Wearable health monitors and methods of monitoring health
Inventors
Matichuk, Bruce • Duguay, Randy • Parker, William • Moore, Mathew • Antoniuk, Tim
Assignees
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Publication Number
US-11183303-B2
Publication Date
2021-11-23
Expiration Date
Abstract
Wearable technologies, such as wearable health monitors, and methods of use are provided. In some embodiments, the wearable technology can be worn at the wrist of an individual and can use an accelerometer, pulse oximeter, and electrocardiogram to measure heart rate, oxygen saturation, blood pressure, pulse wave velocity, and activity. This information can then be provided to the individual. The individual can alter their behaviors and relationships with their own health by using features such as notifications and auto-tagging to better understand their own stress, diet, sleep, and exercise levels over various time periods and subsequently make appropriate behavioral changes.
Core Innovation
The invention describes a wearable apparatus including a strap configured into a wristband or a smart wristwatch. A plurality of circuit boards are positioned at a middle portion of the strap, including a battery charging circuit on a first circuit board, a microcontroller on a second circuit board, and pulse oximeter components on a third circuit board, with flexible electrical wires coupling the plurality of circuit boards.
The pulse oximeter includes a pulse light emitting diode and a light sensor attached to the third circuit board, and emits a first type of light and a second type of light having wavelengths within respective ranges. The light sensor senses the first and second types of light, and the pulse oximeter compares a first reading and a second reading based on amounts of light absorbed by blood corresponding to oxygenated blood and deoxygenated blood to determine an amount of oxygen in the blood.
A second computing component communicatively coupled to the oxygen-determining computing component predicts a health metric of the user using machine learning with the amount of oxygen in the blood as input. In embodiments that include ECG sensing, a first ECG electrode and a second ECG electrode are attached to circuit boards so that ECG readings are produced, and the machine learning predicts the health metric using the amount of oxygen in the blood and an ECG reading as inputs.
Claims Coverage
The independent claims cover a wrist-worn apparatus that determines an amount of oxygen in blood from pulse oximetry and uses machine learning to predict a health metric, with ECG electrode integration in some independent claims. Across the independent claims, the core claim coverage includes oxygen computation from two light types and machine-learning prediction of a health metric, with additional inventive features relating to ECG integration and sensor/strap configuration.
Wrist-worn strap with embedded multi-board pulse oximeter for oxygen determination
A strap configured into a wristband or a smart wristwatch with multiple circuit boards, where the pulse oximeter comprises a pulse LED and a light sensor that emit and sense a first type of light and a second type of light having respective wavelength ranges.
Two light-type pulse oximeter computing by comparing oxygenated and deoxygenated absorption readings
A pulse oximeter computing component compares a first reading corresponding to an amount of the first type of light absorbed by oxygenated blood and a second reading corresponding to an amount of the second type of light absorbed by deoxygenated blood, and determines an amount of oxygen in the blood based on the comparison.
Machine-learning prediction of a health metric using oxygen amount as input
A second computing component predicts a health metric of the user using machine learning, using the amount of oxygen in the blood as input.
Integrated ECG electrodes with oxygen input machine-learning health prediction
A strap apparatus including a first ECG electrode and a second ECG electrode arranged to produce an ECG reading, where the second computing component predicts a health metric of the user using machine learning with the amount of oxygen in the blood and an ECG reading based on outputs of the ECG electrodes as inputs for the machine learning.
Taken together, the independent claims define a wrist-worn strap apparatus with an embedded pulse oximeter that determines oxygen in blood by comparing two light-type absorption readings, and a machine-learning component that predicts a health metric using the computed oxygen amount, and in ECG-integrated embodiments, an ECG reading as well.
Stated Advantages
Not explicitly described in patent.
Documented Applications
Not explicitly described in patent.
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