Intensive Care Window: A Multi-Modal Monitoring Tool for Intensive Care Research and Practice

Gjermundrod, Harald; Papa, Marília Angelina Ferreira; Zeinalipour-Yazti, Demetrios; Dikaiakos, D. Marios; Panayi, George; Kyprianou, Theodoros

doi:10.1109/cbms.2007.64

Cited by 8 publications

(7 citation statements)

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“…In comparison to other frameworks and solutions [7], [8] with a strong focus on data collection and visualization at a central point, the TICoMS framework is intended to be used as a monitoring and control framework with decentralized data accessibility. By distributing all collected information to other connected devices with defined filter rules, arbitrary data routes for measurement and control can be established, while maintaining a fixed and universal message template for data exchange.…”

Section: Discussionmentioning

confidence: 99%

TICoMS -- A Modular and Message-Based Framework for Monitoring and Control of Medical Devices

Peter

Klingert

Königsrainer

et al. 2014

2014 IEEE 27th International Symposium on Computer-Based Medical Systems

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An important aspect of clinical work, especially in the intensive care unit (ICU) is the vigilant observation of patients' vital data on a various number of monitors and displays to allow for rapid decision-making which is often required in critical conditions. Most often, the presented data cannot be collected and used as a whole to aid the decision making by availability and comparison of all relevant data at once. In this paper, a novel approach for handling real-time clinical data is presented. We developed TICoMS (Tübinger ICU Control and Monitoring System), a framework for integration of sensors and effectors into a homogeneous message-based network capable of gathering and distributing real-time data in ICU settings from medical devices. The accumulated data can be presented on a central patient monitoring screen for a fast and extensive overview of the patient's current condition and trends with a homogenous time-base. Furthermore, this framework provides control capabilities for medical devices and is therefore an essential foundation for device interactions that may allow for computer-based support in decision-making or advanced automation in intensive care scenarios.

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Section: Discussionmentioning

confidence: 99%

TICoMS -- A Modular and Message-Based Framework for Monitoring and Control of Medical Devices

Peter

Klingert

Königsrainer

et al. 2014

2014 IEEE 27th International Symposium on Computer-Based Medical Systems

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“…The future of critical care will require "information management", that includes the real-time collection, integration, and interpretation of various types of physiological data from multiple sources. The possible research work will focus on (1) the integration and analysis of massive heterogenous medical data to provide scientific decision-making with machine learning methods [9,30], and (2) the acquisition and processing of vast amount of multi-channel high-density and real-time streaming data using multivariate and nonlinear time series analysis methods to facilitate rapid diagnosis and treatment [31]. Patient care in the ICU can be significantly improved through the application of complex system analysis and information management methods.…”

Section: Discussionmentioning

confidence: 99%

“…heartrate, oxygen saturation) and performing alarm functions based on minimum and maximum limits set by the clinical staff in the monitor. A variety of sensors and associated clinical measurement modules can be connected to the monitor, and these modules are generally interchangeable with other monitors provided by Philips [9]. One of these modules is the Philips VueLink module that provides an interface to more than 100 third-party specialty measurement devices like mechanical ventilators, gas analyzers, anesthesia machines, etc.…”

Section: Patient Monitormentioning

confidence: 99%

INSMA: An integrated system for multimodal data acquisition and analysis in the intensive care unit

Sun

Guo

Kaffashi

et al. 2020

Journal of Biomedical Informatics

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Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre-including this research content-immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

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“…Goldstein et al developed a real-time, physiologic data acquisition system in the pediatric intensive care unit [23]. Gjermundrod et al implemented the Intensive Care Window which can retrieve and integrate data from different patient monitoring devices in ICU [24]. Sun et al proposed an integrated system INSMA, which supports multimodal data acquisition, parsing, real-time data analysis, and visualization in the ICU [25].…”

Section: Introductionmentioning

confidence: 99%

SEPRES: Sepsis prediction via the clinical data integration system in the ICU

Chen

Lin

et al. 2022

Preprint

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Background: The lack of information interoperability between different devices and systems in the ICU hinders further utilization of data, especially for early warning of specific diseases in the ICU. Objectives: We aimed to establish a real-time early warning system for sepsis based on a data integration system that can be implemented at the bedside of the intensive care unit (ICU), named SEPRES. Methods: Data is collected from bedside devices through the integration hub and uploaded to the integration system through the local area network. The data integration system was designed to integrate vital signs data, laboratory data, ventilator data, demographic data, pharmacy data, nursing data, etc. from multiple medical devices and systems. It integrates, standardizes, and stores information, making the real-time inference of the early warning module possible. The built-in sepsis early warning module can detect the onset of sepsis within 5 hours preceding at most. Results: Our data integration system has already been deployed in Ruijin Hospital, confirming the effectiveness of our system. Conclusions: We highlight that SEPRES has the potential to improve ICU management by helping medical practitioners identify at-sepsis-risk patients and prepare for timely diagnosis and intervention.

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Intensive Care Window: A Multi-Modal Monitoring Tool for Intensive Care Research and Practice

Cited by 8 publications

References 0 publications

TICoMS -- A Modular and Message-Based Framework for Monitoring and Control of Medical Devices

TICoMS -- A Modular and Message-Based Framework for Monitoring and Control of Medical Devices

INSMA: An integrated system for multimodal data acquisition and analysis in the intensive care unit

SEPRES: Sepsis prediction via the clinical data integration system in the ICU

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