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Machines
Special Issues
Design and Control of Wearable Mechatronics Devices
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Design and Control of Wearable Mechatronics Devices

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Robotics, Mechatronics and Intelligent Machines".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 2287

Special Issue Editor

Dr. Nicola Secciani

E-Mail Website
Guest Editor
Department of Industrial Engineering, The University of Florence, Florence, Italy
Interests: wearable robots; assistive and rehabilitative robotics; device control

Special Issue Information

Dear Colleagues,

Wearable devices are becoming everyday-life companions. Smart glasses, smart trackers, smart watches, etc., are just the tip of the iceberg. Specialized sectors of industry (thanks also goes to the new “Industry 5.0” paradigm), healthcare systems, and the entertainment world demonstrate a definite interest in enlarging the adoption of wearable solutions. However, state-of-the-art wearable devices still fail to penetrate the market because of their prohibitive cost or because their close interaction with humans imposes stringent requirements on them.

The robust interest in the manufacturing, healthcare, and entertainment industries, and their still-unsatisfactory performance, has made the development of wearable devices one of the hottest trends in technology research. This Special Issue aims to collect innovative contributions on this subject, from both design and control perspectives. Specifically, the contributions may deal with all the following aspects of “Design and Control of Wearable Electromechanical Devices”:

  • Trend and challenges in designing wearable devices;
  • Intelligent, intuitive, and robust control for wearable devices;
  • Design for wearability;
  • The user-centered design of wearable devices;
  • The acceptability of wearable devices;
  • Human–machine interfaces for wearable devices.

Both review papers and in-depth research papers on new developments in this field will be collected in this Special Issue.

Dr. Nicola Secciani
Guest Editor

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. Machines 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

  • trend and challenges in designing wearable devices
  • intelligent, intuitive, and robust control for wearable devices
  • design for wearability
  • the user-centered design of wearable devices
  • the acceptability of wearable devices
  • human–machine interfaces for wearable devices

Published Papers (2 papers)

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Research

19 pages, 3423 KiB  
Article
Design and Preliminary Evaluation of a Soft Finger Exoskeleton Controlled by Isometric Grip Force
by Quentin Sanders and David J. Reinkensmeyer
Machines 2024, 12(4), 230; https://doi.org/10.3390/machines12040230 - 30 Mar 2024
Viewed by 513
Abstract
Hand exoskeletons are potential solutions for enhancing upper extremity function after stroke, yet achieving intuitive control remains challenging. We recently showed that isometric grip force tracking is preserved after stroke, providing a possible control source for a hand exoskeleton. In this study, we [...] Read more.
Hand exoskeletons are potential solutions for enhancing upper extremity function after stroke, yet achieving intuitive control remains challenging. We recently showed that isometric grip force tracking is preserved after stroke, providing a possible control source for a hand exoskeleton. In this study, we developed a hand exoskeleton with a soft compliant mechanism and novel force control strategy that leverages isometric grip force control of digits 3–5 to control an index–thumb pinch grip. We first present characterization of the compliant mechanisms output impedance (34.77 N/m), and output force (2.3 ± 0.57 N). We then present results of a study that assessed the intuitiveness of the strategy during a grip–lift–move task in ten unimpaired individuals. From four unimpaired individuals we also gathered user preferences on force sensitivity and operating mode, where in one mode flexion force from digits 3–5 caused index finger closing, while in the other mode it caused index finger opening. The strategy proved intuitive, improving movement frequency on the grip–lift–move task by 30%. Users preferred greater force sensitivity and using flexion force from digits 3–5 to drive index finger extension. The force control strategy incorporated into the exoskeleton shows promise warranting further investigation in neurologically impaired participants. Full article
(This article belongs to the Special Issue Design and Control of Wearable Mechatronics Devices)
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19 pages, 8010 KiB  
Article
Enhancing sEMG-Based Finger Motion Prediction with CNN-LSTM Regressors for Controlling a Hand Exoskeleton
by Mirco Vangi, Chiara Brogi, Alberto Topini, Nicola Secciani and Alessandro Ridolfi
Machines 2023, 11(7), 747; https://doi.org/10.3390/machines11070747 - 17 Jul 2023
Cited by 1 | Viewed by 1235
Abstract
In recent years, the number of people with disabilities has increased hugely, especially in low- and middle-income countries. At the same time, robotics has made significant advances in the medical field, and many research groups have begun to develop low-cost wearable solutions. The [...] Read more.
In recent years, the number of people with disabilities has increased hugely, especially in low- and middle-income countries. At the same time, robotics has made significant advances in the medical field, and many research groups have begun to develop low-cost wearable solutions. The Mechatronics and Dynamic Modelling Lab of the Department of Industrial Engineering at the University of Florence has recently developed a new version of a wearable hand exoskeleton for assistive purposes. In this paper, we will present a new regression method to predict the finger angle position of the first joint from the value of the sEMG of the forearm and the previous position of the finger itself. To acquire the dataset necessary to train the regressor a specific graphical user interface was developed which was able to acquire sEMG data from a Myo armband and the finger position from a Leap Motion Controller. Two long short-term memory (LSTM) models were compared, one in its standard configuration and the other with a convolutional layer, yielding significantly better performance for the second one, with an increase in R2 coefficient from an average value of 0.746 to 0.825, leading to the conclusion that a convolutional layer could increase performance when few sensors are available. Full article
(This article belongs to the Special Issue Design and Control of Wearable Mechatronics Devices)
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