An explosion of healthcare data has occurred in recent years due to the widespread availability of sophisticated
physiological signal monitoring devices and the development of telemetry and cognitive communication systems. Additionally, the
accessibility of medical data for the establishment of applications in big data has rapidly increased due to affordable and efficient
storage and power techniques. With the current state of technology, healthcare professionals are unable to effectively handle and
understand large, rapidly changing, and complex data; this is where big data applications come in. Making medical services more cost-
effective and sustainable is a driving force behind the creation of such systems. In this article, we present a discussion of the present
condition of big data applications that make use of physiological signals or derived metrics to aid in medical decision making in the
home and in the hospital. Specifically, we examine critical care systems designed for continuous healthcare management and address
the obstacles that must be surmounted before such systems may be used in real-world practice. Big data technologies might
revolutionize future hospital administration if these problems are solved.
Keywords
Big Data, Big Data Analytics, Electronic Health Records, Data Modality, Physiological Signal Analysis
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Cite this article
Madeleine Liu Qinghui, “A Survey on Big Data Application for Modality and Physiological Signal Analysis”, Advances in Intelligent Systems and Technologies, pp. 044-054. 2022. doi:10.53759/aist/978-9914-9946-0-5_6
