Sublingual nerve stimulation control system and portable stimulator

Abstract

The invention provides a hypoglossal nerve stimulation control system and a portable stimulator, and the system comprises a data collection module which is used for collecting the three-axis acceleration data of a detected object at the current moment, and determining the roll angle and the pitch angle of the detected object based on the three-axis acceleration data; the posture recognition module is used for determining the posture of the detected object based on the roll angle and the pitch angle; the respiration detection module is used for determining a respiration signal source based on the posture and identifying an apnea event based on the respiration signal source; the respiration signal source comprises a roll angle and / or a pitch angle; and the stimulation control module is used for responding to the apnea event and triggering hypoglossal nerve electrical stimulation. The apnea event is identified based on the respiratory signal source, the opportunity of hypoglossal nerve electrical stimulation can be accurately identified, the respiratory signal source is determined based on the posture, the more accurate respiratory signal source is selected, and the effectiveness of hypoglossal nerve electrical stimulation is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical health, in particular to a hypoglossal nerve stimulation control system and a portable stimulator. BACKGROUND

[0002] With the development of modern medicine, the treatment methods for apnea symptoms are increasingly diversified, among which hypoglossal nerve stimulation as an effective treatment method is widely used in the treatment of airway obstruction caused by tongue collapse.

[0003] The existing hypoglossal nerve stimulation device relies on fixed time points or manual intervention to trigger electrical stimulation operation, and it is difficult to dynamically adjust the stimulation strategy according to the real-time state of the user. In particular, in the case of the user falling asleep or apnea, the traditional treatment method may cause premature or late stimulation, thereby affecting the treatment effect. In addition, the existing respiratory monitoring system usually works independently and cannot fully combine the posture changes of the user, resulting in that the hypoglossal nerve electrical stimulation cannot effectively combine the posture changes to achieve accurate stimulation, thereby affecting the effectiveness of the hypoglossal nerve electrical stimulation.

[0004] Therefore, it is necessary to provide a hypoglossal nerve stimulation control system and a portable stimulator, which can accurately determine the stimulation opportunity and combine the posture of the detected object during stimulation to ensure the effectiveness of the hypoglossal nerve electrical stimulation. SUMMARY

[0005] Therefore, it is necessary to provide a hypoglossal nerve stimulation control system and a portable stimulator, which can accurately determine the stimulation opportunity and combine the posture of the detected object during stimulation to ensure the effectiveness of the hypoglossal nerve electrical stimulation.

[0006] In a first aspect, to solve the above technical problems, the present application provides a hypoglossal nerve stimulation control system, comprising: a data acquisition module, configured to acquire three-axis acceleration data of a detected object at a current time, and determine a roll angle and a pitch angle of the detected object based on the three-axis acceleration data; a posture recognition module, configured to determine a posture of the detected object based on the roll angle and the pitch angle; a respiratory detection module, configured to determine a respiratory signal source based on the posture, and identify an apnea event based on the respiratory signal source; the respiratory signal source includes a roll angle and / or a pitch angle; a stimulation control module, configured to trigger hypoglossal nerve electrical stimulation in response to the apnea event.

[0007] In a possible implementation, the data acquisition module comprises a three-axis acceleration acquisition unit, an initial roll-pitch calculation unit, an initial quaternion calculation unit, an angular velocity determination unit, a quaternion updating unit, and a roll-pitch determination unit. The three-axis acceleration acquisition unit is configured to acquire three-axis acceleration data of the detected object at a current time point. The initial roll-pitch calculation unit is configured to determine an initial roll angle and an initial pitch angle based on the three-axis angular acceleration. The initial quaternion calculation unit is configured to determine an initial quaternion based on the initial roll angle and the initial pitch angle. The angular velocity determination unit is configured to determine an angular velocity based on three-axis acceleration data at a previous time point and three-axis acceleration data at the current time point. The quaternion updating unit is configured to update the initial quaternion based on the angular velocity to obtain an updated quaternion. The roll-pitch determination unit is configured to perform normalization processing on the updated quaternion, and determine the roll angle and the pitch angle based on the updated quaternion after the normalization processing.

[0008] In a possible implementation, the angular velocity determination unit comprises an initial rotation angle determination subunit, an initial rotation axis determination subunit, an average rotation axis vector determination subunit, an average acceleration vector determination subunit, and an angular velocity determination subunit. The rotation angle determination subunit is configured to perform dot product calculation on three-axis acceleration data at a previous time point and three-axis acceleration data at a current time point, and perform arccosine operation on a result of the dot product calculation to obtain an initial rotation angle vector. The initial rotation axis determination subunit is configured to perform cross product calculation on three-axis acceleration data at a previous time point and three-axis acceleration data at a current time point to obtain an initial rotation axis vector. The average rotation axis vector determination subunit is configured to perform weighted average on the initial rotation axis vector based on a Hamming window function to obtain an average rotation axis vector. The average acceleration vector determination subunit is configured to average the initial rotation angle vector based on a sliding window to obtain an average acceleration vector. The angular velocity determination subunit is configured to determine a rotation angle based on the average rotation axis vector and the average acceleration vector, and perform derivation operation on the rotation angle to obtain an angular velocity.

