Patent Application
20240032816
Monitoring the respiratory state of a person is an important aspect of health monitoring in many circumstances. These include post-operative patients, those who suffer from chronic cardio-pulmonary diseases, and those with respiratory infections such as those infected by the COVID-19. The respiratory rate of an individual can be measured as the number of breaths a person takes within a certain amount of time, such as breaths per minute. In addition, respiratory patterns that may consist of the amplitude and duration of inhalation and exhalation contain clinical indications of the normal and abnormal respiratory state. Fluctuations in the respiratory patterns induced by the cardiac cycle, called the cardiogenic oscillations, may be indicators of cardiac conditions such as heart failure. The tidal volume defines the volume of air that moves through the lungs during a breath, and the product of the tidal volume and the respiratory rate defines the minute ventilation, an important measure of respiratory health. In a hospital setting, a clinician may use respiratory rate, minute ventilation, as well as respiratory pattern measurements to determine whether a patient is experiencing respiratory distress and/or dysfunction. Further, respiratory rate and pattern measurements may also be used in sports medicine for evidence based in fitness/endurance assessments of athletes as well as general population.
Embodiments consistent with principles of the present invention include a method and system for monitoring an individual's respiratory function to detecting a baseline respiratory frequency and any abnormal changes in the respiratory signals that may be indicative of a disease or fitness state.
In one embodiment, a wearable device with embedded fiber Bragg gratings (FBGs) can be worn on individual's body in a manner that may detect the expansion and contraction of the body at respiratory frequencies by measuring the time dependent shifts of the Bragg wavelengths due to the induced strain on the FBGs from body deformation. By detecting effective shifts of the Bragg wavelengths of the FBGs caused by body deformation over a period of time, the device may establish a baseline respiratory pattern. In some embodiments, the wearable device may be a wearable strap wrapped lightly round the thorax or the abdomen. In other embodiments, the wearable device may be a patch with embedded FBGs attached with adhesives to the thorax or the abdomen. Using the FBGs, the device may compare the baseline respiratory pattern with profiled respiratory patterns to determine whether the baseline respiratory pattern is indicative of a potential disease state and provide an alert of the potential disease state. In yet other embodiments, the device may be a pad to be placed under an individual, or as a blanket to be placed on top of an individual such that the embedded FBGs can detect an individual's respiratory movement. Such an embodiment may be particularly useful in a hospital setting, where the device may provide the FBG data to a processor and interface to provide health care professionals with monitoring of a patient's respiratory patterns.
In other embodiments, the device may further continue to acquire wavelength data from the plurality of FBGs to detect any changes in the any abnormal changes in the respiratory signals beyond a set threshold that may be indicative of a disease state; and provide an alert of the potential disease state.
Such a device could be part of hospital based critical or inpatient care system or a home healthcare system. In another form factor such a device can be a wearable system for the general population as part of a comprehensive “wearable continuous vitals monitoring system” for the general population as part of mobile health or telemedicine. Such a device could also be used for real time continuous infant health monitoring.
The foregoing will be apparent from the following more particular description of example embodiments, as illustrated in the accompanying drawings in which like reference characters refer to the same parts throughout the different views. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating embodiments.
A description of example embodiments follows.
As illustrated in
1B=2·neffΛ (1)
neff is the effective refractive index of the single-mode photosensitive fiber. As the fiber is stretched and grating parameter Λ increases by δΛ while effective refractive index neff decreases by δneff. The Bragg wavelength λB shifts by
δ1B=2{neff·δΛ+Λ·δneff} (1a)
By embedding one or more optical fibers with one or more FBG in wearable materials that can be wrapped over parts of anatomically relevant parts of the human body, a wearable device can be used to sense the deformation of that part resulting from physiological processes such as breathing. In certain embodiments consistent with principles of the invention, the deformation data may be used to measure and establish respiratory and cardiac patterns in a body.
