Monitoring and estimating inhalation of particular matter using personal physiological data

It is shown that the excessive inhalation of PM (Particulate Matter) 2.5 will seriously affect the health of human. Many countries have deployed various detectors for air pollution in order to report concentration of PM2.5 to show how much seriousness of air pollution is. But, what more important is how much PM 2.5 has been inhaled by people anytime and anywhere. Therefore, in this paper, we propose a method for monitoring and estimating people's PM2.5 inhalation by using personally physiological data, such as heart rate (HR), and mobile PM2.5 sensor. We can retrieve people's heart rate from company's cloud platform of smart bracelet and then calculate his/her PM2.5 inhalation based on personal HR and minute ventilation (VE). In the method, we first adopt Bruce protocol to measure various functions of body, such as HR and VE, on a treadmill and exploit regression model to build predictive model for VE. Therefore, we can utilize smart bracelet to monitor people heart rate and then calculate PM2.5 inhalation based on personal HR and mobile PM2.5 sensor (MPS). We think that the method can effectively estimate the PM 2.5 inhalation of physical activity.