BACKGROUND OF THE INVENTION

Field of the Invention

This invention is in the field of breathing rate measurement, respiratory status measurement, oscillometric measurement methods and technology.

Description of the Related Art

Respiration rate (RR), also called “breathing rate”, typically expressed in breaths per minute, is an essential but underused vital sign. Jonsdottir et al., in “Nursing documentation prior to emergency admissions to the intensive care unit”, Nursing in Critical Care—June2011” reports that although respiratory failures are the most common cause of emergency admissions to ICU, nonetheless respiratory rate is one of the least documented vital signs. This problem is due in part to lack of appropriate breathing rate monitoring equipment.

With the recent worldwide COVID-19 pandemic, adequate methods of assessing respiratory system status have become increasingly important. For example, Xu et al., inRisk factors for2019novel coronavirus disease(COVID-19)patients progressing to critical illness: a systematic review and meta-analysis, AGING2020, Vol. 12, No. 12” reports that elderly male patients with a high respiratory rate (along with high body mass index, and other risk factors) are more likely to develop severe COVID-19 infections.

Although a significant amount of prior art exists covering various automated systems and methods for determining respiration rate, to date, as evidenced by the Jonsdottir study, such methods are still lacking. By contrast, consider oscillometric blood pressure monitors, which are now widely available on a low-cost basis. Oscillometric blood pressure monitors are widely available on a non-prescription basis and are in widespread use for home blood pressure monitoring.

Respiration does have an impact on blood pressure measurements. However, to date, efforts to harness oscillometric techniques for respiration rate monitoring purposes have generally been ineffective. Typically, data from multiple physiological sensors (pulse oximeters, multiple cuff devices, non-oscillometric sensors, ECG sensors) has been needed for such devices to function, and such proposals have generally not been met with commercial success. Thus, further advances in this area would be of significant medical importance.

Previous art on oscillometric monitors equipped with additional physiological sensors, such as ECG and pulse oximetry sensors, includes the work of Li, U.S. Pat. No. 10,022,053, the complete contents of which are incorporated herein by reference.

Other automated breathing sensor art includes Dekker, US 2003/0163054; Callahan U.S. Pat. No. 5,094,244; Aung U.S. Pat. No. 5,682,898; Knoll U.S. Pat. No. 10,349,849; Kawamoto 2017/027358, the complete contents of these are incorporated herein by reference.

Academic work in this area includes the work of Chen and Chen, “A method for extracting respiratory frequency during blood pressure measurement, from oscillometric cuff pressure pulses and Korotkoff sounds recorded during the measurement”2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society(EMBC)”; other academic work includes the work of Gui et. al., “Pulse interval modulation-based method to extract the respiratory rate from oscillometric cuff pressure waveform during blood pressure measurement” Computing in Cardiology(CinC) September 2017—ieeexplore.ieee.org.

Correlation with pain: Other workers (Bendall J C, et. al. “Prehospital vital signs can predict pain severity: analysis using ordinal logistic regression.” Eur J Emerg. Med 2011 December; 18(6):334-339) have shown that elevated respiratory rates, heart rate, and systolic pressure are associated with severe pain.

Previous work on computerized methods of using acoustic signals for analyzing coughs and other audible signals of respiratory interruptions and/or distress includes MacAuslan, U.S. Pat. Nos. 9,526,458 and 10,485,449, the entire contents of which are incorporated herein by reference.

BRIEF SUMMARY OF THE INVENTION

Breathing causes relatively small changes in an individual's pulse waves, and oscillometric blood pressure monitoring devices can monitor such pulses. However, these breathing rate induced changes and other such respiratory status changes are relatively small, and are frequently confounded by noise and artifacts in the oscillometric data. The present invention was inspired, in part, by the insight that if a sufficient number of methods to remove artifacts from oscillometric blood pressure monitor data could be found, then it might be possible to employ more aggressive analytical methods to automatically distinguish the subtle breathing rate signals from the oscillometric pulse rate data.

The present invention was also inspired, in part, on the insight that if the faint breathing signal could be distinguished in different ways (e.g., through their impact on multiple characteristics or dimensions on the dominant pulse wave signal), then each different dimension could be used to verify the accuracy of the other dimension. In other words, if the impact of the patient's or user's respiratory rate could be found to impact multiple observable parameters of the underlying pulse rate signal, then the accuracy of the method would be improved. That is, when the different methods were in agreement, the breathing rate results would be more likely to be accurate. When the different rates were not in agreement, the system could report a warning or an error.

In some embodiments, the invention may be a system, device, and method for automatically determining a breathing rate of a patient. This method is based on analyzing pulse waveforms obtained from an oscillometric device mounted on the patient's limb (often on the patient's wrist). This oscillometric device will often comprise a processor (e.g., microprocessor), air pressure generating and release devices, a pressure sensor, and a built-in inflatable cuff configured to go around the patient's limb. The device will often further comprise a display and/or a wireless transceiver (such as a Bluetooth Low Energy transceiver) for displaying the results. The device may optionally also contain a tri-axial (e.g. three-axis) accelerometer. In some embodiments, a wrist-mounted oscillometric device is preferred.

In addition to operating as a standard oscillometric blood pressure monitor, the device also is configured to analyze the pulse waveforms and to determine artifact-free regions of these pulse waveforms. Here various methods may be used, and the artifact-free or at least artifact-reduced areas of the pulse waveforms may be termed edited pulse waveforms.

To obtain multiple dimensions of breathing rate data, the system makes use of the experimental observation that breathing impacts both the amplitude of the individual pulse waves, as well as the time duration between successive pulse waves (e.g., frequency). These show up as changes in the amplitude of the envelope of the pulse wave signals “AM envelope signals” as well as changes in the frequency of the pulses “FM between-pulse-time signals.” The invention determines these AM envelope signals and FM between-pulse-time signals and then determines their AM envelope primary harmonics and FM between-pulse-time main harmonics.

The invention then checks to be sure that the AM envelope primary (or main) harmonics and FM between-pulse-time main harmonic are consistent, and if not, may return a warning or error code. However, if the two results meet consistency criteria, the system will then calculate a weighted function of the AM envelope primary harmonics and FM between-pulse-time main harmonics. These results will then be output (or stored in memory) as the patient's breathing rate (respiratory rate) or respiratory status. Alternatively, both AM envelope main harmonics and FM between-pulse-time main harmonics may be used.

Normal breathing is occasionally interrupted by coughing, sneezing, wheezing, or other respiratory interruptions. In some embodiments, as will be discussed, the accuracy of the system may be further improved by utilizing one or microphones to pick up audio data indicative of such respiratory interruptions, and correct the breathing data accordingly. The system may further record when such interruptions were detected, as desired.

In some embodiments, as will be discussed, the pulse wave data may additionally be analyzed to obtain information pertaining to the depth of breathing (e.g., the amount of air being inhaled or exhaled.).

