An MCU-Based Peak Expiratory Flow Rate Device and Mobile-App Interface for Asthma Attack Prevention
Abstract
Purpose – Monitoring of the peak expiratory flow rate (PEFR) and its corresponding asthma management plan is one of the ways to prevent an asthma attack. The study introduces an MCU-Based Monitoring and Control Prototype with mobile application that prompts the person of the scheduled time to take the PEFR and automatically records the rate and displays the asthma management plan corresponding to it. When the reading hits a critical level, it sends an alert to the immediate family and doctor of the patient.
Method –The prototype was tested with asthmatic and non-asthmatic patients to evaluate its accuracy and timeliness. Data were also taken using the commercially available peak flow meters and all information were recorded manually. T-test and variability measures were used for all the samples of both devices.
Results – The results show that the values measured by the prototype compared with the commercially available meter have no significant difference. Moreover, the on-time data-logged monitoring has shown the trend on the PEFR of a patient relative to his personal best reading. The data showed the decline of the PEFR measured for days. When the medical intervention was done, the PEFR readings improved.
Conclusion – The prototype reading has high degree of accuracy and consistency as seen from the results of the testing. The system has shown critical values with the continuous decline of the PEFR measured. This has served as an important information for immediate control and intervention of an impending asthma attack.
Recommendations – Future works must include mobile application that works for all platforms. Also, communication between the hardware and the mobile device must not be limited to Bluetooth technology.
Research Implications – The study will serve as a reference for other research or technological breakthroughs that can aid not only in the field of technology but also in other professional fields.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.