Before one can use the embedded FBG as a strain gauge, the FBG's response function and linearity should be characterized as a function of load. To characterize the FBG's response function and linearity, an electrical strain gauge may be used to calibrate the FBG such that the applied tensile loading approximates readings of the displacement of the body within the Cartesian coordinate system for a three-dimensional object. For the FBG to perform as a reliable strain gauge, the change in the reflection wavelength of the FBG as it gets stretched under tensile load must linearly track the electrical strain gauge data. Once calibrated, the response of an FBG may be reliably used as an embedded strain gauge for detecting object surface deformation. Within reasonable limits on the elasticity of the gauge, it may also be used for detecting the degree to which the object surface has been displaced. Based on a calibration curve comparing pressure against strain or wavelength, along with the strain data from the sensors, one can detect the degree of displacement. In other cases, the calibration curves may be derived from comparing reflected Bragg wavelengths to secondary respiratory measurements that can include physical or image based measurements.
The change in wavelength measured over time for a free breathing patient wearing such a garment represents the patient specific respiratory signal. The respiratory signal may be compared to known respiratory patterns indicative of disease states, or monitored to detect for changes in respiratory patterns that may indicate potential disease states or the onset of such a state.
In yet other embodiments, as illustrated in
In embodiments of the garment with embedded FBGs for real time measurement of the deformation of the patient body under respiration, one may embed a number of FBGs using a predetermined coordinate system, such as a cartesian coordinate system or polar coordinate system. Additionally, the predetermined coordinate system may be determined in such a way as to balance competing interests of maximizing the fidelity of the measured deformation map while also using the least number of embedded FBGs. This could mean that the embedded FBGs are aligned along a coordinate system with respect to the patient body or in other cases they could be located for a pseudorandom sampling of the patient body. In some embodiments, this could mean that the FBGs could be distributed such that a concentration of embedded FBGs are aligned in a more dense distribution in one region, and loosely distribute in others. Depending on the nature of the garment, the distribution of FBGs within the garment may vary, as a belt or shirt may have a different, more contoured fit around a body than a blanket. Additionally, multiple FBGs can be inscribed inside a single mode optical fiber, and as long as they are separated by an predetermined optimal distance from each other and that each of these FBGs have a unique and distinct Bragg wavelength, a single such optical fiber can be used to measure the strain along its length using a single broadband light source and a single wavelength multiplex detection system. Such a system has distinct advantages over an electrical strain gauge-based system as in the latter case each strain gauge needs is own electrical connection.
Once collected, data may be used to create algorithms designed to spot physiological changes that happen to the wearer and indicate sickness is on the way. These changes involve certain changes in respiratory patterns or changes within certain thresholds that might be indicative of particular conditions. As additional data concerning users is gathered, the system can employ machine learning and predictive models to identify the onset of those conditions in patients or users. The system can then warn the wearer with an alert that they may be developing an illness or particular symptoms requiring treatment. In another use case these observed changes can be used to adapt and optimize training for professional athletes and exercise regimens of general population using connected exercise equipment. As an example, it may be used to monitor respiratory activity during a training session to ensure the wearer does not exceed certain respiratory thresholds that may be unsafe. These thresholds may be set based on an individual's personal health history, or based on collective respiratory profiles. In the fitness/endurance monitoring case, the detected respiratory patterns may also be used to optimize and individualize training/exercise regimes based on baseline data and thresholds.
By embedding one or more optical fibers with one or more FBGs in wearable materials that can be wrapped over parts of anatomically relevant parts of the human body, the one or more FBGs can be configured to sense the motion resulting from physiological processes such as breathing, heart beats, blood pressure, and blood flow. In some embodiments, the respiratory data may be used with other monitored physiological data (whether from FBGs or other monitoring means) to provide a more comprehensive view of the monitored individual, and employ better predictive models to identify the onset of conditions in patients or users.
