US-12622649-B2 - Personal healthcare device

Abstract

A wearable personal healthcare device for measuring personal health is provided that is configured to detect a photoplethysmograph (PPG) wave generated by infra-red, green, or red lights emitted from the device, the personal healthcare device. The device includes an outward facing face, a lateral side, and a bottom side, wherein the bottom side faces a user's skin, a plurality of electrical contact sensors, wherein a first of the plurality of sensors is located on one of the top face, lateral side, and bottom side, and a second of the plurality of sensors is located on one of the top face and lateral side of the personal health care device. The first and second sensors are configured to complete a circuit therebetween when a user contacts the first sensor with a first surface of the user's skin and contacts the second sensor with the first or a second surface of the user's skin. The device further includes a network communication module configured to transmit the detected PPG wave to a server, wherein the server processes the PPG wave and infers therefrom biometric data based on machine learned correlations generated from a training set of PPG waves and biometric data, a processor configured to generate the biometric data, and an interface screen comprising the biometric data.

Inventors

• Fabio Galdi

Assignees

• Fabio Galdi

Dates

Publication Date

20260512

Application Date

20211006

Claims (20)

1. 1 . A method, in a data processing system comprising a processor and a memory, for measuring personal health, the method comprising: detecting a plurality of photoplethysmograph (PPG) waves by a personal healthcare device, the plurality of PPG waves are generated by infra-red, green, or red lights emitted from the personal healthcare device, wherein the personal health care device comprises: a bezel having a top bezel portion and a bottom bezel portion; a top outward facing face, a lateral side, and a bottom side, wherein the bottom side faces a user's wrist; and a plurality of electrical contact sensors, wherein a first of the plurality of sensors is located at the top bezel portion and a second of the plurality of sensors is located at the bottom bezel portion wherein the first and second sensors are configured to complete a circuit therebetween when a user contacts the first sensor with a first surface of the user's skin and contacts the second sensor with the first or a second surface of the user's skin; a lateral side sensor located within a recessed ridge on the lateral side of the personal healthcare device wherein the lateral side sensor detects an overlapping photoplethysmograph (PPG) wave, wherein the overlapping PPG wave overlaps at least one of the plurality of PPG waves; transmitting the detected plurality of PPG waves to a server, wherein the server processes the detected plurality of PPG waves and infers therefrom biometric data based on machine learned correlations generated from a training set of PPG waves and biometric data; receiving the biometric data from the server; and generating an interface screen comprising the biometric data.
2. 2 . The method of claim 1 , wherein the personal health care device further comprises: an inline sensor (IS) comprising a first Near Field Infrared (NIR) Light Emitting Diode (LED), a second NIR LED, and a photodiode with wavelength sensitivity range between about 900 nm to about 1700 nm±10%, the photodiode located on the IS between the first and second NIR LEDs and configured relative thereto to receive reflected light from the first and second NIR LEDs, and a first and second angular mirror, each configured to reflect light from either of the first and second NIR LEDs onto a user's skin and for the user's skin to reflect light back to the photodiode, wherein the personal healthcare device generates the detected PPG wave based on the light reflected off of the user's skin.
3. 3 . The method of claim 2 , wherein the first NIR LED has a first wavelength in the near infrared spectrum and the second NIR LED has a second wavelength in the near infrared spectrum.
4. 4 . The method of claim 1 , wherein a first intermediate detected PPG wave is generated from light reflected off of the user's skin from the first NIR LED and a second intermediate detected PPG wave is generated from light reflected off of the user's skin from the second NIR LED, and the detected PPG wave is generated from the combination of the first and second intermediate detected PPG waves.
5. 5 . The method of claim 1 , wherein the first NIR LED has a wavelength of about 1550 nm±10% and the second NIR LED has a wavelength of about 1300 nm±10%.
6. 6 . The method of claim 1 , wherein light from the first NIR LED is directed to the user's skin via the first angular mirror, and light from the second NIR LED is directed to the user's skin via the second angular mirror, such that the light from the first NIR LED is reflected back off of blood glucose molecules to the photodiode at a first predetermined angle and light from the second NIR LED is reflected back off of blood glucose molecules to the photodiode at a second predetermined angle.
