Non-contact Sensing Technologies for Motion Analysis and Health Monitoring
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: 30 October 2024 | Viewed by 56
Special Issue Editors
Interests: terahertz radar; FMCW radar; vital signs monitoring
Special Issues, Collections and Topics in MDPI journals
Interests: automotive radars; radar measurements; radar digital signal processing
Special Issues, Collections and Topics in MDPI journals
Interests: bioengineering; biomedical signal processing; biostatistics; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: communication systems; machine learning techniques for radar applications; physical layer security
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
There has been a great deal of research on the use of contactless sensors to monitor people’s health and motion, with the aim of improving their quality of life. Subject monitoring encompasses a wide range of applications, involving the use of extremely differentiated sensor technologies capable of monitoring many aspects of people’s health. In this context, various sensor technologies can be leveraged to obtain such information. These can be obtained from contact or noncontact sensing, directly from sensors, by applying signal processing techniques or machine learning and deep learning approaches. Since the recognition of human health characteristics can be crucial to improving and preserving people’s lives, the progress of the technologies in this field is extremely exciting and pioneering.
This Special Issue intends to collect contributions of the most recent research in the context of people motion and health monitoring based on contactless technologies.
Prof. Dr. Ennio Gambi
Dr. Gianluca Ciattaglia
Dr. Agnese Sbrollini
Dr. Linda Senigagliesi
Guest Editors
Manuscript Submission Information
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Keywords
- vital signs
- signal processing
- health
- machine learning
- noncontact sensing
