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Actuators
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Human-Centric Intelligent Actuation Systems: Innovations in Control, Sensing, and Multidisciplinary...
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Human-Centric Intelligent Actuation Systems: Innovations in Control, Sensing, and Multidisciplinary Applications

A special issue of Actuators (ISSN 2076-0825). This special issue belongs to the section "Actuators for Robotics".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 141

Special Issue Editors

Dr. Shenglin Mu

E-Mail Website
Guest Editor
Graduate School of Science and Engineering, Ehime University, Matsuyama, Japan
Interests: control engineering; evolutionary optimization theory; soft computing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Satoru Shibata

E-Mail Website
Guest Editor
Graduate School of Science and Engineering, Ehime University, Matsuyama, Japan
Interests: intelligent control; welfare engineering; man-machine Interface
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In order to help people live more comfortably and support various activities, research and development on actuators is being actively conducted every day, and actuators are being used in various fields related to humans. Thus, it is very important to improve actuation systems that are useful for humans, and we must continue to accelerate this movement. This Special Issue covers a wide range of research activities that are working to achieve high precision, high efficiency, low power consumption, development of new materials, development of new control technologies, and miniaturization in actuation related to humans. We also invite proposals and integration of a wide range of actuation systems to be used in new fields, including actuation systems used in transportation equipment including automobiles and aircraft, and actuation systems developed in medical welfare, nursing care, and robots. We welcome approaches to control, sensing, and system integration of actuation to enrich human life, or actuation that promotes smooth interaction between humans and machines or robots. We also welcome submissions of actuation systems that directly or indirectly affect the human body and help make humans healthier and more wholesome, both physically and mentally. In addition, we welcome the development of new fundamental actuators that are expected to be relevant to humans in the future.

Dr. Shenglin Mu
Prof. Dr. Satoru Shibata
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Actuators 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 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

  • human-centric actuation
  • intelligent control systems
  • human–machine interaction
  • advanced sensing technologies
  • multidisciplinary applications
  • high-precision actuation
  • energy-efficient actuation
  • miniaturized actuators
  • smart materials for actuation

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Published Papers (1 paper)

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Research

11 pages, 1251 KB  
Article
AI-Enhanced Model for Integrated Performance Prediction and Classification of Vibration-Reducing Gloves for Hand-Transmitted Vibration Control
by Yumeng Yao, Wei Xiao, Alireza Moezi, Marco Tarabini, Paola Saccomandi and Subhash Rakheja
Actuators 2025, 14(9), 436; https://doi.org/10.3390/act14090436 - 3 Sep 2025
Abstract
This study presents a human-centric, data-driven modeling framework for the intelligent evaluation and classification of vibration-reducing (VR) gloves used in hand-transmitted vibration environments. Recognizing the trade-offs between protection and functionality, the integrated performance assessment incorporates three critical and often conflicting metrics: manual dexterity, [...] Read more.
This study presents a human-centric, data-driven modeling framework for the intelligent evaluation and classification of vibration-reducing (VR) gloves used in hand-transmitted vibration environments. Recognizing the trade-offs between protection and functionality, the integrated performance assessment incorporates three critical and often conflicting metrics: manual dexterity, grip strength, and distributed vibration transmissibility at the palm and fingers. Three independent experiments involving fifteen participants were conducted to evaluate the individual performance of ten commercially available VR gloves fabricated from air bladders, polymers, and viscoelastic gels. The effects of VR gloves on manual dexterity, grip strength, and distributed vibration transmission were investigated. The resulting experimental data were used to train and tune seven different machine learning models. The results suggested that the AdaBoost model demonstrated superior predictive performance, achieving 92% accuracy in efficiently evaluating the integrated performance of VR gloves. It is further shown that the proposed data-driven model could be effectively applied to classify the performances of VR gloves in three workplace conditions based on the dominant vibration frequencies (low-, medium-, and high-frequency). The proposed framework demonstrates the potential of AI-enhanced intelligent actuation systems to support personalized selection of wearable protective equipment, thereby enhancing occupational safety, usability, and task efficiency in vibration-intensive environments. Full article
(This article belongs to the Special Issue Human-Centric Intelligent Actuation Systems: Innovations in Control, Sensing, and Multidisciplinary Applications)
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