Revista de Ciencias Tecnológicas (RECIT). Volumen 3 (1): 10-22
Revista de Ciencias Tecnológicas (RECIT). Universidad Autónoma de Baja California ISSN 2594-1925
Volumen 9 (2): e448. Abril-Junio, 2026. https://doi.org/10.37636/recit.v9n2e448
ISSN: 2594-1925
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Research article
Structural analysis of generative design applied to ergonomic plantar
orthoses
Análisis estructural del diseño generativo aplicado a órtesis plantares ergonómicas
Christian Enrique Nava-Alcantar1, Agustín Vidal-Lesso2, Marco Antonio Martínez-Bocanegra3, Luis
Ángel Ortiz-Lango4, Juan Carlos García-Valadez4, Sergio Alonso Romero5, Israel Miguel-Andrés4
1Posgrado PICYT, Centro de Innovación Aplicada en Tecnologías Competitivas, León 37545, Guanajuato, México.
2Mechanical Engineering Department, Universidad de Guanajuato, Salamanca, 36885, Guanajuato, México.
3TecNM: Instituto Tecnológico Superior del Sur de Guanajuato, Uriangato, 38982, Guanajuato, México.
4Laboratorio Nacional CONAHCYT en Biomecánica del Cuerpo Humano, CIATEC, León, 37545, Guanajuato, México.
5Dirección de Investigación y Soluciones Tecnológicas, CIATEC, León, 37545, Guanajuato, México.
Corresponding author: Israel Miguel-Andrés; Laboratorio Nacional CONAHCYT en Biomecánica del Cuerpo Humano, CIATEC, León,
37545, Guanajuato, México; imiguel@ciatec.mx; https://orcid.org/0000-0002-9433-7864.
Received: March 9, 2026 Accepted: May 19, 2026 Published: May 22, 2026
Abstract. - Plantar orthoses are devices designed to provide support and correct the biomechanics of the foot. Generative
design offers ample potential for personalization; however, the analysis of its structural behavior continues to be a significant
challenge. This research aims to evaluate the structural optimization of orthoses designed by generative design compared to
traditional models. An analysis of 33 middle-aged adult men classified as normal weight, with an average weight of 65.32 ±
6.79 kg, was performed using a baropodometric database. An optimized orthosis was designed by parametric modeling to
evaluate its mechanical response in static standing conditions, using the finite element method with the TPU A95 material. The
results indicated that the trabecular structures produced by generative design absorb more energy (0.3876 J) than a
bilaminated orthosis made with EVA A40 and A15 materials (0.0362 J). The levels of deformation obtained (maximum principal
strain = 1.34%, equivalent elastic strain = 2.14%) indicate that the composition of the generative model works well within the
elastic regime, ensuring structural integrity. However, the low strain and strain energy values suggest relatively rigid behavior,
which can limit the shock absorption capacity. The main contribution of this work is to demonstrate how generative design can
be integrated into methodologies for designing plantar orthotics. It explores the potential benefits of this approach and
examines how generative design parameters influence mechanical responses. This research provides a technical foundation
for optimizing ergonomic orthoses through generative design and structural modeling. The findings emphasize the potential of
generative design in creating optimized orthoses and highlight the significance of design parameters on the outcomes achieved.
This insight is valuable for future applications of generative design in the field of ergonomics.
Keywords: Finite element analysis; Generative design; Ergonomics; Elastomeric materials.
