Mark Borg, Stephen Mizzi, Robert Farrugia, Tiziana Mifsud, Anabelle Mizzi, Josef Bajada, Owen Falzon
{"title":"健康个体足底热模式数据驱动聚类:一种基于鞋垫的足部健康监测方法。","authors":"Mark Borg, Stephen Mizzi, Robert Farrugia, Tiziana Mifsud, Anabelle Mizzi, Josef Bajada, Owen Falzon","doi":"10.3390/bioengineering12020143","DOIUrl":null,"url":null,"abstract":"<p><p>Monitoring plantar foot temperatures is essential for assessing foot health, particularly in individuals with diabetes at increased risk of complications. Traditional thermographic imaging measures foot temperatures in unshod individuals lying down, which may not reflect thermal characteristics of feet in shod, active, real-world conditions. These controlled settings limit understanding of dynamic foot temperatures during daily activities. Recent advancements in wearable technology, such as insole-based sensors, overcome these limitations by enabling continuous temperature monitoring. This study leverages a data-driven clustering approach, independent of pre-selected foot regions or models like the angiosome concept, to explore normative thermal patterns in shod feet with insole-based sensors. Data were collected from 27 healthy participants using insoles embedded with 21 temperature sensors. The data were analysed using clustering algorithms, including k-means, fuzzy c-means, OPTICS, and hierarchical clustering. The clustering algorithms showed a high degree of similarity, with variations primarily influenced by clustering granularity. Six primary thermal patterns were identified, with the \"butterfly pattern\" (elevated medial arch temperatures) predominant, representing 51.5% of the dataset, aligning with findings in thermographic studies. Other patterns, like the \"medial arch + metatarsal area\" pattern, were also observed, highlighting diverse yet consistent thermal distributions. This study shows that while normative thermal patterns observed in thermographic imaging are reflected in insole data, the temperature distribution within the shoe may better represent foot behaviour during everyday activities, particularly when enclosed in a shoe. Unlike thermal imaging, the proposed in-shoe system offers the potential to capture dynamic thermal variations during ambulatory activities, enabling richer insights into foot health in real-world conditions.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 2","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11851639/pdf/","citationCount":"0","resultStr":"{\"title\":\"Data-Driven Clustering of Plantar Thermal Patterns in Healthy Individuals: An Insole-Based Approach to Foot Health Monitoring.\",\"authors\":\"Mark Borg, Stephen Mizzi, Robert Farrugia, Tiziana Mifsud, Anabelle Mizzi, Josef Bajada, Owen Falzon\",\"doi\":\"10.3390/bioengineering12020143\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Monitoring plantar foot temperatures is essential for assessing foot health, particularly in individuals with diabetes at increased risk of complications. Traditional thermographic imaging measures foot temperatures in unshod individuals lying down, which may not reflect thermal characteristics of feet in shod, active, real-world conditions. These controlled settings limit understanding of dynamic foot temperatures during daily activities. Recent advancements in wearable technology, such as insole-based sensors, overcome these limitations by enabling continuous temperature monitoring. This study leverages a data-driven clustering approach, independent of pre-selected foot regions or models like the angiosome concept, to explore normative thermal patterns in shod feet with insole-based sensors. Data were collected from 27 healthy participants using insoles embedded with 21 temperature sensors. The data were analysed using clustering algorithms, including k-means, fuzzy c-means, OPTICS, and hierarchical clustering. The clustering algorithms showed a high degree of similarity, with variations primarily influenced by clustering granularity. Six primary thermal patterns were identified, with the \\\"butterfly pattern\\\" (elevated medial arch temperatures) predominant, representing 51.5% of the dataset, aligning with findings in thermographic studies. Other patterns, like the \\\"medial arch + metatarsal area\\\" pattern, were also observed, highlighting diverse yet consistent thermal distributions. This study shows that while normative thermal patterns observed in thermographic imaging are reflected in insole data, the temperature distribution within the shoe may better represent foot behaviour during everyday activities, particularly when enclosed in a shoe. Unlike thermal imaging, the proposed in-shoe system offers the potential to capture dynamic thermal variations during ambulatory activities, enabling richer insights into foot health in real-world conditions.</p>\",\"PeriodicalId\":8874,\"journal\":{\"name\":\"Bioengineering\",\"volume\":\"12 2\",\"pages\":\"\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2025-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11851639/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bioengineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.3390/bioengineering12020143\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioengineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3390/bioengineering12020143","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
Data-Driven Clustering of Plantar Thermal Patterns in Healthy Individuals: An Insole-Based Approach to Foot Health Monitoring.