In other embodiments, if the system does not detect any indications of potential disease states, it may continue to monitor the respiratory patterns of the patient. If the respiratory patterns change above certain thresholds (based on either respiratory rates, amplitudes or duration), the thresholds either manually set by the patient or caregiver, or learned by the system through training algorithms, an alert can be provided to an interface. In some embodiments consistent with principles of the invention, baseline respiratory patterns may be collected at a database and processed through a training algorithm to help the system identify profiled respiratory patterns or respiratory thresholds.
In yet other embodiments, if the system does detect an indication of potential disease states, it may continue to monitor the respiratory patterns of the patient to detect improvements in their respiratory state. If such a change were to occur, the system could then provide an alert indicating that improvement.
While the prior art teaches different means of measuring respiratory rate, the use of embedded FBGs in a measurement device provides a level of sensitivity and precision of monitoring not capable in those prior art systems. The examples below illustrate the various applications of the monitoring capabilities of embedded FBGs.
As one example, respiratory rate despite being a key indicator of human health does not provide sufficient information on the pulmonary state of a patient as it does not contain any information on respiratory volume changes, a key component of what is known as the “minute ventilation” defined as the product of the respiratory rate and tidal volume. Minute ventilation has shown to be an early indicator of pulmonary distress compared to pulse oximetry measurements. Currently available non-invasive minute ventilation methods include spirometry that is prone to errors due to significant patient training and compliance required, and end-tidal CO2 measurements that are used only for intubated patients. Recently there has been interest in impedance pneumography via the measurements of transthoracic impedance as a tool for non-invasive measurements of tidal volumes and in turn minute ventilation. This method requires measuring small changes in impedance under respiration and is dependent on placement of electrodes.
Wearable devices with embedded FBGs on the other hand, can measure minute changes in the strain that are more than two orders of magnitude smaller than those induced under respiration, as a consequence such devices can perform very accurate non-invasive and continuous measurements of tidal volumes and minute ventilation in multitude of circumstances, from hospital and home healthcare to sports and fitness training.
Cardiogenic oscillations in the respiratory waveform induced by the variations of pulmonary blood volume with correspondence to the cardiac cycle of a patient has been shown to be an indicator of Heart Failure (HF). Heart Failure and in particular, Acute Decompensated Heart Failure (ADHF) due to many underlying conditions is serious condition that often results in respiratory distress and hospitalization. Continuous cardiac function and respiratory monitoring of HF patients is highly desirable but currently all available solutions for such monitoring such as Pulmonary Artery Catheterization (PAC) are invasive procedures and can only be performed in the clinical setting under physician supervision.
Measurements of Cardiogenic Oscillations of Respiratory Waveforms (small waveforms superimposed on pressure and flow signals) is known to be a promising method for monitoring respiratory system mechanics, cardiac function, and heart failure. A wearable respiratory monitoring system based on embedded FBG strain sensing has the sensitivity for measuring these oscillations and can be a promising device for non-invasive cardiac monitoring and HF.
Physiologic monitoring of infants while sleeping or otherwise unsupervised and alerts based on onsets of adverse events is an important area in of health monitoring that has seen growth with the advent of new technology for non-invasive and remote monitoring. One particular method for infant physiologic monitoring has been the use of pulse oximetry. However, as described above, that change in pulse oximetry is known to be a late indicator of respiratory distress. As an alternative, a wearable non-invasive respiratory monitoring system based on embedded FBG strain measurement system can be the true real time infant physiologic monitoring system that is currently not available in the market.
Sleep monitoring in general, and physiologic monitoring of humans while sleeping in particular, are important parts of health monitoring that can provide insights to human health and can be an important tool for management of chronic conditions such as Asthma and Apnea. However, there has been no commercially available non-invasive physiologic monitoring system available for general population. Once available, such systems and the data that they can acquire and the machine learning that they can enable will provide new insights into health conditions that have not been available so far. A physiologic monitoring system based on dynamic strain sensing using embedded FBGs in wearable straps or in the bedding can provide an easy to use non-invasive physiologic monitoring system that can provide such data even during sleep and can help usher a new era of proactive healthcare.