Resumen. - Las órtesis plantares son dispositivos diseñados para proporcionar soporte y corregir la biomecánica del pie. El
diseño generativo ofrece un gran potencial para la personalización; sin embargo, el análisis de su comportamiento estructural
continúa siendo un desao significativo. Este estudio tiene como objetivo evaluar la optimización estructural de órtesis
diseñadas mediante diseño generativo en comparación con los modelos tradicionales. Se realizó un análisis de 33 hombres
adultos de mediana edad clasificados como normopeso, con un peso promedio de 65.32 ± 6.79 kg a partir de una base de datos
de baropodometría. Se diseñó mediante modelado paramétrico una órtesis optimizada para evaluar su respuesta mecánica en
condiciones de bipedestación estática, utilizando el método de elementos finitos con el material TPU A95. Los resultados
indicaron que las estructuras trabeculares producidas mediante diseño generativo absorben más energía (0.3876 J) que una
órtesis bilaminada confeccionada con materiales EVA A40 y A15 (0.0362 J). Los niveles de deformación obtenidos
(deformación principal xima = 1.34%, deformación elástica equivalente = 2.14%) indican que la composición del modelo
generativo funciona bien dentro del régimen elástico, asegurando la integridad estructural. Sin embargo, los bajos valores de
deformación y energía de deformación sugieren un comportamiento relativamente rígido, lo que puede restringir la capacidad
de absorción de impactos. La principal contribución de este estudio es demostrar cómo el diseño generativo puede integrarse
en metodologías para diseñar órtesis plantares. Explora los posibles beneficios de este enfoque y examina cómo los parámetros
generativos del diseño influyen en las respuestas mecánicas. Esta investigación proporciona una base técnica para optimizar
las órtesis ergonómicas mediante modelado estructural y diseño generativo. Los hallazgos subrayan el potencial del diseño
generativo para crear órtesis optimizadas y destacan la importancia de los parámetros de diseño en los resultados alcanzados.
Esta información es valiosa para futuras aplicaciones del diseño generativo en el campo de la ergonomía.
Palabras clave: Análisis de elementos finitos; Diseño generativo; Ergonomía; Materiales elastoméricos.
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1. Introduction
The human foot is designed for load absorption and to provide stability to the body; however, increased
body weight can lead to musculoskeletal alterations in the foot [1], [2], [3]. Several studies have
associated body mass index (BMI) with increased plantar pressure, a larger contact area, and abnormal
load redistribution in the plantar area, which directly influence the onset of pain and fatigue [4], [5],
[6], [7].
To mitigate the adverse effects of these weight conditions, plantar orthoses are used to support, align,
or redistribute the pressure of the foot, improving the function of the foot, treating pathologies with
materials such as Ethyl-Vinyl-Acetate (EVA) in varying degrees of rigidity that can be prefabricated
or customized to the needs of the patient [8], [9], [10]. However, the design of these orthoses is still
based on solid geometries that have limitations in their mechanical capabilities [11], [12], [13].
Additive manufacturing has enabled the incorporation of advanced structures with adjustable
mechanical properties, thereby improving plantar pressure distribution [14], [15], [16], [17].
Among the wide range of structural optimization techniques in human ergonomics, the application of
generative design has great potential to meet patients' needs; however, it also faces certain challenges,
including structural behavior, one of the most prominent [18], [19]. This research aims to investigate
structural optimization through the application of generative design in plantar foot orthoses compared
to traditional orthoses to design optimized orthoses from statistical data from a sample of
baropodometric data and characterization of materials to analyze their structural behavior under static
standing loads by finite element analysis
2. Background
The effect of optimized structures applied in plantar orthoses on load distribution has been
investigated, demonstrating their potential to withstand areas of high pressure and energy absorption,
including optimization methods and generative structures [20], [21], [22]. Generative design is an AI-
assisted process where goals and constraints are defined to automatically explore and generate multiple
optimized design solutions, producing biomimetic organic shapes [23], [24]. Generative design is
based on four main algorithmic processes: shape synthesis to explore geometries and structures,
surface optimization to determine optimal configurations, topological optimization to minimize
weight while maintaining strength, and trabecular structures to generate complex geometries inspired
by trabecular patterns [25], [26], [27]. In Hüseyin Özsoy’s review [28], it is mentioned that ergonomics
is one of the main approaches to generative design. Urquhart et al. [29] report that generative design
focused on human factors, ergonomics, anatomy, and functionality is essential for applying discrete
data and design intelligence in real case studies. Specifically, Schneider et al. [30] investigated the
application of generative design in plantar orthoses; the study highlights the potential to optimize
orthotic design that improves patient comfort and mobility and the impact of boundary conditions on
structure generation.
