Evidence map›Paper›PMID 33800949›Full record

ArticleSensors (Basel, Switzerland)2021

Modeling, Fabrication and Integration of Wearable Smart Sensors in a Monitoring Platform for Diabetic Patients.

Chiara De Pascali, Luca Francioso, Lucia Giampetruzzi, Gabriele Rescio, Maria Assunta Signore, Alessandro Leone, Pietro Siciliano

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 9% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. 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

7 authors at 1 institution in 1 country.

Chiara De PascaliNational Research Council of Italy, Institute for Microelectronics and Microsystems (CNR-IMM), 95121 Lecce, Italy.ORCID 0000-0002-2673-4593
Luca FranciosoNational Research Council of Italy, Institute for Microelectronics and Microsystems (CNR-IMM), 95121 Lecce, Italy.
Lucia GiampetruzziNational Research Council of Italy, Institute for Microelectronics and Microsystems (CNR-IMM), 95121 Lecce, Italy.
Gabriele RescioNational Research Council of Italy, Institute for Microelectronics and Microsystems (CNR-IMM), 95121 Lecce, Italy.
Maria Assunta SignoreNational Research Council of Italy, Institute for Microelectronics and Microsystems (CNR-IMM), 95121 Lecce, Italy.
Alessandro LeoneNational Research Council of Italy, Institute for Microelectronics and Microsystems (CNR-IMM), 95121 Lecce, Italy.ORCID 0000-0002-8970-3313
Pietro SicilianoNational Research Council of Italy, Institute for Microelectronics and Microsystems (CNR-IMM), 95121 Lecce, Italy.ORCID 0000-0002-1312-4593
National Research Council · IT

Funding

Ministero dell'Istruzione, dell'Università e della Ricerca ARS01_01120
6 · The paper itself

Abstract

The monitoring of some parameters, such as pressure loads, temperature, and glucose level in sweat on the plantar surface, is one of the most promising approaches for evaluating the health state of the diabetic foot and for preventing the onset of inflammatory events later degenerating in ulcerative lesions. This work presents the results of sensors microfabrication, experimental characterization and FEA-based thermal analysis of a 3D foot-insole model, aimed to advance in the development of a fully custom smart multisensory hardware-software monitoring platform for the diabetic foot. In this system, the simultaneous detection of temperature-, pressure- and sweat-based glucose level by means of full custom microfabricated sensors distributed on eight reading points of a smart insole will be possible, and the unit for data acquisition and wireless transmission will be fully integrated into the platform. Finite element analysis simulations, based on an accurate bioheat transfer model of the metabolic response of the foot tissue, demonstrated that subcutaneous inflamed lesions located up to the muscle layer, and ischemic damage located not below the reticular/fat layer, can be successfully detected. The microfabrication processes and preliminary results of functional characterization of flexible piezoelectric pressure sensors and glucose sensors are presented. Full custom pressure sensors generate an electric charge in the range 0-20 pC, proportional to the applied load in the range 0-4 N, with a figure of merit of 4.7 ± 1 GPa. The disposable glucose sensors exhibit a 0-6 mM (0-108 mg/dL) glucose concentration optimized linear response (for sweat-sensing), with a LOD of 3.27 µM (0.058 mg/dL) and a sensitivity of 21 µA/mM cm

Indexed as

Diabetes MellitusDiabetic FootWearable Electronic DevicesFootHumansShoesSweatAlN piezoelectric pressure sensorbioheat transferdiabetic foot ulcerfinite element method simulationsglucose sensormicrofabrication techniquessmart multisensory platform

Identifiers

PMID33800949
PMCPMC7962045
OpenAlexW3134729913

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.