Distributed Processing Intra-Oral Respiratory Monitor
20200375528 ยท 2020-12-03
Inventors
Cpc classification
A61B5/082
HUMAN NECESSITIES
A61B5/11
HUMAN NECESSITIES
A61B5/01
HUMAN NECESSITIES
A61B5/0022
HUMAN NECESSITIES
International classification
Abstract
Systems, methods, devices, and apparatus for monitoring intra-oral physiologic and biologic data related to sleep performance for patients with obstructive sleep apnea (OSA). In embodiments, the monitor collects data within the mouth of the patient and sends this data to a smart phone running a dedicated APP which in turn sends this data to the computer of the health care worker for evaluation. In embodiments, data collected is processed using a distributed processing arrangement and an integral scoring algorithm to produce parameters key to the diagnosis and/or monitoring of patients with OSA.
Claims
1. A respiratory monitor system for monitoring sleep disorders such as obstructive sleep apnea, the system comprising: an intra-oral electronics module attached to an oral appliance, a smart phone with dedicated APP, and a remote computer. Said system comprising: a. a distributed data processing architecture comprised of three processor-based devices in communications with each other, and with devices (1) and (3) communicating through a smart phone (2) intermediary: 1. said intra-oral electronics module, 2. said smart phone with dedicated APP, 3. said remote computer with dedicated program, b. a scoring algorithm for processing raw intra-oral data into clinical measures of sleep apnea disease state or progression, said scoring algorithm running on either the said smart phone with dedicated APP or the said remote computer.
2. The system of claim 1 wherein the said intra-oral electronics module is removably attached to the oral appliance.
3. The system of claim 1 wherein the said intra-oral electronics module contains a breath flow sensor.
4. The system of claim 1 wherein the said smart phone with dedicated APP processes raw intro-oral data into the apnea/hypopnea index using an apnea disease scoring algorithm.
5. The system of claim 1 wherein the said intra-oral electronics module measures patient device use (compliance) by means of one or a combination of the following techniques: a. resistivity between exposed terminals on the module housing, b. measures of head movement, c. measures of breathing flow, d. measures of patient sounds, e. measures of pulse-oximetry data, f. measures of mean humidity, mean pressure or mean temperature, g. measures of biologic indicators of disease state,
6. The system of claim 1 wherein the said intra-oral electronics module is divided into two or more devices and wherein the divided devices communicate with each other using mesh networking techniques.
7. The system of claim 1 wherein a predictive analytics algorithm for sleep apnea therapeutic use is integrated into either said smart phone with dedicated APP or said remote computer.
8. A method for monitoring a patient undergoing oral device-based sleep apnea therapy, the method comprising: a. receiving intra-oral sensor data from one or more sensors configured to track both patient sleep performance, and therapeutic compliance, b. relaying sensor data, by bi-directional means, to a smart phone with a dedicated APP running an apnea disease scoring algorithm, c. further relaying the data by bi-directional means from said smart phone with a dedicated APP to a remote computer, smart phone or tablet for display of therapeutic data to health care workers.
9. The method of claim 8 further comprising a means of calculating the apnea/hypopnea index using the said apnea disease scoring algorithm.
10. The method of claim 8 further comprising a means of calculating future disease states or future therapeutic intervention suggestions using a predictive analytics algorithm running on either said smart phone with dedicated APP or said remote computer.
11. The method of claim 8 comprising a means of measuring breath gas flow.
12. The method of claim 8 comprising a means of measuring biologic indicators of sleep apnea disease state.
13. The method of claim 8 comprising a means of measuring patient therapeutic compliance by means of one or a combination of the following techniques: a. resistivity between exposed terminals on an electronics module housing, b. measures of head movement, c. measures of breathing flow, d. measures of patient sounds, e. measures of pulse-oximetry data, f. measures of mean humidity, mean pressure or mean temperature, g. measures of biologic indicators of disease state,
14. A respiratory monitor system for monitoring sleep disorders such as obstructive sleep apnea, the system comprising: a. three or more processor-based devices in communications with each other, said devices comprising an intra-oral electronics module, a smart phone with dedicated APP, and remote computer. i. said intra-oral module itself comprised of two or more intra-oral electronic sub-modules, all sub-modules equipped with sensing and processing means, and all sub-modules in wireless communications with each other. ii. Said intra-oral sub-modules comprising nodes in a mesh network,
15. The respiratory monitor system of claim 14 wherein the said intra-oral electronics sub-modules are removably attached to the oral appliance.
