Deep Learning Applications in Healthcare Wearable Devices

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Point-of-Care Diagnostics and Devices".

Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 658

Special Issue Editor

Department of Electrical, Electronics and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia
Interests: SoC design (AI accelerator); biomedical sensor; AI for biomedical applications

Special Issue Information

Dear Colleagues,

In recent years, wearable devices have been widely used in the field of healthcare. They can detect critical healthcare data such as body temperature, heart rate, respiration, EEG, ECG, EMG, and electrodermal activity in a non-invasive, automatic, and continuous way in helping with daily health monitoring and disease diagnosis. The collected data can be processed and analyzed with the help of artificial intelligence, improving the efficiency of patient monitoring and reducing the burden on the patient care system.

Therefore, this Special Issue on “Deep Learning Applications in Healthcare Wearable Devices” aims to highlight the application of artificial intelligence approaches such as deep learning and machine learning in healthcare wearable devices to help to detect, evaluate, and analyze patient health data. Researchers, scientists, and medical professionals are welcome to submit your works to Diagnostics. Both original articles and reviews will be considered.

Topics of interest include but are not limited to the following aspects:

  • Design and development of smart wearable devices;
  • Challenges of wearable devices in healthcare data acquisition, data transmission, and more;
  • Development of mobile applications for wearable devices and AI;
  • Data analysis methods for wearable devices;
  • Prospects for the application of artificial intelligence methods in wearable devices.

Prof. Dr. Mamun Bin Ibne Reaz
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. Diagnostics 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 2600 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
  • deep learning
  • machine learning
  • portable devices
  • health monitoring

Published Papers

There is no accepted submissions to this special issue at this moment.
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