Analysis of Medical Sensor Data with Machine Learning

Dear Colleagues,

The development of information technology and telecommunications has allowed their application  in health care in the form of telemedicine and telecare, which represent a promising alternative to traditional hospital admission. This basic premise is included in the strategic plans of the EU and the rest of the world. Research efforts are focused on the development of devices and instruments which are smaller, simple to use and reliable. Measurements from these devices, which are novel both in terms of their duration and activity coverage, require novel approaches to their analysis. Efficient and reliable methods for the analysis of signals acquired by wireless body devices will increase interest in them and push them to become the new standard in patient monitoring and health care. These algorithms should be able to deal with different challenges present in the data, including noise and sparsely sampled signals. Moreover, the inclusion of data analysis methods throughout the complete data life cycle contributes towards a better understanding of the data. This entails the use of data analysis methods starting from data acquisition, data pre-procession, data storage and curation, data modeling, and visualization. Further 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, on the topics provided below in the context of the analysis of medical sensor data. Analysis can integrate concepts from different machine learning areas, including data mining and knowledge discovery, data and knowledge representation, the extraction of new knowledge and data fusion.

Topics of interest include, but are not limited to:

• Data representation;
• Knowledge representation;
• Explainable AI methods;
• Decision support systems;
• 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;
• Wearable sensors and networks.

Dr. Aleksandra Rashkovska
Dr. Dragi Kocev
Guest Editors

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• medical sensor data
• explainable AI
• wearable sensors
• machine learning