16. The respiratory system of claim 14 wherein at least one of the said intra-oral electronics sub-modules consists of a breath flow sensor.
17. The respiratory system of claim 14 wherein at least one of the said intra-oral electronics sub-modules senses a biologic indicator of sleep apnea disease state.
18. The respiratory system of claim 14 wherein at least one of the said intra-oral electronics sub-modules measures patient device use (compliance) by means of one or a combination of the following techniques: a. resistivity between exposed terminals on the module housing, b. measures of head movement, c. measures of breathing flow, d. measures of patient sounds, e. measures of pulse-oximetry data, f. measures of mean humidity, mean pressure or mean temperature, g. measures of biologic indicators of disease state,
19. The respiratory system of claim 14 wherein a sleep apnea scoring algorithm for processing of raw intra-oral data into clinical measures of sleep apnea disease state or progression is integrated into either said smart phone with dedicated APP or said remote computer.
20. The respiratory system of claim 14 wherein a predictive analytics algorithm for sleep apnea therapeutic use is integrated into either said smart phone with dedicated APP or said remote computer.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
[0025] The features and advantages of the present disclosure will be more fully understood with reference to the following detailed description when taken in conjunction with the accompanying figures, wherein:
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DETAILED DESCRIPTION
[0048] An improved understanding of the advantages, features, and elements of the present disclosure will be obtained by reference to the following detailed description. This description sets forth descriptive and illustrative embodiments, for which the principles of the present disclosure will become clear.
[0049] Current methods of determining the efficacy of patient treatment with respect to mandibular advancement therapy for OSA patients include the use of home sleep monitors such as TYPE III and IV home sleep devices. These devices take disparate data from a variety of sensor sources and integrate this raw data into clinically meaningful data for evaluation of patient sleep performance. Such devices are obtrusive and worn at night upon physician recommendation to obtain insight into sleep performance, ostensibly for improved titration of the mandibular advancement devices. The invention described herein produces measures of clinical importance similar to TYPE III and IV sleep monitors but in a significantly less obtrusive way.
[0050] Specifically, the invention herein uses three analytically integrated components, an intra-oral electronics module, a smart phone running a dedicated APP and a terminal device such as a computer, smart phone or table which displays calculated sleep metrics for health care workers to see.
[0051] The invention presented here uses intra-oral sensing as a means of determining clinical parameters such as the Apnea/Hypopnea Index which is a function performed by current devices known in the art as home sleep test (HST) devices which are available commercially and are divided by capability or sensing means as TYPE I, II, III, and IV devices. This invention provides functionality roughly equivalent to TYPE III or IV HST devices in that, as with these monitors, it uses a small number of sensors to obtain clinically meaningful information on the sleep status of patients throughout the night including sleep apnea frequency/severity.
[0052] In embodiments, display of the nightly sleep data collected by the intra-oral electronics module can occur (for the patient to view) on the smart phone APP 6, or (for the health care worker to view) on the terminal device 8. Either way, the data is transmitted in an encrypted fashion to prevent potential loss of private data.
[0053] In some embodiments, the bulk or majority of data or signal processing is performed by either the smart phone 6 APP or by the terminal program 8 or by a combination thereof. It is understood that the electronics module is only responsible for collection of sensor data, mild processing if any, and relay of that data (in essentially raw form) to the smart phone APP or terminal program where it is processed and this processing comprises the bulk of data and/or signal processing performed on the invention.
[0054] In some embodiments, the electronics module may be configured with a high-power processor to itself perform the bulk of data and/or signal processing. It should be noted that the drawback of a high-power processor is heavy current consumption which requires larger batteries, and this is suboptimal in the space constrained intra-oral environment.
[0055] In embodiments,
[0056] In embodiments,
[0057] In some embodiments, the electronics module may be protected from liquid ingress using a biocompatible polymer or elastomer.
[0058] In embodiments,
[0059] In some embodiments, the microprocessor may be substituted with a microcontroller, a field programmable gate array (FPGA), an application specific integrated chip (ASIC) or a similar programmable digital logic processing device.
[0060] One embodiment of the electronics elements of the invention is shown in
[0061] In embodiments, the microprocessor uses input from an external accelerometer to both put the electronics to sleep as well as to wake the electronics based on device movement. This serves two key purposes, battery preservation and ease of use. With respect to battery preservation, the device will fall asleep due to lack of movement, for instance when the electronics module is placed on a table during the day when the device is not in use. This preserves battery life. Second, the wakeup and sleep functionality provided by the accelerometer allows the electronics module to function without an external power switch. This is advantageous as it prevents accidental misuse by the patient, who might forget to turn the device on, for instance.