In some embodiments, the processor 730 may be configured to monitor the baseline respiratory pattern for any significant changes in the respiratory patterns, including changes in a person's minute ventilation as discussed above. By detecting any threshold changes, or changes in pattern, the system can provide an alert of the onset of change in condition, or use predictive algorithms to warn of a potential change in condition to allow the user or medical personnel to take action prior to the onset.
In some embodiments, the processor 730 may be located locally on the device 710. In other embodiments, the processor 730 may be located on a remote general purpose computer or cloud based processor. The interface may include a display on a computer, a display on a handheld device, a display on the wearable device 710, or may take the form of an audio alert or text message on a mobile phone. Consistent with other embodiments, similar system may be used to monitor real time respiratory patterns to optimize and individualize training/exercise regimes based on baseline data and thresholds. Such embodiments may present the respiratory patterns to the user over the interface 740, and provide alerts related to changes in those patterns.
While example embodiments have been particularly shown and described, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope encompassed by the appended claims.
It should be understood that the example embodiments described above may be implemented in many different ways. In some instances, the various methods and machines described herein may each be implemented by a physical, virtual or hybrid general purpose computer having a central processor, memory, disk or other mass storage, communication interface(s), input/output (I/O) device(s), and other peripherals. The general purpose computer is transformed into the machines that execute the methods described above, for example, by loading software instructions into a data processor, and then causing execution of the instructions to carry out the functions described, herein.
As is known in the art, such a computer may contain a system bus, where a bus is a set of hardware lines used for data transfer among the components of a computer or processing system. The bus or busses are essentially shared conduit(s) that connect different elements of the computer system, e.g., processor, disk storage, memory, input/output ports, network ports, etcetera, which enables the transfer of information between the elements. One or more central processor units are attached to the system bus and provide for the execution of computer instructions. Also attached to system bus are typically I/O device interfaces for connecting various input and output devices, e.g., keyboard, mouse, displays, printers, speakers, etcetera, to the computer. Network interface(s) allow the computer to connect to various other devices attached to a network. Memory provides volatile storage for computer software instructions and data used to implement an embodiment. Disk or other mass storage provides non-volatile storage for computer software instructions and data used to implement, for example, the various procedures described herein.
Embodiments may therefore typically be implemented in hardware, firmware, software, or any combination thereof.
In certain embodiments, the procedures, devices, and processes described herein constitute a computer program product, including a non-transitory computer-readable medium, e.g., a removable storage medium such as one or more DVD-ROM's, CD-ROM's, diskettes, tapes, etcetera, that provides at least a portion of the software instructions for the system. Such a computer program product can be installed by any suitable software installation procedure, as is well known in the art. In another embodiment, at least a portion of the software instructions may also be downloaded over a cable, communication and/or wireless connection.
Further, firmware, software, routines, or instructions may be described herein as performing certain actions and/or functions of the data processors. However, it should be appreciated that such descriptions contained herein are merely for convenience and that such actions in fact result from computing devices, processors, controllers, or other devices executing the firmware, software, routines, instructions, etcetera.
It also should be understood that the flow diagrams, block diagrams, and network diagrams may include more or fewer elements, be arranged differently, or be represented differently. But it further should be understood that certain implementations may dictate the block and network diagrams and the number of block and network diagrams illustrating the execution of the embodiments be implemented in a particular way.
Accordingly, further embodiments may also be implemented in a variety of computer architectures, physical, virtual, cloud computers, and/or some combination thereof, and, thus, the data processors described herein are intended for purposes of illustration only and not as a limitation of the embodiments.
While this invention has been particularly shown and described with references to example embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the invention encompassed by the appended claims.
This application is claims the benefit of U.S. Provisional Application No. 63/054,874, filed on Jul. 22, 2020. The entire teachings of the above application are incorporated herein by reference.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/US2021/042641 | 7/21/2021 | WO |
| Number | Date | Country | |
|---|---|---|---|
| 63054874 | Jul 2020 | US |
