Intelligent Health Services Based on Biomedical Smart Sensors
Source abstract
Abstract
Health services can be improved by means of intelligent techniques that handle efficiently massive volumes of data collected from biomedical variables. Nowadays, these services are not only oriented to disease diagnosis and prevention, but wellness too. Advanced technologies and last trends in computing, internet of things, sensors, and data science are driving the development of new systems and applications in the area of intelligent health services based on biomedical smart sensors that deserve to be known. Through five research articles and a review, this Special Issue provides the opportunity to obtain a representative view of the potential of these technologies when applied to such a human welfare-oriented area.
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Research context
OpenAlex topics: IoT and Edge/Fog Computing · Artificial Intelligence in Healthcare · Context-Aware Activity Recognition Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Computer Science, Østfold University College, 1783 Halden, Norway
Department of Technologies of Computers and Communications, University of Extremadura, 10003 Cáceres, Spain
TSYS School of Computer Science, Columbus State University, Columbus, GA 31907, USA
References (6)
Show source-provided references
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2. Machorro-Cano, I., Alor-Hernández, G., Paredes-Valverde, M.A., Ramos-Deonati, U., Sánchez-Cervantes, J.L., and Rodríguez-Mazahua, L. (2019). PISIoT: A Machine Learning and IoT-Based Smart Health Platform for Overweight and Obesity Control. Appl. Sci., 9.10.3390/app9153037 ↗
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5. Pilco, H., Sanchez-Gordon, S., Calle-Jimenez, T., Pérez-Medina, J., Rybarczyk, Y., Jadán-Guerrero, J., Maldonado, C., and Nunes, I. (2019). An Agile Approach to Improve the Usability of a Physical Telerehabilitation Platform. Appl. Sci., 9.10.3390/app9030480 ↗
6. Díaz, S., Stephenson, J.B., and Labrador, M.A. (2019). Use of Wearable Sensor Technology in Gait, Balance, and Range of Motion Analysis. Appl. Sci., 10.10.3390/app10010234 ↗