[0062] In embodiments, the electronics module includes a chipset which allows for the determination of patient head position/orientation
[0063] In embodiments, a sensor element which is sensitive to a biologic indicator of patient status is present in the electronics module,
[0064] In some embodiments, a MEMS or amperometric or miniature fuel cell or other type of small sensor is used to obtain discrete values of the biologic indicator concentration in the breath. For example, clinically significant levels of carbon monoxide in the exhaled breath of approximately 2 to 5 PPM can provide clinical insight into obstructive sleep apnea disease state severity and such ranges are within the measurable ranges of off-the-shelf carbon monoxide sensors.
[0065] In some embodiments, the invention includes the use of a small gas sensor,
[0066] In some embodiments,
[0067] In some embodiments a pulse oximeter chip may be integrated into the electronics module
[0068] In some embodiments,
[0069] In some embodiments,
[0070] In embodiments, the processing of data by the system, may include program flow as depicted in
[0071] In some embodiments, the electronics module of the invention may be split into two or more elements 18 as depicted in
[0072] In some embodiments,
[0073] In some embodiments, the split elements would be treated as nodes of a mesh network. In such a configuration, the nodes would connect non-hierarchically and/or directly and/or dynamically to each other. The nodes are understood to be capable of self-configuring and/or self-organizing (self-forming) and/or self-healing and/or self-optimizing. The nodes may be configured as well with multi-hop connectivity.
[0074] Commercially available TYPE III and IV HST devices for diagnosing and/or determining sleep apnea severity often rely on one of two types of sensors to determine breathing air flow, an oro-nasal thermal sensor or nasal pressure sensor. It should be noted that sleep belts (plethysmography) for thoracoabdominal movement are also often used as well. These sensors are used to obtain an indication of gas flow amplitude and direction and are further used to determine if there has been a cessation or slow down of inhaled gas flow, a condition synonymous with sleep apnea. Neither of these types of sensors provide a high degree of accuracy of inhaled gas flow and thus one might consider the output signal from these sensors as being pseudo-proportionate or loosely proportionate to actual inhaled flow magnitude.
[0075] In embodiments,
[0076] In some embodiments the flow sensor
[0077] In embodiments,
[0078] In embodiments, the gas sensor operates by using baffling to force a small stream of inhaled or exhaled gas flow through its inner chamber thereby directing the breathing gas flow into the inner chamber. Within the chamber is a temperature sensor but it is understood that the temperature sensor could be replaced with a pressure sensor or a humidity sensor. On inhalation, the gas temperature within the mouth quickly changes from the temperature of the gas at end exhalation (approximately 35-37 degrees C.) to room temperature as this end exhalation gas is quickly replaced with room temperature air within the mouth as air streams into the lungs.
[0079] In some embodiments of the invention, patient compliance with the treatment regime is determined by monitoring the use of the electronics module during sleep. Such monitoring can take many forms and are discussed here. Firstly,
[0080] In some embodiments of the invention, patient compliance with the treatment regimen may be monitored by changes in signals obtained by the on-board sensor technologies in the electronics. Patient use of the device is synonymous with patient compliance given that patient use of the device meets the treating health care workers requirements for device use. Examples are now listed and it should be noted that while individual measures of patient compliance (e.g. meeting criterion c below should be considered sufficient for assessing patient compliance, it should also be understood that any combination of the criteria below could also be considered an indicator of patient compliance (e.g. combining criterion d and criterion f):
[0081] In embodiments, modes of determining patient compliance are now listed to include movement indicators used as a means of assessing patient compliance. This includes movement indicators as measured using integral head orientation sensing electronics (note: head movement is assumed to be the equivalent of electronics module movement when device is being worn). [0082] a. Intermittent head rotation about the patient's vertical, long or longitudinal axis above a predefined event threshold value. [0083] b. Movement of head above a predefined threshold value for translational or rotational movement. With rate of translational movement in the X, Y or Z axis or combination thereof and rate of rotational movement along the X, Y or Z axis or combination thereof [0084] c. Oscillatory head movement within a temporal band defined by typical human breathing patterns (e.g. back and forth head movement in the Z axis direction at a frequency of 0.7 Hz). [0085] d. Head movement above a power spectral density threshold within spectral bands associated with human breathing or snoring. [0086] e. Oscillation of head movement-based power spectral densities (measured within spectral bands associated with human snoring) with oscillation occurring at frequencies associated with human breathing. [0087] f. Movement of the head/device away (for X hours) from the resting position that the device has occupied for the previous Y hours. Note: values of X and Y are predefined.
