain experience. However, there is a lack of prior studies in this research area. Therefore, this paper explores the potential of E-Skin sensors to detect and measure the anatomical angles of lumbar-pelvic movements by building a linear relationship model to compare its performance to clinically validated inertial measurement unit (IMU)-based sensing system (ViMove).

methodsThe paper first presents a review and classification of existing wireless sensing technologies for monitoring of body movements, and then it describes a series of experiments performed with E-Skin sensors for detecting five standard LPMs including flexion, extension, pelvic tilt, lateral flexion, and rotation, and measure their anatomical angles. The outputs of both E-Skin and ViMove sensors were recorded during each experiment and further analysed to build the comparative models to evaluate the performance of detecting and measuring LPMs.

resultsE-Skin sensor outputs showed a persistently repeating pattern for each movement. Due to the ability to sense minor skin deformation by E-skin sensor, its reaction time in detecting lumbar-pelvic movement is quicker than ViMove by ~1 s.

conclusionsE-Skin sensors offer new capabilities for detecting and measuring lumbar-pelvic movements. They have lower cost compared to commercially available IMU-based systems and their non-invasive highly stretchable characteristic makes them more comfortable for long-term use. These features make them a suitable sensing technology for developing continuous, out-of-hospital real-time monitoring and management systems for individuals with low back pain.

Indexed as

Monitoring, PhysiologicWearable Electronic DevicesAdultEquipment DesignFemaleHumansLumbosacral RegionMaleMovementNanostructuresPelvisSpineYoung AdultE-Skin sensorsmonitoringmovement detectionwireless sensing technology

Identifiers

PMID32182928
PMCPMC7085722
OpenAlexW3009191660

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.