IIUM Repository

Network data acquisition and monitoring system for intensive care mechanical ventilation treatment

Qing, Arn Ng and Chiew, Yeong Shiong and Xin, Wang and Chee, Pin Tan and Mat Nor, Mohd Basri and Damanhuri, Nor Salwa and Chase, Geoffrey (2021) Network data acquisition and monitoring system for intensive care mechanical ventilation treatment. IEEE Access, 9. pp. 91859-91873. ISSN 2169-3536 E-ISSN 2169-3536

[img] PDF - Published Version
Restricted to Registered users only

Download (3MB) | Request a copy
[img] PDF (SCOPUS) - Supplemental Material
Restricted to Registered users only

Download (632kB) | Request a copy


The rise of model-based and machine learning methods have created increasingly realistic opportunities to implement personalized, patient-specific mechanical ventilation (MV) in the ICU. These methods require monitoring of real-time patient ventilation waveform data (VWD) during MV treatment. However, there are relatively few non-invasive and/or non-proprietary systems to monitor and record patient-specific lung condition in real-time. In this paper, we present a CARE network data acquisition and monitoring system (CARENet) to automate data collection and to remotely monitor patient-specific lung condition and ventilation parameters. The automated system acquires VWD from a mechanical ventilator using a data acquisition device (DAQ), stores data in network-attached storage (NAS), and processes VWDs via a data management platform (DMP) web application. The web application enables real-time and retrospective model-based monitoring and analysis of clinical MV data. In particular, CARENet provides detailed breath-by-breath patient-specific respiratory mechanics, as well as the overall trends assessing changes in patient condition. Validation testing with a retrospective data set illustrated how breath-to-breath and time-varying patient-ventilator interaction during MV can be monitored, and, in turn, can be used to guide MV treatment. The network data acquisition system design presented is low-cost, open, and enables continuous, automated, scalable, real-time collection and analysis of waveform data, to help improve decision making, care, and outcomes in MV.

Item Type: Article (Journal)
Uncontrolled Keywords: Mechanical ventilation (MV), ventilator waveform data (VWD), network data acquisition, respiratory mechanics, data management platform (DMP)
Subjects: R Medicine > RC Internal medicine > RC82 Medical Emergencies, Critical Care, Intensive Care, First Aid
T Technology > TJ Mechanical engineering and machinery > TJ181 Mechanical movements
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Medicine
Kulliyyah of Medicine > Department of Anaesthesiology & Intensive Care
Depositing User: Dr. Mohd Basri Mat Nor
Date Deposited: 06 Jul 2021 07:49
Last Modified: 27 Aug 2021 08:25
URI: http://irep.iium.edu.my/id/eprint/90571

Actions (login required)

View Item View Item


Downloads per month over past year