Academic Journal
Data-driven clustering of plantar thermal patterns in healthy individuals : an insole-based approach to foot health monitoring
| Title: | Data-driven clustering of plantar thermal patterns in healthy individuals : an insole-based approach to foot health monitoring |
|---|---|
| Authors: | Borg, Mark, Mizzi, Stephen, Farrugia, Robert, Mifsud, Tiziana, Mizzi, Anabelle, Bajada, Josef, Falzon, Owen |
| Publisher Information: | MDPI AG |
| Publication Year: | 2025 |
| Collection: | University of Malta: OAR@UM / L-Università ta' Malta |
| Subject Terms: | Wearable technology -- Design, Orthopedic apparatus -- Technological innovations, Foot -- Thermography -- Methodology, Cluster analysis -- Data processing, Smart materials -- Health aspects |
| Description: | 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. ; peer-reviewed |
| Document Type: | article in journal/newspaper |
| Language: | English |
| Relation: | https://www.um.edu.mt/library/oar/handle/123456789/131762 |
| DOI: | 10.3390/bioengineering12020143 |
| Availability: | https://www.um.edu.mt/library/oar/handle/123456789/131762 https://doi.org/10.3390/bioengineering12020143 |
| Rights: | info:eu-repo/semantics/openAccess ; The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. |
| Accession Number: | edsbas.7BA487CA |
| Database: | BASE |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://www.um.edu.mt/library/oar/handle/123456789/131762# Name: EDS - BASE (ns324271) Category: fullText Text: View record from BASE |
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| Header | DbId: edsbas DbLabel: BASE An: edsbas.7BA487CA RelevancyScore: 978 AccessLevel: 3 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 977.8095703125 |
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| Items | – Name: Title Label: Title Group: Ti Data: Data-driven clustering of plantar thermal patterns in healthy individuals : an insole-based approach to foot health monitoring – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Borg%2C+Mark%22">Borg, Mark</searchLink><br /><searchLink fieldCode="AR" term="%22Mizzi%2C+Stephen%22">Mizzi, Stephen</searchLink><br /><searchLink fieldCode="AR" term="%22Farrugia%2C+Robert%22">Farrugia, Robert</searchLink><br /><searchLink fieldCode="AR" term="%22Mifsud%2C+Tiziana%22">Mifsud, Tiziana</searchLink><br /><searchLink fieldCode="AR" term="%22Mizzi%2C+Anabelle%22">Mizzi, Anabelle</searchLink><br /><searchLink fieldCode="AR" term="%22Bajada%2C+Josef%22">Bajada, Josef</searchLink><br /><searchLink fieldCode="AR" term="%22Falzon%2C+Owen%22">Falzon, Owen</searchLink> – Name: Publisher Label: Publisher Information Group: PubInfo Data: MDPI AG – Name: DatePubCY Label: Publication Year Group: Date Data: 2025 – Name: Subset Label: Collection Group: HoldingsInfo Data: University of Malta: OAR@UM / L-Università ta' Malta – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Wearable+technology+--+Design%22">Wearable technology -- Design</searchLink><br /><searchLink fieldCode="DE" term="%22Orthopedic+apparatus+--+Technological+innovations%22">Orthopedic apparatus -- Technological innovations</searchLink><br /><searchLink fieldCode="DE" term="%22Foot+--+Thermography+--+Methodology%22">Foot -- Thermography -- Methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Cluster+analysis+--+Data+processing%22">Cluster analysis -- Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Smart+materials+--+Health+aspects%22">Smart materials -- Health aspects</searchLink> – Name: Abstract Label: Description Group: Ab Data: 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. ; peer-reviewed – Name: TypeDocument Label: Document Type Group: TypDoc Data: article in journal/newspaper – Name: Language Label: Language Group: Lang Data: English – Name: NoteTitleSource Label: Relation Group: SrcInfo Data: https://www.um.edu.mt/library/oar/handle/123456789/131762 – Name: DOI Label: DOI Group: ID Data: 10.3390/bioengineering12020143 – Name: URL Label: Availability Group: URL Data: https://www.um.edu.mt/library/oar/handle/123456789/131762<br />https://doi.org/10.3390/bioengineering12020143 – Name: Copyright Label: Rights Group: Cpyrght Data: info:eu-repo/semantics/openAccess ; The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. – Name: AN Label: Accession Number Group: ID Data: edsbas.7BA487CA |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.7BA487CA |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/bioengineering12020143 Languages: – Text: English Subjects: – SubjectFull: Wearable technology -- Design Type: general – SubjectFull: Orthopedic apparatus -- Technological innovations Type: general – SubjectFull: Foot -- Thermography -- Methodology Type: general – SubjectFull: Cluster analysis -- Data processing Type: general – SubjectFull: Smart materials -- Health aspects Type: general Titles: – TitleFull: Data-driven clustering of plantar thermal patterns in healthy individuals : an insole-based approach to foot health monitoring Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Borg, Mark – PersonEntity: Name: NameFull: Mizzi, Stephen – PersonEntity: Name: NameFull: Farrugia, Robert – PersonEntity: Name: NameFull: Mifsud, Tiziana – PersonEntity: Name: NameFull: Mizzi, Anabelle – PersonEntity: Name: NameFull: Bajada, Josef – PersonEntity: Name: NameFull: Falzon, Owen IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2025 Identifiers: – Type: issn-locals Value: edsbas – Type: issn-locals Value: edsbas.oa |
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