Cardiovascular health metric determination from wearable-based physiological data
Inventors
Assignees
Publication Number
US-12343125-B2
Publication Date
2025-07-01
Expiration Date
2042-08-08
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Abstract
Methods, systems, and devices for cardiovascular health metric determination are described. A system may be configured to receive a photoplethysmogram (PPG) signal representative of a pulse waveform for a user. The pulse waveform may include a first local maximum, a downward slope following the first local maximum, and a curved feature representative of a transition from a systolic phase to a diastolic phase of a cardiac cycle. Additionally, the system may extract one or more morphological features from the pulse waveform and compare the one or more morphological features with one or more features from a plurality of baseline PPG signal morphologies associated with a plurality of chronological ages. The system may determine a cardiovascular health metric that indicates a cardiovascular health of the user relative to a chronological age of the user and cause a graphical user interface to display an indication of the cardiovascular health metric.
Core Innovation
The invention relates to methods, systems, and devices for determining a cardiovascular health metric from physiological data collected by wearable devices. This includes receiving a photoplethysmogram (PPG) signal representative of a pulse waveform comprising a first local maximum, a downward slope following the first local maximum, and a curved feature representing a transition from a systolic phase to a diastolic phase of a cardiac cycle. One or more morphological features are extracted from this waveform and then compared with baseline PPG signal morphologies associated with multiple chronological ages. This comparison is used to determine a cardiovascular health metric indicating the cardiovascular health of the user relative to their chronological age. The system can display this metric to the user via a graphical user interface.
The problem addressed is that existing wearable devices and health measurement techniques lack robust capabilities to determine a cardiovascular health metric accurately and comprehensively. Conventional devices either only gather data at a single instance or lack integration of behavioral, physiological, or contextual inputs to provide a comprehensive assessment of cardiovascular health. This limitation prevents users from obtaining actionable insights into their cardiovascular age, heart health, arterial stiffness, and risk for cardiovascular disease using wearable technology.
The invention leverages continuous physiological data collection by wearable devices, particularly from ring-type wearables that collect PPG signals based on arterial blood flow at the user's finger. By analyzing morphological features of the pulse waveform obtained from PPG signals over a plurality of days and comparing them to baseline PPG morphologies from different age groups, the system personalizes the cardiovascular health metric relative to a user's chronological age. This personalized metric enables providing recommendations and alerts to users regarding cardiovascular health status, potential risks, and lifestyle adjustments.
Claims Coverage
The patent includes one independent claim and several dependent claims that describe features related to the method and apparatus for determining a cardiovascular health metric from wearable device data. The main inventive features extracted address the specific morphological feature extraction from the pulse waveform, comparison to baseline morphologies, determination of the health metric relative to age, and display of the metric.
Extraction of morphological features from pulse waveform
Receiving a PPG signal representative of a pulse waveform comprising a first local maximum, a downward slope following the first local maximum, and a curved feature indicative of the transition from systolic to diastolic phase, and extracting morphological features related to the position of the first local maximum, value of the downward slope, and degree of the curved feature.
Comparison with baseline PPG signal morphologies associated with chronological ages
Comparing the extracted morphological features with baseline morphological features of baseline pulse waveforms, each associated with a different chronological age, and identifying the baseline pulse waveform that matches the extracted features.
Determination of cardiovascular health metric relative to user's chronological age
Determining a cardiovascular health metric based on the difference between the user’s chronological age and the chronological age associated with the matched baseline pulse waveform.
Graphical user interface display of cardiovascular health metric
Causing a GUI to display an indication of the cardiovascular health metric determined.
Use of derivatives of the pulse waveform for feature extraction
Computing the first derivative, second derivative, or both of the pulse waveform and identifying local maxima or minima in these derivatives as morphological features.
Adjustment of cardiovascular health metric based on additional health data
Receiving data related to the user's health record, physiological data, or both, and adjusting the cardiovascular health metric accordingly before display.
Utilization of machine learning classifier for cardiovascular health metric determination
Inputting the PPG signal into a machine learning classifier to determine the cardiovascular health metric.
The claims collectively cover the innovative extraction of specific morphological features from PPG pulse waveforms, comparison with age-associated baseline waveforms, determination of a cardiovascular health metric relative to a user's age, and graphical presentation of this metric. The claims also include derivative-based feature extraction, health data-based adjustments, and use of machine learning classifiers to enhance metric determination.
Stated Advantages
Provides a robust technique to determine cardiovascular health metrics based on wearable-collected physiological data, overcoming deficiencies of typical devices.
Enables personalized cardiovascular health assessment relative to chronological age, offering actionable insights to users.
Utilizes continuous data collection from wearable devices, such as rings that access arterial blood flow, to provide stronger signals and more accurate morphological features.
Supports early warnings and behavioral recommendations to improve cardiovascular health and potentially reduce risks for cardiovascular diseases.
Improves user experience by integrating data processing with graphical user interface outputs and personalized messaging.
Documented Applications
Use in wearable devices, particularly ring-type devices, to continuously collect physiological data like PPG signals, temperature, heart rate, and respiratory rate.
Determining cardiovascular health metrics for users to understand their cardiovascular age relative to chronological age.
Displaying cardiovascular health metrics and related recommendations to users via user device graphical user interfaces.
Providing monitoring for clinicians, caregivers, or other associated users with relevant cardiovascular health information.
Enabling personalized health and lifestyle recommendations based on cardiovascular health status to reduce risks of heart diseases.
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