Evidence map›Paper›PMID 37837039›Full record

ArticleSensors (Basel, Switzerland)2023

Dynamic Characterization of a Low-Cost Fully and Continuously 3D Printed Capacitive Pressure-Sensing System for Plantar Pressure Measurements.

Andrew T Gothard, Jacob W Hott, Steven R Anton

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 35% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. Static and dynamic optimisation of fluid-filled responsive orthotic insoles.Biomechanics and modeling in mechanobiology · 2025
    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

3 authors at 1 institution in 1 country.

Andrew T GothardDynamic and Smart Systems Laboratory, Department of Mechanical Engineering, Tennessee Technological University, Cookeville, TN 38505, USA.ORCID 0009-0000-5990-1442
Jacob W HottDynamic and Smart Systems Laboratory, Department of Mechanical Engineering, Tennessee Technological University, Cookeville, TN 38505, USA.
Steven R AntonDynamic and Smart Systems Laboratory, Department of Mechanical Engineering, Tennessee Technological University, Cookeville, TN 38505, USA.ORCID 0000-0003-2777-5458
Tennessee Technological University · US

Funding

National Science Foundation 1757558
6 · The paper itself

Abstract

In orthopedics, the evaluation of footbed pressure distribution maps is a valuable gait analysis technique that aids physicians in diagnosing musculoskeletal and gait disorders. Recently, the use of pressure-sensing insoles to collect pressure distributions has become more popular due to the passive collection of natural gait data during daily activities and the reduction in physical strain experienced by patients. However, current pressure-sensing insoles face the limitations of low customizability and high cost. Previous works have shown the ability to construct customizable pressure-sensing insoles with capacitive sensors using fused-deposition modeling (FDM) 3D printing. This work explores the feasibility of low-cost fully and continuously 3D printed pressure sensors for pressure-sensing insoles using three sensor designs, which use flexible thermoplastic polyurethane (TPU) as the dielectric layer and either conductive TPU or conductive polylactic acid (PLA) for the conductive plates. The sensors are paired with a commercial capacitance-to-voltage converter board to form the sensing system. Dynamic sensor performance is evaluated via sinusoidal compressive tests at frequencies of 1, 3, 5, and 7 Hz, with pressure levels varying from 14.33 to 23.88, 33.43, 52.54, and 71.65 N/cm

Indexed as

GaitPolyestersElectric CapacitanceElectric ConductivityHumansPolyurethanesPrinting, Three-DimensionalPolyestersPolyurethanes3D printingdynamic sensor characterizationflexible capacitive pressure sensororthopedicsplantar pressure measurement

Identifiers

PMID37837039
PMCPMC10575072
OpenAlexW4387264678

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.