For the design of plantar foot orthoses, various anthropometric factors adjusted to the patient's needs
are taken into account [31]. Among these factors, one of the most closely related to the distribution of
plantar pressure is the areas of support of the foot [32]. This metric quantifies what percentage of the
total load is distributed in certain areas. Generally, the plantar area is divided into three parts: forefoot,
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midfoot, and hindfoot. These areas are the ones that support the individual's body weight. It has been
reported that weight is the main factor for the increase in plantar pressure in critical areas such as the
forefoot and hindfoot [33], [34]. Ramos-Frutos et al. [35] reported that when people are in static
standing, the hindfoot presents more pressure (55.64 ± 18.80%) than the forefoot (45.18 ± 19.50%) in
the Mexican population.
For the manufacture of these orthoses, EVA material is usually used because it is a lightweight,
flexible, durable material and offers good cushioning and support. Bilaminated orthoses of two degrees
of EVA hardness are usually manufactured; high hardness grades serve as structural support and
impact absorption, while lower hardness grades are used for plantar pressure redistribution [36].
However, these materials can only be applied to machinable solid geometries, which have limited
capacity. With the incorporation of optimized structures, additive manufacturing has enabled the use
of materials such as thermoplastic polyurethane (TPU) for structural support and shock absorption,
owing to its high resistance to wear and abrasion. TPU offers high cushioning, ergonomic support,
and durability [37], [38].
3. Methodology
As shown in Figure 1, a methodology was developed for the parametric modeling of an optimized
orthosis with a generative design with anthropometric-based data from a representative sample of
middle-aged adults classified as normal weight and the mechanical properties of characterized
materials, finally analyzing their mechanical behavior through finite element analysis.
Figure 1. Workflow diagram of the study.
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3.1 Procedure
From a baropodometric database, an analysis of 33 middle-aged adult men classified as normal weight
was carried out, with an average weight of 65.32 ± 6.79 kg and a BMI of 22.68 ± 1.82 kg/m2. The data
were taken directly from the FreeStep® software (version 1.6.009, Sensormedica®, Guidonia
Montecelio, Rome, Italy). Once the data were obtained, an average body load of 640.78 N was
calculated for the total sample. The right foot was selected for the orthosis design due to its functional
predominance. According to the analysis carried out, it is determined that the right foot supports 46.70
± 7.80% of the body weight of the sample, the forefoot supports 40.64 ± 17.85%, while the hindfoot
supports 59.36 ± 17.85% of the load of the right foot.
3.2 Materials characterization
Material characterization was carried out on an Instron® 8872 universal testing machine (Instron®,
Norwood, Massachusetts, USA) by tensile testing in accordance with ASTM D412-16 with type C
specimens, applicable to thermoset rubbers and thermoplastic elastomers, commonly used to evaluate
both EVA and TPU under tension [39], [40]. This choice is considering the trabecular nature of the
generative design; the internal components of the geometry are subjected to complex stress states,
including local stress and flexural forces. Therefore, it is crucial to evaluate the elongation capacity
and strength of the base material under these conditions.
The tensile properties of two EVA hardness levels were evaluated: A40 (medium hardness) and A15
(soft hardness). EVA A15 exhibited low stiffness and reduced tensile strength, while EVA A40
demonstrated significantly higher rigidity, tensile strength, and elongation capacity, as shown in
Figure 2. Both materials showed high flexibility and ductility, consistent with prior literature [41],
[42].
Figure 2. ASTM D412-16 Type C EVA specimens in different hardness grades. a) A40. b) A15. c) Stress-strain diagram.
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TPU A95 was characterized; its tensile properties exhibit ductile and elastomeric behavior, as shown
in Figure 3. It demonstrates high deformation capacity prior to fracture and a stable load response,
indicating good resistance to tension and impact, consistent with literature trends [43], [44].
Figure 3. a) ASTM D412-16 Type C specimen of TPU A95. b) Stress-strain diagram.
The data obtained from the stress tests served as input data for the definition of materials and their
properties for numerical simulation, simplified as a linear elastic material. The properties of the
materials are shown in Table 1.
Table 1. Tensile mechanical properties of the characterized materials.