Monitoring plantar foot temperatures is essential for assessing foot health, particularly in individuals with diabetes at increased risk of complications. Traditional thermographic imaging measures foot temperatures in unshod individuals lying down, which may not reflect thermal characteristics of feet in shod, active, real-world conditions. These controlled settings limit understanding of dynamic foot temperatures during daily activities. Recent advancements in wearable technology, such as insole-based sensors, overcome these limitations by enabling continuous temperature monitoring. This study leverages a data-driven clustering approach, independent of pre-selected foot regions or models like the angiosome concept, to explore normative thermal patterns in shod feet with insole-based sensors. Data were collected from 27 healthy participants using insoles embedded with 21 temperature sensors. The data were analysed using clustering algorithms, including k-means, fuzzy c-means, OPTICS, and hierarchical clustering. The clustering algorithms showed a high degree of similarity, with variations primarily influenced by clustering granularity. Six primary thermal patterns were identified, with the "butterfly pattern" (elevated medial arch temperatures) predominant, representing 51.5% of the dataset, aligning with findings in thermographic studies. Other patterns, like the "medial arch + metatarsal area" pattern, were also observed, highlighting diverse yet consistent thermal distributions. This study shows that while normative thermal patterns observed in thermographic imaging are reflected in insole data, the temperature distribution within the shoe may better represent foot behaviour during everyday activities, particularly when enclosed in a shoe. Unlike thermal imaging, the proposed in-shoe system offers the potential to capture dynamic thermal variations during ambulatory activities, enabling richer insights into foot health in real-world conditions.
期刊介绍:
Aims
Bioengineering (ISSN 2306-5354) provides an advanced forum for the science and technology of bioengineering. It publishes original research papers, comprehensive reviews, communications and case reports. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. All aspects of bioengineering are welcomed from theoretical concepts to education and applications. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. There are, in addition, four key features of this Journal:
● We are introducing a new concept in scientific and technical publications “The Translational Case Report in Bioengineering”. It is a descriptive explanatory analysis of a transformative or translational event. Understanding that the goal of bioengineering scholarship is to advance towards a transformative or clinical solution to an identified transformative/clinical need, the translational case report is used to explore causation in order to find underlying principles that may guide other similar transformative/translational undertakings.
● Manuscripts regarding research proposals and research ideas will be particularly welcomed.
● Electronic files and software regarding the full details of the calculation and experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material.
● We also accept manuscripts communicating to a broader audience with regard to research projects financed with public funds.
Scope
● Bionics and biological cybernetics: implantology; bio–abio interfaces
● Bioelectronics: wearable electronics; implantable electronics; “more than Moore” electronics; bioelectronics devices
● Bioprocess and biosystems engineering and applications: bioprocess design; biocatalysis; bioseparation and bioreactors; bioinformatics; bioenergy; etc.
● Biomolecular, cellular and tissue engineering and applications: tissue engineering; chromosome engineering; embryo engineering; cellular, molecular and synthetic biology; metabolic engineering; bio-nanotechnology; micro/nano technologies; genetic engineering; transgenic technology
● Biomedical engineering and applications: biomechatronics; biomedical electronics; biomechanics; biomaterials; biomimetics; biomedical diagnostics; biomedical therapy; biomedical devices; sensors and circuits; biomedical imaging and medical information systems; implants and regenerative medicine; neurotechnology; clinical engineering; rehabilitation engineering
● Biochemical engineering and applications: metabolic pathway engineering; modeling and simulation
● Translational bioengineering