Smart Sensing and Applications in Health Assessment
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 317
Special Issue Editors
Interests: digital health; Smart Home; AI and IoT in healthcare; social-assistive robotics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The assessment of a patient’s mental and physical status plays a vital role in clinical diagnosis, decision-making, and treatment. It examines a patient's health, physical, psychological, and social functions through the collection of health data, including subjective data collected during health interviews, and objective data observed during physical examinations.
However, sometimes the accuracy of health assessments is limited because:
- Subjective assessments are likely to be influenced by biases such as recall bias, interviewer bias, and social desirability bias;
- Objective assessments are usually performed in a clinical setting, which is often different from the patient’s daily environment;
- Assessments are conducted infrequently and therefore do not provide real-time, continuous results within prospective follow-up periods.
Smart sensing with its AI-driven applications has the potential to address the aforementioned problems and improve the accuracy of health assessments, through providing automated, accurate, objective, and continuous assessments of patients. Therefore, there is a need to better understand the available smart sensing technologies and their applications in the digitization and automation of various health assessments.
The goal of this Special Issue is to bring together scientists, researchers, practitioners, and service providers in order to publish high-quality manuscripts related to sensing technologies, data analytics, and their application in health assessment and physical examinations. Topics of interest include, but are not limited to, the following:
- Novel sensor technologies in health assessment;
- Novel application-specific and general predictive analytics techniques for sensors;
- Applications that support effective deployment of sensing technologies for heath assessments;
- Case studies of predictive, personalised and precision health assessment using data analytics in combination with sensors.
Original research and comprehensive review papers will be considered.
Submitted manuscripts should not have been previously published or currently under review by other journals or conferences/symposia/workshops. Papers previously published as part of conference/workshop proceedings can be considered for publication in the Special Issue provided that they are modified to contain at least 50% new content. Authors of such submissions must clearly indicate how the submitted article extends their prior publication. Moreover, authors must acknowledge their previous paper in the manuscript and resolve any potential copyright issues prior to submission.
Dr. Qing Zhang
Dr. Lei Yu
Guest Editors
Manuscript Submission Information
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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. Sensors 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
- sensors for health assessment
- sensor data analytics
- artificial intelligence
- health assessment applications
- health IoT
- precision health
- personalised prevention
- health monitoring
- telemedicine
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