Development of an interpretable model for foot soft tissue stiffness based on gait plantar pressure analysis

Plantar soft tissue properties affect foot biomechanics during movement. This study aims to explore the relationship between plantar pressure features and soft tissue stiffness through interpretable neural network model. The findings could inform orthotic insole design. A sample of 30 healthy young...

Full description

Saved in:
Bibliographic Details
Published inFrontiers in bioengineering and biotechnology Vol. 12; p. 1482382
Main Authors Bai, Xiaotian, Hou, Xiao, Lv, Dazhi, Wei, Jialin, Song, Yiling, Tang, Zhengyan, Huo, Hongfeng, Liu, Jingmin
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 06.01.2025
Subjects
Online AccessGet full text
ISSN2296-4185
2296-4185
DOI10.3389/fbioe.2024.1482382

Cover

Abstract Plantar soft tissue properties affect foot biomechanics during movement. This study aims to explore the relationship between plantar pressure features and soft tissue stiffness through interpretable neural network model. The findings could inform orthotic insole design. A sample of 30 healthy young male subjects with normal feet were recruited (age 23.56 ± 3.28 years, height 1.76 ± 0.04 m, weight 72.21 ± 5.69 kg). Plantar pressure data were collected during 5 trials at the subjects' preferred walking speed (1.15 ± 0.04 m/s). Foot soft tissue stiffness was recorded using a MyotonPRO biological soft tissue stiffness meter before each walking trial. A backpropagation neural network, optimized by integrating particle swarm optimization and genetic algorithm, was constructed to predict foot soft tissue stiffness using plantar pressure data collected during walking. Mean impact value analysis was conducted in parallel to investigate the relative importance of different plantar pressure features. The predicted values for the training set are slightly higher than the actual values (MBE = 0.77N/m, RMSE = 11.89 N/m), with a maximum relative error of 7.82% and an average relative error of 1.98%, and the predicted values for the test set are slightly lower than the actual values (MBE = -4.43N/m, RMSE = 14.73 N/m), with a maximum relative error of 7.35% and an average relative error of 2.55%. Regions with highest contribution rates to foot soft tissue stiffness prediction were the third metatarsal (13.58%), fourth metatarsal (14.71%), midfoot (12.43%) and medial heel (12.58%) regions, which accounted for 53.3% of total contribution. The pressure features in the medial heel, midfoot area, and lateral mid-metatarsal regions during walking can better reflect plantar soft tissue stiffness. Future studies should ensure measurement stability of this region and refine insole designs to mitigate plantar soft tissue fatigue in the specified areas.
AbstractList Plantar soft tissue properties affect foot biomechanics during movement. This study aims to explore the relationship between plantar pressure features and soft tissue stiffness through interpretable neural network model. The findings could inform orthotic insole design.PurposePlantar soft tissue properties affect foot biomechanics during movement. This study aims to explore the relationship between plantar pressure features and soft tissue stiffness through interpretable neural network model. The findings could inform orthotic insole design.A sample of 30 healthy young male subjects with normal feet were recruited (age 23.56 ± 3.28 years, height 1.76 ± 0.04 m, weight 72.21 ± 5.69 kg). Plantar pressure data were collected during 5 trials at the subjects' preferred walking speed (1.15 ± 0.04 m/s). Foot soft tissue stiffness was recorded using a MyotonPRO biological soft tissue stiffness meter before each walking trial. A backpropagation neural network, optimized by integrating particle swarm optimization and genetic algorithm, was constructed to predict foot soft tissue stiffness using plantar pressure data collected during walking. Mean impact value analysis was conducted in parallel to investigate the relative importance of different plantar pressure features.MethodsA sample of 30 healthy young male subjects with normal feet were recruited (age 23.56 ± 3.28 years, height 1.76 ± 0.04 m, weight 72.21 ± 5.69 kg). Plantar pressure data were collected during 5 trials at the subjects' preferred walking speed (1.15 ± 0.04 m/s). Foot soft tissue stiffness was recorded using a MyotonPRO biological soft tissue stiffness meter before each walking trial. A backpropagation neural network, optimized by integrating particle swarm optimization and genetic algorithm, was constructed to predict foot soft tissue stiffness using plantar pressure data collected during walking. Mean impact value analysis was conducted in parallel to investigate the relative importance of different plantar pressure features.The predicted values for the training set are slightly higher than the actual values (MBE = 0.77N/m, RMSE = 11.89 N/m), with a maximum relative error of 7.82% and an average relative error of 1.98%, and the predicted values for the test set are slightly lower than the actual values (MBE = -4.43N/m, RMSE = 14.73 N/m), with a maximum relative error of 7.35% and an average relative error of 2.55%. Regions with highest contribution rates to foot soft tissue stiffness prediction were the third metatarsal (13.58%), fourth metatarsal (14.71%), midfoot (12.43%) and medial heel (12.58%) regions, which accounted for 53.3% of total contribution.ResultsThe predicted values for the training set are slightly higher than the actual values (MBE = 0.77N/m, RMSE = 11.89 N/m), with a maximum relative error of 7.82% and an average relative error of 1.98%, and the predicted values for the test set are slightly lower than the actual values (MBE = -4.43N/m, RMSE = 14.73 N/m), with a maximum relative error of 7.35% and an average relative error of 2.55%. Regions with highest contribution rates to foot soft tissue stiffness prediction were the third metatarsal (13.58%), fourth metatarsal (14.71%), midfoot (12.43%) and medial heel (12.58%) regions, which accounted for 53.3% of total contribution.The pressure features in the medial heel, midfoot area, and lateral mid-metatarsal regions during walking can better reflect plantar soft tissue stiffness. Future studies should ensure measurement stability of this region and refine insole designs to mitigate plantar soft tissue fatigue in the specified areas.ConclusionThe pressure features in the medial heel, midfoot area, and lateral mid-metatarsal regions during walking can better reflect plantar soft tissue stiffness. Future studies should ensure measurement stability of this region and refine insole designs to mitigate plantar soft tissue fatigue in the specified areas.
