Estimation of Physical Activity Level and Ambient Condition Thresholds for Respiratory Health using Smartphone Sensors
Chinazunwa Uwaoma

TL;DR
This study investigates how smartphone motion sensors can estimate safe physical activity levels and ambient thresholds to prevent respiratory distress in individuals with exercise-induced respiratory conditions.
Contribution
It introduces a method to use smartphone sensors to monitor activity and ambient conditions, aiding in managing respiratory health during physical exertion.
Findings
Correlation between Signal Magnitude Area and Energy Expenditure established
Ambient temperature and humidity impact respiratory distress thresholds
Real-time smartphone data can guide safe physical activity levels
Abstract
While physical activity has been described as a primary prevention against chronic diseases, strenuous physical exertion under adverse ambient conditions has also been reported as a major contributor to exacerbation of chronic respiratory conditions. Maintaining a balance by monitoring the type and the level of physical activities of affected individuals, could help in reducing the cost and burden of managing respiratory ailments. This paper explores the potentiality of motion sensors in Smartphones to estimate physical activity thresholds that could trigger symptoms of exercise induced respiratory conditions (EiRCs). The focus is on the extraction of measurements from the embedded motion sensors to determine the activity level and the type of activity that is tolerable to individuals respiratory health. The calculations are based on the correlation between Signal Magnitude Area (SMA)…
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Taxonomy
TopicsChronic Obstructive Pulmonary Disease (COPD) Research · Non-Invasive Vital Sign Monitoring · Physical Activity and Health
