Wearable LED Sensor Device Configured to Identify a Wearer's Pulse

A wearable sensor device can include at least one LED and a light sensor for generating a photoplethysmogram (“PPG”) from light emitted by the at least one LED. The wearable sensor device can also include a processing unit that is configured to process the PPG to produce a highly reliable representation of the wearer's pulse.

BACKGROUND

A wearable sensor device is a device worn by a user that is configured to monitor an action or characteristic of the user. For example, a wearable sensor device may include an accelerometer for detecting a user's movement and/or a biometric sensor for measuring the user's pulse rate. Many wearable sensor devices have been created that can track a wearer's pulse. However, such devices are typically limited to detecting the pulse rate and provide very little additional useful information. Although some devices have been produced for generating further details beyond pulse rate, the nature of wearable sensor devices make it difficult to generate reliable information.

BRIEF SUMMARY

The present invention extends to wearable sensor devices that are configured to process a photoplethysmogram (PPG) and other pulse and heartbeat information to produce a highly reliable representation of the wearer's pulse. This processed PPG data (or “beat data”) can then be further analyzed to detect many different characteristics of the wearer's pulse which may represent that the wearer has a particular condition (e.g., an arrhythmia) or that the wearer is in a particular state (e.g., REM sleep).

In one embodiment, the present invention is implemented as a wearable sensor device that includes a housing configured to allow the wearable sensor device to be worn on a portion of the body, and a circuit that includes a first LED secured to the housing in a manner that causes the first LED to face the portion of the body when the wearable sensor device is worn; a light sensor secured to the housing, the light sensor being positioned to receive light that is transmitted from the first LED and reflected from or transmitted through the portion of the body, the light sensor being configured to generate a PPG representing the amount of light that is received by the light sensor over time; a processing unit configured to receive the PPG and to process the PPG, the processing of the PPG including: identifying peaks in the PPG; identifying valleys in the PPG; using the valleys to generate a base of the PPG; and subtracting the base from the PPG to yield beat data; and a storage for storing the beat data.

In another embodiment, the present invention is implemented as a method, performed by a wearable sensor device that includes at least one LED and at least one light sensor that generates a photoplethysmogram (“PPG”) from light emitted from one or more of the at least one LED, for generating beat data from the PPG. The PPG is received at a processing unit of the wearable sensor device. Peaks in the PPG are identified. Valleys in the PPG are also identified. The valleys are used to generate a base of the PPG. The base is subtracted from the PPG to yield the beat data. The beat data is then stored in a storage of the wearable sensor device.

In another embodiment, the acquired heartbeat information is used to derive the left ventricle ejection time (LVET), or to perform differential diagnosis of heart disease by distinguishing between conditions such as hypertrophy, cardio myopathy, aortic stenosis, hypertension, arrhythmia or low perfusion.

By using the derived measurements of cardiopulmonary health, sleep quality and surrogate measures of functional performance, physical capacity can be determined when compared to the other measurements taken at various physical activity levels.

This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description.

DETAILED DESCRIPTION

FIG. 1illustrates an example of a bracelet100that can be configured to implement embodiments of the present invention. Although a bracelet configured to be worn around the wrist will be used to describe the present invention, it is noted that other types of wearable devices that can be worn on the wrist or other parts of the body can also be configured for use with or as embodiments of the present invention.

Bracelet100includes a red LED101aand an infrared (IR) LED101bthat are exposed on an inner surface of bracelet100. Accordingly, when bracelet100is worn by a wearer, red LED101aand IR LED101bwill emit red light and infrared waves (collectively referred to as “light”) onto the wearer's skin. The use of two separate LEDs is only an example, and a wearable sensor device configured in accordance with embodiments of the present invention may equally include only a single LED or light source.