Plantar soft tissue properties affect foot biomechanics during movement. This study aims to explore the relationship between plantar pressure features and soft tissue stiffness through interpretable neural network model. The findings could inform orthotic insole design. A sample of 30 healthy young male subjects with normal feet were recruited (age 23.56 ± 3.28 years, height 1.76 ± 0.04 m, weight 72.21 ± 5.69 kg). Plantar pressure data were collected during 5 trials at the subjects' preferred walking speed (1.15 ± 0.04 m/s). Foot soft tissue stiffness was recorded using a MyotonPRO biological soft tissue stiffness meter before each walking trial. A backpropagation neural network, optimized by integrating particle swarm optimization and genetic algorithm, was constructed to predict foot soft tissue stiffness using plantar pressure data collected during walking. Mean impact value analysis was conducted in parallel to investigate the relative importance of different plantar pressure features. The predicted values for the training set are slightly higher than the actual values (MBE = 0.77N/m, RMSE = 11.89 N/m), with a maximum relative error of 7.82% and an average relative error of 1.98%, and the predicted values for the test set are slightly lower than the actual values (MBE = -4.43N/m, RMSE = 14.73 N/m), with a maximum relative error of 7.35% and an average relative error of 2.55%. Regions with highest contribution rates to foot soft tissue stiffness prediction were the third metatarsal (13.58%), fourth metatarsal (14.71%), midfoot (12.43%) and medial heel (12.58%) regions, which accounted for 53.3% of total contribution. The pressure features in the medial heel, midfoot area, and lateral mid-metatarsal regions during walking can better reflect plantar soft tissue stiffness. Future studies should ensure measurement stability of this region and refine insole designs to mitigate plantar soft tissue fatigue in the specified areas.
PurposePlantar soft tissue properties affect foot biomechanics during movement. This study aims to explore the relationship between plantar pressure features and soft tissue stiffness through interpretable neural network model. The findings could inform orthotic insole design.MethodsA sample of 30 healthy young male subjects with normal feet were recruited (age 23.56 ± 3.28 years, height 1.76 ± 0.04 m, weight 72.21 ± 5.69 kg). Plantar pressure data were collected during 5 trials at the subjects’ preferred walking speed (1.15 ± 0.04 m/s). Foot soft tissue stiffness was recorded using a MyotonPRO biological soft tissue stiffness meter before each walking trial. A backpropagation neural network, optimized by integrating particle swarm optimization and genetic algorithm, was constructed to predict foot soft tissue stiffness using plantar pressure data collected during walking. Mean impact value analysis was conducted in parallel to investigate the relative importance of different plantar pressure features.ResultsThe predicted values for the training set are slightly higher than the actual values (MBE = 0.77N/m, RMSE = 11.89 N/m), with a maximum relative error of 7.82% and an average relative error of 1.98%, and the predicted values for the test set are slightly lower than the actual values (MBE = −4.43N/m, RMSE = 14.73 N/m), with a maximum relative error of 7.35% and an average relative error of 2.55%. Regions with highest contribution rates to foot soft tissue stiffness prediction were the third metatarsal (13.58%), fourth metatarsal (14.71%), midfoot (12.43%) and medial heel (12.58%) regions, which accounted for 53.3% of total contribution.ConclusionThe pressure features in the medial heel, midfoot area, and lateral mid-metatarsal regions during walking can better reflect plantar soft tissue stiffness. Future studies should ensure measurement stability of this region and refine insole designs to mitigate plantar soft tissue fatigue in the specified areas.
