{"title":"基于高斯基函数的垂直地面反作用力的生理约束分解:步态表征的全曲线方法","authors":"Thomas Ertelt","doi":"10.1016/j.jbiomech.2025.112990","DOIUrl":null,"url":null,"abstract":"<div><div>We aimed to test whether a healthy-derived, phase-anchored μ template can approximate pathological vGRF waveforms and quantify deviations relative to normative patterns. Traditional peak-based metrics capture only fragments of gait dynamics. This study introduces a physiologically anchored model that reconstructs the entire vertical ground-reaction-force (vGRF) curve with eight Gaussian basis functions, each linked to a specific sub-phase of stance. Ninety-one published vGRF traces representing healthy walking and running, post-stroke recovery stages, total-hip-arthroplasty gait, transtibial and foot-prosthesis use, and athletic sprinting were digitised, amplitude- and time-normalised, and fitted with constrained non-linear optimisation. Position parameters (μ) were restricted to ± 1 standard deviation around phase-specific mean values, while amplitudes (A) and widths (σ) were freely optimised. The model reproduced GRF morphology with coefficients of determination (R<sup>2</sup>) from 0.95 to 0.99 and root-mean-square errors below 0.03 body-weight across all conditions. Fixed μ values alone reconstructed a reference walking curve with R<sup>2</sup> = 0.996, demonstrating the validity of the phase template. Radar plot visualisations of A and σ revealed characteristic deviations that were obscured in peak-based analysis: elevated mid-stance loads and diminished push-off in post-stroke gait, broadened mid-stance components after hip arthroplasty, and attenuated late-stance amplitudes in prosthetic limbs. The eight-component Gaussian model provides a concise 24-parameter representation of vGRF trajectories, enabling accurate, interpretable and storage-efficient gait profiling. Its phase-anchored structure enhances diagnostic sensitivity, supports progress monitoring in rehabilitation, and is readily transferable to wearable or large-scale database applications. Radar plots offer an exploratory summary of gait morphology, supporting objective comparisons within and between individuals.</div></div>","PeriodicalId":15168,"journal":{"name":"Journal of biomechanics","volume":"193 ","pages":"Article 112990"},"PeriodicalIF":2.4000,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Physiologically-constrained decomposition of vertical ground reaction forces using gaussian basis functions: A full-curve approach to gait characterization\",\"authors\":\"Thomas Ertelt\",\"doi\":\"10.1016/j.jbiomech.2025.112990\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>We aimed to test whether a healthy-derived, phase-anchored μ template can approximate pathological vGRF waveforms and quantify deviations relative to normative patterns. Traditional peak-based metrics capture only fragments of gait dynamics. This study introduces a physiologically anchored model that reconstructs the entire vertical ground-reaction-force (vGRF) curve with eight Gaussian basis functions, each linked to a specific sub-phase of stance. Ninety-one published vGRF traces representing healthy walking and running, post-stroke recovery stages, total-hip-arthroplasty gait, transtibial and foot-prosthesis use, and athletic sprinting were digitised, amplitude- and time-normalised, and fitted with constrained non-linear optimisation. Position parameters (μ) were restricted to ± 1 standard deviation around phase-specific mean values, while amplitudes (A) and widths (σ) were freely optimised. The model reproduced GRF morphology with coefficients of determination (R<sup>2</sup>) from 0.95 to 0.99 and root-mean-square errors below 0.03 body-weight across all conditions. Fixed μ values alone reconstructed a reference walking curve with R<sup>2</sup> = 0.996, demonstrating the validity of the phase template. Radar plot visualisations of A and σ revealed characteristic deviations that were obscured in peak-based analysis: elevated mid-stance loads and diminished push-off in post-stroke gait, broadened mid-stance components after hip arthroplasty, and attenuated late-stance amplitudes in prosthetic limbs. The eight-component Gaussian model provides a concise 24-parameter representation of vGRF trajectories, enabling accurate, interpretable and storage-efficient gait profiling. Its phase-anchored structure enhances diagnostic sensitivity, supports progress monitoring in rehabilitation, and is readily transferable to wearable or large-scale database applications. Radar plots offer an exploratory summary of gait morphology, supporting objective comparisons within and between individuals.</div></div>\",\"PeriodicalId\":15168,\"journal\":{\"name\":\"Journal of biomechanics\",\"volume\":\"193 \",\"pages\":\"Article 112990\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2025-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of biomechanics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0021929025005020\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of biomechanics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0021929025005020","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOPHYSICS","Score":null,"Total":0}
