Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
3.7
Journals
Bioengineering
Special Issues
Biomechanics in Sport and Motion Analysis
share announcement

Biomechanics in Sport and Motion Analysis

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

Deadline for manuscript submissions: closed (30 November 2025) | Viewed by 9554

Special Issue Editors

Prof. Dr. Kamran Iqbal

E-Mail Website
Guest Editor
Department of Systems Engineering, University of Arkansas Little Rock, Little Rock, AR 72204, USA
Interests: sensorimotor control of human movement; biomedical signal and image processing
Special Issues, Collections and Topics in MDPI journals
Dr. Rajat Emanuel Singh

E-Mail Website
Guest Editor
Department of Kinesiology, Northwestern College, Orange City, IA 51041, USA
Interests: biomechanics; neural engineering; motor control; motor learning; electromyography; motion capture; kinesiology

Special Issue Information

Dear Colleagues,

Technological advancements, including motion capture, electromyography, inertial measurement units, and force plates, have significantly enhanced our ability to capture variables associated with the laws of physics that govern movement during sports-related activities. Furthermore, these physical variables can be simulated for prediction and/or modeled with a proper artificial intelligence (AI) system, leading to enhanced performance or improved foul detection during sports activities and events. Therefore, in this Special Issue, we aim to collect relevant theories, methods, mathematical models, simulations, and clinical results that advance our understanding of biomechanical systems in the form of original research articles, review articles, short articles, and opinions applied in the fields of biomechanics and sports medicine.

We welcome contributions from biomedical engineers, biomechanists, sports scientists, neuroscientists, physical therapists, and other practitioners.

The major topics of interest for this Special Issue include (but are not limited to) the following:

  1. Biomedical signal processing;
  2. Biomechanics and sports medicine;
  3. Motor control and motor learning;
  4. Artificial intelligence and bioinformatics;
  5. Biomedical signal and image processing;
  6. Biomechanical modeling and simulation;
  7. Motion and data capture;
  8. Electromyography;
  9. EMG-driven models;
  10. Muscle synergies.

Prof. Dr. Kamran Iqbal
Dr. Rajat Emanuel Singh
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

  • biomechanics
  • sports science
  • human motion
  • artificial intelligence

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (5 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

18 pages, 1598 KB  
Article
Inter-Segmental Coordination During Soccer Instep Kicking: A Vector-Coding Comparison Between Experienced Athletes and Novices
by Liwen Zhang, Meizhen Zhang and Hui Liu
Bioengineering 2025, 12(11), 1151; https://doi.org/10.3390/bioengineering12111151 - 24 Oct 2025
Viewed by 1090
Abstract
The purpose of this study was to characterize the inter-segmental coordination of hip, knee, and ankle movement of the kicking leg during instep kicking for experienced athletes and novices, using vector coding as a non-linear technique. Motion capture and electromyographic data were collected [...] Read more.
The purpose of this study was to characterize the inter-segmental coordination of hip, knee, and ankle movement of the kicking leg during instep kicking for experienced athletes and novices, using vector coding as a non-linear technique. Motion capture and electromyographic data were collected for 14 soccer-majored college students and 32 novices performing the instep kicking task. The percentage of time spent on the coordination patterns, defined based on hip–knee and knee–ankle coupling angles, was calculated and compared. The agonist–antagonist activity ratio was calculated and compared. The time percentages of the knee–ankle shank dominance of the experienced athletes during the whole kicking movement were significantly greater than those of the novices (p < 0.050). Athletes achieving greater maximum ball speed had more knee flexion dominant coordination patterns in the back swing and leg-cocking, and knee extension dominant coordination patterns in the leg acceleration phase. The lower activity ratio of the tibialis anterior and gastrocnemius muscles contributed significantly to increasing kicking accuracy. These results underscore the value of vector coding in identifying key inter-segmental coordination features and directly support targeted soccer kick training. The dynamic stability exercises involving knee flexion and extension to optimize power transfer for speed, as well as activation and relaxation control exercises of the lower leg muscles to improve the kicking accuracy, may be effective ways to enhance instep kicking motor control ability and performance for soccer athletes. Full article
(This article belongs to the Special Issue Biomechanics in Sport and Motion Analysis)
►▼ Show Figures

