Breathing training application on a smartwatch

Abstract

A breathing training system and method is disclosed, comprising a biometric device capable of measuring one or more biometric parameters of a user; an application running on a processor of a portable device that monitors the one or more biometric parameters, is coupled to the biometric device, and notifies the user to perform a recommended breathing pattern to influence the one or more biometric parameters when one or more of the one or more biometric parameters are within a predetermined range.

Description

CROSS-REFERENCE TO RELATED REGISTRATIONS This application is a partial continuation of US patent application No. 17 / 876,744, filed on July 29, 2022, published on December 1, 2022, which in turn is a partial continuation of US patent application No. 17 / 334,891, filed on May 31, 2021, published on December 1, 2022, the disclosure contents of which are hereby incorporated by reference. BACKGROUND Smartwatches (or other smart wearable devices) have the ability to monitor the user's breathing rate. This measurement is typically used to provide retrospective statistics. There is a need to use these measurements to give users immediate feedback, enabling them to modify their breathing patterns and aid in managing anxiety and relaxation. By monitoring their breathing in real time, users can influence their well-being throughout the day. BRIEF SUMMARY In a first embodiment, a breathing coach system and method are disclosed, comprising a biometric device capable of measuring one or more biometric parameters of a user; an application running on a processor of a portable device that monitors the one or more biometric parameters, is coupled to the biometric device, and notifies the user to perform a recommended breathing pattern to influence the one or more biometric parameters when one or more of the one or more biometric parameters are within a predetermined range. In another embodiment, the one or more biometric measurements include heart rate, blood pressure, or body temperature. According to a further aspect, a monitoring system is provided, comprising: at least one wearable respiratory sensor; a user device communicatively coupled to the wearable respiratory sensor, the user device comprising one or more processors coupled to a user interface and to memory comprising computer-executable instructions that cause the one or more processors to: receive a signal from each of the at least one wearable respiratory sensor relating to a user's respiratory event; extract respiratory data from the signal, comprising a respiratory rate and inhalation depth; cause the user interface to display a corresponding plurality of successive elements for each of the at least one wearable respiratory sensor;and to cause a visual change in each of the multitude of elements in succession, in order to indicate a ratio of inhalation depth to a predetermined inhalation threshold. In some embodiments, the instructions further instruct one or more processors to: provide a notification to the user via the user device if the inhalation depth during the said breathing event is not equal to or exceeds the predetermined inhalation threshold. In some implementation examples, the notification is only provided if the breathing data indicates that the user is not speaking. In some embodiments, the change is reset if an exhalation is detected in the aforementioned breathing data. In some embodiments, the instructions cause one or more processors to define the inhalation depth when extracting from a subsequent signal as the aforementioned predetermined threshold. In some embodiments, the instructions instruct one or more processors to extract the breathing data using one or more machine learning algorithms. In some embodiments, the portable breathing sensor includes a force sensor coupled to an elastic band. In some embodiments, the force sensor comprises: a variable impedance coupled to the elastic band; a constant current source; and a voltage amplifier. In some embodiments, the at least one portable respiratory sensor is configured to monitor diaphragmatic breathing. In some embodiments, the at least one wearable breathing sensor comprises a first wearable sensor configured to monitor chest breathing and a second wearable sensor configured to simultaneously monitor diaphragmatic breathing, wherein the inhalation depth includes both a chest-based inhalation depth and a diaphragmatic inhalation depth; and wherein the inhalation threshold includes both a chest-based inhalation threshold and a diaphragmatic inhalation threshold. In some embodiments, the instructions further cause one or more processors to: provide a notification to the user via the user device if the diaphragmatic inhalation depth during the said breathing event is not equal to or exceeds the diaphragmatic inhalation threshold. According to a further aspect, a method is provided comprising the steps of: attaching at least one wearable respiratory sensor to a user's body; receiving a signal relating to a user's respiratory event from each of the at least one wearable respiratory sensor on a user device that is communicatively linked to the at least one wearable respiratory sensor; extracting respiratory data, comprising a respiratory rate and inhalation depth, from the signal by the user device; causing a user interface of the user device to display a corresponding plurality of successive elements for each of the at least one wearable respiratory sensor; and causing a visual change on the user interface in each of the plurality of elements successively to