[0009] In a possible implementation, the posture comprises a supine state, a prone state, a left lateral decubitus state, a right lateral decubitus state, and a transition state.

[0010] In a possible implementation, the respiration detection module comprises a signal source determination unit and a respiratory pause event identification unit. The signal source determination unit is configured to: when the posture is a supine posture or a prone posture, take the pitch angle as the respiration signal source; when the posture is a left lateral posture or a right lateral posture, take the roll angle as the respiration signal source; and when the posture is a transition posture, weight and fuse the pitch angle and the roll angle to obtain a fusion signal, and take the fusion signal as the respiration source signal. The respiratory pause event identification unit is configured to: when, within a preset time, the value of the respiration source signal is less than a signal threshold value, and the duration for which the value of the respiration source signal is less than the signal threshold value is greater than a time threshold value, determine that the duration for which the value of the respiration source signal is less than the signal threshold value is a respiratory pause event.

[0011] In a possible implementation, the signal source determination unit comprises a weight determination subunit and a fusion subunit. The weight determination subunit is configured to determine fusion weights of the roll angle and the pitch angle based on a switching rate of the roll angle or a switching rate of the pitch angle and a signal-to-noise ratio of the roll angle and the pitch angle. The fusion subunit is configured to fuse the pitch angle and the roll angle based on the fusion weights to obtain the fusion signal.

[0012] In a possible implementation, the stimulation control module comprises a stimulation time point determination unit and a stimulation control unit. The stimulation time point determination unit is configured to determine a trough point of the respiration source signal corresponding to the respiratory pause event, and take a time point of the trough point as a stimulation time point. The stimulation control unit is configured to generate a closed-loop control strategy based on a physiological state of the detected object, and perform hypoglossal nerve electrical stimulation on the detected object at the stimulation time point based on the closed-loop control strategy.

[0013] In a possible implementation, the closed-loop control strategy comprises: When it is detected that the detected object enters a sleep state, when a sleep-in time is less than a preset delay duration, no electrical stimulation operation is performed, and when the sleep-in time is greater than or equal to the preset delay duration, a first group of electrodes and a plurality of second groups of electrodes are activated in sequence, a stimulation intensity of the first group of electrodes is less than a stimulation intensity of the second groups of electrodes, and the plurality of second groups of electrodes are cyclically activated. The first group of electrodes comprises a plurality of first electrodes with stimulation intensities from small to large, and the second groups of electrodes comprise a plurality of second electrodes with stimulation intensities from small to large.

[0014] In a possible implementation, the respiration detection module further comprises a signal confidence determination unit; The signal confidence determination unit is configured to determine a rotation center of the initial rotation axis vector within a preset time window, determine a trajectory variance and a spectral energy of the rotation center, determine a rotation center stability index based on the trajectory variance and the spectral energy, and determine a confidence of the respiration signal source based on the rotation center stability index. The respiration detection module is further configured to: When the confidence of the respiration signal source is greater than a confidence threshold, identify an apnea event based on the respiration signal source.

[0015] In a second aspect, the present application further provides a portable stimulator integrated with a hypoglossal nerve stimulation control system and a wireless communication module. The wireless communication module is configured to adjust a stimulation parameter of the hypoglossal nerve electrical stimulation. The hypoglossal nerve stimulation control system is configured to perform hypoglossal nerve stimulation control on the detected object based on the stimulation parameter. The hypoglossal nerve stimulation control system is any one of the possible implementation manners described above.

[0016] The hypoglossal nerve stimulation control system provided by the present application can accurately identify the timing of the hypoglossal nerve electrical stimulation based on the apnea event, avoid the problem of not responding in time to the stimulation control, and improve the effectiveness of the hypoglossal nerve electrical stimulation. At the same time, the posture recognition module is configured to recognize the posture of the detected object, and the respiration signal source is determined based on the recognized posture. The horizontal roll angle and the pitch angle are sensitive to different directions, and the more accurate respiration signal source is selected to identify the apnea event, which can further improve the identification accuracy of the apnea event and further improve the effectiveness of the hypoglossal nerve electrical stimulation. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0018] Figure 1 An embodiment structure diagram of the hypoglossal nerve stimulation control system provided by the present application; Figure 2 An embodiment structure diagram of the data acquisition module provided by the present application; Figure 3 An embodiment structure diagram of an angular velocity determination unit provided by the present application; Figure 4 An embodiment structure diagram of a respiration detection module provided by the present application; Figure 5 An embodiment diagram of a respiration source signal and apnea events provided by the present application; Figure 6 An embodiment structure diagram of a stimulation control module provided by the present application; Figure 7 An embodiment diagram of a stimulation time instant in a respiration source signal provided by the present application; Figure 8 An embodiment structure diagram of a portable stimulator provided by the present application. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present application will be clearly and completely described in connection with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person skilled in the art without creative work fall within the scope of protection of the present application.