Author Song, Yiling
Liu, Jingmin
Lv, Dazhi
Wei, Jialin
Huo, Hongfeng
Tang, Zhengyan
Hou, Xiao
Bai, Xiaotian
AuthorAffiliation 4 Key Laboratory of Bioinformatics Evaluation of Human Movement , Hebei Normal University , Shijiazhuang , China
1 Department of Physical Education , Tsinghua University , Beijing , China
3 College of Physical Education , Hebei Normal University , Shijiazhuang , China
2 School of Sport Science , Beijing Sport University , Beijing , China
AuthorAffiliation_xml – name: 3 College of Physical Education , Hebei Normal University , Shijiazhuang , China
– name: 1 Department of Physical Education , Tsinghua University , Beijing , China
– name: 4 Key Laboratory of Bioinformatics Evaluation of Human Movement , Hebei Normal University , Shijiazhuang , China
– name: 2 School of Sport Science , Beijing Sport University , Beijing , China
Author_xml – sequence: 1
  givenname: Xiaotian
  surname: Bai
  fullname: Bai, Xiaotian
– sequence: 2
  givenname: Xiao
  surname: Hou
  fullname: Hou, Xiao
– sequence: 3
  givenname: Dazhi
  surname: Lv
  fullname: Lv, Dazhi
– sequence: 4
  givenname: Jialin
  surname: Wei
  fullname: Wei, Jialin
– sequence: 5
  givenname: Yiling
  surname: Song
  fullname: Song, Yiling
– sequence: 6
  givenname: Zhengyan
  surname: Tang
  fullname: Tang, Zhengyan
– sequence: 7
  givenname: Hongfeng
  surname: Huo
  fullname: Huo, Hongfeng
– sequence: 8
  givenname: Jingmin
  surname: Liu
  fullname: Liu, Jingmin
BackLink https://www.ncbi.nlm.nih.gov/pubmed/39834637$$D View this record in MEDLINE/PubMed
BookMark eNpVkk9vGyEQxVdVquZP8wV6qDj2YhcY2GVPVZW2aaRIvbRnBOzgErGLCzhSvn1w7EbJAQ0wT78nzbzz7mRJC3bdB0bXAGr87G1IuOaUizUTioPib7ozzsd-JZiSJy_up91lKXeUUsblIBV_153CqED0MJx18RveY0zbGZdKkidmIWGpmLcZq7ERyZwmjMSn3E6qpCRfSQ2l7JCUGrxfsBRiTcGJpIVsTKhkG81STSaN0XQZG9TEhxLK--6tN7Hg5bFedH9-fP999XN1--v65urr7coJTusKlBkcnyYpkEHPpAI5guWOTtQJNbY3WC-RWmaFH0TfS-OBcykUOAco4aK7OXCnZO70NofZ5AedTNBPHylvtMk1uIhaSoOUWofKWkFhstOIgio7WmUkKNFYXw6s7c7OOLk2p2ziK-jrzhL-6k2614wNAgbaN8KnIyGnfzssVc-hOIxtSph2RQNra5E9pXuzjy_Nnl3-76sJ-EHgciolo3-WMKr3udBPudD7XOhjLuAR0U6thQ
Cites_doi 10.1016/j.clinbiomech.2021.105383
10.1007/s11600-020-00504-2
10.1123/jsr.21.4.327
10.12659/MSM.916975
10.3389/fphy.2022.1058615
10.1016/j.jbiomech.2004.03.025
10.1016/j.jdiacomp.2014.03.011
10.1098/rsif.2013.1188
10.1002/rob.22169
10.1136/bjsports-2013-092690
10.1186/s12891-022-05197-w
10.1016/0021-9290(87)90255-7
10.1038/s41598-020-63730-0
10.1177/1071100717702463
10.1016/j.gaitpost.2024.08.074
10.3390/s22124343
10.3389/fbioe.2021.791238
10.1016/j.jmbbm.2015.09.015
10.3390/jcm10112351
10.1177/107110079301400609
10.3389/fbioe.2022.853085
10.3109/03008200903389127
10.1177/1071100712459173
10.1177/2309499018802482
10.3390/ijerph20010087
10.1080/10255842.2023.2268231
10.1016/j.acra.2019.04.009
10.1016/j.isatra.2024.09.008
10.1177/107110070602700210
10.3390/su132413746
10.1007/s10439-017-1918-1
10.1038/325147a0
10.1080/19424280.2024.2363536
10.1249/MSS.0000000000003020
10.12659/MSM.909550
10.2519/jospt.2006.2078
ContentType Journal Article
Copyright Copyright © 2025 Bai, Hou, Lv, Wei, Song, Tang, Huo and Liu.