indicate a ratio of inhalation depth to a predetermined inhalation threshold. BRIEF DESCRIPTION OF THE MULTIPLE VIEWS OF THE DRAWINGS To facilitate the identification of the discussion of a particular element or action, the most significant digit(s) in a reference number refer to the figure number in which that element is first introduced. Fig. 1 shows a portable smart device according to one embodiment. Fig. 2 shows an embodiment of the breathing coach system. Fig. 3 shows a schematic diagram of an improved breathing monitoring and guidance system according to one embodiment. Fig. 4 is a schematic diagram of a force sensor of the system from Fig. 3 according to one embodiment. Fig. 5 is a graphical diagram illustrating a breathing waveform according to one embodiment. Fig. 6 is a graphical diagram illustrating a chest-based breathing waveform superimposed on a diaphragm-based breathing waveform according to one embodiment. Fig. 7, Fig. 8, and Fig. 9Figure 9 shows exemplary user interfaces according to different implementation examples. Figure 10 illustrates one aspect of the subject according to one implementation example. DETAILED DESCRIPTION The details of one or more embodiments of the subject matter of this description are set forth in the accompanying drawings and in the following description. Further features, aspects, and advantages of the subject matter will become apparent from the description, the drawings, and the claims. Identical reference numbers and designations in the different drawings indicate identical elements. Fig. 1 shows a portable smart device 106 that can measure respiratory rate. An application downloaded to the portable smart device 106 displays bars reflecting the user's inhalation level 102 and exhalation level 104, measured and compared to the user's natural, conscious basal breathing. In another embodiment, the biometric device is a separate device that is coupled to the application device via a communication protocol. According to Fig. 2, the user initializes the application by recording the conscious basic breathing pattern 202. The conscious breathing pattern is stored as a base value in the portable smart device 106. The application then measures the respiratory rate 204 and displays the target respiratory rate 206 by showing the inhalation level 102 and the exhalation level 104 on the screen of the wearable smart device 106. The levels and rate can be displayed using bars, as shown in Fig. 1. For example, the inhalation level 102 is shown by bars that light up from left to right, and the exhalation level 104 by bars that move from right to left. If the application is configured to include a pause between inhalation and exhalation and / or between exhalation and inhalation, another graphic symbol can be used as a pause counter. The display can have any design that allows the two dimensions of breathing to be represented, namely frequency and depth. If the measured respiratory rate does not match the baseline value (208), the user (210) will be notified by a vibration or a sound generated by the wearable smart device (106). For example, if the user attempts to exhale before reaching the fourth bar of the inhalation. The user can configure the application to use different tones, vibration types, and their intensity levels. The application continuously measures respiratory rates (204) and compares them to a baseline value to provide ongoing feedback. Optionally, the application can be configured in the settings to provide feedback only at specific times of day. If the user goes about their daily routine and forgets to breathe consciously, the watch will continuously remind the user to return to their natural, conscious basic breathing pattern. In another embodiment, the application can be configured to implement different types of breathing rhythms, including a pause after inhalation and / or before exhalation. Optionally, the application can use different types of vibration for inhalation, the pause, and exhalation. An example of this is the 4-4-4 box breathing technique used by Navy SEALs. Any other type of breathing technique or pattern can be programmed into the application. By using the application, the user doesn't have to worry about counting breaths and can focus on their breathing and visualize toxic energy leaving their body. A subtle vibration from the wearable smart device 106 on the wrist prompts the user to inhale and hold their breath for four seconds; another vibration then signals the user to exhale. The application acts as a metronome for the user's breathing, resulting in continuous relaxation in real time. In another embodiment, the application on the portable smart device 106 prompts the user to take deeper breaths than the baseline value to increase relaxation. When using this setting, the vibration can optionally feel different or a different tone can be played. In this embodiment, the application functions as a metronome for breathing. In another embodiment, the application records the user's breathing pattern. Using this data, the application can display the breathing pattern in comparison to previous time segments or to the conscious baseline breathing pattern to illustrate the improvements achieved through the notifications. In another embodiment, the application provides statistics on the number of notifications sent; these statistics can show the user an improvement over time. In another embodiment, the application uses the heart rate measured by device 106 to determine whether a predetermined breathing pattern is required. If the measured heart rate is within a predetermined range (e.g., higher than a first threshold and lower than a second threshold), a breathing pattern is recommended via an audible and / or vibration notification on the wearable device. Optionally, multiple predetermined ranges can be set, and a different breathing pattern can be used if the heart rate enters a different range. If the user's heart rate drops to another predetermined range, the application reverts to a normal breathing pattern and stops the notifications. For example, if the user's heart rate is above 120 bpm and below 150 bpm, a first breathing pattern is executed on the portable device 106. If the heart rate exceeds 150 bpm, a second breathing pattern is executed. If the heart rate falls below 120 bpm, the breathing alerts stop. In another embodiment, the application uses the blood pressure measured by the device to calculate which type of predetermined breathing pattern is required. If the measured blood pressure is within a predetermined range, a breathing pattern is recommended via an audible or vibration notification on the wearable device. If the user follows the breathing pattern and the blood pressure drops to another predetermined range, the application reverts to a normal breathing pattern and stops the notifications. In another embodiment, the user notifies the application before taking a blood pressure measurement, and a predetermined breathing pattern is executed for a predetermined duration (e.g., 60 seconds) to lower the blood pressure. For example, the breathing pattern would involve a 60-second slow and deep breathing rhythm, with a vibration at the end of each inhalation and exhalation, signaling the user to breathe in the opposite direction for 60 seconds, or until the resting heart rate drops below a threshold (e.g., 60 bpm), before the user begins the blood pressure measurement. In another embodiment, the application uses the body temperature measured by the device to calculate which type of predetermined breathing pattern is required. If the measured temperature is within a predetermined range, a breathing pattern is recommended via an audible or vibration notification on the wearable device. If the user follows the breathing pattern and the temperature changes to another predetermined range, the application reverts to a normal breathing pattern and stops the notifications. In another embodiment, the application uses the respiratory rate measured by the device to calculate which type of predetermined breathing pattern is required. If the measured respiratory rate is within a predetermined range, a breathing pattern is recommended via an audible or vibration notification on the wearable device. If the user follows the breathing pattern and the respiratory rate changes to another predetermined range, the application reverts to a normal breathing pattern and stops the notifications. In another embodiment, the biometric device uses a pulse oximeter, whereby the respiratory rate is derived from the oxygen saturation. The recommended breathing pattern can include a combination of longer, deeper, shallower, or shorter breaths. Optionally, the application takes the user's activity into account. The user enters the currently performed activity from a predefined list (e.g., weight training, running, cycling, working, meditating) via the application interface or voice commands. The application then recommends a breathing pattern specifically tailored to the selected activity. As a first example, the application helps a user lower their heart rate. A user is working out in a gym with a heart rate of 170 bpm. However, the user could perform the same activity at 155 beats per minute. The application detects the high heart rate and selects a breathing pattern to lower it. The user begins to follow the recommended breathing pattern (e.g., by taking deeper breaths), and the heart rate decreases. The breathing application implements the required pattern, which includes a deeper breathing pattern that is directly uploaded to the device 106, with the frequency, speed and depth all predetermined by the application, with the aim of lowering the heart rate. As another example, the application helps lower an elevated heart rate during relaxation. A user runs the breathing application on their portable device 106 while relaxing, with a resting heart rate of 75 bpm. The heart rate might be slightly lower given the user's activity level. The application sets a breathing pattern with a specific frequency, depth, and speed to lower the heart rate to a set target of 60 beats per minute. Once the target of 60 beats per minute is reached, the deeper and slower breathing pattern reverts to the original, predetermined breathing pattern. The original breathing pattern is the one the user uses by default with the application. As another example, the user sets the application to "Training," and their heart rate is 120 beats per minute, which is within the predetermined target range. However, their breathing is faster and shallower than the set target values. The application selects and executes a predetermined breathing pattern that prompts the user to take in deeper breaths at a slower rate. The user follows the recommended breathing pattern to take in more oxygen and further reduce their heart rate. In another embodiment, the application includes speech recognition or a sensor that detects voice vibrations via the wrist. This feature mutes breathing notifications when the user speaks, as the user does not breathe normally while speaking, which would trigger a large number of notifications. Once the user stops speaking for a predetermined period, the