[0020] It should be understood that the schematic drawings are not drawn to scale. The flowcharts used in the present application show the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowcharts can not be implemented in sequence, and the steps without logical context relationship can be reversed in sequence or implemented simultaneously. In addition, one or more other operations can be added to the flowcharts or removed from the flowcharts by a person skilled in the art under the guidance of the content of the present application. Some block diagrams shown in the drawings are functional entities, which do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different network and / or processor systems and / or microcontroller systems.

[0021] Reference to "an embodiment" in this text means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application. The phrase appears at various places in the specification does not necessarily all refer to the same embodiment, nor is it necessarily independent or alternative embodiments to other embodiments. It is explicitly and implicitly understood by a person skilled in the art that the embodiments described herein can be combined with other embodiments.

[0022] The application provides a hypoglossal nerve stimulation control system and a portable stimulator, which are described below respectively.

[0023] Figure 1 An embodiment structure schematic diagram of the hypoglossal nerve stimulation control system provided by the application is shown in the figure, and the hypoglossal nerve stimulation control system 10 comprises a data acquisition module 100, a posture recognition module 200, a respiration detection module 300 and a stimulation control module 400. Figure 1 The data acquisition module 100 is used for acquiring three-axis acceleration data of a detected object at a current time, and determining a roll angle and a pitch angle of the detected object based on the three-axis acceleration data.

[0024] The three-axis acceleration data can be acquired by an accelerometer, a micro-electromechanical system (MEMS) sensor or an inertial navigation (INS) system.

[0025] The posture recognition module 200 is used for determining a posture of the detected object based on the roll angle and the pitch angle.

[0026] In specific embodiments of the application, the posture comprises a supine state, a prone state, a left lateral decubitus state, a right lateral decubitus state and a transition state.

[0027] Specifically, the posture recognition module 200 recognizes the posture in the following manner: When the absolute value of the pitch angle satisfies , and the absolute value of the roll angle satisfies , it is determined that the detected object is in the supine state. When the pitch angle is close to , i.e., satisfies (tolerance angle), and , it is determined that the detected object is in the prone state. When the roll angle is close to , i.e., satisfies , it is determined that the detected object is in the left lateral decubitus state. When the roll angle is close to , i.e., satisfies , it is determined that the detected object is in the right lateral decubitus state. When the pitch angle and the roll angle do not satisfy any of the above posture conditions, it is determined that the detected object is in the transition state.

[0028] Specifically, the transition state can include but is not limited to a sitting state and a semi-recumbent state.

[0029] ​The respiratory detection module 300 is configured to determine a respiratory signal source based on the posture and identify the apnea event based on the respiratory signal source. The respiratory signal source includes the roll angle and / or the pitch angle.

[0030] The roll angle and the pitch angle each include values at multiple time points. The values are arranged in time sequence to obtain a sequence signal as the respiratory signal source.

[0031] The stimulation control module 400 is configured to trigger the hypoglossal nerve electrical stimulation in response to the apnea event.

[0032] Compared with the prior art, the hypoglossal nerve stimulation control system 10 provided by the embodiment of the present application can determine the respiratory signal source based on the respiratory signal source to identify the apnea event, accurately identify the timing of the hypoglossal nerve electrical stimulation based on the apnea event, and avoid the problem of delayed response to stimulation control, thereby improving the effectiveness of the hypoglossal nerve electrical stimulation. Meanwhile, the posture of the detected object is identified by the posture recognition module 200, and the respiratory signal source is determined based on the identified posture. The roll angle and the pitch angle are sensitive to different directions, and the more accurate respiratory signal source is selected to identify the apnea event, which can further improve the identification accuracy of the apnea event and further improve the effectiveness of the hypoglossal nerve electrical stimulation.

[0033] Further, the embodiment of the present application realizes the detection of continuous postures by setting the posture to include the transition posture, avoids the problem of interruption of the respiratory signal when the posture is the transition posture, ensures the continuity of the respiratory signal, and further improves the continuity and accuracy of the apnea event judgment, thereby further improving the stability and continuity of the hypoglossal nerve electrical stimulation.

[0034] In some embodiments of the present application, as shown in Figure 2 The data acquisition module 100 includes a three-axis acceleration acquisition unit 110, an initial roll-pitch calculation unit 120, an initial quaternion calculation unit 130, an angular velocity determination unit 140, a quaternion update unit 150, and a roll-pitch determination unit 160. The three-axis acceleration acquisition unit 110 is configured to acquire three-axis acceleration data of the detected object at the current time point.

[0035] Specifically, the three-axis acceleration acquisition unit 110 can be a single accelerometer, a micro-electromechanical system (MEMS) sensor, or an accelerometer in an inertial navigation (INS) system.

[0036] The initial roll-pitch calculation unit 120 is configured to determine an initial roll angle and an initial pitch angle based on the three-axis angular acceleration.

