Method and device for in-home sleep and signal analysis

What is this patent about?

’399 is related to the field of sleep analysis and diagnostic monitoring, specifically focusing on systems that allow for clinical-grade polysomnography to be conducted in a subject's home. Traditional sleep studies often suffer from the 'first night effect,' where patients cannot sleep naturally in a lab setting, or from unattended home studies that lack real-time data verification. The invention addresses these limitations by providing a comprehensive, portable data acquisition framework that bridges the gap between home comfort and laboratory-level oversight.

The underlying idea behind ’399 is the integration of a multi-channel sensor suite into a wearable, battery-powered interface box that synchronizes physiological, kinetic, and environmental data for remote clinical review. By utilizing a pressure transducer within the wearable unit to derive multiple respiratory metrics and incorporating 3-D accelerometers for motion artifact correction, the system ensures high data integrity without tethering the patient to bulky bedside equipment. This allows for a 'remotely attended' study where a technician can verify signal adequacy and communicate with the subject in real-time to correct sensor displacements.

The claims of ’399 focus on a method for home sleep testing that utilizes a portable patient interface box worn on the torso, which serves as a centralized hub for a specific sensor array. This array includes a nasal cannula or facemask connected via an air port to an internal pressure transducer, a respiratory effort belt, and a fingertip pulse oximeter. The claims specifically require the digitization and storage of airflow, respiratory effort, body orientation, and oxygenation data within nonvolatile digital memory located directly on the wearable device before the data is transferred to a remote location for professional analysis.

In practice, the system functions by collecting high-fidelity signals while the subject sleeps in their own bed, utilizing the interface box to buffer data against potential transmission failures. The implementation relies on a remote computer or processor to automatically identify and draw attention to physiological or technological events, such as oxygen desaturation or electrode disconnection. This automated flagging allows clinicians to focus on critical diagnostic windows and ensures that the study is not invalidated by simple technical errors that would otherwise go unnoticed in a standard unattended home test.

The invention differentiates itself from prior approaches by combining the mobility of a wearable device with the robust data-checking capabilities of a lab-based study. Unlike previous home systems that merely recorded data for later retrieval, this method emphasizes the wireless transfer of collected data to a remote database, enabling near-instantaneous evaluation. Furthermore, the use of kinetic sensors to correct motion artifacts in the biopotential signals significantly reduces the risk of misdiagnosis caused by the subject's natural movement during sleep, providing a more reliable diagnostic tool for neurological and respiratory disorders.