NON-INVASIVE DETERMINATION OF AIRWAY RESISTANCE

Abstract

An apparatus and method for non-invasive determination of airway resistance for the detection of pulmonary airway disease includes providing an apparatus and method wherein changes in a pulsatile blood pressure waveform are detected by PhotoPlethysmoGram (PPG) or Ballistography (BSG) and are automatically determined to reflect decreases in airflow and changes in airway resistance.

Claims

1. A method (100) of non-invasively determining a pulmonary airway resistance in a person, comprising: detecting (110) a pulsatile blood pressure pulse of the person with a wearable device (7) worn by the person; based at least in part upon the pulsatile blood pressure pulse, determining (120) a number of parameters of the person including a pulsus paradoxus; determining (130) the pulmonary airway resistance in the person based at least in part upon at least a subset of the number of parameters; and generating (140) an output that is representative at least in part of the pulmonary airway resistance.

2. The method of claim 1, further comprising determining the pulsus paradoxus by comparing an amplitude of a systolic peak the pulsatile blood pressure pulse during an inspiratory phase of the person with another amplitude of another systolic peak the pulsatile blood pressure pulse during an expiratory phase of the person.

3. The method of claim 1 wherein the detecting of the pulsatile blood pressure pulse comprises detecting a pulsatile blood pressure waveform of the person, and wherein the determining of the number of parameters comprises determining the number of parameters based at least in part upon the pulsatile blood pressure waveform.

4. The method of claim 3, further comprising determining the pulsus paradoxus by comparing an area under a portion of the pulsatile blood pressure waveform during an inspiratory phase of the person with another area under another portion of the pulsatile blood pressure waveform during an expiratory phase of the person.

5. The method of claim wherein 4 the portion of the pulsatile blood pressure waveform comprises at least one of a systolic peak and a diastolic peak, and wherein the another portion of the pulsatile blood pressure waveform comprises at least one of another systolic peak and another diastolic peak.

6. The method of claim 3, further comprising: determining among the number of parameters at least one of a heart rate variability and a respiration rate variability; and determining the pulmonary airway resistance based at least in part upon the at least one of the heart rate variability and the respiration rate variability.

7. The method of claim 1, further comprising: measuring an activity level of the person; and differentiating an exertion due to respiratory resistance from another exertion due to the activity level in the determining of the pulmonary airway resistance.

8. The method of claim 7, further comprising: measuring as a contextual factor at least one of an altitude, an air temperature, an air density, and an air pollution level that is experienced by the person; and employing the contextual factor in the differentiating.

9. The method of claim 1, further comprising: calculating at least one of a trend over time of the pulmonary airway resistance and a comparison of the pulmonary airway resistance with a threshold value; and generating as at least a part of the output the at least one of the trend over time and the comparison.

10. The method of claim 9, further comprising: outputting as the at least a part of the output the trend over time; and indexing the trend over time with at least one of an activity level of the person over time and a recovery level of the person over time.

11. An apparatus (4) structured to non-invasively determine a pulmonary airway resistance in a person, comprising: a processor apparatus (8) comprising a processor (12) and a storage (16); an input apparatus (24) structured to provide input signals to the processor apparatus; an output apparatus (28) structured to receive output signals from the processor apparatus; a wearable device (7) having situated therein at least a portion of at least one of the processor apparatus, the input apparatus, and the output apparatus; and the storage having stored therein a number of instructions (20) which, when executed on the processor, cause the apparatus to perform a number of operations comprising: detecting (110) a pulsatile blood pressure pulse of the person with a wearable device worn by the person; based at least in part upon the pulsatile blood pressure pulse, determining (120) a number of parameters of the person including a pulsus paradoxus; determining (130) the pulmonary airway resistance in the person based at least in part upon at least a subset of the number of parameters; and generating (140) an output that is representative at least in part of the pulmonary airway resistance.

12. The apparatus of claim 11, wherein the operations further comprise determining the pulsus paradoxus by comparing an amplitude of a systolic peak the pulsatile blood pressure pulse during an inspiratory phase of the person with another amplitude of another systolic peak the pulsatile blood pressure pulse during an expiratory phase of the person.

13. The apparatus of claim 11 wherein the detecting of the pulsatile blood pressure pulse comprises detecting a pulsatile blood pressure waveform of the person, and wherein the determining of the number of parameters comprises determining the number of parameters based at least in part upon the pulsatile blood pressure waveform.