[0037] Specifically, the initial roll angle is:

[0038] initial pitch angle is:

[0039] wherein, , , are the accelerations of the x-axis, y-axis and z-axis respectively.

[0040] The initial quaternion calculation unit 130 is configured to determine an initial quaternion based on the initial roll angle and the initial pitch angle.

[0041] Specifically, the initial quaternion q0 is determined as: wherein,

[0042] The angular velocity determination unit 140 is configured to determine angular velocity data based on the three-axis acceleration data at the previous time and the three-axis acceleration data at the current time, or, to collect the angular velocity data at the current time.

[0043] It should be noted that the angular velocity data in the embodiment of the application can be calculated based on the three-axis acceleration data, or can be directly collected.

[0044] Specifically, when the angular velocity data is directly collected, the collection device can be a gyroscope, or a micro-electromechanical system (MEMS) sensor or a gyroscope in an inertial navigation (INS) system.

[0045] It should be understood that when only three-axis acceleration data can be collected in the actual application scenario, the angular velocity data can be calculated based on the three-axis acceleration data, and when the collection device in the actual application scenario can directly collect the angular velocity data, the angular velocity data can be directly collected based on the collection device.

[0046] It should be noted that if the angular velocity data is directly collected based on the collection device, the pitch angle and the roll angle can be determined based on the angular velocity data and the three-axis acceleration data by filtering the angular velocity data and the three-axis acceleration data based on a Kalman filtering algorithm or the like.

[0047] wherein the angular velocity data is three-axis angular velocity data.

[0048] The quaternion updating unit 150 is configured to update the initial quaternion based on the angular velocity data to obtain an updated quaternion.

[0049] Specifically, the updated quaternion q1 is determined as: , , wherein q1 represents the updated quaternion, for a preset time step.

[0050] The roll-pitch determination unit 160 is configured to normalize the update quaternion, and determine a roll angle and a pitch angle based on the normalized update quaternion.

[0051] Specifically, The normalization formula is:

[0052] The roll angle is:

[0053] The pitch angle is: .

[0054] The embodiment of the present application can improve the diversity of the angle velocity data acquisition method, and further improve the practicability by setting two ways to obtain the angle velocity data. In addition, the embodiment of the present application can improve the numerical stability by normalizing the quaternion to ensure that the length of the quaternion is 1.

[0055] When the angle velocity data is determined by the three-axis acceleration data, in some embodiments of the present application, as shown in Figure 3 The angle velocity determination unit 140 includes an initial rotation angle determination subunit 141, an initial rotation axis determination subunit 142, an average rotation axis vector determination subunit 143, an average acceleration vector determination subunit 144, and an angle velocity determination subunit 145. The rotation angle determination subunit 141 is configured to perform a dot product calculation on the three-axis acceleration data at the last time and the three-axis acceleration data at the current time, and perform an inverse cosine operation on the dot product calculation result to obtain an initial rotation angle vector.

[0056] Specifically, the initial rotation angle vector is:

[0057] In the formula, is the three-axis acceleration data at the current time; is the three-axis acceleration data at the last time; is a dot product calculation symbol.

[0058] The initial rotation axis determination subunit 142 is configured to perform a cross product calculation on the three-axis acceleration data at the last time and the three-axis acceleration data at the current time to obtain an initial rotation axis vector.

[0059] Specifically, the initial rotation axis vector is:

[0060] In the formula, is a cross product calculation symbol.

[0061] wherein the initial rotation axis vector represents a rotation axis at a time point t.

[0062] For oscillatory rotation, when the rotation direction is reversed, is inverted, in order to realize the normalization of the initial rotation axis vector, in the specific embodiment of the application, the initial rotation axis vector is as follows:

[0063] In the formula, is a reference axis.

[0064] The average rotation axis vector determination subunit 143 is configured to perform weighted average on the initial rotation axis vector based on a Hamming window function, to obtain an average rotation axis vector.

[0065] Specifically, the average rotation axis vector is:

[0066] In the formula, is a Hamming window function.

[0067] The average acceleration vector determination subunit 144 performs average on the initial rotation angle vector based on a sliding window, to obtain an average acceleration vector.

[0068] Specifically, the average acceleration vector is:

[0069] In the formula, is a window length.

[0070] The angular velocity determination subunit 145 is configured to determine a rotation angle based on the average rotation axis vector and the average acceleration vector, and perform a derivative operation on the rotation angle, to obtain an angular velocity.

[0071] Specifically, the rotation angle is:

[0072] wherein the rotation angle represents a rotation angle on the main rotation axis, from the average gravity direction to the current acceleration vector , and the rotation angle represents a rotation degree caused by respiration.

[0073] Specifically, the angular velocity is:

[0074] wherein the angular velocity represents the angular velocity of the respiratory motion on the principal rotation axis.

[0075] The embodiment of the present application realizes high-frequency noise suppression of the acceleration data, eliminates jitter, and improves the stability of the determined average acceleration vector and average rotation axis vector by weighted averaging of the initial rotation axis vector and averaging of the initial rotation angle vector.

