Evidence map›Paper›PMID 39517824›Full record

ArticleSensors (Basel, Switzerland)2024

Smart Compression Sock for Early Detection of Diabetic Foot Ulcers.

Julia Billings, Julia Gee, Zinah Ghulam, Hussein A Abdullah

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Observational
  5. 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

4 authors.

Julia BillingsSchool of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada.
Julia GeeSchool of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada.
Zinah GhulamSchool of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada.ORCID 0009-0000-6088-0669
Hussein A AbdullahSchool of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada.ORCID 0000-0002-1716-3186

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The prevention of diabetic foot ulcers remains a critical challenge. This study evaluates a smart compression sock designed to address this issue by integrating temperature, plantar pressure, and blood oxygen sensors and monitoring data recorded by these sensors. The smart sock, developed with input from a certified Pedorthist, was tested on 20 healthy adult participants aged 16 to 53. It includes four temperature sensors and pressure sensors at common ulcer sites (first and fifth metatarsal heads, calcaneus, and hallux), and a blood oxygen sensor on the hallux. The sensors are monitored, and their transduced data are collected and stored through an app installed on a personal cell phone. The mobile app interface is user-friendly, providing intuitive navigation and easy access to the sensors' data. Using repeated measures ANOVA and post hoc tests, we analyzed the impact of various physical activities on physiological changes in the foot. The device effectively detected significant variations in blood oxygen, temperature, and pressure across six activities. Statistical analyses revealed significant differences based on activity type and sensor location. These results highlight the smart sock's sensitivity and accuracy, suggesting its potential to prevent diabetic foot ulcers. Further clinical trials are needed to evaluate its efficacy in a larger, more diverse population.

Indexed as

Diabetic FootPressureAdolescentAdultEarly DiagnosisFemaleHumansMaleMiddle AgedMobile ApplicationsOxygenYoung AdultOxygenblood oxygendiabetic foot ulcersdiabetic neuropathymedical deviceplantar pressuretemperature

Identifiers

PMID39517824
PMCPMC11548053

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.