14. The apparatus of claim 13, wherein the operations further comprise determining the pulsus paradoxus by comparing an area under a portion of the pulsatile blood pressure waveform during an inspiratory phase of the person with another area under another portion of the pulsatile blood pressure waveform during an expiratory phase of the person.

15. The apparatus of claim wherein 14 the portion of the pulsatile blood pressure waveform comprises at least one of a systolic peak and a diastolic peak, and wherein the another portion of the pulsatile blood pressure waveform comprises at least one of another systolic peak and another diastolic peak.

16. The apparatus of claim 13, wherein the operations further comprise: determining among the number of parameters at least one of a heart rate variability and a respiration rate variability; and determining the pulmonary airway resistance based at least in part upon the at least one of the heart rate variability and the respiration rate variability.

17. The apparatus of claim 11, wherein the operations further comprise: measuring an activity level of the person; and differentiating an exertion due to respiratory resistance from another exertion due to the activity level in the determining of the pulmonary airway resistance.

18. The apparatus of claim 17, wherein the operations further comprise: measuring as a contextual factor at least one of an altitude, an air temperature, an air density, and an air pollution level that is experienced by the person; and employing the contextual factor in the differentiating.

19. The apparatus of claim 11, wherein the operations further comprise: calculating at least one of a trend over time of the pulmonary airway resistance and a comparison of the pulmonary airway resistance with a threshold value; and generating as at least a part of the output the at least one of the trend over time and the comparison.

20. The apparatus of claim 19, wherein the operations further comprise: outputting as the at least a part of the output the trend over time; and indexing the trend over time with at least one of an activity level of the person over time and a recovery level of the person over time.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0015] FIG. 1 is a schematic depiction of an improved apparatus in accordance with an embodiment of the disclosed and claimed concept;

[0016] FIG. 2 is a schematic depiction of a pulsatile blood pressure waveform of a person synchronized with a curve depicting corresponding respiratory phases of the person;

[0017] FIG. 3 is an depiction of a portion of the pulsatile blood pressure waveform of FIG. 2 and depicting an area under the pulsatile blood pressure waveform for each of two pulses;

[0018] FIG. 4 is an exemplary alternative depiction of a number of ways in which an area under the pulsatile blood pressure waveform pulse can be evaluated;

[0019] FIG. 5 is a schematic depiction of data flows using the apparatus of FIGS. 1; and

[0020] FIG. 6 is a flowchart depicting certain aspects of an improved method in accordance with the disclosed and claimed concept.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

[0021] As used herein, the singular form of “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise. As used herein, the statement that two or more parts or components are “coupled” shall mean that the parts are joined or operate together either directly or indirectly, i.e., through one or more intermediate parts or components, so long as a link occurs. As used herein, “directly coupled” means that two elements are directly in contact with each other. As used herein, “fixedly coupled” or “fixed” means that two components are coupled so as to move as one while maintaining a constant orientation relative to each other.

[0022] As used herein, the word “unitary” means a component is created as a single piece or unit. That is, a component that includes pieces that are created separately and then coupled together as a unit is not a “unitary” component or body. As employed herein, the statement that two or more parts or components “engage” one another shall mean that the parts exert a force against one another either directly or through one or more intermediate parts or components. As employed herein, the term “number” shall mean one or an integer greater than one (i.e., a plurality).

[0023] Directional phrases used herein, such as, for example and without limitation, top, bottom, left, right, upper, lower, front, back, and derivatives thereof, relate to the orientation of the elements shown in the drawings and are not limiting upon the claims unless expressly recited therein.

[0024] As will be set forth in greater detail elsewhere herein, the disclosed and claimed concept includes a sensing device that can detect an individual's pressure pulse waveform, which is indicative of cardio-pulmonary coupling and that can be associated with a person's airway resistance and respiratory airflow. Photoplethysmography (PPG) is an electro-optic technique of measuring a cardiovascular pulse wave found throughout the human body. This pulse wave is caused by the periodic pulsations in arterial blood volume and is measured by the consequential changing of optical absorption that is thereby induced. The measurement system consists of a light source, typically infrared, and a detector that is typically positioned in reflection or transmission mode. PPG is completely noninvasive, is found in pulse oximeters, and is the standard to measure a person's oxyhemoglobin (SpO2) levels, which is the arterial oxygen saturation in the blood.