Copyright © 2025 Bai, Hou, Lv, Wei, Song, Tang, Huo and Liu. 2025 Bai, Hou, Lv, Wei, Song, Tang, Huo and Liu
Copyright_xml – notice: Copyright © 2025 Bai, Hou, Lv, Wei, Song, Tang, Huo and Liu.
– notice: Copyright © 2025 Bai, Hou, Lv, Wei, Song, Tang, Huo and Liu. 2025 Bai, Hou, Lv, Wei, Song, Tang, Huo and Liu
DBID AAYXX
CITATION
NPM
7X8
5PM
DOA
DOI 10.3389/fbioe.2024.1482382
DatabaseName CrossRef
PubMed
MEDLINE - Academic
PubMed Central (Full Participant titles)
DOAJ Directory of Open Access Journals
DatabaseTitle CrossRef
PubMed
MEDLINE - Academic
DatabaseTitleList MEDLINE - Academic
PubMed

Database_xml – sequence: 1
  dbid: DOA
  name: DOAJ Directory of Open Access Journals
  url: https://www.doaj.org/
  sourceTypes: Open Website
– sequence: 2
  dbid: NPM
  name: PubMed
  url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
DocumentTitleAlternate Bai et al
EISSN 2296-4185
ExternalDocumentID oai_doaj_org_article_55ae00bce8bb403dbd9e408b9b8a5384
PMC11743706
39834637
10_3389_fbioe_2024_1482382
Genre Journal Article
GroupedDBID 53G
5VS
9T4
AAFWJ
AAYXX
ACGFS
ACXDI
ADBBV
ADRAZ
AFPKN
ALMA_UNASSIGNED_HOLDINGS
AOIJS
BAWUL
BCNDV
CITATION
DIK
GROUPED_DOAJ
GX1
HYE
KQ8
M48
M~E
OK1
PGMZT
RPM
IAO
IEA
IHR
IPNFZ
ISR
NPM
RIG
7X8
5PM
ID FETCH-LOGICAL-c420t-38a7c2dd54e1361583593b2c0d0c4895833bf5e0b1b4f74665af3225483cc3e53
IEDL.DBID M48
ISSN 2296-4185
IngestDate Wed Aug 27 01:32:13 EDT 2025
Thu Aug 21 18:40:16 EDT 2025
Fri Sep 05 03:57:07 EDT 2025
Thu Jan 30 12:30:00 EST 2025
Tue Jul 01 03:36:41 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Keywords biomechanics
plantar soft tissue
gait
neural network
plantar pressure
Language English
License Copyright © 2025 Bai, Hou, Lv, Wei, Song, Tang, Huo and Liu.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c420t-38a7c2dd54e1361583593b2c0d0c4895833bf5e0b1b4f74665af3225483cc3e53
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Edited by: Sangkyun Cho, Stanford University, United States
These authors have contributed equally to this work and share first authorship
Tariq Alkhatatbeh, Xi’an Jiaotong University, Xi’an, China, in collaboration with reviewer JS
Shoukun Wang, Beijing Institute of Technology, China
Reviewed by: Jidong Song, Xi’an Jiaotong University, China
OpenAccessLink https://doaj.org/article/55ae00bce8bb403dbd9e408b9b8a5384
PMID 39834637
PQID 3157556004
PQPubID 23479
ParticipantIDs doaj_primary_oai_doaj_org_article_55ae00bce8bb403dbd9e408b9b8a5384
pubmedcentral_primary_oai_pubmedcentral_nih_gov_11743706
proquest_miscellaneous_3157556004
pubmed_primary_39834637
crossref_primary_10_3389_fbioe_2024_1482382
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2025-01-06
PublicationDateYYYYMMDD 2025-01-06
PublicationDate_xml – month: 01
  year: 2025
  text: 2025-01-06
  day: 06
PublicationDecade 2020
PublicationPlace Switzerland
PublicationPlace_xml – name: Switzerland
PublicationTitle Frontiers in bioengineering and biotechnology
PublicationTitleAlternate Front Bioeng Biotechnol
PublicationYear 2025
Publisher Frontiers Media S.A
Publisher_xml – name: Frontiers Media S.A
References Cheung (B9) 2006; 27
Li (B23) 2023; 40
Gatz (B11) 2020; 27
Cavanagh (B5) 1987; 20
Wang (B37) 2021; 9
Shiotani (B32) 2023; 55
Xu (B40) 2021; 13
Lee (B21) 2023; 20
Mckeon (B27) 2015; 49
Sakalauskaitė (B31) 2012; 14
Teng (B35) 2022; 23
Lewin (B22) 2024; 16
Hyland (B17) 2006; 36
Ker (B20) 1987; 325
Teoh (B36) 2016; 54
Lynn (B26) 2012; 21
Huang (B16) 2004; 27
Bolivar (B4) 2013; 34
Tas (B34) 2018; 26
Bai (B1) 2022; 10
Chen (B8) 2024; 155
Xia (B38) 2019
Xu (B39) 2019; 25
Chatzistergos (B7) 2014; 28
Huang (B15) 2018; 24
Cifuentes-De (B10) 2021; 86
Liu (B25) 2020; 10
Gu (B12) 2020; 68
Cen (B6) 2023; 27
Tas (B33) 2017; 38
Li (B24) 2022; 22
Kasai (B18) 2024; 114
Baur (B2) 2021; 10
Huang (B14) 1993; 14
Peng (B29) 2022; 10
Ridola (B30) 2001; 106
Natali (B28) 2010; 51
Behforootan (B3) 2017; 45
Hof (B13) 2005; 38
Kelly (B19) 2014; 11
References_xml – volume: 86
  start-page: 105383
  year: 2021
  ident: B10
  article-title: Peroneus longus overload caused by soft tissue deficiencies associated with early adult acquired flatfoot: a finite element analysis
  publication-title: Clin. Biomech.
