Robust spectral analysis of thoraco-abdominal motion and oxymetry in obstructive sleep apnea

The diagnosis of obstructive sleep apnea (OSA) relies on polysomnography (PSG), a multidimensional biosignal recording that is conducted in sleep laboratories. Standard PSG montage involves the use of nasal-oral airflow sensors to visualize cyclic episodes of upper airflow interruption, which are considered diagnostic of sleep apnea. Given the high-cost and discomfort associated with in-laboratory PSG, there is an emergent need for novel technology that simplifies OSA screening and diagnosis with less expensive methods. The main goal of this project was to identify novel OSA signatures based on the spectral analysis of thoraco-abdominal motion channels. Our main hypothesis was that proper spectral analysis can detect OSA cycles in adults using simultaneous recording of oxygen saturation (SaO2) and either, chest or abdominal motion. A sample study on 35 individuals was conducted with statistically significant results that suggest a strong relationship between airflow-independent signals and oxygen saturation. The impact of this new approach is that it may allow the design of more comfortable and reliable portable devices for screening, diagnosis and monitoring of OSA, functioning only with oximetry and airflow-independent (abdominal or chest) breathing sensors.