Mobile Networks and Applications - Mobile Computing For Digital Health: Challenges, Opportunities, and Approaches
Overview:
The current needs for remote healthcare and daily health status monitoring, especially under the era of COVID-19, stimulate the researches on both digital health-related mechanisms and platforms like wearables and smart-home devices. On one hand, wearables and smart-home devices continuously acquire health data, infer physiological states and enable early invention remotely. Such technical studies develop and improve the platforms that mainly focus on rapid inter-subject adaptations with streaming data, data security issues and low-cost hardwares and algorithms for multi-modal monitoring and intervening methods, etc. On the other hand, artificial intelligence (AI), and in particular algorithms for machine learning, are on their way to becoming a key technology for digital health. This also gives rise to a new data-driven medical health management model. In addition to enabling various human-machine interactions, AI has also changed the clinician-patient and inter-patient interactions. Such interactions will pose new challenges to decision-making and may lead to unintended consequences of AI implementation and use. The abovementioned research opportunities can provide beneficial feedback and new application scenarios for residents' active healthcare.
The special issue brings together experts’ works on biomedical signal processing, data science, machine learning and digital health, in order to foster a fruitful and multi-disciplinary discussion.
Topics
Topics of interest include, but are not limited to, the following scope:
Wearables and smart-home devices for healthcare | Human physiological state inferring and context-awared understanding |
Ethics, security, privacy and safety issues in smart home healthcare | Data management, data quality, and machine learning |
Intelligent or digital health management and performance | Human-computer interaction and decision making |
Human-AI collaboration | AI-based medical data analytics |
Manuscript submission deadline: 31st, Oct,2023
Notification of acceptance: 31st, Jan 2024
Submission of final revised paper: 31st Mar, 2024
Publication of special issue (tentative): 31st, Jun, 2024
Submission Procedure
Authors should follow the MONET Journal manuscript format described at the journal site. Manuscripts should be submitted on-line through http://www.editorialmanager.com/mone/ (this opens in a new tab).
A copy of the manuscript should also be emailed to the Guest Editors at the following email address(es): xitongguo@hit.edu.cn (this opens in a new tab), chunzhiyi@hit.edu.cn, (this opens in a new tab) and chenshuqinghit@gmail.com (this opens in a new tab)
Guest Editors:
Dr. Xitong Guo, Affiliation: Professor, School of Management, Harbin Institute of Technology, Harbin China, 150001.
Email: xitongguo@hit.edu.cn
ShortBio: Xitong Guo received his PhD in Information Systems from the City University of Hong Kong and PhD in Management Science and Engineering from the University of Science and Technology of China. His current research focuses on Big Data and Business Analysis.
Google Scholar: https://scholar.google.com/citations?user=CErASxgAAAAJ&hl=zh-CN
Dr. Chunzhi Yi, Affiliation: Assistant Professor, School of Medicine and Health, Harbin Institute of Technology, Harbin, China
Email: chunzhiyi@hit.edu.cn
Short Bio: Chunzhi Yi received his Ph.D degree from Harbin Institute of Technology in 2022 and am now an Assistant Prof. He’s been guest editors of several peer-reviewed journals. His research interest includes wearable devices, neural signal processing and human biomechanics.
Google Scholar: https://scholar.google.com/citations?user=ti3oQP4AAAAJ&hl=zh-CN
Dr. Shuqing Chen, Affiliation: Associate Research Fellow of School of Medicine and Health at Harbin Institute of Technology, Harbin, China.
Email: chenshuqinghit@gmail.com
ShortBio: Shuqing Chen obtained her PhD in School of Management from Harbin Institute of Technology. Her research focus on the digital health, big data analysis and text mining.
Google Scholar: https://scholar.google.com/citations?user=ZSBEUzLyx7IC&hl=zh-CN