Advancements in Artificial Intelligence for Wearable Devices: A New Perspective on Healthcare Applications
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".
Deadline for manuscript submissions: 31 May 2024 | Viewed by 124
Special Issue Editors
Interests: biomedical signal processing (EMG, EEG, ECoG, and LFP); wearable medical devices; machine learning; structural MRI analysis
Special Issues, Collections and Topics in MDPI journals
Interests: sensors; biomedical signal processing; ion-sensitive field-effect transistors; PH sensors; sensing; wearable medical devices; electrocardiography; electrodes; textiles
Special Issues, Collections and Topics in MDPI journals
Interests: analog/mixed-signal integrated circuits; monolithic sensors; semiconductor devices
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Today, wearable devices (WDs) have emerged as an interesting frontier for innovation, poised to shape the future of human interaction with technology. The progress in sensing technologies and integrated electronic circuits has facilitated the creation of sophisticated devices capable of integrating sensors.
Sensor technology and electronic interfaces have been receiving growing interest from scientists as promising developments have been made. The high degree of miniaturization of classic measurement techniques has led to the realization of complex analytical systems including integrated sensors as in lab-on-a-chip. This new class of sensors extensively contributes to a broad range of activities with widespread applications including biology and medicine. Recent advances in artificial intelligence (AI) provide opportunities to reveal hidden information in biosignals that is not apparent using conventional methods of analysis. Beyond mere accessories, wearables play a pivotal role in healthcare, and the incorporation of AI technologies has played a crucial role in rapidly advancing the field.
This Special Issue aims to collect original scientific papers that apply novel or state-of-the-art AI technologies on wearable devices. We encourage original scientific papers about the application of machine learning and deep learning and real-time monitoring using WDs. Systematic reviews or meta-analyses are also welcome.
Dr. Maria Giovanna Bianco
Dr. Salvatore Pullano
Prof. Dr. Syed Kamrul Islam
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. 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
- artificial lntelligence
- machine learning
- biomedical signal processing
- deep learning
- bio-inspired systems
- biosensor devices
