Evidence map›Paper›PMID 38139502›Full record

ArticleSensors (Basel, Switzerland)2023

Textile-Based Body Capacitive Sensing for Knee Angle Monitoring.

Valeria Galli, Chakaveh Ahmadizadeh, Raffael Kunz, Carlo Menon

Open access · goldAbstract 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
0.5field-weighted citation impact, top 37% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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 1 institution in 1 country.

Valeria GalliBiomedical and Mobile Health Technology Laboratory, Department of Health Science and Technology, ETH Zurich, Balgrist Campus, Lengghalde 5, 8008 Zürich, Switzerland.ORCID 0000-0001-8522-3251
Chakaveh AhmadizadehBiomedical and Mobile Health Technology Laboratory, Department of Health Science and Technology, ETH Zurich, Balgrist Campus, Lengghalde 5, 8008 Zürich, Switzerland.
Raffael KunzBiomedical and Mobile Health Technology Laboratory, Department of Health Science and Technology, ETH Zurich, Balgrist Campus, Lengghalde 5, 8008 Zürich, Switzerland.
Carlo MenonBiomedical and Mobile Health Technology Laboratory, Department of Health Science and Technology, ETH Zurich, Balgrist Campus, Lengghalde 5, 8008 Zürich, Switzerland.ORCID 0000-0002-2309-9977
ETH Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Monitoring human movement is highly relevant in mobile health applications. Textile-based wearable solutions have the potential for continuous and unobtrusive monitoring. The precise estimation of joint angles is important in applications such as the prevention of osteoarthritis or in the assessment of the progress of physical rehabilitation. We propose a textile-based wearable device for knee angle estimation through capacitive sensors placed in different locations above the knee and in contact with the skin. We exploited this modality to enhance the baseline value of the capacitive sensors, hence facilitating readout. Moreover, the sensors are fabricated with only one layer of conductive fabric, which facilitates the design and realization of the wearable device. We observed the capability of our system to predict knee sagittal angle in comparison to gold-standard optical motion capture during knee flexion from a seated position and squats: the results showed an R

Indexed as

KneeWearable Electronic DevicesHumansKnee JointMovementTextilesmotion capturesmart clothingstrain sensortextile sensorwearable technology

Identifiers

PMID38139502
PMCPMC10747625
OpenAlexW4389381310

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.