Identifying conditions using respiration rate
Inventors
Pho, Gerald • Aschbacher, Kirstin Elizabeth • Chapp, Michael • Rai, Harpreet Singh
Assignees
Publication Number
US-12220221-B2
Publication Date
2025-02-11
Expiration Date
2041-08-18
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Abstract
Methods, systems, and devices for detection of medical conditions using respiration rate data are described. A method may include receiving physiological data associated with a user, the physiological data being continuously collected via a wearable device associated with the user, determining a set of respiration rate values for the user over a time interval based on the physiological data, and determining one or more respiration rate parameters associated with a change of the set of respiration rate values over the time interval. The method may further include determining one or more condition risk metrics associated with one or more medical conditions based on the one or more respiration rate parameters, where the one or more condition risk metrics associated with a relative probability that the user is associated with a respective medical condition.
Core Innovation
The invention provides methods, systems, and devices for detecting medical conditions using respiration rate data continuously collected from a user via wearable devices such as rings. The system determines respiration rate values over a time interval, derives one or more respiration rate parameters indicating changes in respiration rate over the interval, and then determines condition risk metrics associated with medical conditions based on these parameters. These condition risk metrics represent relative probabilities that the user is experiencing respective medical conditions.
The problem being solved is that existing wearable devices collect physiological data but provide limited insight and often do not continuously track respiration rate or utilize it to determine condition risk metrics. Typical physiological measurements occur infrequently, such as during annual checkups, limiting the view of the user's health. Moreover, conventional devices may compute daily averages that do not capture fluctuations over shorter time frames. There is a need to continuously monitor and utilize respiration rate to predict and detect medical conditions such as sleep deprivation, sleep apnea, asthma, and lung-related conditions.
Claims Coverage
The patent includes one independent claim directed to a wearable ring device and its configuration for detecting medical conditions using respiration rate data, supported by several dependent claims further detailing the features.
Wearable ring device for continuous physiological data collection and condition risk assessment
A wearable ring device configured to be worn on a user's finger, comprising a housing with optical components that obtain continuous physiological data, wherein one or more processors determine respiration rate values over a time interval, determine respiration rate parameters associated with change in respiration rate, and determine condition risk metrics for sleep deprivation based on these parameters, and transmit signals to display these metrics on a user device GUI.
Fitting a line to respiration rate values for parameter determination
The device fits a line to the respiration rate values over the time interval, determines a slope of the line, uses the slope as a respiration rate parameter, and bases condition risk metrics at least in part on this slope.
Condition risk metric determination based on slope comparison
Determines different condition risk metrics associated with sleep deprivation depending on whether the slope is greater or less than a threshold slope value, thereby differentiating risk probabilities.
Association of risk metrics with relative probability of sleep deprivation
The condition risk metric corresponding to a slope greater than the threshold is associated with a higher relative probability of sleep deprivation compared to the metric associated with a slope less than the threshold.
Incorporation of additional physiological parameters
Determines one or more additional parameters of the physiological data collected during the time interval, and bases the condition risk metrics on both respiration rate values and these additional parameters.
Baseline respiration rate determination through earlier data
Obtains additional physiological data over a preceding time interval to determine baseline respiration rate data, and bases subsequent respiration rate values, parameters, and condition risk metrics on this baseline.
Sleep period classification and condition risk assessment
Determines sleep periods within the time interval, classifies each into awake, light, REM, or deep sleep periods, and bases condition risk metrics on the respiration rate parameters in conjunction with these classified sleep periods.
Graphical display of respiration rate values
Causes the graphical user interface of the user device to display a graph showing respiration rate values over the time interval.
Determination of sleep and readiness scores
Determines one or more scores for the user, including sleep score and readiness score, based at least in part on the respiration rate values and/or parameters.
Physiological data collected based on arterial blood flow
The wearable ring device collects physiological data from the user based on arterial blood flow in the finger, enhancing data quality.
The independent claim recites a wearable ring device configured with optical components and processors to continuously collect physiological data, determine respiration rates and related parameters, and evaluate condition risk metrics for sleep deprivation, while dependent claims elaborate features including baseline determination, sleep stage classification, slope-based risk assessment, and user interface presentation of detection results.
Stated Advantages
Continuous monitoring of respiration rate provides more comprehensive health insights compared to infrequent clinical measurements.
Using arterial blood flow measurement via a ring device yields stronger physiological signals and improved data quality compared to wrist-worn wearable devices.
Determining condition risk metrics from respiration rate parameters enables early detection and prediction of medical conditions such as sleep deprivation, sleep apnea, asthma, and lung damage.
Incorporating respiration rate with other physiological parameters and classified sleep stages improves the accuracy of condition risk assessment.
Displaying condition risk metrics and related graphs on a user device helps users better understand their health and make informed behavioral decisions.
Documented Applications
Continuous physiological monitoring via wearable ring devices to detect and predict medical conditions including sleep deprivation, sleep apnea, asthma, allergies, chronic obstructive pulmonary disease, and respiratory infections like COVID-19.
Using respiration rate parameters to adjust sleep and readiness scores for users.
Providing users with graphical user interfaces to observe respiration rate trends in relation to sleep stages and other physiological parameters.
Utilizing circadian and other biological rhythm adjustments to improve physiological data analysis and health monitoring.
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