Figure 1

12 pages, 538 KB  
Article
Gait and Postural Control Deficits in Diabetic Patients with Peripheral Neuropathy Compared to Healthy Controls
by Safi Ullah, Kamran Iqbal and Muhammad Rizwan
Bioengineering 2025, 12(10), 1034; https://doi.org/10.3390/bioengineering12101034 - 26 Sep 2025
Viewed by 1189
Abstract
Diabetic peripheral neuropathy (DPN) is a common complication of type 2 diabetes that impairs gait and balance, increasing fall risk. This study investigated gait characteristics and postural control in individuals with DPN, compared to age- and gender-matched healthy controls. Fifteen DPN patients and [...] Read more.
Diabetic peripheral neuropathy (DPN) is a common complication of type 2 diabetes that impairs gait and balance, increasing fall risk. This study investigated gait characteristics and postural control in individuals with DPN, compared to age- and gender-matched healthy controls. Fifteen DPN patients and fifteen controls underwent assessments of gait, static balance, and mobility. Gait parameters were measured during overground walking using motion capture and force platforms. Static balance was evaluated via tandem stance tests (eyes open/closed), while mobility was assessed with the Timed-Up-and-Go (TUG) test. Dynamic stability was assessed by computing the center-of-pressure Time-to-Contact (TTC) with the mediolateral (ML) stability boundary. We hypothesized that patients with DPN would exhibit an altered gait and reduced ML postural stability during walking. The study results show no significant differences in ML center-of-pressure (COP) excursion or its velocity during walking between groups. Patients with DPN walked relatively slowly, with shorter steps, and showed markedly poorer static balance (earlier failure during tandem stance test), as well as slower TUG performance. Clinically, these findings support routine fall risk screening in DPN using both static balance tests (e.g., tandem stance) and mobility measures (e.g., TUG or gait speed). These findings further suggest that while dynamic postural control during walking may be preserved, DPN patients exhibit gait adaptations and significant static balance deficits, highlighting the need for comprehensive balance assessment in this population. Full article
(This article belongs to the Special Issue Biomechanics in Sport and Motion Analysis)
►▼ Show Figures

Graphical abstract

15 pages, 860 KB  
Article
Normative Muscle Activation Patterns During One and Five Countermovement Jumps
by Anabel Gallego-Pérez, Elisa Benito-Martínez and Beatriz Alonso-Cortés Fradejas
Bioengineering 2025, 12(7), 767; https://doi.org/10.3390/bioengineering12070767 - 16 Jul 2025
Cited by 1 | Viewed by 1809
Abstract
Studying normative values for muscle activation in the vastus lateralis (VL), vastus medialis (VM), and biceps femoris (BF), as well as the hamstrings/quadriceps (H:Q) ratio during the Countermovement Jump (CMJ). Determine whether there were differences between the CMJ and the trial of 5 [...] Read more.
Studying normative values for muscle activation in the vastus lateralis (VL), vastus medialis (VM), and biceps femoris (BF), as well as the hamstrings/quadriceps (H:Q) ratio during the Countermovement Jump (CMJ). Determine whether there were differences between the CMJ and the trial of 5 consecutive CMJs (5 CMJ) and between the take-off and landing phases. A cross-sectional descriptive study. Thirty-one participants (20 females and 11 males, 22.52 ± 3.295 years, BMI 24.32, weight 58.23 ± 4.32 Surface electromyography has been used to determine muscle activation during the CMJ and 5 CMJ. Muscle activation in the VL, VM, and BF, as well as the hamstrings/quadriceps ratio in take-off and landing phases of the CMJ and 5 CMJ. The results show normative values in the VL, VM, and BF during both the CMJ and 5 CMJ, with the exception of the BF during the landing phase of the 5 CMJ. In conclusion, the activation in the take-off phase of the VM and VL is greater than during the landing phase. The BF shows similar activation in both the take-off and landing phases. The 5 CMJ does not induce greater muscular fatigue than the CMJ. Full article
(This article belongs to the Special Issue Biomechanics in Sport and Motion Analysis)
►▼ Show Figures

