Development and use of SLEEPTRONIX for ambulatory assessment of sleep, temperature, and cortisol

PROJECT SUMMARY Obstructive Sleep Apnea (OSA) is a common chronic condition that affects over 1 billion people worldwide. Clinically, OSA is defined using the apnea-hypopnea index (AHI) which quantifies the rate of respiratory events. Recent evidence suggests that AHI has demonstrable limitations including poor predictive ability and relationship to outcomes. To overcome the limitations of AHI, our group has recently developed “ventilatory burden”, a fully automated breath-by-breath measure of abnormal breathing overnight, which is independent of hypoxia or arousal consequences, as an alternative metric better suited in clinical management of OSA. Another pathway that several groups have attempted to overcome the limitations of AHI is to use wearable devices that are easy to use and provide surrogates of AHI (e.g., WatchPAT, Oximetry etc.). However, these devices do not characterize the underlying ventilatory burden in OSA, which first and foremost is a sleep-related “breathing” disorder. Further, the exclusion of EEG in these devices implies that the denominator for AHI, which is the total sleep time, is estimated and not accurate. In this proposal, we aim to tackle both these issues by investigating the utility of a low-profile, low-cost, non-commercial, open-source wearable sensor system (SLEEPTRONIX), with physical resemblance to adhesive bandages that can monitor the requisite signals for fully characterizing OSA pathophysiology (EEG/EOG/airflow/SpO2). Using innovative algorithms, we aim to show that the SLEEPTRONIX derives accurate estimates of not only clinically used AHI metric, but also the ventilatory burden which overcomes limitations of AHI. Using N=30 subjects newly diagnosed with OSA, and age, sex matched healthy controls our primary aim is to develop and refine the SLEEPTRONIX system for continuous assessment of multiple night’s sleep and breathing patterns. In addition, we will refine our SLEEPTRONIX system to measure circadian rhythm parameters using temperature and cortisol levels that are assessed using novel nanotechnologies. The successful completion of above aims will establish that sacrificing on the requisite measurements of characterizing an individual’s underlying OSA is avoidable, and the use of wearables coupled with innovative measurements of underlying ventilatory deficit in OSA has the potential to shift the paradigm in OSA management.