  doi: 10.1016/j.clinbiomech.2021.105383
– volume: 68
  start-page: 1727
  year: 2020
  ident: B12
  article-title: Complex lithology prediction using mean impact value, particle swarm optimization, and probabilistic neural network techniques
  publication-title: Acta geophys.
  doi: 10.1007/s11600-020-00504-2
– volume: 21
  start-page: 327
  year: 2012
  ident: B26
  article-title: Differences in static- and dynamic-balance task performance after 4 weeks of intrinsic-foot-muscle training: the short-foot exercise versus the towel-curl exercise
  publication-title: J. Sport Rehabil.
  doi: 10.1123/jsr.21.4.327
– volume: 25
  start-page: 3510
  year: 2019
  ident: B39
  article-title: Comparative study of the effects of customized 3d printed insole and prefabricated insole on plantar pressure and comfort in patients with symptomatic flatfoot
  publication-title: Med. Sci. Monit.
  doi: 10.12659/MSM.916975
– volume: 10
  year: 2022
  ident: B1
  article-title: Analysis of plantar impact characteristics of walking in patients with flatfoot according to basic mechanical features and continuous wavelet transform
  publication-title: Front. Phys.
  doi: 10.3389/fphy.2022.1058615
– volume: 38
  start-page: 1
  year: 2005
  ident: B13
  article-title: The condition for dynamic stability
  publication-title: J. Biomech.
  doi: 10.1016/j.jbiomech.2004.03.025
– volume: 28
  start-page: 488
  year: 2014
  ident: B7
  article-title: The relationship between the mechanical properties of heel-pad and common clinical measures associated with foot ulcers in patients with diabetes
  publication-title: J. Diabetes. Complicat.
  doi: 10.1016/j.jdiacomp.2014.03.011
– volume: 11
  start-page: 20131188
  year: 2014
  ident: B19
  article-title: Intrinsic foot muscles have the capacity to control deformation of the longitudinal arch
  publication-title: J. R. Soc. Interface
  doi: 10.1098/rsif.2013.1188
– volume: 40
  start-page: 1097
  year: 2023
  ident: B23
  article-title: Position-based force tracking adaptive impedance control strategy for robot grinding complex surfaces system
  publication-title: J. Field Robot.
  doi: 10.1002/rob.22169
– volume: 49
  start-page: 290
  year: 2015
  ident: B27
  article-title: The foot core system: a new paradigm for understanding intrinsic foot muscle function
  publication-title: Br. J. Sports Med.
  doi: 10.1136/bjsports-2013-092690
– volume: 23
  start-page: 254
  year: 2022
  ident: B35
  article-title: Effect of loading history on material properties of human heel pad: an in-vivo pilot investigation during gait
  publication-title: BMC Musculoskelet. Disord.
  doi: 10.1186/s12891-022-05197-w
– volume: 20
  start-page: 547
  year: 1987
  ident: B5
  article-title: The arch index: a useful measure from footprints
  publication-title: J. Biomech.
  doi: 10.1016/0021-9290(87)90255-7
– volume: 10
  start-page: 6643
  year: 2020
  ident: B25
  article-title: Influence of different knee and ankle ranges of motion on the elasticity of triceps surae muscles, achilles tendon, and plantar fascia
  publication-title: Sci. Rep.
  doi: 10.1038/s41598-020-63730-0
– volume: 38
  start-page: 779
  year: 2017
  ident: B33
  article-title: Effects of body mass index on mechanical properties of the plantar fascia and heel pad in asymptomatic participants
  publication-title: Foot. Ankle. Int.
  doi: 10.1177/1071100717702463
– volume: 27
  start-page: 443
  year: 2004
  ident: B16
  article-title: The relationship between the flexible flatfoot and plantar fasciitis: ultrasonographic evaluation
  publication-title: Chang. Gung Med. J.