Figure 1

12 pages, 3764 KB  
Article
Estimation of Three-Dimensional Ground Reaction Force and Center of Pressure During Walking Using a Machine-Learning-Based Markerless Motion Capture System
by Ru Feng, Ukadike Christopher Ugbolue, Chen Yang and Hui Liu
Bioengineering 2025, 12(6), 588; https://doi.org/10.3390/bioengineering12060588 - 29 May 2025
Viewed by 2731
Abstract
Objective: We developed two neural network models to estimate the three-dimensional ground reaction force (GRF) and center of pressure (COP) based on marker trajectories obtained from a markerless motion capture system. Methods: Gait data were collected using two cameras and three force plates. [...] Read more.
Objective: We developed two neural network models to estimate the three-dimensional ground reaction force (GRF) and center of pressure (COP) based on marker trajectories obtained from a markerless motion capture system. Methods: Gait data were collected using two cameras and three force plates. Each gait dataset contained kinematic data and kinetic data from the stance phase. A multi-layer perceptron (MLP) and convolutional neural network (CNN) were constructed to estimate each component of GRF and COP based on the three-dimensional trajectories of the markers. A total of 100 samples were randomly selected as the test set, and the estimation performance was evaluated using the correlation coefficient (r) and relative root mean square error (rRMSE). Results: The r-values for MLP in each GRF component ranged from 0.918 to 0.989, with rRMSEs between 5.06% and 12.08%. The r-values for CNN in each GRF component ranged from 0.956 to 0.988, with rRMSEs between 6.03–9.44%. For the COP estimation, the r-values for MLP ranged from 0.727 to 0.982, with rRMSEs between 6.43% and 27.64%, while the r-values for CNN ranged from 0.896 to 0.977, with rRMSEs between 6.41% and 7.90%. Conclusions: It is possible to estimate GRF and COP from markerless motion capture data. This approach provides an alternative method for measuring kinetic parameters without force plates during gait analysis. Full article
(This article belongs to the Special Issue Biomechanics in Sport and Motion Analysis)
►▼ Show Figures

Figure 1

15 pages, 3916 KB  
Article
Does the Fatigue Induced by a 30-Minute Run Affect the Lower Limb Acceleration Spikes’ Asymmetries?
by Gabriel Delgado-García, Isabel M. Martín-López, Fulgencio Soto-Méndez, Arturo Quílez-Maimón and Salvador Boned-Gómez
Bioengineering 2025, 12(3), 294; https://doi.org/10.3390/bioengineering12030294 - 14 Mar 2025
Viewed by 1298
Abstract
Running-induced fatigue affects several biomechanical parameters, and yet few studies are focused on the acceleration spikes’ asymmetries. This study aimed to evaluate the effects of a 30 min run on lower limbs spikes’ asymmetries. Eighteen recreational runners (35.6 ± 7.5 years; seven women) [...] Read more.
Running-induced fatigue affects several biomechanical parameters, and yet few studies are focused on the acceleration spikes’ asymmetries. This study aimed to evaluate the effects of a 30 min run on lower limbs spikes’ asymmetries. Eighteen recreational runners (35.6 ± 7.5 years; seven women) performed a treadmill running protocol at a moderate speed and acceleration spikes’ asymmetries and kinematic (temporal) parameters were measured via accelerometers—on the tibias and sacrum—and photogrammetry. Acceleration spikes’ parameters were continuously measured and averaged per minute to assess the relationship between fatigue and acceleration spike asymmetries via a linear regression model. Right tibial acceleration spikes increased over time (r = 0.9; p < 0.001) and left tibia spikes decreased (r = 0.78; p < 0.001), with a rise in tibial load asymmetry from 9% to 25% at the end (r = 0.98; p < 0.001). This study suggest that fatigue affects the acceleration spikes of the two legs differently, with increasingly greater acceleration spikes in the right (dominant) leg. These findings should be considered, as greater asymmetries are related to overuse injuries and lower efficiency. Also, in studies focusing on running mechanics with fatigue, it is recommended that researchers collect data from both limbs, and not only from the right (dominant) leg. Full article
(This article belongs to the Special Issue Biomechanics in Sport and Motion Analysis)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-5
Back to TopTop