mute mode is deactivated, and the user resumes receiving breathing notifications as described above. The user of the application sets several parameters, such as age, height, weight, gender, and other biometric parameters like resting heart rate, along with predetermined thresholds for rate and depth that trigger notifications. Predefined breathing patterns can be downloaded and customized to the user's specific information. For example, in the case of a watch, the vibration generated by the wearable device can be transmitted via the dial and / or the strap. Fig. 3 shows an improved respiratory monitoring and training system 302 according to an exemplary embodiment. In this example, the system 302 comprises a first wearable respiratory sensor 304 and, optionally but preferably, a second wearable respiratory sensor 306. If only the first wearable respiratory depth sensor 304 is used, it can be sized and configured to be worn comfortably over the user's chest to monitor intercostal breathing (i.e., chest breathing) exclusively, or over the user's abdomen to monitor diaphragmatic breathing exclusively. If, on the other hand, the second wearable respiratory sensor 306 is also used, as shown in Fig. 4, the first sensor 304 can be used to monitor chest breathing, while the second sensor 306 can be used to simultaneously monitor diaphragmatic breathing.Each breathing sensor comprises an elastic band 308 or the like, and a chest band sensor 310, configured to measure respiratory rate and depth based on the time-dependent variation in force exerted on the elastic band due to chest and abdominal expansion and contraction. The 302 system thus includes different operating modes: a normal mode, which monitors only chest breathing; an abdominal mode, which monitors only diaphragmatic breathing; and a third mode (breathing training mode), which monitors both chest and diaphragmatic breathing. Each of these modes may also include a supplementary "everyday mode" or "download mode," as explained below. The elastic band 302 is configured to provide sufficient tension to remain in position without being too uncomfortable for a user 312. In some embodiments, the elastic band 302 can be adjusted to different sizes and / or body types. Additionally, in some embodiments, shoulder straps 342 or the like can be provided to prevent the bands from slipping. In some embodiments, each band can have its own straps, or a single strap can be configured to accommodate two bands. Each band sensor comprises a controller 314 coupled to a force sensor 316 and a wireless transmitter 318. As discussed below, the force sensor 316 is coupled to the elastic band and converts the change in force resulting from the expansion and recovery of the elastic band during breathing into an electrical signal. The measured analog signal is digitized by the controller 314, and one or more wireless signals 320 are transmitted to a wearable smart device 322 (here represented as a smartwatch worn by the user). The signal(s) 320 can be transmitted using any known short-range communication technology (e.g., near-field communication (NFC), Bluetooth® communication, or the like) or a combination thereof.In some embodiments, additional information or data can be transmitted with signal(s) 320, for example a device ID to identify the portable sensor (useful when more than one sensor is used). The wearable smart device 322, such as the smartwatch shown, typically comprises one or more processors 324 coupled with a memory 326, a network adapter 328, and a digital display 330. Respiratory data 332, received from the signal(s) 320, is stored in the memory 326 via a software application 334. Other components may also be present, such as one or more input interfaces, speakers (for generating acoustic cues), haptic feedback components (for generating vibrations), or the like. The software application 334 includes instructions that provide further analysis using a respiratory rate and depth module 336 and cause the processors to display information or instructions on the digital display 330.Although a smartwatch is depicted, it is understood that other personal computing devices can also be used, such as a PC or a tablet. The applications 334 can also be configured to save whether one or two wearable sensors are used, and in the latter case, which wearable sensor is used to monitor the user's chest area and which wearable sensor is used to monitor the user's abdomen. The respiratory rate and depth module 336 comprises instructions which, when executed by the processor(s), cause a respiratory rate and depth (e.g., amplitude) to be determined from the respiratory data 332. In the case where the second sensor band 304 is used to monitor diaphragmatic breathing, the module is further configured to determine whether a given respiratory rate and depth are associated with intercostal or diaphragmatic breathing. A number of respiratory depth levels 338 (or thresholds) can also be stored in memory 326. As discussed below, these can be entered by the user or determined automatically. Fig. 4 shows a schematic diagram of the force sensor 316 according to an exemplary embodiment. The force sensor 316 is used to determine the respiratory depth and respiratory rate and includes the analog signal processing circuit shown. The circuit has a variable chest band impedance component 402, a constant current source 404, and a voltage amplifier 406. During inhalation, the chest / abdominal volume expands, thereby increasing the force acting on the force sensor 316, which causes an increase in impedance. During exhalation, the