Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.1
2.9
Journals
Applied Sciences
Special Issues
Advances in Motion Monitoring System, 2nd Edition
applsci-logo
Submit to Special Issue Submit Abstract to Special Issue Review for Applied Sciences Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Advances in Motion Monitoring System, 2nd Edition

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Biomedical Engineering".

Deadline for manuscript submissions: 30 October 2026 | Viewed by 1093

Editors

Dr. Yupeng Mao

E-Mail
Guest Editor
Physical Education Department, Northeastern University, Shenyang 110819, China
Interests: sustainable renewable energy; nanogenerators and its applications; wearable electronic devices and human body monitoring; the competitive performance of sports
Dr. Tianming Zhao

E-Mail Website
Guest Editor
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
Interests: Invasive brain–computer interfaces; implantable electronics; biosensing; human–computer intelligent interaction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Motion data collection during sports is crucial for athletes, coaches, and healthcare professionals to gather valuable information. Detailed data on athletes and their workout habits is vital for improving training programs and optimizing athletic performance. The recent surge in the use of motion monitoring devices has driven technological advancements in this field, offering innovative solutions. Motion monitoring systems integrate these devices with advanced back-end processing solutions to expedite the analysis and identification of exercise data, streamlining the motion monitoring process. This Special Issue aims to present a comprehensive examination of the latest developments in motion monitoring systems, encompassing technological innovations, practical applications, and future prospects. The Editorial Board welcomes researchers from various fields and disciplines to submit original research, reviews, case studies, and technical reports.

Dr. Yupeng Mao
Dr. Tianming Zhao
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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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

  • motion monitoring system
  • data analysis
  • sports science
  • training optimization
  • triboelectric nanogenerator
  • self-powered
  • flexible
  • intelligent system

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 (3 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

Jump to: Review, Other

21 pages, 2732 KB  
Article
Assessing Stand-to-Sit Kinematics via mmWave Radar: A Real-to-Sim Robust Bidirectional State-Space Model
by Yancheng Liu, Yan Fu, Le Chang, Zhengke Gao and Alex Mihailidis
Appl. Sci. 2026, 16(10), 4584; https://doi.org/10.3390/app16104584 - 7 May 2026
Viewed by 272
Abstract
Continuous monitoring of the Stand-to-Sit (STS) transition serves as a critical indicator of lower-limb frailty in the elderly, for which millimeter-wave radar provides an ideal privacy-preserving, device-free sensing solution. However, robustly distinguishing between safe Controlled Sits (CSs) and dangerous Uncontrolled Descents (UDs) is [...] Read more.
Continuous monitoring of the Stand-to-Sit (STS) transition serves as a critical indicator of lower-limb frailty in the elderly, for which millimeter-wave radar provides an ideal privacy-preserving, device-free sensing solution. However, robustly distinguishing between safe Controlled Sits (CSs) and dangerous Uncontrolled Descents (UDs) is severely hindered by the prohibitive cost of subjective expert scoring for fine-grained labels, alongside the pervasive “Clever Hans” effect where existing deep models overfit static environmental clutter rather than learning intrinsic human kinematics. To circumvent these bottlenecks, we formulate STS evaluation as a dynamic boundary detection problem and propose SCA-BiMamba, a linear-complexity bidirectional State-Space Model that utilizes actual fall events as extreme kinematic surrogates for UDs. This forces the network to learn a strict physical boundary between CS and physiological failure without subjective grading. Furthermore, we establish a stringent Real-to-Sim diagnostic audit as a core methodological contribution. By projecting models trained on noisy real-world data onto pure-kinematics simulations—incorporating stochastic temporal phase shifts, kinematic overlaps, and unified physiological tremors—we explicitly quantify feature disentanglement. This protocol serves as a formal ‘probing test’ to expose the ‘Clever Hans’ effect, ensuring the model relies on invariant human physics rather than transient environmental artifacts. Extensive experiments demonstrate that SCA-BiMamba achieves highly robust classification on real-world data (averaging 94.2% Macro F1 with 100.0% Uncontrolled Descent Recall), and achieves a highly robust 99.4% ± 1.1% Macro F1 in the simulated zero-shot transfer. We emphasize that this optimal performance reflects the successful abstraction of extreme kinematic boundaries, rather than a flawless resolution of all clinical complexities. Concurrently, it exhibits strict resistance to shortcut learning and sustains robust real-world scalability using merely 20% of the training data, thereby establishing a promising privacy-preserving boundary-based radar motion classification framework for distinguishing controlled sitting from extreme instability surrogates. Full article
(This article belongs to the Special Issue Advances in Motion Monitoring System, 2nd Edition)
►▼ Show Figures