Bracelet100also includes a light sensor102that is exposed on the inner surface of bracelet100. Light sensor102is positioned adjacent LEDs101a,101bso as to be able to capture light (i.e., both red light and infrared waves) that is emitted by LEDs101a,101band reflected from the wearer's body. Alternatively, light sensor102could be positioned opposite LEDs101a,101bso as to detect light that is transmitted through the wearer's wrist. Accordingly, the present invention extends to wearable sensor devices that include one or more LEDs and one or more light sensors for sensing light that is either transmitted through or reflected by the wearer's skin. Light sensor102outputs a PPG representing the intensity of light that it receives over time. A PPG can be output for each of LEDs101a,101b.

FIG. 2illustrates a block diagram of a circuit200that can be employed within bracelet100in accordance with one or more embodiments of the present invention. Circuit200includes LEDs101a,101b,light sensor102, processing unit201, and storage202. The PPG(s) that is/are output from light sensor102can be input to processing unit201to perform a number of processing steps which convert the PPG into a more useful form, i.e., into “beat data.” The beat data can then be stored for subsequent analysis as will be further described below.

FIG. 3Aillustrates a graph of an example PPG300that can be generated by light sensor102when bracelet100is worn. As shown, PPG300includes a number of pulses that each represents the occurrence of a heartbeat. However, these pulses include a significant amount of variability such as, for example, in their vertical positioning and overall shape. As was discussed in the background, this variability can be caused by a number of factors including, for example, the breathing pattern (which primarily causes the vertical movement of the PPG) or movement of the wearer. This variability in the PPG can make it difficult to extract useful information from the PPG.

In accordance with embodiments of the present invention, processing unit201can be configured to convert the PPG into beat data to facilitate the extraction of more useful information from the PPG. This conversion process may encompass a number of steps including: (1) identifying peaks in the PPG; (2) identifying valleys in the PPG; (3) validating the peaks and valleys; (4) generating a base from the valleys; (5) generating a hat from the peaks; and (6) generating the beat data.

To identify peaks in the PPG, wavelets may be employed. Wavelets are not sensitive to variations in the baseline of a signal, which variations are common in the PPG as shown inFIG. 3A. Wavelets are also capable of functioning on short-duration signals allowing beat data to be generated quickly when bracelet100is initially employed. After the peaks have been identified, the minimum value in the PPG between each peak can be identified as a valley. Accordingly, the result of this initial processing is an array of peak values and an array of valley values corresponding to a particular segment of the PPG.

In some embodiments, the peaks and valleys can be validated prior to commencing further processing. This validation can be performed using a model of the human pulse. For example, if the difference between two adjacent peaks or valleys exceeds what would be reasonable in view of the model of the human pulse, the corresponding portion of the PPG may be excluded from further processing. In this way, PPG data that is unreliable is prevented from influencing later analysis of the beat data.

The arrays of peak and valley values can then be used in a three-degree polynomial to generate a hat and base respectively for the PPG.FIG. 3Billustrates an example of a hat301(dashed line) that was generated for PPG300. As shown, hat301generally extends from peak to peak in accordance with the three-degree polynomial.FIG. 3Cillustrates an example of base302(dotted line) that was generated for PPG300. Similar to hat301, base302extends from valley to valley in accordance with the three-degree polynomial.

As stated above, the base generally represents the effects that breathing has on the PPG. More particularly, breathing directly alters blood volume which in turn alters the amount of light that is reflected by or transmitted through the blood. Therefore, the effects of breathing on the PPG must be removed in order to properly extract some heartbeat characteristics from the PPG. To accomplish this, the present invention subtracts the base from the PPG yielding a reliable representation of the wearer's pulse (or beat data310) as shown inFIG. 3D.

In some embodiments, in addition to subtracting base302from PPG300to yield beat data310, Kalman smoothing can be performed on beat data310and then each beat in beat data310can be linearly de-trended to produce a more accurate beat-shaped bellow such as is shown inFIG. 3Efor one beat320of beat data310.

Once beat data310has been generated, the values for each beat in beat data310(“individual beats”) can be stored (in storage202). Each individual beat can then be evaluated to identify a number of beat model parameters for the individual beat including, for example, the foot of the beat, left ventricular ejection time onset, systolic ramp up, systolic peak, systolic ramp down, left ventricular ejection time offset, dicrotic notch, diastolic ramp up, diastolic peak, diastolic ramp down, etc. Although it is possible to estimate such parameters using PPG300, the variability in PPG300makes such estimations difficult and inaccurate.

