Respiratory effort monitoring system for sleep apnea screening for both supine and lateral recumbent positions

Sleep disorders are a major health problem affecting more than 50 million people in the US alone. Sleep Apnea (SA) is by far the most common of these disorders, causing excessive sleepiness and diminished cognitive functions. Monitoring the respiratory effort is essential for SA detection. Conventional methods are limited to measuring only respiratory effort, and methods based on Inertial Measuring Units have been constrained to supine or standing/sitting positions. In this work, we propose a solution to such limitations, allowing the IMU to detect the respiratory effort on both supine and lateral recumbent positions, based on a sensor fusion algorithm. In addition, the body position is also obtained from the IMU data. Using the Pearson Cross-correlation Coefficient as a success metric, our results show correlation values ranging from 0.8550 to 0.9413 for various tests.

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