[0076] In some embodiments of the present application, as shown in Figure 4 The respiratory detection module 300 includes a signal source determination unit 310 and a respiratory pause event identification unit 320. The signal source determination unit 310 is configured to, when the posture is in a supine state or a prone state, take the pitch angle as the respiratory signal source, when the posture is in a left lateral decubitus state or a right lateral decubitus state, take the roll angle as the respiratory signal source, and when the posture is in a transition state, perform weighted fusion on the pitch angle and the roll angle to obtain a fusion signal, and take the fusion signal as the respiratory source signal. The respiratory pause event identification unit 320 is configured to, when the value of the respiratory source signal is less than the signal threshold value within a preset time, and the duration of the value being less than the signal threshold value is greater than a time threshold value, determine that the duration of the value of the respiratory source signal being less than the signal threshold value is a respiratory pause event.

[0077] The embodiment of the present application determines the respiratory signal source according to the posture, selects a respiratory signal source that is more matched with the posture, and improves the accuracy of the respiratory signal source. Moreover, when the posture is in a transition state, the pitch angle and the roll angle are weightedly fused to ensure the continuity and stability of the respiratory source signal, effectively solve the problem that the respiratory signal monitoring is easily interrupted or distorted in the posture change process, ensure the accuracy of the respiratory source signal, and further improve the identification accuracy and reliability of the respiratory pause event.

[0078] In specific embodiments of the present application, the signal threshold value can be a fixed value or a dynamic value. To improve its adaptability to factors such as scenarios, in some embodiments of the present application, the signal threshold value is a dynamic value, specifically, the signal threshold value is:

[0079] In the formula, is the average amplitude of the historical respiratory source signal; is the standard deviation of the historical respiratory source signal; is an adjustment coefficient.

[0080] The embodiment of the present application determines the signal threshold value based on the historical respiratory source signal, which can improve the rationality of the signal threshold value setting.

[0081] The time threshold value can be set or adjusted according to an actual scene or an experience value, and in specific embodiments of the present application, the time threshold value is 10s.

[0082] In specific embodiments of the present application, as shown in FIG. 6, the condition that the value of the respiratory source signal is less than the signal threshold value and the duration of the value less than the signal threshold value is greater than the time threshold value is met between 20.14s-32.77s, 46.81s-61.73s and 79.48s-91.36s of the respiratory source signal, which indicates that there is an apnea event in these time intervals, and the duration is the apnea duration. Figure 5

[0083] It should be noted that: in order to further improve the accuracy of the determination of the apnea event, in some embodiments of the present application, in addition to the respiratory signal source, other physiological signals such as heart rate and blood oxygen can also be used to determine the apnea event, so as to improve the accuracy of the determination result.

[0084] In specific embodiments of the present application, when the posture is a transition state, the respiratory source signal is:

[0085] In the formula, w is the weight of the pitch angle; w is the weight of the roll angle.

[0086] It should be understood that: is a sequence of the pitch angle at a plurality of times, is a sequence of the roll angle at a plurality of times.

[0087] In order to improve the accuracy of the weight, in some embodiments of the present application, as shown in FIG. 11, the signal source determination unit 310 includes a weight determination sub-unit 311 and a fusion sub-unit 312; Figure 4 The weight determination sub-unit 311 is configured to determine the fusion weight of the roll angle and the pitch angle based on the switching rate of the roll angle or the switching rate of the pitch angle and the signal-to-noise ratio of the roll angle and the pitch angle. The fusion sub-unit 312 is configured to fuse the pitch angle and the roll angle based on the fusion weight to obtain a fusion signal.

[0088] In the embodiments of the present application, the fusion weight is determined based on the switching rate of the roll angle or the switching rate of the pitch angle and the signal-to-noise ratio of the roll angle and the pitch angle, which are two-dimensional parameters, compared with the way of determining the fusion weight based on a single-dimensional parameter, the rationality of the determined fusion weight can be improved.

[0089] ​​​​​Specifically, the signal with a smaller switching rate of the roll angle or a switching rate of the pitch angle is tilted to enhance signal stability.

[0090] switching rate of the roll angle is:

[0091] switching rate of the pitch angle is: .

[0092] Specifically, the corresponding relationship between the signal ratio and the fusion weight is:

[0093] In the formula, is the signal-to-noise ratio of the signal at the t th moment.

[0094] It should be understood that the weight determination sub-unit 311 can determine two groups of weights according to the switching rate and the signal-to-noise ratio of the signal respectively, and then further weight fusion is performed on the two groups of weights to obtain the fusion weight. That is, the fusion weight is determined by two dimensions of parameters, and the specific determination process is not described here.