Accordingly, by generating beat data310as described above, the present invention greatly increases the accuracy of detecting such parameters. Any individual beat that appears to be invalid (i.e., any beat that does not fit within reasonable parameters of what a beat should look like) can be discarded to eliminate any potential that the invalid beat may degrade subsequent calculations of cardiovascular performance.

Once the beat data is generated, or more specifically, once the individual beats including their beat model parameters have been identified, the present invention can employ the beat data to identify different characteristics or states of the wearer. For example, the beat data can be evaluated to identify one or more patterns that are indicative of an arrhythmia Similarly, the beat data can be evaluated to identify when the wearer transitions between different stages of sleep. In another embodiment, the acquired heartbeat information is used to derive the left ventricle ejection time (LVET), or to perform differential diagnosis of heart disease by distinguishing between conditions such as hypertrophy, cardio myopathy, aortic stenosis, hypertension, arrhythmia or low perfusion.

By using the derived measurements of cardiopulmonary health, sleep quality and surrogate measures of functional performance, physical capacity can be determined when compared to the other measurements taken at various physical activity levels.

Although it is possible to perform such evaluations using the PPG directly, the evaluations are inaccurate and unreliable due to the high degree of variations that exist in the PPG that are not directly caused by the heart. Accordingly, the above described process of converting the PPG into beat data yields a highly reliable and accurate representation of the heart's performance This in turn enables a great number of evaluations to be easily and accurately performed using a portable and relatively simple wearable sensor device.

In addition to producing beat data310as described above, processing unit210can also be configured to employ hat301and base302to accurately detect other parameters such as oxygen saturation and breathing. As indicated above, in embodiments that include both red LED101aand IR LED101b,processing unit210can be configured to generate a hat and base for the PPG for each LED. These hats and bases will be referred to hereafter as hat basered, hatir, and baseir. Processing unit210can also be configured to derive the oxygen saturation using these hats and bases in accordance with the following formula:

To detect breathing, processing unit210can be configured to analyze the base and hat (e.g., using Bayesian frequency detection) to identify a recurring pattern. This recurring pattern is a repeating peak indicative of the occurrence of either an inhale or an exhale. From this processing, the wearer's respiration rate can be detected.

From the base and hat alone, it cannot be definitively determined when an inhale or exhale occurs since both will be represented as peaks in the hat and base. To address this, processing unit210can be configured to employ additional parameters so that peaks in the base and hat can be accurately identified as representing either an inhale or an exhale. For example, when an inhale occurs, a measurement of the beats per minute should be maximized while the pulse pressure value should be minimized Conversely, when an exhale occurs, the measurement of the beats per minute should be minimized while the pulse pressure value should be maximized

Accordingly, processing unit210can be configured to derive beats per minute and pulse pressure values from beat data310and use such values to identify whether peaks in the base and hat represent an inhale or an exhale.FIGS. 4A and 4Brepresent how this can be done.FIG. 4Ais a graph of an example PPG401along with a corresponding hat402and base403which can be generated for PPG401as described above. The vertical black lines represent the peaks within the base and hat.FIG. 4Billustrates a graph a beats per minute404and pulse pressure405which were derived from PPG401. The location of a peak in beats per minute404and the location of a valley in pulse pressure405(both of which are represented by stars inFIG. 4B) can be used to identify that a peak at the corresponding location inFIG. 4Arepresents the occurrence of an inhale. Similarly, a peak in pulse pressure405and a valley in beats per minute404(both of which are also represented by stars inFIG. 4B) can be used to identify that a peak at the corresponding location inFIG. 4Arepresents the occurrence of an exhale.

FIG. 4Aincludes black vertical lines indicating where peaks occur in hat402and base403. Using beats per minute404and pulse pressure405, these peaks can be identified as representing an inhale or exhale. For example, the peaks identified by lines410can be categorized as representing inhales, while the peaks identified by lines411can be categorized as representing exhales.