Wearable Tool for Breathing Pattern Recognition and Exacerbation Monitoring for COPD Patients via a Device -to- Cloud Communication Model.

ABSTRACT

Chronic Obstructive Pulmonary Disease (COPD) has become one of the major causes of disability in the Philippines today. COPD is incurable and would also be one of the most painstaking diseases because it progresses over time. Patient self-monitoring, especially breathing patterns and frequency has become an increasingly recognized process which is beneficial for the ongoing care of COPD. Many potential technologies for the diagnosis and monitoring of COPD have been developed, but focusing on telehealth, imaging, and spirometry. This study has designed and created an IoT based system that could recognize and monitor the respiratory rate through breathing patterns and provide a means for doctors to remotely monitor the patient. The prototype device that has been developed was named X-Hale. X-Hale is a cost-effective and portable remote monitoring IoT-based tool, integrated within a wearable oxygen mask responsible for recognizing and recording accurate breathing frequency patterns. The system was designed to interweave underlying elements of Device-to-Cloud model for a straight-forward communication used in remote monitoring. The wearable device was tested using an HT50 ventilator that delivers machine-controlled dummy breathing in an actual hospital setting. Results show high accuracy in detecting breathing patterns in Slow, Normal and Fast respiratory rate per minute. X-Hale was also tested in actual patients to facilitate the remote monitoring of breathing patterns via the IoT communication model used.

Keywords: Wearable, internet of things, device-to-cloud communication, breathing pattern

Citation:

Martillano, D. A., Iligan, M., Ramos, A.R.R., Daraman, Jr. A., & Abadines, M.F. (2022). Wearable Tool for Breathing Pattern Recognition and Exacerbation Monitoring for COPD Patients via a Device – to – Cloud Communication Model. Journal of Communications vol. 17, no. 6, June 2022. https://doi:10.12720/jcm.17.6.423