iSyNCC: An intelligent system for patient monitoring &amp;amp; clinical decision support in Neuro-Critical-Care

Mortality and morbidity related to traumatic brain injury (TBI) present a major health care burden. Patients with severe TBI must be managed rapidly and efficiently to minimize secondary brain injury potentially leading to permanent sequelae. This is especially important in young patients, whose brain is still in development, making them particularly susceptible to secondary insults. The complexity of both brain injury pathophysiology and the intensive care unit environment makes the management of these patients challenging, with a risk of delayed response and/or patient instability contributing to worsened outcome. Computerized assistance in TBI appears likely to improve patient management, by helping clinicians quickly analyze and respond to ongoing clinical changes and optimizing patient status by guiding management. Currently, computerized decision support systems (CDSSs) do not feature continuous medical assistance with individualized treatment plans. This review presents new developments in CDSSs specialized in TBI. We also present the framework for future CDSSs needed to improve TBI management in real time, taking into account individual patient characteristics.

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Multi-signal Visualization of Physiology (MVP): A novel visualization dashboard for physiological monitoring of Traumatic Brain Injury patients

Sebastian¹,

Sari²,

Loy

et al. 2012

2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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To prevent Traumatic Brain Injury (TBI) patients from secondary brain injuries, patients' physiological readings are continuously monitored. However, the visualization dashboards of most existing monitoring devices cannot effectively present all physiological information of TBI patients and are also ineffective in facilitating neuro-clinicians for fast and accurate diagnosis. To address these shortcomings, we proposed a new visualization dashboard, namely the Multi-signal Visualization of Physiology (MVP). MVP makes use of multi-signal polygram to collate various physiological signals, and it also utilizes colors and the concept of "safe/danger zones" to assist neuro-clinicians to achieve fast and accurate diagnosis. Moreover, MVP allows neuro-clinicians to review historical physiological statuses of TBI patients, which can guide and optimize clinicians' diagnosis and prognosis decisions. The performance of MVP is tested and justified with an actual Philips monitoring device.

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iSyNCC: An intelligent system for patient monitoring & clinical decision support in Neuro-Critical-Care

Cited by 6 publications

References 11 publications

Efficient Approach for Patient Monitoring: ML-Enabled Framework with Smart Connected Systems

Efficient Approach for Patient Monitoring: ML-Enabled Framework with Smart Connected Systems

Computerized Decision Support System for Traumatic Brain Injury Management

Multi-signal Visualization of Physiology (MVP): A novel visualization dashboard for physiological monitoring of Traumatic Brain Injury patients

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