Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.2
4.6
Journals
Bioengineering
Special Issues
Wearable and Implantable Electronics for the Next Generation of Human-...
share announcement

Wearable and Implantable Electronics for the Next Generation of Human- Machine Interactive Devices

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".

Deadline for manuscript submissions: 25 June 2024 | Viewed by 2070

Special Issue Editor

Dr. Zijie Zhu

E-Mail Website
Guest Editor
Micro-Nano Innovations (MiNI) Laboratory, Department of Biomedical Engineering, University of California, Davis, CA 95616, USA
Interests: sensors; wearable devices; health monitoring; functional materials; human-machine interaction

Special Issue Information

Dear Colleagues,

The recent advances in materials, novel electronics, and artificial intelligence are redefining the ways that humans exchange information with machines. The potential of human–machine interactive devices has expanded tremendously in the form of wearable and implantable devices, from monitoring vital biosignals and daily activity to establishing virtual interaction in prosthetic and robotic control. Therefore, this Special Issue, “Wearable and Implantable Electronics for the Next Generation of Human–Machine Interactive Devices”, will summarize and focus on recent studies and technologies in wearable and implantable devices and their uses in and impacts on various applications. Areas of interest for this Special Issue may include but are not limited to:

  • Novel materials for the wearable and implantable sensor applications;
  • Advanced fabrication technology in making wearable and implantable devices;
  • Energy harvesting technology and self-powered systems;
  • New advancements in implantable electronics for chronic disease monitoring and biosignal sensing;
  • Immersive wearables of virtual reality (VR) and augmented reality (AR);
  • Machine learning techniques for remote healthcare and personal monitoring.

Dr. Zijie Zhu
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. 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

  • wearable devices
  • implantable devices
  • human-machine interaction
  • health care

Published Papers (2 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

13 pages, 1668 KiB  
Article
Intelligent Human–Computer Interaction: Combined Wrist and Forearm Myoelectric Signals for Handwriting Recognition
by Andrea Tigrini, Simone Ranaldi, Federica Verdini, Rami Mobarak, Mara Scattolini, Silvia Conforto, Maurizio Schmid, Laura Burattini, Ennio Gambi, Sandro Fioretti and Alessandro Mengarelli
Bioengineering 2024, 11(5), 458; https://doi.org/10.3390/bioengineering11050458 - 4 May 2024
Viewed by 673
Abstract
Recent studies have highlighted the possibility of using surface electromyographic (EMG) signals to develop human–computer interfaces that are also able to recognize complex motor tasks involving the hand as the handwriting of digits. However, the automatic recognition of words from EMG information has [...] Read more.
Recent studies have highlighted the possibility of using surface electromyographic (EMG) signals to develop human–computer interfaces that are also able to recognize complex motor tasks involving the hand as the handwriting of digits. However, the automatic recognition of words from EMG information has not yet been studied. The aim of this study is to investigate the feasibility of using combined forearm and wrist EMG probes for solving the handwriting recognition problem of 30 words with consolidated machine-learning techniques and aggregating state-of-the-art features extracted in the time and frequency domains. Six healthy subjects, three females and three males aged between 25 and 40 years, were recruited for the study. Two tests in pattern recognition were conducted to assess the possibility of classifying fine hand movements through EMG signals. The first test was designed to assess the feasibility of using consolidated myoelectric control technology with shallow machine-learning methods in the field of handwriting detection. The second test was implemented to assess if specific feature extraction schemes can guarantee high performances with limited complexity of the processing pipeline. Among support vector machine, linear discriminant analysis, and K-nearest neighbours (KNN), the last one showed the best classification performances in the 30-word classification problem, with a mean accuracy of 95% and 85% when using all the features and a specific feature set known as TDAR, respectively. The obtained results confirmed the validity of using combined wrist and forearm EMG data for intelligent handwriting recognition through pattern recognition approaches in real scenarios. Full article
(This article belongs to the Special Issue Wearable and Implantable Electronics for the Next Generation of Human- Machine Interactive Devices)
►▼ Show Figures

Figure 1

19 pages, 12716 KiB  
Article
Thermal Cues Composed of Sequences of Pulses for Transferring Data via a Haptic Thermal Interface
by Yosef Y. Shani and Simon Lineykin
Bioengineering 2023, 10(10), 1156; https://doi.org/10.3390/bioengineering10101156 - 2 Oct 2023
Viewed by 859
Abstract
This research study is the preliminary phase of an effort to develop a generic data transfer method via human haptic thermal sensation (i.e., a coded language such as Morse or Braille). For the method to be effective, it must include a large variety [...] Read more.
This research study is the preliminary phase of an effort to develop a generic data transfer method via human haptic thermal sensation (i.e., a coded language such as Morse or Braille). For the method to be effective, it must include a large variety of short, recognizable cues. Hence, we propose the concept of cues based on sequences of thermal pulses: combinations of warm and cool pulses with several levels of intensity. The objective of this study was to determine the feasibility of basing a generic data transfer method on haptic thermal cues using sequences of short pulses. The research included defining the basic characteristics of the stimuli parameters and developing practical methods for generating and measuring them. Several patterns of different sequences were designed considering the relevant data known to date and improved by implementing new insights acquired throughout the tests that were conducted. The final thermal cues presented to the participants were sensed by touch and clearly recognized. The results of this study indicate that developing this new method is feasible and that it could be applicable in various scenarios. In addition, the low impact measured on the user’s skin temperature represents an inherent advantage for future implementation. This report presents promising findings and offers insights for further investigations. Full article
(This article belongs to the Special Issue Wearable and Implantable Electronics for the Next Generation of Human- Machine Interactive Devices)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop