IEEE Access Special Section Editorial: Smart Health Sensing and Computational Intelligence: From Big Data to Big Impacts

Abstract

Smart health big data is paving a promising way for ubiquitous health management, leveraging exciting advances in biomedical engineering technologies, such as convenient bio-sensing, health monitoring, in-home monitoring, biomedical signal processing, data mining, health trend tracking, and evidence-based medical decision support. To build and utilize the smart health big data, advanced data sensing and data mining technologies are closely coupled key enabling factors. In smart health big data innovations, challenges arise in how to informatively and robustly build the big data with advanced sensing technologies, and how to automatically and effectively decode patterns from the big data with intelligent computational methods. More specifically, advanced sensing techniques should be able to capture more modalities that can reflect rich physiological and behavioral states of humans, and enhance the signal robustness in daily wearable applications. In addition, intelligent computational techniques are required to unveil patterns deeply hidden in the data and nonlinearly convert the patterns to high-level medical insights.