Material
Poisson’s ratio
Young's modulus
(MPa)
Yield tensile
strength (MPa)
Ultimate tensile
strength (MPa)
EVA A15
0.48
0.60
0.002
0.648
EVA A40
0.48
2.20
0.020
2.768
TPU A95
0.40
9.70
3.694
8.002
3.3 Generative design of the orthosis
To establish a base geometry with which the generative design can be integrated, Autodesk® Fusion
360 software (version 2.0, Autodesk® Inc., San Rafael, California, USA) was utilized to model a
bilaminated flat orthosis measuring 270 mm in length, 78 mm in width, and 10 mm in thickness. This
design consists of 8 mm of EVA A40 for structural support and a 2 mm surface layer of EVA A15,
intended for structural analysis purposes without considering the morphology of the foot, as shown in
Figure 4.
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Figure 4. Bilaminated EVA orthosis. a) Lateral view. b) Isometric view.
A generative design study was carried out in which boundary conditions were established based on
the inputs obtained from the database to define the loads distributed along the contact surface of the
orthosis. According to Perry [45] in her Gait Analysis book and Schneider et al. [46], in their previous
work on generative design applied to plantar orthoses, it is mentioned that shear forces should be
considered within the parameters of the generative study. This is relevant, as the application of vertical
loads on a single axis would lead to the creation of straight structures, designed exclusively to
withstand vertical compression. Therefore, it was assigned a percentage of the total load to the forces
on the horizontal axis; the assigned load values correspond to each area of the contact surface. These
values were calculated according to the percentages of load distribution of the average right foot from
the sample; the values are shown in Table 2.
Table 2. Loads corresponding to the boundary conditions of the analysis.
In addition, the movement of both rotation and translation of the lower contact surface of the orthosis
was restricted. As can be seen in Figure 5, preserved volumes were defined in the direct contact areas
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that act as a solid interface to ensure a uniform load distribution towards the internal trabecular
structure. Finally, a 6 mm-thick geometry core was established as the initial geometry for the
generation of generative structures. The criterion of maximizing stiffness was chosen to guarantee
structural support, a minimum safety factor of 2.0, and, as a manufacturing method, unrestricted was
chosen. The material defined for the study was the previously characterized TPU A95.
Figure 5. Boundary conditions for generative design study.
A plantar orthosis optimized under the parameters of the generative design of a single iteration was
obtained, as observed in Figure 6.
Figure 6. Orthosis (generative design). a) Lateral view. b) Isometric view. c) Top view (plane cut).
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3.4 Numerical simulation
Finally, a static structural analysis was performed using the finite element method, both for the
bilaminated EVA orthosis and for the generative design orthosis for comparison. The same boundary
conditions used in the generative design study were defined, with the difference that only the
compressive forces exerted on the Z axis were considered, simulating standing loads, as shown in
Figure 7. These conditions were applied to both models. Additionally, a mesh sensitivity analysis was
performed, from which a second-order tetrahedral element mesh with an element size of 2 mm was
chosen for both models, with an error of less than 2%.
Figure 7. Boundary conditions for static structural study.
The mechanical behavior was interpreted using criteria based on deformation, displacement, and
energy, which allow the evaluation of effective stiffness, absorption capacity, and load distribution,
avoiding the use of classical failure criteria that are not representative of linear and nonlinear elastic
materials. The selection of the four variables analyzed is based on the need to evaluate the structural
performance of both EVA and TPU materials, which were considered as plastic materials. Maximum
principal strain and equivalent elastic strain were examined to observe the structural capacity of these
materials and their behavior within their yield strength. Likewise, total deformation was used to study
the overall geometric change of the device under load. Finally, energy absorption was chosen as a
parameter to quantify the efficiency of orthoses in load management.
4. Results
The finite element analysis allowed for the comparison of the mechanical behavior of the bilaminated
EVA orthosis and the TPU orthosis with generative design under the same load conditions. The
mechanical variables obtained by simulation were compared, evaluating absolute and relative
differences, as well as the performance ratios between materials, consistent with linear and nonlinear
elastic models.