impedance decreases. Fig. 5 shows an exemplary waveform 502 illustrating the output signal of the force sensor 316 (regardless of whether it is chest or diaphragmatic breathing). The respiratory rate can be determined by measuring the time between two peaks (e.g.,504), and a breathing depth can be determined from the amplitude 506 of the signal during the detected breath or breathing event. In some embodiments, the controller 314 can average a large number of successive measurements to obtain a less noisy signal. Other signal processing techniques can also be used, for example, by applying one or more filters to the raw voltage to remove vibrations or other movements not directly related to the user's breathing. In cases where only the first wearable breathing sensor 304 is used, only one breathing pattern is monitored, and the procedures discussed above can be used without restriction. However, if both sensors 304 and 306 are used, different breathing patterns may require breathing-specific calibrations because the signals from the force sensor 316 differ depending on body position. In some embodiments, the system can be configured to calibrate the sensors for each individual user by providing breathing instructions (inhale or exhale, through the chest or diaphragm) and simultaneously measuring the sensor output signals.In some embodiments, the applications 334 can be configured to automatically identify whether the signals relate to chest-based or diaphragmatic breathing, and thus automatically assign a specific wearable sensor to a particular body location of the user. Other embodiments can simply be used directly. Furthermore, respiration typically results in both sensors measuring at least one signal simultaneously, and the Respiratory Rate and Depth Module 336 is configured to determine, based on both signals, whether the breathing pattern can be characterized as intercostal or diaphragmatic. An example of two waveforms illustrating this is shown in Fig. 6. Different peak detection algorithms can be used by the Respiratory Rate and Depth Module 336 to determine the breathing depth associated with each breathing pattern. In some embodiments, this may include, for example, determining the relative amplitude of the signals received by each sensor and using a user-defined threshold to categorize the measured respiration. In the example shown, an inhalation level or threshold 602 and 604 is used.This inhalation level can be manually set by the user via application 334 or determined based on a calibration procedure or the like (including the user consciously setting a relaxed baseline breathing pattern). Furthermore, a variety of sub-thresholds can also be set. Other examples, not shown, may involve the use of one or more thresholds for each signal. In some embodiments, one or more machine learning algorithms may be used to perform the categorization, including, for example, gradient amplification, which is well-suited for feature extraction and classification of time-series data.In some implementations, this may involve the use of an artificial neural network (ANN), support vector machines (SVMs), random forests, or similar instruments trained to make such determinations using data from a large number of users over time. The neural networks may be based on different architectures, such as a long-short-term memory (LSTM) architecture (which is well-suited for time series analysis) or a convolutional neural network (CNN) architecture (which performs well in feature extraction and classification of time series data). In some implementations, time series analysis algorithms, such as dynamic time warping (DTW) or longest common subsequence (LCSS), may be used to compare the shape and duration of inhalation events.In some embodiments, each waveform is calibrated individually and / or independently (as shown, for example, in Fig. 8 or Fig. 9 and discussed below). In some embodiments, the application 334 is further configured to present the user with dynamic graphical outputs via the display 330, providing real-time information on the breathing pattern, respiratory rate, and respiratory depth. This advantageously enables a significant amount of information to be conveyed in a more concise and efficient manner. This results in a marked improvement over similar systems, as a larger amount of information can be transmitted quickly, making the system 302 usable in real time. Fig. 7 shows an exemplary user interface 702 used when only a single wearable sensor is used, either on the chest or abdomen, according to one embodiment. In this example, a single row of four bars is provided to indicate breathing range or breathing depth (from left to right). Unlike the display in Fig. 1, which shows both inhalation and exhalation ranges, this example shows only inhalation ranges. It is further understood that a breathing range or breathing depth is displayed dynamically by causing a visual change to the bars in the direction of the arrows 704 (from left to right, although other directions or orientations of the bars may also be used).Initiating a visual change can include lighting up the bars, changing their color or intensity, appearing and disappearing, or other similar modifications. Although this example uses four vertical bars, it is understood that a different number of bars can be displayed. In some embodiments, the last bar is illuminated or changes when the user's inhalation value reaches the predetermined threshold (for example, thresholds 602 or 604 stored in memory 326). The other bars can be configured to display specific percentages of this upper threshold (for example, 25% (first bar), 50% (second bar), 75% (third bar)), or each bar can have its own predetermined lower threshold.The graphical display resets immediately (no bars are illuminated) as soon as the breathing rate and depth module 336 detects the user's exhalation (e.g., by recognizing that a maximum signal has been reached). If the user takes a deeper breath than the predetermined threshold, no notification is issued or displayed. However, if the user does not reach the threshold in a particular breath (for example, if only three bars or fewer are illuminated), a notification is issued. In some embodiments, the System 302 may also include various monitoring and coaching functionalities. One such mode includes an “everyday mode” that monitors the counting of inhalations up to a predetermined threshold, as shown in Fig. 7 (from bar No. 1 to bar No. 4 on the right). As noted above, the threshold corresponding to bar No. 4 (breathing depth) can be adjusted to individual breathing needs. In “everyday mode,” the wearable smart device (via the Application 334) notifies the user only if their inhalation depth does not reach a certain depth threshold. After the notification, the user can take a deeper breath on the next inhalation, thereby disabling the notification. This subtle cue encourages the maintenance of a consistent and optimal breathing depth. To establish a conscious, relaxed breathing pattern as a baseline or threshold, the user can put the application 334 into a "download mode" and consciously inhale. This conscious action allows the device to capture the user's relaxed breathing pattern (in the breathing data 332) and store it in memory 326. This stored baseline breath can serve as a reference point for tracking the user's breathing patterns and providing appropriate feedback. Advantageously, the application 334 is configured to synchronize in real time with the user's current breathing depth, thereby providing accurate and precise feedback. This contrasts with other monitoring applications or devices that merely capture breathing rates or provide independent visual cues. In some implementations, the setting of conscious relaxed breathing can be combined with the natural conscious breathing pattern functionality described above, where both inhalation and exhalation values ​​are displayed to the user. In such examples, the breathing pattern includes both inhalation and exhalation data, and the conscious relaxed baseline breathing or threshold is determined by the user exhaling during a breathing event. Fig. 8 shows a similar example of an interface 802, which is displayed when both chest and abdominal sensors are used simultaneously. In this example, the user interface comprises two rows of vertical bars, each row representing inhalation values ​​exclusively, but for different breathing modes. The upper row 804 is used (for example) to communicate chest breathing information, while the lower row 806 is used (for example) to communicate diaphragmatic breathing information. Thus, if the user inhales from the chest, the upper row of bars illuminates from left to right in this example. If the user inhales from the abdominal area (diaphragmatic breathing), the lower row of bars illuminates from left to right. If the user uses both chest and diaphragmatic inhalation, both rows of bars illuminate simultaneously. The exemplary bars in Fig.Figure 8 illustrates, for example, inhalation level 606 from Figure 6, while Figure 9 shows inhalation level 608 in the same figure (in which diaphragmatic breathing is significantly more pronounced). In some embodiments, the application 334 can store user-defined inhalation preferences for specific breathing patterns (chest-based or diaphragmatic-based) in memory 326. For example, if the user has set a diaphragmatic-based inhalation preference, the application 334 can be configured to notify the user if this goal is not achieved (e.g., if breathing is too forcefully from the chest). In some embodiments, the GUI (graphical user interface) can be used to provide coaching instructions to the user, for example, to help the user relax or breathe correctly. In other applications, it can be used to treat panic attacks or the like. In configurations where only a single wearable sensor is used, the GUI can then operate similarly to the one described in Fig. 1, but is able to monitor inhalation / exhalation levels as well as respiratory rate for either chest-based or diaphragmatic-based breathing. The foregoing descriptions of specific embodiments of the present invention have been provided for illustrative and descriptive purposes. They are not intended to be exhaustive or to limit the invention and its uses to the forms disclosed. Obviously, in light of the foregoing teaching, numerous modifications and adaptations are possible. The described embodiments were selected and described to best illustrate the principles of the invention and its practical application, thereby enabling other skilled persons to make the best possible use of the invention and its various embodiments with different modifications appropriate to the respective intended purpose. It is understood that various omissions or substitutions with equivalents may be considered as the circumstances suggest or make expedient, but the intention is to encompass the application or implementation without departing from the spirit or scope of the claims of the present invention. QUOTES INCLUDED IN THE DESCRIPTION This list of documents cited by the applicant was automatically generated and is included solely for the reader's convenience. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions. Cited patent literature US 17 / 876,744