– volume: 114
  start-page: 42
  year: 2024
  ident: B18
  article-title: Smart insole-based analysis of gait biomechanics for insoles in patients with flatfoot
  publication-title: Gait Posture
  doi: 10.1016/j.gaitpost.2024.08.074
– volume: 14
  year: 2012
  ident: B31
  article-title: The foot arch and viscoelastic properties of plantar fascia and achilles tendon
  publication-title: J. Vibroeng.
– volume: 106
  start-page: 85
  year: 2001
  ident: B30
  article-title: Functional anatomy and imaging of the foot
  publication-title: Ital. J. Anat. Embryol.
– volume: 22
  start-page: 4343
  year: 2022
  ident: B24
  article-title: The identification of ecg signals using wavelet transform and woa-pnn
  publication-title: Sensors
  doi: 10.3390/s22124343
– volume: 9
  start-page: 791238
  year: 2021
  ident: B37
  article-title: The influence of heel height on strain variation of plantar fascia during high heel shoes walking-combined musculoskeletal modeling and finite element analysis
  publication-title: Front. Bioeng. Biotechnol.
  doi: 10.3389/fbioe.2021.791238
– volume: 54
  start-page: 219
  year: 2016
  ident: B36
  article-title: Prediction of plantar soft tissue stiffness based on sex, age, bodyweight, height and body mass index
  publication-title: J. Mech. Behav. Biomed. Mater.
  doi: 10.1016/j.jmbbm.2015.09.015
– volume: 10
  start-page: 2351
  year: 2021
  ident: B2
  article-title: Shear wave elastography of the plantar fascia: comparison between patients with plantar fasciitis and healthy control subjects
  publication-title: J. Clin. Med.
  doi: 10.3390/jcm10112351
– volume: 14
  start-page: 353
  year: 1993
  ident: B14
  article-title: Biomechanical evaluation of longitudinal arch stability
  publication-title: Foot Ankle
  doi: 10.1177/107110079301400609
– volume: 10
  start-page: 853085
  year: 2022
  ident: B29
  article-title: Different design feature combinations of flatfoot orthosis on plantar fascia strain and plantar pressure: a muscle-driven finite element analysis with taguchi method
  publication-title: Front. Bioeng. Biotechnol.
  doi: 10.3389/fbioe.2022.853085
– volume: 51
  start-page: 337
  year: 2010
  ident: B28
  article-title: A constitutive model for the mechanical characterization of the plantar fascia
  publication-title: Res
  doi: 10.3109/03008200903389127
– volume: 34
  start-page: 42
  year: 2013
  ident: B4
  article-title: Relationship between tightness of the posterior muscles of the lower limb and plantar fasciitis
  publication-title: Int
  doi: 10.1177/1071100712459173
– volume: 26
  start-page: 2309499018802482
  year: 2018
  ident: B34
  article-title: Morphological and mechanical properties of plantar fascia and intrinsic foot muscles in individuals with and without flat foot
  publication-title: J. Orthop. Surg.
  doi: 10.1177/2309499018802482
– volume: 20
  start-page: 87
  year: 2023
  ident: B21
  article-title: Lower extremity muscle performance and foot pressure in patients who have plantar fasciitis with and without flat foot posture
  publication-title: Int. J. Environ. Res. Public Health
  doi: 10.3390/ijerph20010087
– volume: 27
  start-page: 1961
  year: 2023
  ident: B6
  article-title: Effects of plantar fascia stiffness on the internal mechanics of idiopathic pes cavus by finite element analysis: implications for metatarsalgia
  publication-title: Comput. Methods Biomech. Biomed. Eng.
  doi: 10.1080/10255842.2023.2268231
– volume: 27
  start-page: 363
  year: 2020
  ident: B11
  article-title: Shear wave elastography (swe) for the evaluation of patients with plantar fasciitis
  publication-title: Acad. Radiol.
  doi: 10.1016/j.acra.2019.04.009
– volume: 155
  start-page: 361
  year: 2024
  ident: B8
  article-title: Adaptive impedance control for docking robot via stewart parallel mechanism
  publication-title: ISA Trans.
  doi: 10.1016/j.isatra.2024.09.008
– volume: 27
  start-page: 125
  year: 2006
  ident: B9
  article-title: Consequences of partial and total plantar fascia release: a finite element study
  publication-title: Foot. Ankle. Int.
  doi: 10.1177/107110070602700210
– volume: 13
  start-page: 13746
  year: 2021
  ident: B40
  article-title: Research on substation project cost prediction based on sparrow search algorithm optimized bp neural network
  publication-title: Sustainability
  doi: 10.3390/su132413746
– volume: 45
  start-page: 2750
  year: 2017
  ident: B3
  article-title: A simulation of the viscoelastic behaviour of heel pad during weight-bearing activities of daily living
  publication-title: Ann. Biomed. Eng.
