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Applied Sciences
Special Issues
Monitoring of Human Physiological Signals
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Monitoring of Human Physiological Signals

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

Deadline for manuscript submissions: 20 November 2024 | Viewed by 550

Special Issue Editor

Prof. Dr. Miran Lee

E-Mail Website
Guest Editor
Human-Computer Interaction Lab, Daegu University, Gyeongsan 38453, Republic of Korea
Interests: human–computer interaction; biosignal processing; human physiological signals; robotic mood transition

Special Issue Information

Dear Colleagues,

Health systems and their applications utilizing human physiological signals have a significant scope of application. Physiological signals are used to improve the performance of health monitoring and diagnosis systems by integrating complex health data such as electromyogram, electrocardiogram, electroencephalogram, and pulse. In addition, methods for processing multiple physiological signals are evolving into various complex and intelligent methods, such as deep learning and machine learning methods, which enable a smart health management system based on AI.

Prof. Dr. Miran Lee
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. 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

  • healthcare
  • health management
  • Internet of Things healthcare
  • sensor fusion in biomedical imaging
  • remote sensing in healthcare
  • diagnostics
  • health monitoring
  • biosignal processing

Published Papers (1 paper)

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Research

9 pages, 1613 KiB  
Article
Development of Sensory Virtual Reality Interface Using EMG Signal-Based Grip Strength Reflection System
by Younghoon Shin and Miran Lee
Appl. Sci. 2024, 14(11), 4415; https://doi.org/10.3390/app14114415 - 23 May 2024
Viewed by 282
Abstract
In virtual reality (VR), a factor that can maximize user immersion is the development of an intuitive and sensory interaction method. Physical devices such as controllers or data gloves of existing VR devices are used to control the movement intentions of the user, [...] Read more.
In virtual reality (VR), a factor that can maximize user immersion is the development of an intuitive and sensory interaction method. Physical devices such as controllers or data gloves of existing VR devices are used to control the movement intentions of the user, but their shortfall is that grip strength and detailed muscle strength cannot be reflected. Therefore, this study intended to establish a more sensory VR environment compared to existing methods by reflecting the grip strength of the flexor digitorum profundus of the user of the VR content. In this experiment, the muscle activity of the flexor digitorum profundus was obtained from six subjects based on surface electromyography, and four objects with differing intensity were created within a VR program in which the objects were made to be destroyed depending on muscle activity. As a result, satisfaction was improved because the users could sensitively interact with the objects inside the VR environment, and the intended motion control of the user was reflected in the VR content. Full article
(This article belongs to the Special Issue Monitoring of Human Physiological Signals)
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