Dear Colleagues,

The development of information technology and telecommunications has reached a level where their usefulness can be applied for healthcare needs towards Telemedicine and Telecare, which represent a promising alternative to traditional hospital admission. This basic premise is included in all strategic plans of the European Union and the rest of the world. Research efforts are focused on the development of devices and instruments that are smaller, simple to use, and reliable. The measurements from these devices, which are novel both in terms of their duration and activity coverage, also require novel approaches to their analysis. Efficient and reliable methods for analysis of signals acquired by wireless body devices will increase the interest in them and will push them forward to become the new standard in patient monitoring and healthcare. These algorithms should be able to deal with different challenges present in the data, including noise and sparsely sampled signals. Moreover, the research community recognizes that the inclusion of data analysis methods throughout the complete data life cycle is the way towards a better understanding of the data. This entails the use of data analysis methods, from data acquisition to data pre-processing, data storage and curation, data modeling, and data visualization methods. By doing so, data can be made FAIR, i.e., the data will adhere to the FAIR data principles: Findable, Accessible, Interoperable, and Reusable. The community further recognizes that some of the necessities in this area are novel measurements and datasets for the proper evaluation and benchmarking of data analysis methods.

This Special Issue welcomes original scientific contributions, as well as case studies and reviews of the state-of-the-art in the topics provided below, in the context of analysis of medical sensor data. Analysis can integrate concepts from different areas, including signal processing, data mining, and knowledge discovery, i.e., approaches ranging from basic algorithms for pre-processing and segmentation of the raw measured signal to more complex algorithms for data analytics, targeting tasks like data and knowledge representation, extraction of new knowledge, and data fusion.

The topics of interest include, but are not limited to:

• data representation;
• knowledge representation;
• FAIR sensor data;
• explainable artificial intelligence (AI) methods;
• decision support systems;
• semantic technologies;
• ontologies for sensor data;
• analysis of data streams;
• benchmarking of analysis methods;
• sensor data repositories and curation;
• advanced bio-signal processing and interpretation;
• monitoring of vital functions with sensor and ICT systems; and
• wearable sensors and networks.

Dr. Aleksandra Rashkovska
Dr. Dragi Kocev
Dr. Panče Panov
Guest Editors

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• Medical sensor data
• FAIR data
• Explainable AI
• Wearable sensors
• Bio-signal processing