Physiologically-constrained decomposition of vertical ground reaction forces using gaussian basis functions: A full-curve approach to gait characterization
We aimed to test whether a healthy-derived, phase-anchored μ template can approximate pathological vGRF waveforms and quantify deviations relative to normative patterns. Traditional peak-based metrics capture only fragments of gait dynamics. This study introduces a physiologically anchored model that reconstructs the entire vertical ground-reaction-force (vGRF) curve with eight Gaussian basis functions, each linked to a specific sub-phase of stance. Ninety-one published vGRF traces representing healthy walking and running, post-stroke recovery stages, total-hip-arthroplasty gait, transtibial and foot-prosthesis use, and athletic sprinting were digitised, amplitude- and time-normalised, and fitted with constrained non-linear optimisation. Position parameters (μ) were restricted to ± 1 standard deviation around phase-specific mean values, while amplitudes (A) and widths (σ) were freely optimised. The model reproduced GRF morphology with coefficients of determination (R2) from 0.95 to 0.99 and root-mean-square errors below 0.03 body-weight across all conditions. Fixed μ values alone reconstructed a reference walking curve with R2 = 0.996, demonstrating the validity of the phase template. Radar plot visualisations of A and σ revealed characteristic deviations that were obscured in peak-based analysis: elevated mid-stance loads and diminished push-off in post-stroke gait, broadened mid-stance components after hip arthroplasty, and attenuated late-stance amplitudes in prosthetic limbs. The eight-component Gaussian model provides a concise 24-parameter representation of vGRF trajectories, enabling accurate, interpretable and storage-efficient gait profiling. Its phase-anchored structure enhances diagnostic sensitivity, supports progress monitoring in rehabilitation, and is readily transferable to wearable or large-scale database applications. Radar plots offer an exploratory summary of gait morphology, supporting objective comparisons within and between individuals.
期刊介绍:
The Journal of Biomechanics publishes reports of original and substantial findings using the principles of mechanics to explore biological problems. Analytical, as well as experimental papers may be submitted, and the journal accepts original articles, surveys and perspective articles (usually by Editorial invitation only), book reviews and letters to the Editor. The criteria for acceptance of manuscripts include excellence, novelty, significance, clarity, conciseness and interest to the readership.
Papers published in the journal may cover a wide range of topics in biomechanics, including, but not limited to:
-Fundamental Topics - Biomechanics of the musculoskeletal, cardiovascular, and respiratory systems, mechanics of hard and soft tissues, biofluid mechanics, mechanics of prostheses and implant-tissue interfaces, mechanics of cells.
-Cardiovascular and Respiratory Biomechanics - Mechanics of blood-flow, air-flow, mechanics of the soft tissues, flow-tissue or flow-prosthesis interactions.
-Cell Biomechanics - Biomechanic analyses of cells, membranes and sub-cellular structures; the relationship of the mechanical environment to cell and tissue response.
-Dental Biomechanics - Design and analysis of dental tissues and prostheses, mechanics of chewing.
-Functional Tissue Engineering - The role of biomechanical factors in engineered tissue replacements and regenerative medicine.
-Injury Biomechanics - Mechanics of impact and trauma, dynamics of man-machine interaction.
-Molecular Biomechanics - Mechanical analyses of biomolecules.
-Orthopedic Biomechanics - Mechanics of fracture and fracture fixation, mechanics of implants and implant fixation, mechanics of bones and joints, wear of natural and artificial joints.
-Rehabilitation Biomechanics - Analyses of gait, mechanics of prosthetics and orthotics.
-Sports Biomechanics - Mechanical analyses of sports performance.