Evidence map›Paper›PMID 39001080›Full record

ReviewSensors (Basel, Switzerland)2024

Recent Innovations in Footwear and the Role of Smart Footwear in Healthcare-A Survey.

Pradyumna G Rukmini, Roopa B Hegde, Bommegowda K Basavarajappa, Anil Kumar Bhat, Amit N Pujari, Gaetano D Gargiulo, Upul Gunawardana, Tony Jan, Ganesh R Naik

Abstract readReview
In one paragraph

Review 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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

9 authors.

Pradyumna G RukminiDepartment of Electronics & Communication Engineering, NMAM Institute Technology, NITTE (Deemed to be University), Nitte 574110, India.ORCID 0000-0001-5798-6083
Roopa B HegdeDepartment of Electronics & Communication Engineering, NMAM Institute Technology, NITTE (Deemed to be University), Nitte 574110, India.ORCID 0000-0002-7152-3971
Bommegowda K BasavarajappaDepartment of Electronics & Communication Engineering, NMAM Institute Technology, NITTE (Deemed to be University), Nitte 574110, India.ORCID 0000-0001-8352-6865
Anil Kumar BhatDepartment of Electronics & Communication Engineering, NMAM Institute Technology, NITTE (Deemed to be University), Nitte 574110, India.
Amit N PujariSchool of Physics, Engineering and Computer Science, University of Hertfordshire, Hertfordshire AL10 9AB, UK.ORCID 0000-0003-1688-4448
Gaetano D GargiuloSchool of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW 2751, Australia.ORCID 0000-0002-2616-2804
Upul GunawardanaSchool of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW 2751, Australia.ORCID 0000-0003-0932-5306
Tony JanCentre for Artificial Intelligence Research and Optimization (AIRO), Design and Creative Technology Vertical, Torrens University, Ultimo, NSW 2007, Australia.ORCID 0000-0002-3114-8978
Ganesh R NaikCentre for Artificial Intelligence Research and Optimization (AIRO), Design and Creative Technology Vertical, Torrens University, Ultimo, NSW 2007, Australia.ORCID 0000-0003-1790-9838

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Smart shoes have ushered in a new era of personalised health monitoring and assistive technologies. Smart shoes leverage technologies such as Bluetooth for data collection and wireless transmission, and incorporate features such as GPS tracking, obstacle detection, and fitness tracking. As the 2010s unfolded, the smart shoe landscape diversified and advanced rapidly, driven by sensor technology enhancements and smartphones' ubiquity. Shoes have begun incorporating accelerometers, gyroscopes, and pressure sensors, significantly improving the accuracy of data collection and enabling functionalities such as gait analysis. The healthcare sector has recognised the potential of smart shoes, leading to innovations such as shoes designed to monitor diabetic foot ulcers, track rehabilitation progress, and detect falls among older people, thus expanding their application beyond fitness into medical monitoring. This article provides an overview of the current state of smart shoe technology, highlighting the integration of advanced sensors for health monitoring, energy harvesting, assistive features for the visually impaired, and deep learning for data analysis. This study discusses the potential of smart footwear in medical applications, particularly for patients with diabetes, and the ongoing research in this field. Current footwear challenges are also discussed, including complex construction, poor fit, comfort, and high cost.

Indexed as

ShoesAccelerometryDiabetic FootGaitHumansMonitoring, AmbulatoryMonitoring, PhysiologicSmartphoneSurveys and QuestionnairesWearable Electronic Devicesassistive technologydeep learningdiabetes managementenergy harvestinghealth monitoringIoTsmart footweartechnological advancements in footwear

Identifiers

PMID39001080
PMCPMC11243832

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.