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Applied Sciences
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Advanced Robotics, Mechatronics, and Automation
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Advanced Robotics, Mechatronics, and Automation

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 1863

Special Issue Editors

Prof. Dr. Yan Shi

E-Mail Website
Guest Editor
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Interests: mechatronic engineering; hydraulic transmission and control; precision detection technique
Special Issues, Collections and Topics in MDPI journals
Dr. Shuai Ren

E-Mail Website
Guest Editor
School of Automation, Beijing Institute of Technology, Beijing, China
Interests: robotic

Special Issue Information

Dear Colleagues,

This Special Issue focuses on Advanced Intelligent Systems and Techniques for Healthcare Applications.

Nowadays, with the development of computational intelligence and hardware design technologies, advanced robotics, mechatronics, and automation in healthcare have attracted growing research interests in an enormous scope of practical applications, such as in hospitals, homes, rehabilitation robots, and health management and promotion. However, due to the lack of adequate intelligence in traditional healthcare systems, their functional development has been limited. The cross-type research direction, which requires complex design and setup, is a research field that deeply integrates medicine and engineering technology and has extensive developments in medical and rehabilitation devices.

The existing challenges of healthcare mechatronic devices include the shortage of structure complexity, low-end products, the lowness of competitiveness, and non-intelligence. Most previous assistive devices/robots were developed to provide patients with rehabilitation training in hospitals. Furthermore, there have also been limited advanced intelligent systems and techniques available for healthcare applications. With the ageing population rapidly increasing, these assistive devices must have smaller and cheaper production costs. In addition, since every individual's rehabilitation needs are quite different, the advanced healthcare systems must combine multi-modal human rehabilitation data with stochastic analysis, pattern recognition, and machine learning methods to design customized complex healthcare programs for each user. Hence, advanced intelligent systems and techniques for healthcare applications are imminently essential.

Prof. Dr. Yan Shi
Dr. Shuai Ren
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. 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

  • surgery robotics
  • rehabilitation medical
  • advanced intelligent
  • healthcare application
  • digital diagnosis and treatment

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Published Papers (2 papers)

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Research

16 pages, 5421 KiB  
Article
Design and Development of Hugging Mechanism for Capturing Chest and Back Auscultatory Sounds
by Ryosuke Tsumura, Takuma Ogawa, Reina Umeno, Ryuta Baba, Yuko Morishima, Kiyoshi Yoshinaka and Hiroyasu Iwata
Appl. Sci. 2025, 15(3), 1669; https://doi.org/10.3390/app15031669 - 6 Feb 2025
Viewed by 716
Abstract
Robotic auscultation has the potential to solve problems associated with gender issues by allowing examinations that eliminate the need for physical contact between doctor and patient. Aiming toward a robotic auscultation device capable of safely acquiring chest and back auscultatory sounds simultaneously, this [...] Read more.
Robotic auscultation has the potential to solve problems associated with gender issues by allowing examinations that eliminate the need for physical contact between doctor and patient. Aiming toward a robotic auscultation device capable of safely acquiring chest and back auscultatory sounds simultaneously, this study aimed to develop a unique actuator-less hugging mechanism with a multi-acoustic sensor array that can be transformed to wrap around the chest and back to fit the patient’s body shape. The mechanism consists of a twin-articulated arm with multi-layer gear coupling and a cam mechanism for power transmissions. The hugging motion is generated by pushing the cam mechanism by the patient. The force applied to the cam mechanism acts as the driving force for the twin-articulated arm. The trajectory of the arm changes depending on the distance that the cam mechanism is pressed, and it was designed to fit typical body types (obese, standard, and slender). Our results demonstrated that the proposed mechanism was able to be transformed for each body type, and its positional error was less than 15 mm in all body types. This means that the proposed mechanism is capable of safely acquiring chest and back auscultatory sounds whilst simultaneously fitting to various body shapes. Full article
(This article belongs to the Special Issue Advanced Robotics, Mechatronics, and Automation)
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17 pages, 16205 KiB  
Article
On-Site Implementation of External Wrench Measurement via Non-Linear Optimization in Six-Axis Force–Torque Sensor Calibration and Crosstalk Compensation
by Jiyou Shin, Jinjae Shin, Hong-ryul Jung, Jaeseok Won, Eugene Auh and Hyungpil Moon
Appl. Sci. 2025, 15(3), 1510; https://doi.org/10.3390/app15031510 - 2 Feb 2025
Viewed by 801
Abstract
This study introduces a novel calibration method for accurate external wrench measurement using a six-axis FT (force–torque) sensor. We propose a sensor model and calibration method for FT sensors that enable precise separation of the force and torque components without the need for [...] Read more.
This study introduces a novel calibration method for accurate external wrench measurement using a six-axis FT (force–torque) sensor. We propose a sensor model and calibration method for FT sensors that enable precise separation of the force and torque components without the need for additional devices or sensors by estimating essential parameters: bias, crosstalk, CoM (center of mass), and inclination. By directly utilizing manufacturer-provided data, our approach eliminates the complexities of traditional calibration processes while achieving higher accuracy in force–torque measurements. This method simplifies the calibration workflow and enhances the practicality of FT sensor applications. A mobile manipulator installed with an FT sensor and a gripper is used to demonstrate calibration effectiveness across varying postures and incline conditions, with non-linear optimization based on the gradient descent method applied to minimize sensor-data errors. The tilt of the base is implemented by placing a step under the wheels of the mobile base to simulate roll or pitch scenarios. A digital level was used to measure the angle and verify that our predicted results were accurate. The proposed method addresses typical calibration challenges, including the effects of the end tool and base incline, which are not commonly covered in existing methods. The results show that, on a non-inclined base, crosstalk and CoM calibration reduces the MSE (mean squared error) by 55.8%, 56.2%, and 14.5% for the external force with respect to data without any calibration conducted. On an inclined base, our full calibration process reduces the MSE by a maximum of 98.6% for external mass measurement with respect to no calibration method applied. These findings highlight the importance of incline calibration for achieving accurate external force estimations, especially in mobile manipulator applications where the environment frequently changes. Full article
(This article belongs to the Special Issue Advanced Robotics, Mechatronics, and Automation)
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