[0001] US 17 / 334,891

[0001]

Claims

A monitoring system comprising: at least one wearable respiratory sensor; a user device communicatively coupled to the wearable respiratory sensor, the user device comprising one or more processors coupled to a user interface and to memory comprising computer-executable instructions that cause the one or more processors to: receive a signal from each of the at least one wearable respiratory sensors relating to a user's respiratory event; extract respiratory data from the signal, comprising a respiratory rate and inhalation depth; cause the user interface to display a corresponding plurality of successive elements for each of the at least one wearable respiratory sensors; and effect a visual change in each of the plurality of elements successively to indicate a ratio of inhalation depth to a predetermined inhalation threshold. The monitoring system according to claim 1, wherein the instructions further cause the one or more processors to: provide a notification to the user via the user device if the inhalation depth during the breathing event is not equal to or exceeds the predetermined breathing threshold. The monitoring system according to claim 2, wherein the notification is only provided when the breathing data indicates that the user is not speaking. The monitoring system according to claim 2, wherein the change is reset when an exhalation is detected in the said breathing data. The monitoring system according to claim 1, wherein the instructions cause the one or more processors to define the inhalation depth when extracting from a subsequent signal as the said predetermined threshold. The monitoring system according to claim 1, wherein the instructions cause the one or more processors to extract the respiratory data using one or more machine learning algorithms. The monitoring system according to claim 1, wherein the portable breathing sensor comprises a force sensor connected to an elastic band. The monitoring system according to claim 6, wherein the force sensor comprises: a variable impedance coupled to the elastic band; a constant current source; and a voltage amplifier. The monitoring system according to claim 1, wherein the at least one portable respiratory sensor is configured to monitor diaphragmatic breathing. The monitoring system according to claim 1, wherein the at least one wearable breathing sensor comprises a first wearable sensor configured to monitor chest-based breathing and a second wearable sensor configured to simultaneously monitor diaphragmatic-based breathing, and wherein the inhalation depth comprises both a chest-based inhalation depth and a diaphragmatic-based inhalation depth; and wherein the inhalation threshold comprises both a chest-based inhalation threshold and a diaphragmatic-based inhalation threshold. The monitoring system according to claim 10, wherein the instructions further cause the one or more processors to: provide a notification to the user via the user device when the diaphragm-based inhalation depth during the breathing event is not equal to or exceeds the diaphragm-based inhalation threshold. A computer-implemented method comprising the steps of: attaching at least one wearable respiratory sensor to a user's body; receiving a signal relating to a user's respiratory event from each of the at least one wearable respiratory sensor on a user device communicatively linked to the at least one wearable respiratory sensor; extracting respiratory data, comprising a respiratory rate and inhalation depth, from the signal by the user device; causing a user interface of the user device to display a corresponding plurality of successive elements for each of the at least one wearable respiratory sensor; and causing a visual change on the user interface in each of the plurality of elements successively to indicate a ratio of inhalation depth to a predetermined inhalation threshold. The method according to claim 10, further comprising: providing a notification to the user by the user device if the inhalation depth during the breathing event is not equal to or exceeds the predetermined inhalation threshold. The method according to claim 10, wherein the change is reset when an exhalation is detected in the breathing data. The method according to claim 10, wherein the inhalation depth when extracting from a subsequent signal is defined as the predetermined threshold. The method according to claim 10, wherein the extraction is carried out using one or more machine learning algorithms. The method according to claim 10, wherein the at least one portable breathing sensor is arranged on the abdomen of the user to monitor diaphragmatic breathing. The method according to claim 10, wherein the at least one wearable breathing sensor comprises a first wearable sensor located on the user's chest to monitor chest-based breathing, and a second wearable sensor located on the user's abdomen to simultaneously monitor diaphragmatic-based breathing, and wherein said inhalation depth comprises both a chest-based inhalation depth and a diaphragmatic-based inhalation depth; and wherein said inhalation threshold comprises both a chest-based inhalation threshold and a diaphragmatic-based inhalation threshold. The method according to claim 18, further comprising: providing a notification to the user via the user device when the diaphragm-based inhalation depth during the breathing event is not equal to or exceeds the diaphragm-based inhalation threshold.

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