[0088] In embodiments, modes of determining patient compliance are now listed to include gas flow indicators used as a means of assessing patient compliance. This includes gas flow indicators as measured using the integral flow sensor of the invention which is described herein as being either a pressure, humidity or temperature sensor disposed within a sampling chamber: [0089] a. Oscillatory flow as measured by the flow sensor within a frequency band associated with human breathing over a predefined time threshold (e.g. oscillatory flow measured at 0.6 Hz for 6 minutes). [0090] b. Inhaled or exhaled flow as measured by the flow sensor above a predefined threshold value.
[0091] In embodiments, modes of determining patient compliance are now listed to include sound indicators used as a means of assessing patient compliance. This includes sound indicators as measured using the integral microphone of the invention: [0092] a. Oscillatory sound power spectral densities as measured at frequencies bands associated with human snoring and oscillating at frequencies associated with human breathing. [0093] b. Power spectral densities above a threshold as measured at frequency bands associated with human snoring. [0094] c. Oscillatory sound power spectral densities as measured at frequencies bands associated with human breathing sounds and oscillating at frequencies associated with human breathing. [0095] d. Power spectral densities above a threshold value as measured at frequency bands associated with human coughing.
[0096] In embodiments, modes of determining patient compliance are now listed to include pulse oximetry indicators used as a means of assessing patient compliance. This includes pulse oximeter data indicators as measured using an integral pulse-oximeter chip: [0097] a. Heart rate measurement within predefined limits associated with human rates for a predefined duration (e.g. heart rate measured at 68 BPM for 5 minutes). [0098] b. SpO2 measurements within predefined limits associated with human blood oxygen saturation levels for a predefined duration (e.g. SpO2 measured at 92% for 7 minutes).
[0099] In embodiments, modes of determining patient compliance are now listed to include mean humidity indicators used as a means of assessing patient compliance. This includes mean humidity data indicators as measured by taking the mean value of the sensed humidity. [0100] a. Mean humidity (absolute and relative) level changes above a threshold value for a predefined duration (e.g. mean Rh seen to change from 38% to 62% for 11 minutes).
[0101] In embodiments, modes of determining patient compliance are now listed to include mean temperature indicators used as a means of assessing patient compliance. This includes mean temperature data indicators as measured by taking the mean value of the sensed temperature. [0102] a. Mean temperature value changes above a threshold value for a predefined duration (e.g. mean temperature seen to change from 25 degrees C. to 31 degrees C. for 4 minutes).
[0103] In embodiments, modes of determining patient compliance are now listed to include biologic indicators used as a means of assessing patient compliance. This includes biologic indicator data as measured by taking a periodic value of a biologic indicator. [0104] a. Value of measured biologic indicator seen to change above a threshold value for a predefined duration (e.g. Carbon Monoxide level seen to increase from 0.2 PPM to 3.1 PPM for 16 minutes).
[0105] In embodiments, a depiction of the electronic circuit board of the invention is shown in
[0106] In embodiments, the orientation of the invention with respect to its attached oral appliance is fixed and the orientation of the oral appliance when worn by the patient is also fixed relative to overall head position. Therefore, data obtained from orientation-based sensors do not need to accommodate any variation in head orientation with respect to mandibular advancement device orientation as their respective orientations are fixed with respect to each other. Thus, there needs to be only one orientation calibration, and this will suffice.
[0107] In embodiments of this invention, data is collected by the integral orientation sensing integrated circuit chips and sent to a microcontroller or similar digital processing chip as shown in
[0108] In embodiments, the configuration of
[0109] In embodiments,
[0110] In embodiments of this invention, digital signal processing techniques employed on the head position data are employed in one or more of three locations to process the orientation data coming from said orientation sensitive integrated circuits. These locations include digital signal processing on the electronics module, digital signal processing on an external smart phone (with dedicated APP) or external tablet or computer (with dedicated APP) which is in wireless communications with the electronics module, or finally digital signal processing may occur on a device with which the dedicated APP is in communications with such as a cloud connected program on a health care workers computer or tablet or smart phone.
[0111] In embodiments of the invention, said digital signal processing techniques may include refinement or synthesis of disparate sensor information into a 3-D representation of head position such as a Euler angles, quaternions or matrix algebra representations. Such a representation may be timestamped or sequentially stored in order that head position vs. time is known or may even be subjected to further mathematical operations such as differentiation with time or integration with time to obtain insight into movement characteristics not readily available or observable in a time stamped sequence of head position data.
