{"title":"基于步态足底压力分析的足部软组织刚度可解释模型的建立。","authors":"Xiaotian Bai, Xiao Hou, Dazhi Lv, Jialin Wei, Yiling Song, Zhengyan Tang, Hongfeng Huo, Jingmin Liu","doi":"10.3389/fbioe.2024.1482382","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":12444,"journal":{"name":"Frontiers in Bioengineering and Biotechnology","volume":"12 ","pages":"1482382"},"PeriodicalIF":4.3000,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11743706/pdf/","citationCount":"0","resultStr":"{\"title\":\"Development of an interpretable model for foot soft tissue stiffness based on gait plantar pressure analysis.\",\"authors\":\"Xiaotian Bai, Xiao Hou, Dazhi Lv, Jialin Wei, Yiling Song, Zhengyan Tang, Hongfeng Huo, Jingmin Liu\",\"doi\":\"10.3389/fbioe.2024.1482382\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":12444,\"journal\":{\"name\":\"Frontiers in Bioengineering and Biotechnology\",\"volume\":\"12 \",\"pages\":\"1482382\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2025-01-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11743706/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Bioengineering and Biotechnology\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.3389/fbioe.2024.1482382\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"BIOTECHNOLOGY & APPLIED MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Bioengineering and Biotechnology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3389/fbioe.2024.1482382","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
Development of an interpretable model for foot soft tissue stiffness based on gait plantar pressure analysis.
Purpose: 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.
Methods: 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.
Results: 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.
Conclusion: 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.
期刊介绍：
The translation of new discoveries in medicine to clinical routine has never been easy. During the second half of the last century, thanks to the progress in chemistry, biochemistry and pharmacology, we have seen the development and the application of a large number of drugs and devices aimed at the treatment of symptoms, blocking unwanted pathways and, in the case of infectious diseases, fighting the micro-organisms responsible. However, we are facing, today, a dramatic change in the therapeutic approach to pathologies and diseases. Indeed, the challenge of the present and the next decade is to fully restore the physiological status of the diseased organism and to completely regenerate tissue and organs when they are so seriously affected that treatments cannot be limited to the repression of symptoms or to the repair of damage. This is being made possible thanks to the major developments made in basic cell and molecular biology, including stem cell science, growth factor delivery, gene isolation and transfection, the advances in bioengineering and nanotechnology, including development of new biomaterials, biofabrication technologies and use of bioreactors, and the big improvements in diagnostic tools and imaging of cells, tissues and organs.
In today`s world, an enhancement of communication between multidisciplinary experts, together with the promotion of joint projects and close collaborations among scientists, engineers, industry people, regulatory agencies and physicians are absolute requirements for the success of any attempt to develop and clinically apply a new biological therapy or an innovative device involving the collective use of biomaterials, cells and/or bioactive molecules. “Frontiers in Bioengineering and Biotechnology” aspires to be a forum for all people involved in the process by bridging the gap too often existing between a discovery in the basic sciences and its clinical application.
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