Figure 1

Review

Jump to: Research, Other

27 pages, 2945 KB  
Review
Non-Human Animals and Plants Inspired Triboelectric Nanogenerators for Environmental Energy Harvesting and Human Health and Motion Monitoring
by Xiaobo Yang, Jiaqiang Mao, Xihong Wang and Yupeng Mao
Appl. Sci. 2026, 16(12), 5730; https://doi.org/10.3390/app16125730 - 6 Jun 2026
Viewed by 175
Abstract
The triboelectric nanogenerator (TENG), which converts mechanical energy into electrical energy through the coupled effect of triboelectrification and electrostatic induction, has garnered significant interest among researchers due to its portability and self-powered characteristics. Despite its evident development potential, TENG continues to face challenges, [...] Read more.
The triboelectric nanogenerator (TENG), which converts mechanical energy into electrical energy through the coupled effect of triboelectrification and electrostatic induction, has garnered significant interest among researchers due to its portability and self-powered characteristics. Despite its evident development potential, TENG continues to face challenges, including the necessity to enhance its triboelectric performance through the optimization of structures, materials, and manufacturing techniques to improve energy conversion efficiency. Additionally, its environmental stability and durability also need to be improved. TENGs designed inspired by non-human animals and plants offer feasible solutions to address these limitations. These bio-inspired TENGs optimize the structural design of TENGs and the materials of the triboelectric layers by imitating the structures, functions, and behaviors of organisms, thereby further improving the energy conversion efficiency, sensitivity, wear resistance, adaptability to special environments, biocompatibility, and wearing comfort of TENGs. This paper expounds on the progress of TENGs inspired by non-human animals and plants applied in environmental energy harvesting, human health and motion monitoring. It also discusses the current challenges, with a view to providing insights for the interdisciplinary integration and development of bionics and TENGs. Full article
(This article belongs to the Special Issue Advances in Motion Monitoring System, 2nd Edition)
►▼ Show Figures

Figure 1

Other

Jump to: Research, Review

17 pages, 1246 KB  
Systematic Review
Neuromuscular Assessment in Elite Female Basketball Players: A Systematic Review and Future Directions
by Raúl Nieto-Acevedo, Enrique Alonso-Pérez-Chao, Antonio Reyes-Mora, Francisco Gallardo Marmol, Dimitrije Cabarkapa and Jorge Lorenzo Calvo
Appl. Sci. 2026, 16(11), 5413; https://doi.org/10.3390/app16115413 - 29 May 2026
Viewed by 357
Abstract
This systematic review aimed to evaluate the tests used to assess neuromuscular performance in adult female basketball players and to provide evidence-based recommendations for practice and future research. Following PRISMA guidelines and registered in PROSPERO (CRD42025638889), four databases were systematically searched from inception [...] Read more.
This systematic review aimed to evaluate the tests used to assess neuromuscular performance in adult female basketball players and to provide evidence-based recommendations for practice and future research. Following PRISMA guidelines and registered in PROSPERO (CRD42025638889), four databases were systematically searched from inception to April 2026. A total of 62 studies were included in the qualitative synthesis and 39 in the quantitative analysis. The most frequently reported assessments examined anthropometry, muscular power, linear speed, change-of-direction (COD) performance, strength, anaerobic capacity, and aerobic capacity. However, substantial variability was observed in testing protocols, outcome variables, and reporting methods. Across studies, performance outcomes showed considerable overlap between competition levels, suggesting that competitive standard alone is not a reliable indicator of neuromuscular performance. Differences in anthropometric characteristics and physical performance were largely influenced by playing position and contextual factors. A key finding was the predominant reliance on outcome-based metrics (e.g., jump height, sprint time), with limited use of force–time variables that provide deeper insight into neuromuscular function. In addition, important methodological limitations were identified, including inconsistent testing procedures, lack of standardized reporting, and the absence of female-specific considerations such as menstrual cycle status. To address these limitations, this review proposes a practical testing framework that integrates reliable, sport-specific, and time-efficient assessment methods. Future research should prioritize the implementation of standardized protocols, the inclusion of force–time analysis, and the development of large-scale descriptive datasets specific to female basketball players. These advances are essential to improve performance monitoring, optimize training prescription, and enhance injury risk management in this population. Full article
(This article belongs to the Special Issue Advances in Motion Monitoring System, 2nd Edition)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop