A Wearable Device Integrated with Deep Learning‐Based Algorithms for the Analysis of Breath Patterns

Sleep problems are serious issues that make life difficult for all people, including sleep apnea. apnea, which causes breathlessness more than 10 s, is linked to severe health due the damage it can induce. To mitigate risk of these disorders, monitoring patients has become increasingly challenging. Wearable technologies offer an effective healthcare solution remote patient and diagnosis. A novel wearable system based on Arduino technology introduced, specifically designed monitor breath patterns patients. The analysis data from holds great importance diagnosis continuous address this need, advanced image processing deep learning techniques presented. This automatically detects respiratory patterns, inhalation, exhalation, breathlessness. device average 97.6% sensitivity, 79.7% specificity, 96% accuracy in identifying patterns. institutions a simple, inexpensive, noninvasive, ergonomic be further extended apnea