A review of big data applications of physiological signal data

Abstract

The proliferation of smart physiological signal monitoring sensors, combined with the advancement of telemetry and intelligent communication systems, has led to an explosion in healthcare data in the past few years. Additionally, access to cheaper and more effective power and storage mechanisms has significantly increased the availability of healthcare data for the development of big data applications. Big data applications in healthcare are concerned with the analysis of datasets which are too big, too fast, and too complex for healthcare providers to process and interpret with existing tools. The driver for the development of such systems is the continuing effort in making healthcare services more efficient and sustainable. In this paper, we provide a review of current big data applications which utilize physiological waveforms or derived measurements in order to provide medical decision support, often in real time, in the clinical and home environment. We focus mainly on systems developed for continuous patient monitoring in critical care and discuss the challenges that need to be overcome such that these systems can be incorporated into clinical practice. Once these challenges are overcome, big data systems have the potential to transform healthcare management in the hospital of the future.

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“…First, many institutions do not have an infrastructure amenable to the acquisition and storage of neurocritical care data within a nonrelational database structure. Systems such as Amazon Web Services are open source and tied to platforms with data storage capacity, yet issues surrounding privacy, security, access, and bandwidth [22,51] must be addressed by the local institution and its information technology experts. While these platforms are built to support Health Insurance Portability and Accountability Act (HIPAA) compliance, user-level configuration may lead to unsecured data.…”

[Retracted] Merging RFID and Blockchain Technologies to Accelerate Big Data Medical Research Based on Physiological Signals

“…e steganography technologies monitor patients' health safety and provide patients with data confidentiality and identity authentication. Orphanidou [4] reviewed big data applications of physiological signals, pointed out how the applications use physiological signals to provide real-time support for medical decision making in both clinical and family settings, and need to be overcome in clinical practice. Tartan et al [5] proposed a heart rate monitoring system based on mobile devices and geographical location, which can monitor physiological signals and send alarm information when abnormal heart rate changes.…”

“…e hospitals applications are adopting physiological signals to realize a quicker way to visit these records. e physiological signals are responsible to offer patient care, enhance the clinical performances, and promote the clinical data research [1][2][3][4][5].…”

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“…10 Smart systems capable of automatically recording and evaluating physiological data in real time to improve the quality, safety, and efficacy of medical decisions are of great interest. 126,127 These systems must ensure that all relevant data are recorded and that information is intelligently filtered and presented appropriately. 127 To enable individualized assessment using physiological biomarkers to predict whether a particular patient is likely to experience an adverse event, systems must be capable of automatically transforming raw data into useful information and presenting it in integrated displays showing the information that is most relevant for clinical decision making.…”