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. 2020 Jun:106:103434.
doi: 10.1016/j.jbi.2020.103434. Epub 2020 Apr 28.

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

Yingcheng Sun  1 , Fei Guo  2 , Farhad Kaffashi  2 , Frank J Jacono  3 , Michael DeGeorgia  4 , Kenneth A Loparo  2
Affiliations

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

Yingcheng Sun et al. J Biomed Inform. 2020 Jun.

Abstract

Modern intensive care units (ICU) are equipped with a variety of different medical devices to monitor the physiological status of patients. These devices can generate large amounts of multimodal data daily that include physiological waveform signals (arterial blood pressure, electrocardiogram, respiration), patient alarm messages, numeric vitals data, etc. In order to provide opportunities for increasingly improved patient care, it is necessary to develop an effective data acquisition and analysis system that can assist clinicians and provide decision support at the patient bedside. Previous research has discussed various data collection methods, but a comprehensive solution for bedside data acquisition to analysis has not been achieved. In this paper, we proposed a multimodal data acquisition and analysis system called INSMA, with the ability to acquire, store, process, and visualize multiple types of data from the Philips IntelliVue patient monitor. We also discuss how the acquired data can be used for patient state tracking. INSMA is being tested in the ICU at University Hospitals Cleveland Medical Center.

Keywords: Intensive care unit; Medical data mining; Multimodal data; Philips IntelliVue patient monitor.

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Conflict of interest statement

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

None
Graphical abstract
Fig. 1
Fig. 1
INSMA Architecture: Data Acquistion, Parsing and Visualization modules. INSMA acquires data from patient monitors in real-time through a variety of different types of network communication.
Fig. 2
Fig. 2
Data Acquisition Interface with special features labeled 1–5.
Fig. 3
Fig. 3
The framing structure.
Fig. 4
Fig. 4
The main interface of the Data Visualization Module. The data is from a patient with three measurements: ECG I, RESP and PLETH.
Fig. 5
Fig. 5
Plot Setting dialogue window.
Fig. 6
Fig. 6
Plot one type of wave data: ECG I from 0:0:2 to 0:2:2.
Fig. 7
Fig. 7
Display of three types of wave data: ECG I, RESP and PLETH from 0:0:2 to 0:16:50 in one panel.
Fig. 8
Fig. 8
Patient state tracking using acquired multimodal data. Numbers in bottom-right hand corner correspond to numbering below-this stage is performed once for every variability dynamics algorithm of interest.
Fig. 9
Fig. 9
Flow chart of patient data management.
Fig. 10
Fig. 10
Parsed data from INSMA. ECG, Pleth and Respiration waveforms (top and bottom panels) selected from a recording of a patient in the Neurosurgery ICU.
See this image and copyright information in PMC

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