  doi: 10.1007/s10439-017-1918-1
– year: 2019
  ident: B38
  article-title: Non-invasive continuous blood pressure monitoring method based on ga-miv-bp neural network model
  publication-title: J. Vib. Shock
– volume: 325
  start-page: 147
  year: 1987
  ident: B20
  article-title: The spring in the arch of the human foot
  publication-title: Nature
  doi: 10.1038/325147a0
– volume: 16
  start-page: 209
  year: 2024
  ident: B22
  article-title: Does plantar pressure in short-term standing differ between modular insoles selected based upon preference or matched to self-reported foot shape?
  publication-title: Footwear Sci.
  doi: 10.1080/19424280.2024.2363536
– volume: 55
  start-page: 66
  year: 2023
  ident: B32
  article-title: Mechanical linkage between achilles tendon and plantar fascia accounts for range of motion of human ankle-foot complex
  publication-title: Med. Sci. Sports. Exerc.
  doi: 10.1249/MSS.0000000000003020
– volume: 24
  start-page: 7570
  year: 2018
  ident: B15
  article-title: Assessment of passive stiffness of medial and lateral heads of gastrocnemius muscle, achilles tendon, and plantar fascia at different ankle and knee positions using the myotonpro
  publication-title: Med. Sci. Monit.
  doi: 10.12659/MSM.909550
– volume: 36
  start-page: 364
  year: 2006
  ident: B17
  article-title: Randomized controlled trial of calcaneal taping, sham taping, and plantar fascia stretching for the short-term management of plantar heel pain
  publication-title: J. Orthop. Sports. Phys. Ther.
  doi: 10.2519/jospt.2006.2078
SSID ssj0001257582
Score 2.2875383
Snippet Plantar soft tissue properties affect foot biomechanics during movement. This study aims to explore the relationship between plantar pressure features and soft...
PurposePlantar soft tissue properties affect foot biomechanics during movement. This study aims to explore the relationship between plantar pressure features...
SourceID doaj
pubmedcentral
proquest
pubmed
crossref
SourceType Open Website
Open Access Repository
Aggregation Database
Index Database
StartPage 1482382
SubjectTerms Bioengineering and Biotechnology
biomechanics
gait
neural network
plantar pressure
plantar soft tissue
SummonAdditionalLinks – databaseName: DOAJ Directory of Open Access Journals
  dbid: DOA
  link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1La9wwEBYlp_ZQ0keaTdOiQm_FiWw9LB3T0rAU2lMXchN6pguLHXa9_z8z8mbxhkIuOfhiC1vMQ_ONPPqGkK8xZFebzKuguKoEj6EyIZtK-9rpEGWoBR5w_v1HzRfi1428mbT6wpqwkR54FNyllC4x5kPS3gvGo48mCaa98dqBsxYmUAhjk2Rq3F0BGKKb8ZQMZGHmMvtlj7SYjbhA6svCvDeJRIWw_38o83Gx5CT6XB-T1zvYSK_G6b4hL1L3lryakAm-I6tJ_Q_tM3UdXe4rCv0q0dL0hgJIhasf6AYWYDoUuVPw85xx0aMY1SLtO3rrlgO9W4Hg3ZqWatntOsFLRw6T92Rx_fPvj3m166VQBdGwoeLataGJUYpUc0AxALwM901gkQWhDZ698lkm5msvciuUki6jrwvNQ-BJ8hNy1PVdOiVU1hkWCadCCEy0CRIUyLFMTMqx6HnbzMi3B7nau5Eyw0KqgVqwRQsWtWB3WpiR7yj6_Uikuy43wAjszgjsU0YwI18eFGfBPfCfh-tSv91YXoMhIKqDMR9GRe4_xY3mQvF2RvSBig_mcvikW_4rFNw1JnItU2fPMfuP5GWDXYVxY0edk6NhvU2fAOoM_nOx6nsIY__m
  priority: 102
  providerName: Directory of Open Access Journals
Title Development of an interpretable model for foot soft tissue stiffness based on gait plantar pressure analysis
URI https://www.ncbi.nlm.nih.gov/pubmed/39834637
https://www.proquest.com/docview/3157556004
https://pubmed.ncbi.nlm.nih.gov/PMC11743706
https://doaj.org/article/55ae00bce8bb403dbd9e408b9b8a5384
Volume 12
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVAFT
  databaseName: Open Access Digital Library
  customDbUrl:
  eissn: 2296-4185
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0001257582
  issn: 2296-4185
  databaseCode: KQ8
  dateStart: 20130101
  isFulltext: true