[0025] Alternatively, another technology called Ballistography (BSG) also produces a graphical representation of the pulsatile blood pressure pulse. With BSG, the pulsatile blood pressure pulse is captured by optical sensors, i.e., cameras, radar, or thin film-like piezoelectric sensors that can be placed underneath a subject or woven into textile fabrics. Any approach for capturing cardiopulmonary forces that are generated by the body can be termed ballistography (BSG), and this includes forces due to body movement, breathing motion, and the mechanical action of the beating heart (which is itself also called ballistocardiography, BCG).

[0026] An improved apparatus 4 in accordance with the disclosed and claimed concept is depicted in a schematic fashion in FIG. 1. Apparatus 4 can be employed in performing an improved method 100 that is likewise in accordance with the disclosed and claimed concept and at least a portion of which is depicted in a schematic fashion in FIG. 6. Apparatus 4 can be characterized as including a processor apparatus 8 that can be said to include a processor 12 and a storage 16 that are connected with one another. Storage 16 has stored therein a number of routines 20 that are in the form of a non-transitory storage medium and that include instructions which, when executed on processor 12, cause apparatus 4 to perform certain operations such as are mentioned elsewhere herein.

[0027] Apparatus 4 can be said to further include an input apparatus 24 that provides input signals to processor 12 and an output apparatus 28 that receives output signals from processor 12. Input apparatus 24 can be said to include any of a variety of input components, and output apparatus 28 can likewise be said to include any of a variety of output components. For instance, if apparatus 4 includes a touchscreen, output apparatus 28 might be said to include a visual display of the touchscreen, and input apparatus 24 might be said to include a touch-sensitive overlay that is situated atop the visual display. Likewise, if apparatus 4 includes a wireless transceiver, input apparatus 24 might be said to include a receiver component of the wireless transceiver, and output apparatus 28 might be said to include a transmitter component of the wireless transceiver. In the depicted exemplary embodiment, input apparatus 24 includes a sensor 29 that includes one or both of a PPG sensor and a BSG sensor.

[0028] Apparatus 4 can be any of a wide variety of devices and might include, for instance, a wearable device such as a smart watch or might include a cellular telephone. For instance, any one or more portions of any one or more of processor apparatus 8, input apparatus 24, and output apparatus 28 can be embodied in a wearable device. In certain embodiments of the disclosed and claimed concept, apparatus 4 might be said to include both a wearable device and a cellular telephone that are in wireless communication with one another and with other devices, and it thus can be seen that the depiction of apparatus 4 in FIG. 1 is intended to be schematic in nature, and is understood that the overall apparatus 4 can include any one or more of a wide variety of electronic devices.

[0029] Apparatus 4 is depicted in FIG. 1 as being in wireless communication via a first wireless link 30 with an enterprise data system 32 that itself includes a number of routines 36 that are executable on a processor of enterprise data system 32 in order to cause enterprise data system 32 to perform certain operations. It thus can be understood that FIG. 1 is intended to schematically depicts a data processing system that includes any one or more of a wide variety of components that communicate with other components in order to achieve the goals that are noted herein. As such, it is expressly pointed out that numerous different types of devices can be in communication with other devices in order to perform the operations that are mentioned herein and that meet the goals that are described herein.

[0030] Another aspect of the disclosed and claimed concept is the extraction of a pressure pulse signal 2, such as is depicted in FIG. 2 along with a respiratory signal 3 that is synchronized therewith, and the determination of the various indices that will be associated with a person's airway resistance. It is noted that the pressure pulse signal to is in the exemplary form of a pulsatile blood pressure pulse waveform signal having a plurality of pulses that are representative of heartbeats of a person on whom is situated a wearable device 7 that embodies at least a portion of apparatus 4. Two such pulses are indicated in FIGS. 2 and 3 at the numerals 10 and 13.

[0031] It is conventional to use a comparison 6 of an amplitude of a systolic peak 10 that occurs during an inspiration phase 9 of respiration with an amplitude of another systolic peak 13 that occurs during an expiration phase 15 of respiration. While this is considered to the classical definition of pulsus paradoxus, other procedures described elsewhere herein can be utilized to determine the person's pulsus paradoxus. One such alternative method, such as is shown in FIG. 3, would be to compare an area 31 (or portion Al or A2 of the area 31, such as depicted in FIG. 4) under a pressure pulse waveform 10 that occurs during inspiration to an area 33 (or corresponding portion of the area) under the pressure pulse waveform 13 that occurs during expiration. Other alternative computation methodologies are also considered to be within the spirit of the instant disclosure.