[0095] The way of determining the source of the respiratory signal through the posture may cause false detection, that is, non-respiratory signals are detected as respiratory signals. To avoid this technical problem, in some embodiments of the present application, as shown in Figure 4 the respiratory detection module 300 further comprises a signal confidence determination unit 330; The signal confidence determination unit 330 is configured to determine a rotation center of the initial rotation axis vector within a preset time window, and determine a trajectory variance and a spectral energy of the rotation center, determine a rotation center stability index based on the trajectory variance and the spectral energy, and determine a confidence of the source of the respiratory signal based on the rotation center stability index. Therefore, the respiratory detection module 300 is further configured to: When the confidence of the source of the respiratory signal is greater than a confidence threshold, identify an apnea event based on the source of the respiratory signal.

[0096] By determining the confidence of the source of the respiratory signal, the embodiment of the present application determines the accuracy of the source of the respiratory signal based on the confidence, so as to avoid false detection of the respiratory signal, and further ensures the accuracy of the hypoglossal nerve stimulation control system 10.

[0097] The confidence threshold can be set or adjusted according to the actual application scene, which is not specifically limited here.

[0098] In specific embodiments of the present application, the specific process of the signal confidence determination unit 330 is as follows: First, determine the trajectory variance: The spatial trajectory of the initial rotation axis vector in the preset time window is fitted, and the optimal fitting point is obtained as the rotation center. The rotation center reflects the position of the fixed point or approximate fixed point during the respiratory motion process, and the fitting formula is as follows:

[0099] In the formula, is the rotation center; is the initial rotation axis vector; is the rotation center candidate point; is the Euclidean norm.

[0100] The embodiment of the application can obtain the optimal rotation center by minimizing the sum of squares of distances between the initial rotation axis vector and the rotation axis center candidate point .

[0101] Wherein, the trajectory variance is a statistical characteristic value in the preset time window , and specifically, the trajectory variance is:

[0102] In the formula, is the trajectory mean value in the preset time window .

[0103] It should be understood that: the trajectory variance represents the fluctuation degree of the rotation center, the smaller the trajectory variance, the more stable the rotation center in the respiratory process, and the stronger the respiratory rhythm; if the trajectory variance is large, there may be respiratory abnormalities or body position changes. That is, when the trajectory variance is large, it means that the respiratory signal source may not be the correct respiratory signal.

[0104] Second, determine the spectral energy: First, determine the time variation trend of the rotation center, and specifically, the time variation trend is:

[0105] In the formula, is the rotation center at the historical time point .

[0106] Then, the time variation trend is subjected to fast Fourier transform (FFT), and the spectral energy thereof is extracted, and the respiratory energy in the preset frequency range is determined, wherein the spectral energy is specifically: .

[0107] The embodiment of the present application combines the trajectory center distribution and the spectrum energy, can determine whether the respiratory rhythm is stable, and further assists in determining whether the respiratory signal source is accurate.

[0108] Specifically, the rotation center stability index is :

[0109] In the formula, is the respiratory energy in the preset frequency range; is a tiny constant to prevent the denominator from being zero.

[0110] The rotation center stability index The greater the rotation center stability index is, the higher the confidence of the respiratory signal source is.

[0111] In the specific embodiments of the present application, a mapping relationship between the rotation center stability index and the confidence is constructed, and the confidence can be determined according to the rotation center stability index based on the mapping relationship.

[0112] It should be noted that: in order to avoid the noise and other interference from causing adverse effects on the rotation center stability index, the signal confidence determination unit 330 is further used to perform band-pass filtering and other processing on the initial rotation axis vector before determining the rotation center, so as to eliminate the noise effect.

[0113] In some embodiments of the present application, as shown in Figure 6 The stimulation control module 400 includes a stimulation time determination unit 410 and a stimulation control unit 420. The stimulation time determination unit 410 is used to determine the trough point of the respiratory source signal corresponding to the apnea event, and the time of the trough point is taken as the stimulation time.

[0114] Specifically, if the respiratory source signal is as shown in Figure 5 , the stimulation times are as shown in Figure 7 , which are 20.14S, 46.81S and 80.66S respectively.

[0115] The stimulation control unit 420 is used to generate a closed-loop control strategy based on the physiological state of the detected object, and to perform hypoglossal nerve electrical stimulation on the detected object at the stimulation time based on the closed-loop control strategy.

[0116] The embodiment of the present application generates a closed-loop control strategy based on the physiological state of the detected object, which can significantly improve the adaptability of the closed-loop control strategy to the detected object compared with the fixed control strategy, and further can significantly improve the timeliness of the stimulation response and the treatment effect.

[0117] In the specific embodiments of the present application, the physiological state is a sleep state. Then the closed-loop control strategy is: When it is detected that the detected object enters the sleep state, when the sleep time is less than the preset delay duration, the electric stimulation operation is not performed, when the sleep time is greater than or equal to the preset delay duration, the first group of electrodes and the plurality of second groups of electrodes are activated in turn, the stimulation intensity of the first group of electrodes is less than the stimulation intensity of the second group of electrodes, and the plurality of second groups of electrodes are activated in turn; The first group of electrodes comprises a plurality of first electrodes with stimulation intensity from small to large, and the second group of electrodes comprises a plurality of second electrodes with stimulation intensity from small to large.