[0112] In embodiments of the invention,
[0113] In embodiments of the invention, the head position data is further processed by an algorithm which uncovers or illustrates aspects or characteristics of head position and movement which could be beneficial relative to uncovering or illustrating or identifying aspects of the medical condition of the wearer, or aspects of the behavior of the wearer or aspects of the treatment methodology of the treating health care worker, for instance, in creating an appropriate or effective treatment regimen.
[0114] In embodiments of the invention, post processing of head position data may include measures of patient restlessness during the sleep period. Such information may be clinically valuable as a surrogate for patient awakening or other patient states.
[0115] In embodiments of the invention, the relative degree of rapid patient head movements may also be of value clinically and as such the invention includes an algorithm which measures of the degree of rapid head movement over a period of time as shown in
[0116] In embodiments of the invention and as another example, it is known in the art that obstructive sleep apnea often includes a positional component in which, for instance, the sleep apnea patient suffers increased sleep occlusive breathing while in a particular position such as sleeping on the back. This condition is often referred to as supine-dependent sleep apnea. The invention described here, when combined with additional sensing technology which can determine breathing characteristics or snoring sounds for instance, can be combined with the head position information to obtain clinical insight into possible position dependencies in the severity of the sleep apnea. Such a juxtaposition of data as displayed on a smart phone APP is shown in
[0117] In embodiments, the calculation of clinically valuable parameters with respect to identification and quantification of OSA such as the apnea/hypopnea index (AHI), or the respiratory disturbance index (RDI) are calculated either on the smart phone APP or on the terminal computer, smart phone or table used by the health care worker.
[0118] In embodiments, the calculation of these clinically important parameters such as AHI and RDI are obtained using an artificial neural network (ANN)
[0119] In embodiments of the invention, the calculation of important clinical parameters such as AHI and RDI are obtained using a classical parameter-based or parametric algorithm. In one embodiment of the invention, the parametric algorithm
[0120] In embodiments of the invention, pre-processed and/or processed data such as SpO2, heart rate, mean temperature, mean humidity, head position, breath rate, breath flow, heart rate, biologic indicators and others, received on either the smart phone APP or the external health care workers computer or smart phone or tablet are further processed by way of a predictive analytics algorithm
[0121] In embodiments of the invention, a speaker or haptic device is integrated into the electronics module may be used in combination with sensor data collected and or in combination with clock data available on the microprocessor, to alarm the patient of wake-up time, or aberrant measured physiologic or biologic parameters or conditions. For example, an alarm may wake the patient should the patient's blood oxygen saturation drop by 5% or more, ostensibly as a safety precaution.
[0122] In embodiments, an active noise cancellation (ANC) feature is integrated into the invention,
[0123] In embodiments, tuning steps for the inventions proposed semi-open loop implementation of an ANC system for intra-oral devices involves four steps: 1. A wide spectrum input signal is output from the microprocessor in the absence of input signal, and the input from the microphone is collected. The secondary path transfer function is then obtained and implemented as a FIR filter placed before the LMS adaptation block of the LMS algorithm.2. Variable amplitude and variable spectral snoring sets are collected and documented. 3. An FxLMS and/or FuLMS configuration is exposed to these signal sets until a set of optimized coefficients are obtained. 4. The coefficients are stored in a table. The implementation steps are now described: 1. The reference microphone is removed from the system. 2. The LMS adaptation block is removed from the algorithm and the B(z) IIR adaptation block (if used) is removed from the algorithm. 3. The algorithm then uses off-line spectral and time domain techniques to determine the amplitude and spectral constituents of the input signal during use to determine which table coefficients to use at any given time. 4. The table looked-up coefficients are used for the S(hat)(z) and/or B(z) transfer functions to determine system output. It should be noted that the semi open loop configuration might be used, or this configuration might just be replaced with an ordinary FuLMS or FxLMS configurations complete with the existence of an error microphone. Either way, the algorithm in combination with the following system elements will constitute a novel implementation of an ANC system.
[0124] In embodiments, a magnetic charger which couples to the metal charge stubs of the electronics module will allow for charging of the electronics module between uses.
[0125] In embodiments,
[0126] In embodiments, a pressure transducer integral in the electronics module may be used to determine if the hermetic seal of the housing is compromised.
[0127] In embodiments, a humidity sensor integral in the electronics module may be used to determine if the hermetic seal of the housing is compromised.
[0128] In embodiments, data collected by the invention may be sent to social media sites such as Facebook for display amongst and between fellow patients or patients and health care workers or health care workers only.