[0032] The frequency and amplitude of the heart-related and cardiopulmonary coupling variations in arterial pressure 2 are modulated by respiration 3, as are shown in FIG. 2. The detection of a person's pulsatile blood pressure pulse has advanced significantly in recent years with new designs and miniaturization in opto-mechanics. Early versions used the photo-optic technology only to detect a person's oxygen saturation and heart rate, but advances in hardware and algorithm optimization have enabled the development of highly accurate biometrics in wearable devices, even during vigorous activity. Advanced analytics, machine learning and artificial intelligence have allowed for the extraction of additional indices from pulsatile blood pressure pulse waveform 2. It is the ability to derive these indices that is highly advantageous to the disclosed and claimed concept. Likewise, technology has allowed Ballistography which uses optical sensors (i.e., cameras), radar, or thin film-like piezo-electrical sensors, any one or more of which can be embodied in sensor 29, to now be a more reliable source for capturing the pulsatile blood pressure pulse waveform 2. These improvements in sensor technology advantageously allow for non-invasively capturing pulsatile blood pressure pulse waveform 2 continuously or intermittently and to seamlessly integrate into any wearable or proximity device, such as wearable device 7.

[0033] Heart rate variability (HRV) and respiratory rate variability (RRV) are two measurements from the PPG or BSG signal 2 from sensor 29, and both are known to decrease during sympathetic activation. Coupled with the pulsus paradoxus (PP) effect, the HRV and RRV data will further improve accuracy of detecting when respiratory resistance changes. The method for combining PP and either or both of HRV and RRV is of the following form where parameters a, b and c are calculated to maximize accuracy of a patient population or personalized to the patient:

Rresp=a*F(PP)+b*G(PP,xRV)+c*H(xRV)

where Rresp is the indictor of respiratory resistance, F( ), G( ) and H( ) are generalized functions, and xRV is either HRV or RRV or a function of both HRV or RRV.

[0034] Physiologic measurements are properly interpreted in context of the circumstances under which they were taken. In the case of PP, HRV, and RRV, physical exertion is known to have significant effect on these values. For example, exertion increases the demand for oxygen which will increase heart rate and respiratory rate. As these rates increase, the variation between the heartbeats and breathing decreases. However to differentiate changes in physiologic measurements that are due to an increase in respiratory resistance from other changes in physiologic measurements that are due to exertion (e.g., climbing a flight of stairs, walking up a hill, standing up, sitting down, etc.), the activity of the person needs to be measured.

[0035] Activity and thus exertion can be inferred using acceleration measurements taken from wearables, barometric pressure sensors from wearables to determine elevation changes, positioning data such as that from GPS and Wi-Fi networks, non-contact measurements such from video, ultrasound, infrared motion sensors, and the like, any one or more of which can be embodied in wearable device 7. Various “physiological challenge” contexts can either be coached (i.e., ask a user to perform a maneuver) or can be automatically detected from the person's daily life. In the case of coaching, the person can be coached toward a number of different outcomes, either based on the physical activity (i.e., perform a set number of repetitions or walk at a certain speed for a certain time) or until a predetermined physiological outcome is noted (i.e., walk until respiration rate increases by 20%).

[0036] Pulsatile blood pressure pulse waveform 2 can be analyzed in order to compare one or more indices of the pulsatile blood pressure pulse waveform 2 obtained from PPG or BSG via sensor 29 that occur during the inspiration phase with to one or more like indices of pulsatile blood pressure pulse waveform 2 that occurred during the expiratory phase, and a person's relative airway resistance or pulmonary airflow can be determined from such comparison. Alternatively, in another embodiment, a machine learning algorithm can be deployed to consider multiple indices of pulsatile blood pressure pulse waveform 2, such as heart rate, respiration rate, etc., in order to determine the person's airway resistance and monitor a person's pulmonary health status.

