CARENet - A network monitoring system for intensive care mechanical ventilation treatment

Written by Dr Chiew Yeong Shiong, School of Engineering

CARENet is a network monitoring system for intensive care mechanical ventilation (MV) treatment of respiratory failure patients. The system consists of data acquisition devices, a server, network-attached storage, and a cloud web application. This system collects, stores, and analyses MV patients' breathing data in real-time during MV treatment. These data are converted into patient-specific lung information for clinicians to aid their diagnostic and decision making when setting MV treatment.

Mechanical ventilation (MV) provides breathing support for respiratory failure patients in the hospital. However, MV treatment is challenging to manage due to variable patient conditions and responses to treatment. MV treatment requires constant monitoring and guide to ensure optimum care. It is challenging due to the lack of a real-time continuous lung monitoring tool. Thus, there is a need for a system to collect MV data and process them to clinically useful information in real-time.

The proposed research will provide the opportunity to gain more insight into the patient condition and, eventually, will directly benefit respiratory failure patients and individuals worldwide. Malaysia treats around 38,000 intensive care patients each year, and approximately 22.7% of these patients require MV due to respiratory failure. A more severe form of respiratory failure, acute respiratory distress syndrome, can have a mortality rate of up to 60%. In addition, a respiratory failure patient will receive an average of 3 days of MV treatment, which cost per day is approximately RM3000 extra. Given the high mortality rate and the cost of MV treatment, an improvement in MV treatment will offer a significant return on social and economic costs.

We use state-of-the-art model-based and artificial intelligence methods to analyse patients' data. The network system is integrated with these model-based and AI analyses that enables real-time patient monitoring. We have completed our prototype and tested it in a clinical trial in a local hospital. We will be conducting more clinical trials in different hospitals to test the system and collect more patients' data for model-based analysis.

Initial set-up and testing of the system will be completed soon in a year. However, this is only the beginning. The system will require more patient data to understand further mechanical ventilated patients' conditions and how they respond to treatment. In addition, to utilise the device as a medical device, extensive research and robust testing are necessary. Monash University Malaysia has always provided the foundation and funding support to carry out our research.

Improving mechanical ventilation treatment is a long and tedious process. We welcome researchers or students interested in Biomedical research to join us in this work.