By 2030 it has been predicted that Chronic Obstructive Pulmonary Disease (COPD) will affect, on a global scale, over 64 million people and will be the third leading cause of death worldwide. This work discusses the development of a self-management system that records physiological and contextual information via a smartphone, a wrist worn accelerometer for measuring activity and a chest worn device for monitoring patterns of respiration. The data recorded through this system facilitates analysis to identify changes in the patterns of the bio-signals and may pave the way for advice to be offered regarding the self-management of this long-term condition. Feedback relating to specific activity goals that can be set and monitored will be provided to the user as part of the self-management solution.
CITATION STYLE
Beattie, M. P., Zheng, H., Nugent, C. D., & McCullagh, P. (2014). Technical validation of COPD activity support monitor- towards COPD self-management. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8868, 75–82. https://doi.org/10.1007/978-3-319-13105-4_12
Mendeley helps you to discover research relevant for your work.