The proposed system consists of 7 major components:(1)a mobile digital monitoring box detecting temperature, humidity, ultra-violate, and PM 2.5; (2)implanted mobile physiological sensors on the digital monitoring box, which monitor physiological data such as, oxygen saturation concentration, heart rate, and respiratory rate; (3)a smartphone application to connect all of schemes with the cloud server; (4)integrating data additionally from available pedometer and mobile spirometry measures to assess a patient＇s daily activity and lung function; (5)a computing system of decision support in physical activity; (6)a Line bot, which provides motivating feedback and physical activity record to the user; (7)the website and cloud server. The schematic of the system setup is presented in Figure 1.The digital monitoring device consists of mobile environmental detecting sensors, a Raspberry Pi single-board computer using USB Battery Module, and a 3.5" TFT touchscreen for Raspberry Pi, which could extract the data from remote physiological sensors. The architecture of the hardware components is presented Figure 2.
The system for decision support in physical activity consists of four sections including smartphone App, website, Line bot, and the cloud server. A smartphone App was created using Java JSP and JDK SE 1.8. A Line bot was designed using JSON script and JavaScript to automatically provide user with information such as, goal advice, real-time air quality around the users, and notification of risky environment condition. The concept map of the system has shown in Figure 3.Taking account of the specific needs of health information regarding physical activity management in COPD patients, a technological tool for enhancing physical activity of patients with COPD was proposed. The feature of this prototype was designed to reduce harmful environment condition and by increasing access to safe as well as personal goals focused activity. This tool developed in our study added value of pre-exercise environmental and physiological assessment to exercise monitoring and feedback features in order to help preventing symptoms during daily activity of patients with COPD.