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Advancements in Biomechanical Gait Analysis: Implications for Footwear Biomechanics and...
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Advancements in Biomechanical Gait Analysis: Implications for Footwear Biomechanics and Sports Injury Prevention

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biomechanics and Sports Medicine".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 15063

Special Issue Editors

Dr. Yang Song

E-Mail Website
Guest Editor
Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
Interests: gait biomechanics; footwear biomechanics; computational simulation
Dr. Dong Sun

E-Mail Website
Guest Editor
Faculty of Sports Science, Ningbo University, Ningbo, China
Interests: gait biomechanics; sports shoes; sports injuries
Dr. Xuanzhen Cen

E-Mail Website
Guest Editor
Faculty of Sports Science, Ningbo University, Ningbo, China
Interests: lower limb biomechanics; musculoskeletal bioengineering; computational simulation

Special Issue Information

Dear Colleagues,

In recent years, the field of biomechanical gait analysis has experienced significant advancements, offering profound insights into human movement. This Special Issue focuses on the implications of these advancements for footwear biomechanics and sports injury prevention.

Biomechanical gait analysis involves the study of human locomotion through the application of advanced technologies such as motion capture systems, wearable sensors, and computational modeling. These tools enable the precise assessment of gait patterns, providing critical data for optimizing footwear design and developing strategies to mitigate sports-related injuries.

Footwear biomechanics plays a crucial role in enhancing athletic performance and reducing injury risk. By integrating gait analysis data, researchers and designers can create footwear that better supports natural movement patterns, adapts to individual biomechanical needs, and enhances overall stability and comfort.

Sports injuries, often resulting from abnormal gait mechanics, pose significant challenges to athletes and healthcare providers. This Special Issue will explore innovative approaches to injury prevention, including the use of personalized footwear solutions and the application of machine learning algorithms to predict injury risk based on gait analysis data.

We also aim to highlight interdisciplinary collaborations that bridge the gap between biomechanics, sports science, and footwear design. Contributions may include case studies, technological innovations, and theoretical models that advance our understanding of gait mechanics and their practical applications.

We invite researchers to submit their cutting-edge research, methodologies, and insights to further the field of biomechanical gait analysis and its impact on footwear biomechanics and sports injury prevention.

Dr. Yang Song
Dr. Dong Sun
Dr. Xuanzhen Cen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • human locomotion
  • motion capture technology
  • wearable sensors
  • biomechanical modeling
  • injury risk assessment
  • personalized footwear design
  • machine learning in biomechanics
  • sports science integration

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Published Papers (4 papers)

