A network monitoring system for intensive care mechanical ventilation treatment

A mechanical ventilator is a machine that takes over the work of breathing when a person is not able to breathe enough on their own. It is a form of life support as it provides breathing support for respiratory failure patients in the hospital. However, mechanical ventilation treatment is challenging to manage due to variable patient conditions and responses to treatment.

Mechanical ventilation treatment requires constant monitoring and guidance 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 mechanical ventilation data and process them into clinically useful information in realtime.

Dr. Chiew Yeong Shiong and his research team from the School of Engineering, Monash University Malaysia, have devised a network monitoring system for intensive care mechanical ventilation treatment of respiratory failure patients — CARENet.

“CARENet consists of data acquisition devices, a server, network-attached storage, and a cloud web application. This system collects, stores and analyses mechanical ventilation patients’ breathing data in real-time during treatment. These data are converted into patient-specific lung information for clinicians to aid their diagnostic and decision making when setting mechanical ventilation treatment,” shared Dr. Chiew, who has been working on model-based mechanical ventilation research since he was pursuing his PhD in 2010.

“We conducted model-based mechanical ventilation research in International Islamic University Malaysia Medical Centre (IIUMMC) in Kuantan, Pahang, with Professor Dr. Mohd. Basri Bin Mat Nor. We travelled between Monash University and the medical centre for data collection. Patient mechanical ventilation treatment is 24/7, so we need to have a system to monitor the patient continuously and closely, even when away from the patient’s bedside,” Dr. Chiew said.

The research team utilises state- of-the-art model-based and artificial intelligence (AI) methods to analyse patients’ data. The network system is integrated with these modelbased 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,” Dr. Chiew stated.

According to Dr. Chiew, the proposed research will provide the opportunity to gain more insight into a patient’s condition and eventually benefit respiratory failure patients and individuals worldwide. Malaysia treats around 38,000 intensive care patients each year. Approximately 22.7 per cent of these patients require mechanical ventilation due to respiratory failure. A more severe form of respiratory failure, acute respiratory distress syndrome, can have a mortality rate of up to

60 per cent. In addition, a respiratory failure patient will receive an average of three days of mechanical ventilation treatment, which cost per day is approximately RM3000 extra. Given the high mortality rate and the cost of mechanical ventilation treatment, an improvement in mechanical ventilation treatment will offer a significant return on social and economic costs.

The system’s initial setup and testing will be completed 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.

“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,” added Dr. Chiew.

The research team has collaborations both locally and internationally. Monash University Malaysia provides the foundation and funding support to carry out this research.

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