[0118] Specifically, the closed-loop control strategy comprises a sleep delay stage, a step-by-step activation stage, and an electrode group cycle stimulation stage. The sleep delay stage: after it is detected that the detected object enters the sleep state, a preset start delay time period is automatically entered, that is, when the sleep time is within the start delay time period, the electric stimulation operation is not performed, so as to avoid interference with the sleep process of the detected object, thereby improving sleep comfort and user compliance of the system.

[0119] The step-by-step activation stage: after the start delay time period ends, the electric stimulation operation is started, the first group of electrodes is activated first, the stimulation intensity is gradually increased in an incremental mode until a set treatment threshold is reached, so that the sublingual muscle gradually adapts to the electric stimulation, and the adverse effects of sudden high-intensity stimulation on the physiological response of the detected object are reduced.

[0120] The electrode group cycle stimulation stage: after the step-by-step activation stage is completed, the plurality of second groups of electrodes are activated in turn according to a preset order, each second group of electrodes adjusts the stimulation intensity in an incremental mode within its corresponding stimulation period, and the cycle activation operation of all second groups of electrodes is continuously performed until the detected object wakes up or the treatment time ends.

[0121] In summary, in the entire sleep cycle, the stimulation control module 400 maintains the tension state of the sublingual muscle through periodic sublingual nerve electric stimulation operation to prevent the tongue from collapsing and causing airway obstruction. Periodic stimulation combined with electrode group rotation and dynamic adjustment of stimulation intensity avoids muscle fatigue caused by continuous stimulation, and ensures the stability of the normal breathing rhythm of the detected object and the continuity and effectiveness of the electric stimulation treatment.

[0122] It should be noted that the stimulation intensity, frequency, duration, and electric stimulation waveform of the first group of electrodes and the second group of electrodes can be personalized according to the specific physiological characteristics and disease severity of different detected objects, such as different age groups or different severity of patients. Different stimulation intensity, frequency, and duration parameters are formulated to meet the specific needs of different detected objects and achieve truly personalized treatment. Compared with the traditional general stimulation mode, the treatment effect and user experience can be further improved, and it has wider clinical application value.

[0123] Specifically, the electric stimulation waveform can be a square wave, a sine wave, etc., which is set according to requirements.

[0124] The application also provides a portable stimulator, such as Figure 8 As shown, the sublingual nerve stimulation control system 10 and the wireless communication module 20 are integrated; The wireless communication module 20 is used to adjust the stimulation parameters of the sublingual nerve electric stimulation; The sublingual nerve stimulation control system 10 is used to control the sublingual nerve stimulation of the detected object based on the stimulation parameters; The sublingual nerve stimulation control system 10 is the sublingual nerve stimulation control system in any one of the above embodiments.

[0125] It should be understood that the sublingual nerve stimulation control system 10 is in an embedded structure, embedded in the portable stimulator, and the user or medical staff can adjust the stimulation parameters through the wireless communication module 20. The wireless communication module 20 supports data synchronization and remote configuration functions to optimize the stimulation strategy.

[0126] The embodiment of the application optimizes the system architecture, reduces the overall complexity and cost, facilitates promotion and application, improves the system reliability and stability, and reduces the risk of failure by highly integrating the sublingual nerve stimulation control system 10 in the portable stimulator.

[0127] The above describes in detail the sublingual nerve stimulation control system and the portable stimulator provided by the application. The principle and implementation mode of the application are described by applying specific examples. The above embodiment is only used to help understand the method and core idea of the application. Meanwhile, for those skilled in the art, the specific implementation mode and application range will be changed according to the idea of the application. In conclusion, the content of the specification should not be understood as a limitation of the application.

Claims

1. A hypoglossal nerve stimulation control system, characterized in that, include: The data acquisition module is used to acquire the triaxial acceleration data of the object being detected at the current moment, and to determine the roll angle and pitch angle of the object being detected based on the triaxial acceleration data; The attitude recognition module is used to determine the attitude of the detected object based on the roll angle and the pitch angle; A breathing detection module is used to determine the source of a breathing signal based on the posture, and to identify a breathing apnea event based on the source of the breathing signal; the source of the breathing signal includes roll angle and / or pitch angle; The stimulation control module is used to trigger electrical stimulation of the hypoglossal nerve in response to the apnea event.

2. The hypoglossal nerve stimulation control system according to claim 1, characterized in that, The data acquisition module includes a three-axis acceleration acquisition unit, an initial roll and pitch calculation unit, an initial quaternion calculation unit, an angular velocity determination unit, a quaternion update unit, and a roll and pitch determination unit. The triaxial acceleration acquisition unit is used to acquire the triaxial acceleration data of the object being detected at the current moment; The initial roll and pitch calculation unit is used to determine the initial roll angle and initial pitch angle based on the triaxial angular acceleration; The initial quaternion calculation unit is used to determine the initial quaternion based on the initial roll angle and the initial pitch angle; The angular velocity determination unit is used to determine angular velocity data based on the triaxial acceleration data of the previous moment and the triaxial acceleration data of the current moment, or to collect the angular velocity data of the current moment. The quaternion update unit is used to update the initial quaternion based on the angular velocity data to obtain the updated quaternion; The roll and pitch determination unit is used to normalize the updated quaternion and determine the roll angle and the pitch angle based on the normalized updated quaternion.