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Research

23 pages, 6070 KB  
Article
Test–Retest Reliability and Validity of a Sums-of-Gaussians-Based Markerless Motion Capture System for Human Lower-Limb Gait Kinematics
by Yifei Shou, Chuang Gao, Chenbin Xi, Junqi Jia, Jiaojiao Lü, Yufei Fang, Chengte Lin and Zhiqiang Liang
Bioengineering 2026, 13(3), 271; https://doi.org/10.3390/bioengineering13030271 - 26 Feb 2026
Viewed by 448
Abstract
Background and aim: Traditional marker-based optical motion capture systems are costly, time-consuming to operate, and constrained by laboratory environments, limiting their broader adoption in clinical practice and naturalistic settings. Markerless motion capture based on a sums-of-Gaussians (SoG) body model is a potential alternative; [...] Read more.
Background and aim: Traditional marker-based optical motion capture systems are costly, time-consuming to operate, and constrained by laboratory environments, limiting their broader adoption in clinical practice and naturalistic settings. Markerless motion capture based on a sums-of-Gaussians (SoG) body model is a potential alternative; however, its metrological properties for kinematic assessment during walking and slow running remain insufficiently validated. Using a conventional marker-based Vicon system as the reference, this study evaluated the reliability and concurrent validity of an SoG-based markerless system (MocapGS) for bilateral lower-limb joint range of motion (ROM) during gait. Methods: Thirty-six healthy adults completed self-selected-pace speed walking and slow running tasks while both systems synchronously acquired bilateral lower-limb kinematics. The intraclass correlation coefficient (ICC), standard error of measurement (SEM), SEM percentage (SEM%), minimal detectable change (MDC), MDC percentage (MDC%), and root mean square error (RMSE) were used to assess reliability. Concurrent validity was evaluated using the Pearson correlation coefficient, paired-sample t-tests, and the concordance correlation coefficient (CCC) to compare the ROM. Results: Vicon showed moderate-to-high reliability for ROM in most joints across both tasks. By contrast, the MocapGS achieved acceptable ICC values mainly for the sagittal-plane ROM at the hip and knee. The CCC analysis showed no significant agreement between the two systems. Bland–Altman plots showed systematic biases with spatially heterogeneous random errors. During walking, MocapGS systematically overestimated ROM relative to Vicon at several joint axes; the widest limits of agreement (LOA) occurred at the left knee X-axis and right hip Z-axis. During running, overestimation was consistent across all bilateral joints at the X-axis and the right hip at the Y-axis, while the widest LOA were found at the bilateral hip X-axes. These specific discrepancies highlighted the joint–axis combinations with the greatest measurement variance. In walking, the test–retest reliability of the knee flexion–extension ROM measured by the MocapGS approached that of Vicon; however, the SEM% and MDC% were generally larger for MocapGS than for Vicon. The RMSE exceeded 5 degrees for ROM in most joint planes, especially in the frontal and transverse planes and at distal joints; errors increased further during slow running. Conclusions: MocapGS may be used for coarse monitoring of large-magnitude changes in sagittal-plane kinematics during gait; however, it is currently unlikely to replace Vicon for clinical decision-making or detecting subtle gait changes, and its outputs should be interpreted with caution, particularly for ankle kinematics and non-sagittal-plane motion. Full article
(This article belongs to the Special Issue Advancements in Biomechanical Gait Analysis: Implications for Footwear Biomechanics and Sports Injury Prevention)
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32 pages, 9460 KB  
Article
Step-Length Estimation in Asymmetric Gait Using a Single Lower-Back IMU Data and a Biomechanical Model Inspired by a Double Inverted Pendulum
by Daniela Pinto, Paulina Ortega-Bastidas and Pablo Aqueveque
Bioengineering 2026, 13(1), 3; https://doi.org/10.3390/bioengineering13010003 - 20 Dec 2025
Viewed by 781
Abstract
Step length is a fundamental parameter for gait assessment, reflecting complex neuromuscular and biomechanical behavior. Accurate step-length estimation is clinically relevant for monitoring populations with neurological or musculoskeletal conditions, as well as older adults. This study presents a novel biomechanical model, inspired by [...] Read more.
Step length is a fundamental parameter for gait assessment, reflecting complex neuromuscular and biomechanical behavior. Accurate step-length estimation is clinically relevant for monitoring populations with neurological or musculoskeletal conditions, as well as older adults. This study presents a novel biomechanical model, inspired by the inverted double pendulum, for step-length estimation under asymmetric gait conditions using a single inertial sensor on the lower back. Unlike models that assume symmetry, the proposed model explicitly incorporates pelvic rotation, enabling more accurate step length estimation, particularly in individuals with gait impairment. The model was validated against a gold standard OptiTrack® (Corvallis, OR, USA) system with 33 adults: 21 participants without and 12 with gait impairment. Results show that the model achieved low Median Absolute Errors (MdAE), below 0.04 m in participants without gait impairment and remaining within 0.06 m in those with impairment. Statistical validation confirmed a strong correlation with the reference system (R = 0.96, R2 = 0.93) and a clinically trivial mean bias (0.64 cm) from Bland-Altman analysis. These results validate the model’s effectiveness under various gait conditions, suggesting its technical feasibility and strong potential for clinical and real-world applications, particularly for the longitudinal monitoring of patients with functional impairments. Full article