7. 7 . The method of claim 6 , wherein the first predetermined angle is about 45 degrees and the second predetermined angle is about 90 degrees.
8. 8 . The method of claim 1 wherein the lateral side sensor is recessed within the recessed ridge extending outward from the lateral side of the device, wherein the recessed ridge is configured to form a seal with the first or second surface of the user's skin when the user contacts the at least one of the plurality of sensors with the first or second surface of the user's skin.
9. 9 . The wearable device of claim 2 wherein the plurality of sensors are covered with a glass configured to direct light from either of the first and second NIR LEDs onto a user's skin and receive reflected light from the first and second NIR LEDs at the photodiode.
10. 10 . The method of claim 2 , wherein the inline sensor further comprises a PCB, and the first and second NIR LEDs, photodiode, and first and second angular mirrors are each attached to the PCB.
11. 11 . The method of claim 10 , wherein the first and second NIR LEDs are configured to emit light in a direction parallel to the PCB, and wherein the mirrors reflect the emitted light at an oblique angle relative to the PCB.
12. 12 . The method of claim 1 , wherein the biometric data comprises blood glucose levels.
13. 13 . The method of claim 1 , wherein the server processes the PPG wave and infers therefrom biometric statistics and wherein the biometric statistics comprise at least one of overall health, changes in health, mood, sleep quality, fatigue, and stress.
14. 14 . The method of claim 1 , wherein the machine learned correlations are based on PPG character vectors including a Kaiser-Teager power energy value, a heart rate value, and a spectral entropy value.
15. 15 . A wearable device for measuring personal health configured to detect a plurality of photoplethysmograph (PPG) waves photoplethysmograph (PPG) wave generated by infra-red, green, or red lights emitted from the personal healthcare device, the device comprising: a bezel having a top bezel portion and a bottom bezel portion; a top outward facing face, a lateral side, and a bottom side, wherein the bottom side faces a user's skin; a plurality of electrical contact sensors, wherein a first of the plurality of sensors is located at the top bezel portion and a second of the plurality of sensors is located at the bottom bezel portion wherein the first and second sensors are configured to complete a circuit therebetween when a user contacts the first sensor with a first surface of the user's skin and contacts the second sensor with the first or a second surface of the user's skin; a lateral side sensor located within a recessed ridge on the lateral side of the personal healthcare device wherein the lateral side sensor detects an overlapping photoplethysmograph (PPG) wave, wherein the overlapping PPG wave overlaps at least one of the plurality of PPG waves; a network communication module configured to transmit the detected plurality of PPG waves to a server, wherein the server processes the detected plurality of PPG waves and infers therefrom biometric data based on machine learned correlations generated from a training set of PPG waves and biometric data; a processor configured to generate the biometric data; and an interface screen comprising the biometric data.
16. 16 . The wearable device of claim 15 , further comprising: an inline sensor (IS) comprising a first Near Field Infrared (NIR) Light Emitting Diode (LED), a second NIR LED, and a photodiode with wavelength sensitivity range between about 900 nm to 1700 nm±10%, the photodiode located on the IS between the first and second NIR LEDs and configured relative thereto to receive reflected light from the first and second NIR LEDs; and a first and second angular mirror, each configured to reflect light from either of the first and second NIR LEDs onto a user's skin and for the user's skin to reflect light back to the photodiode, wherein the personal healthcare device generates the detected PPG wave based on the light reflected off of the user's skin.
17. 17 . The wearable device of claim 15 , wherein the lateral side sensor is recessed within the recessed ridge extending outward from the lateral side of the device, wherein the recessed ridge is configured to form a seal with the first or second surface of the user's skin when the user contacts the at least one of the plurality of sensors with the first or second surface of the user's skin.
18. 18 . The wearable device of claim 16 , wherein the plurality of sensors are covered with a glass configured to direct light from either of the first and second NIR LEDs onto a user's skin and receive reflected light from the first and second NIR LEDs at the photodiode.
19. 19 . The wearable device of claim 15 wherein the server processes the PPG wave and infers therefrom biometric statistics and wherein the biometric statistics comprise at least one of overall health, changes in health, mood, sleep quality, fatigue, and stress.
20. 20 . The wearable device of claim 15 , wherein the machine learned correlations are based on PPG character vectors including a Kaiser-Teager power energy value, heart rate value, and spectral entropy value.

