Challenges and Future Trends of Sensing Technology—Applications in Sustainable E-health
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".
Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 296
Special Issue Editors
Interests: biomedical signal processing and modeling; electrophysiological instrumentation; E-health
Special Issues, Collections and Topics in MDPI journals
Interests: biomedical signal processing; connected objects; E-health
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The ambulatory monitoring of the environmental state and physiological parameters of humans for wellbeing and medical applications needs new sensors with reliable precision, miniaturization, and low power/resource consumption for sustainable applications in terms of ecological context. This actual challenge lies not only in sensor technology but also in signal processing algorithms considering noise presence, uncertainty, and sparse modalities/channels. Other challenges are linked to developing low-consumption and robust AI approaches potentially trained on reduced biomedical databases.
In this Special Issue, researchers are invited to submit contributions describing a new approach for sensing in E-Health applications including the innovative technology of sensors and hardware architecture, multimodal and multichannel signal processing algorithms, and robust and optimized AI. All proposed contributions should also be precise in the proposed sustainable measures considering their application.
Potential topics include, but are not limited, to the following:
- Reusable/low resource smart sensors;
- Sensor fusion algorithms and input dimensionality reduction;
- Sparse and robust multichannel signal processing;
- Low consumption and robust AI algorithms;
- Possible applications: ambulatory monitoring, chronic disease or post-surgery monitoring, physiological state detection (ex: sleep, stress, rare event detection), telemedicine.
Prof. Dr. Sofiane Boudaoud
Prof. Dr. Dan Istrate
Guest Editor
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Keywords
- sustainable embedded sensors
- biomedical signals
- low consumption AI
- optimized signal processing
- sustainable E-health applications
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