(This article belongs to the Special Issue Advancements in Biomechanical Gait Analysis: Implications for Footwear Biomechanics and Sports Injury Prevention)
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24 pages, 4301 KB  
Article
Control Deficits and Compensatory Mechanisms in Individuals with Chronic Ankle Instability During Dual-Task Stair-to-Ground Transition
by Yilin Zhong, Xuanzhen Cen, Xiaopan Hu, Datao Xu, Lei Tu, Monèm Jemni, Gusztáv Fekete, Dong Sun and Yang Song
Bioengineering 2025, 12(10), 1120; https://doi.org/10.3390/bioengineering12101120 - 19 Oct 2025
Cited by 1 | Viewed by 1943
Abstract
(1) Background: Chronic ankle instability (CAI), a common outcome of ankle sprains, involves recurrent sprains, balance deficits, and gait impairments linked to both peripheral and central neuromuscular dysfunction. Dual-task (DT) demands further aggravate postural control, especially during stair descent, a major source of [...] Read more.
(1) Background: Chronic ankle instability (CAI), a common outcome of ankle sprains, involves recurrent sprains, balance deficits, and gait impairments linked to both peripheral and central neuromuscular dysfunction. Dual-task (DT) demands further aggravate postural control, especially during stair descent, a major source of fall-related injuries. Yet the biomechanical mechanisms of stair-to-ground transition in CAI under dual-task conditions remain poorly understood. (2) Methods: Sixty individuals with CAI and age- and sex-matched controls performed stair-to-ground transitions under single- and dual-task conditions. Spatiotemporal gait parameters, center of pressure (COP) metrics, ankle inversion angle, and relative joint work contributions (Ankle%, Knee%, Hip%) were obtained using 3D motion capture, a force plate, and musculoskeletal modeling. Correlation and regression analyses assessed the relationships between ankle contributions, postural stability, and proximal joint compensations. (3) Results: Compared with the controls, the CAI group demonstrated marked control deficits during the single task (ST), characterized by reduced gait speed, increased step width, elevated mediolateral COP root mean square (COP-ml RMS), and abnormal ankle inversion and joint kinematics; these impairments were exacerbated under DT conditions. Individuals with CAI exhibited a significantly reduced ankle plantarflexion moment and energy contribution (Ankle%), accompanied by compensatory increases in knee and hip contributions. Regression analyses indicated that Ankle% significantly predicted COP-ml RMS and gait speed (GS), highlighting the pivotal role of ankle function in maintaining dynamic stability. Furthermore, CAI participants adopted a “posture-first” strategy under DT, with concurrent deterioration in gait and cognitive performance, reflecting strong reliance on attentional resources. (4) Conclusions: CAI involves global control deficits, including distal insufficiency, proximal compensation, and an inefficient energy distribution, which intensify under dual-task conditions. As the ankle is central to lower-limb kinetics, its dysfunction induces widespread instability. Rehabilitation should therefore target coordinated lower-limb training and progressive dual-task integration to improve motor control and dynamic stability. Full article
(This article belongs to the Special Issue Advancements in Biomechanical Gait Analysis: Implications for Footwear Biomechanics and Sports Injury Prevention)
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41 pages, 35264 KB  
Article
A New Method and Set of Parameters for Evaluating the Cushioning Effect of Shoe Heels, Revealing the Inadvertent Design of Running Shoes
by Franz Konstantin Fuss, Tizian Scharl and Niko Nagengast
Bioengineering 2025, 12(5), 467; https://doi.org/10.3390/bioengineering12050467 - 28 Apr 2025
Cited by 1 | Viewed by 11011
Abstract
According to standards, the heel soles of running shoes are currently tested with an energy absorption of 5 J. This study offers an alternative method to improve the measurement of cushioning properties. The new method uses the ratio of absorbed energy to applied [...] Read more.
According to standards, the heel soles of running shoes are currently tested with an energy absorption of 5 J. This study offers an alternative method to improve the measurement of cushioning properties. The new method uses the ratio of absorbed energy to applied force and determines the maximum of this ratio (optimum or shoulder point) and the associated optimal force, energy, and displacement. This method was applied to 112 shoe models using compression testing. The method was found to be insensitive to strain rates and identified shoes that were over-, well-, or under-designed (running before, at, or after the shoulder point, respectively) relative to the range of the first ground reaction force peak (0.700–2 kN). The optimum ratio was between 0.6 J/kN (barefoot shoes) and 11.2 J/kN (Puma RuleBreaker), the optimal energy was between 0.5 and 40.6 J, the optimal force was between 0.1 and 4.6 kN, and the optimal displacement was between 3 and 23 mm. Participants ran at or near the shoulder point (within the design forgiveness range) unless they were too heavy and ran at their preferred running speed. This study proposes replacing current standards with the new method, allowing consumers to make informed decisions regarding injury prevention while running. Full article
(This article belongs to the Special Issue Advancements in Biomechanical Gait Analysis: Implications for Footwear Biomechanics and Sports Injury Prevention)
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