[0037] The extraction of the signal components from the pulsatile waveform indicative of the inspiration and or expiration phases of respiration that are induced due to effects of pulsus paradoxus can be derived from any number of methods, including a neural network, frequency domain transforms, amplitude modulation decomposition, or one of many other mathematical methodologies, all of which are considered to be within the scope of the disclosed and claimed concept. Regardless of how the respiratory phase 3 is derived, the pressure pulse indices are then synchronized to each of the respiratory phases to which it coincides and used for comparison, such as is depicted generally in FIG. 2.

[0038] Similar to calculating airway resistance, respiratory volumes can be estimated based on the respiratory volume dependence of the pulsatile blood pressure pulse waveform 2 due to the blood volume being affected by respiration. That is, there is an enhancement of venous return to the thorax and the heart during inspiration, and the opposite occurs during expiration. The intrathoracic pressure variations are caused by variations in total thoracic volume. The inspired volume of air to the lungs is linearly or exponentially related to this pressure and gives rise to the volume dependence in the venous return and therefore in the PPG or BSG signal from sensor 29.

[0039] Although not absolutely essential, calibration of the PPG or BSG signal from sensor 29 improves accuracy. An advantageous calibration methodology is one or more of linear, parabolic, or a hybrid of linear and parabolic resistance. This can be implemented as either multiple resistors of differing resistances or a variable resistance. While having the PPG or BSG monitored, the patient breathes on the resistors. By measuring the responsive PPG or the responsive BSG, as obtained from sensor 29, a table can be generated that relates back to the resistors used. For training machine learning algorithms, healthy and unhealthy volunteers can be measured using the resistances and protocol described here, by way of example.

[0040] Respiratory resistance can advantageously be trended over time for a given person or compared to individualized thresholds. Importantly, measures can be trended over the course of the day (time-specific context) and can be indexed with the total daily exertion (i.e., how much activity of what intensity has happened day-to-date) and recovery capability (i.e., how much recovery has a user had compared to activity level. Recovery can encapsulate both sleep quality (i.e., night before) and quiescent periods of rest during the day (Exertion/Rest context).

[0041] Additionally, respiratory resistance and physiological challenge metrics are advantageously indexed by weather and altitude (environmental context), inasmuch as air density, air temperature, and air pollutants can all impact measurement. Additionally, these the respiratory resistance metrics are advantageously indexed with the usage of 02 or other pharmacotherapy (pharma context, such as inhalers, etc.).

[0042] The various contextual measurements can be directly measured (i.e., total daytime exertion), inferred by local sensing (i.e., air density, temperature, etc.), provided by a connected device (i.e., sleep tracker, O.sub.2 delivery system, inhaler, etc.), and/or provided by a connection with a data service such as the Internet (i.e., pollen level, pollutant level, etc.).

[0043] As noted, FIG. 6 depicts in an exemplary flowchart certain aspects of an improved method 100 in accordance with the disclosed and claimed concept. Method 100 includes, as at 110, detecting a pulsatile blood pressure pulse of the person using a wearable device, such as wearable device 7, that is being worn by the person. A number of parameters of the person are determined, as at 120, and the number of parameters can include a pulsus paradoxus that is based at least in part upon the pulsatile blood pressure pulse. A pulmonary airway resistance of the person can then be determined, as at 130, based on the number of parameters. An output 40 (as in FIG. 5) can then be generated, as at 140, wherein the output is representative of the pulmonary airway resistance of the person. It is understood that the output 40 can be generated and output by the output apparatus 28 or can be otherwise output, and that all such modes of outputting the output 40 are within the scope of the disclosed and claimed concept.

[0044] In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word “comprising” or “including” does not exclude the presence of elements or steps other than those listed in a claim. In a device claim enumerating several means, several of these means may be embodied by one and the same item of hardware. The word “a” or “an” preceding an element does not exclude the presence of a plurality of such elements. In any device claim enumerating several means, several of these means may be embodied by one and the same item of hardware. The mere fact that certain elements are recited in mutually different dependent claims does not indicate that these elements cannot be used in combination.

[0045] Although the invention has been described in detail for the purpose of illustration based on what is currently considered to be the most practical and preferred embodiments, it is to be understood that such detail is solely for that purpose and that the invention is not limited to the disclosed embodiments, but, on the contrary, is intended to cover modifications and equivalent arrangements that are within the spirit and scope of the appended claims. For example, it is to be understood that the present invention contemplates that, to the extent possible, one or more features of any embodiment can be combined with one or more features of any other embodiment.