  titleUrlDefault: http://grweb.coalliance.org/oadl/oadl.html
  providerName: Colorado Alliance of Research Libraries
– providerCode: PRVAON
  databaseName: DOAJ Directory of Open Access Journals
  customDbUrl:
  eissn: 2296-4185
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0001257582
  issn: 2296-4185
  databaseCode: DOA
  dateStart: 20130101
  isFulltext: true
  titleUrlDefault: https://www.doaj.org/
  providerName: Directory of Open Access Journals
– providerCode: PRVBFR
  databaseName: Free Medical Journals
  customDbUrl:
  eissn: 2296-4185
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0001257582
  issn: 2296-4185
  databaseCode: DIK
  dateStart: 20130101
  isFulltext: true
  titleUrlDefault: http://www.freemedicaljournals.com
  providerName: Flying Publisher
– providerCode: PRVFQY
  databaseName: GFMER Free Medical Journals
  customDbUrl:
  eissn: 2296-4185
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0001257582
  issn: 2296-4185
  databaseCode: GX1
  dateStart: 0
  isFulltext: true
  titleUrlDefault: http://www.gfmer.ch/Medical_journals/Free_medical.php
  providerName: Geneva Foundation for Medical Education and Research
– providerCode: PRVHPJ
  databaseName: ROAD: Directory of Open Access Scholarly Resources
  customDbUrl:
  eissn: 2296-4185
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0001257582
  issn: 2296-4185
  databaseCode: M~E
  dateStart: 20130101
  isFulltext: true
  titleUrlDefault: https://road.issn.org
  providerName: ISSN International Centre
– providerCode: PRVAQN
  databaseName: PubMed Central
  customDbUrl:
  eissn: 2296-4185
  dateEnd: 99991231
  omitProxy: true
  ssIdentifier: ssj0001257582
  issn: 2296-4185
  databaseCode: RPM
  dateStart: 20130101
  isFulltext: true
  titleUrlDefault: https://www.ncbi.nlm.nih.gov/pmc/
  providerName: National Library of Medicine
– providerCode: PRVFZP
  databaseName: Scholars Portal Journals: Open Access
  customDbUrl:
  eissn: 2296-4185
  dateEnd: 20250131
  omitProxy: true
  ssIdentifier: ssj0001257582
  issn: 2296-4185
  databaseCode: M48
  dateStart: 20130901
  isFulltext: true
  titleUrlDefault: http://journals.scholarsportal.info
  providerName: Scholars Portal
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1La9wwEBYhvbSH0qav7SOo0FtxKluyLB1KSEtCKKSnLuQm9EwXFjvxeqH9952RvctuSQ89-GILWdY3mvlGHs0Q8iH4ZEudeOEll4XgwRfaJ10oV1rlQ-1LgQecr77Ly7n4dl1fH5BNuaNpAlf3unZYT2reL09-3f0-hQX_GT1OsLefklt0mPGyEieY1ZIrUMkPwDJVKOVXE90f91yAnOT6UVWlYWRgq8ZzNP_oZs9W5ZT-9_HQv8Mpd-zTxRPyeCKW9GyUhKfkILZH5NFOusFnZLkTIUS7RG1LF9uYQ7eMNJfFoUBj4eoGugIVTYeMDAVNkBKqRYp2L9CupTd2MdDbJUBje5rjadd9hE7HLCfPyfzi_MfXy2KqtlB4UbGh4Mo2vgqhFrHkwHOAmmnuKs8C80JpPJ3lUh2ZK51IjZCytgm1gVDcex5r_oIctl0bXxFalwnUiJXeeyaaCC4MeGE6RGlZcLypZuTjZl7N7ZhUw4AzgiiYjIJBFMyEwox8wanftsSE2PlG19-YaX2ZuraRMeejck4wHlzQUTDltFMWdLqYkfcb4AwsIPwrYtvYrVeGlyAUyPugzcsRyO2ruFZcSN7MiNqDeG8s-0_axc-cpLtEV69h8vV_fesb8rDCAsO4xyPfksOhX8d3wHoGd5x3C46zQP8BYRwB7w
linkProvider Scholars Portal
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Development+of+an+interpretable+model+for+foot+soft+tissue+stiffness+based+on+gait+plantar+pressure+analysis&rft.jtitle=Frontiers+in+bioengineering+and+biotechnology&rft.au=Bai%2C+Xiaotian&rft.au=Hou%2C+Xiao&rft.au=Lv%2C+Dazhi&rft.au=Wei%2C+Jialin&rft.date=2025-01-06&rft.issn=2296-4185&rft.eissn=2296-4185&rft.volume=12&rft_id=info:doi/10.3389%2Ffbioe.2024.1482382&rft.externalDBID=n%2Fa&rft.externalDocID=10_3389_fbioe_2024_1482382
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2296-4185&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2296-4185&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2296-4185&client=summon