Description

RELATED APPLICATION This application claims the benefit of U.S. Provisional Patent Application No. 63/088,223, filed on Oct. 6, 2020, which is hereby incorporated herein by reference. BACKGROUND OF THE INVENTION The present application relates to wearable healthcare devices and more particularly devices that gather data and monitor a user's biometrics. One of the challenges when using photoplethysmogram (PPG) technology in smartwatches and other wearable devices is pulse signal detection difficulty because of scattering of reflected light due to the device location. In the case of smartwatches and other wristband devices, Light Emitting Diodes (LEDs) and Photodiodes (PDs) are typically positioned on the wrist where a relatively high presence of bones and low levels of capillaries and veins, and an inadequate skin-sensor seal, cause poor reflection of the various wavelengths of light used in pulse signal detection. This is particularly problematic when high frequency wavelength light is used for pulse signal detection, and it results in weak DC and AC signals, yielding high signal-to-noise ratios and poor quality PPG signals. In medical and clinical applications, this problem of detecting the pulse signal is addressed with the use of a fingertip sensor. The fingertip is an area of the body where there is almost no bone, a wide presence of capillaries, and the opportunity for light to pass directly from the LED through the skin to the PD and where the skin can form a better seal with the LED and PD, resulting in more uniform light scattering effects and more accurate and efficient detection of the pulse wave. A fingertip oximeter is an example of such a device. Typically, a cabled or wireless clip is attached to the finger and LEDs emit Infrared (IR) and Near Infrared (NIR) light with wavelengths between 640 nm and 940 nm. The reflected light is used to accurately detect the pulse wave, create the PPG signal from which the RR-interval (the interval between two successive heartbeats) and other important parameters can be deduced, such as Blood Oxygenation (SpO2), Heart Rate (HR), Heart Rate Variability (HRV) and Blood Pressure (BP). When other higher frequency NIR wavelengths are used, it is also possible to estimate hemoglobin and glucose levels. However, it is difficult to consider that such an attachable fingertip device is a wearable device because of its physical configuration and the need to re-attach it to the body each and every time a measurement is required. In addition, if frequent or even continuous measurements are required, then the current devices restrict the wearer's movements and it is not convenient in terms of daily or continue usage. PPG technology is well established for fingertip use (where it can capture high quality readings because there is no bone and the fingertip skin forms a good seal with the sensor). In addition to traditional devices such as pulse oximeters that capture PPG from fingertip insertion, there are standalone devices that also capture high quality PPG signals from the fingertip, such as smartphones. However, PPG technology does not appear to have been incorporated on the side of a wrist worn device. Though side sensors on smart watches exist, no devices with IR and NIR sensors incorporated into the side of a wearable device to allow the wearer to place their fingertip on the side sensor to obtain high quality PPG readings exists. Accordingly, there is a need for a wearable device that is not so limited. Additionally, although wearable biometric monitors are available, most have limited functionality. For instance, most are limited to measuring steps taken/distance covered and heart rate. Those interested in a more in-depth profile and understanding of their health must do so with an inconvenient trip to their health care professional which often includes an invasive procedure. Moreover, the reliability of data generated when the device is moving, is questionable and PPG signals can create measurement artifacts. Accordingly, there is a need for a wearable device with multiple sensors, detects movement and that continuously or on demand, provides high quality PPG data conveniently and without the need for invasive procedures. 1. Summary of the Invention The present application provides method(s), wearable device(s), and computer readable media for measuring personal health. According to one embodiment, the method includes detecting a photoplethysmograph (PPG) signal by a sensor, the PPG signals are generated by infra-red, green and/or red lights emitted from one or more emitters of a personal healthcare device, transmitting the PPG signal data to a server, the server processing the PPG signal data to infer biometric statistics based on machine learned correlations generated from a training set of PPG signals and biometric data, receiving the biometric statistics from the server, and generating display data based on the biometric statistics. The biometric statistics may