Sleep Apnea Monitoring and Treatment

We have investigated an optimal sensing platform that can be used to monitor the sleep quality and sleep abnormalities for at-home sleep disorder monitoring and diagnosis in cancer patient. As an alternative to a traditional Polysomnography system at the sleep lab, the proposed multisensory suit was embedded with a nonlinear signal processing algorithm and decision-rule-based machine learning model to provide at-home diagnostics of obstructive sleep apnea (OSA), a very common sleep breathing disorder. An ongoing extension of this system, designed as a wearable device with the added cardiorespiratory monitoring functions, has been developed for the screening and diagnosis of central sleep apnea, nocturnal asthma and cardiovascular-related diseases. Research in this direction has produced 3 so far patent applications and ongoing translational research projects within the industry