Algorithm for identification of asthma severity level using CO2 waveform

Asthma is known as one of the top causes of death in Malaysia, especially with increased morbidity. Many deaths and morbidity have been associated with poor treatment, under-use of objective measurement of severity level and lack of supervision. A survey carried out by Asthma Council Malaysia indicated that 66% of asthmatic patients have never undergone a lung function test due to high cost, non-portable and lack of availability of diagnostic devices in the clinical set-up in Malaysia. Apart from this, the existing methods (Spirometer and Peak Flow Meter) cannot give accurate result if a patient or children under the age of 6 years old, does not cooperate, suffering from chest pain averting a forceful effort or does not understand the set of instructions. To overcome the limitation of existing diagnostic method, a CO2 waveform that varies in shape based on the CO2 concentration level has been proposed in literature as a noninvasive, real-time, and effort-independent diagnostic and screening tool for monitoring asthmatic condition. However, to date, the studies have been conducted offline in order to extract the features from CO2 waveform in correlation with asthmatic condition. Hence a real time CO2 waveform interpreter screening tool is proposed here for monitoring level of that may lead to reduce the morbidity and mortality rate.