3. The hypoglossal nerve stimulation control system according to claim 2, characterized in that, The angular velocity determination unit includes an initial rotation angle determination subunit, an initial rotation axis determination subunit, an average rotation axis vector determination subunit, an average acceleration vector determination subunit, and an angular velocity determination subunit. The rotation angle determination subunit is used to perform a dot product calculation on the triaxial acceleration data of the previous moment and the triaxial acceleration data of the current moment, and to perform an inverse cosine operation on the dot product calculation result to obtain the initial rotation angle vector. The initial rotation axis determination subunit is used to perform a cross product calculation on the triaxial acceleration data of the previous moment and the triaxial acceleration data of the current moment to obtain the initial rotation axis vector; The average rotation axis vector determination subunit is used to perform a weighted average of the initial rotation axis vector based on the Hamming window function to obtain the average rotation axis vector. The average acceleration vector determination subunit averages the initial rotation angle vector based on a sliding window to obtain the average acceleration vector. The angular velocity determination subunit is used to determine the rotation angle based on the average rotation axis vector and the average acceleration vector, and to perform a derivative operation on the rotation angle to obtain the angular velocity.

4. The hypoglossal nerve stimulation control system according to claim 1, characterized in that, The postures include supine, prone, left lateral, right lateral and transitional positions.

5. The hypoglossal nerve stimulation control system according to claim 4, characterized in that, The respiratory detection module includes a signal source determination unit and a breathing apnea event recognition unit; The signal source determination unit is used to use the pitch angle as the respiratory signal source when the posture is supine or prone, the roll angle as the respiratory signal source when the posture is left lateral or right lateral, and the weighted fusion of the pitch angle and the roll angle to obtain a fused signal when the posture is in a transitional state, and the fused signal as the respiratory source signal. The sleep apnea event identification unit is used to determine that the duration during which the value of the breathing source signal is less than the signal threshold is a sleep apnea event when, within a preset time period, the value of the breathing source signal is less than the signal threshold and the duration of the period of the signal threshold being less than the signal threshold is greater than the time threshold.

6. The hypoglossal nerve stimulation control system according to claim 5, characterized in that, The signal source determination unit includes a weight determination subunit and a fusion subunit; The weight determination subunit is used to determine the fusion weight of the roll angle and the pitch angle based on the switching rate of the roll angle or the switching rate of the pitch angle and the signal-to-noise ratio of the roll angle and the pitch angle. The fusion subunit is used to fuse the pitch angle and the roll angle based on the fusion weight to obtain the fused signal.

7. The hypoglossal nerve stimulation control system according to claim 1, characterized in that, The stimulation control module includes a stimulation timing determination unit and a stimulation control unit; The stimulation time determination unit is used to determine the trough point of the respiratory source signal corresponding to the apnea event, and to take the time of the trough point as the stimulation time. The stimulation control unit is used to generate a closed-loop control strategy based on the physiological state of the subject being tested, and to perform hypoglossal nerve electrical stimulation on the subject being tested at the stimulation time based on the closed-loop control strategy.

8. The hypoglossal nerve stimulation control system according to claim 7, characterized in that, The closed-loop control strategy is as follows: When the detected subject enters a sleep state, if the sleep onset time is less than the preset delay time, no electrical stimulation operation is performed. If the sleep onset time is greater than or equal to the preset delay time, the first group of electrodes and multiple second groups of electrodes are activated in sequence. The stimulation intensity of the first group of electrodes is less than the stimulation intensity of the second group of electrodes, and the multiple second groups of electrodes are activated cyclically. The first group of electrodes includes multiple first electrodes with stimulation intensities ranging from low to high, and the second group of electrodes includes multiple second electrodes with stimulation intensities ranging from low to high.

9. The hypoglossal nerve stimulation control system according to claim 3, characterized in that, The respiratory detection module also includes a signal confidence determination unit; The signal confidence determination unit is used to determine the rotation center of the initial rotation axis vector within a preset time window, and to determine the trajectory variance and spectral energy of the rotation center. Based on the trajectory variance and the spectral energy, it determines the rotation center stability index, and based on the rotation center stability index, it determines the confidence level of the source of the respiratory signal. The respiratory detection module is also used for: When the confidence level of the respiratory signal source is greater than the confidence level threshold, the apnea event is identified based on the respiratory signal source.

10. A portable stimulator, characterized in that, It integrates a hypoglossal nerve stimulation control system and a wireless communication module; The wireless communication module is used to adjust the stimulation parameters of the hypoglossal nerve electrical stimulation. The hypoglossal nerve stimulation control system is used to control the hypoglossal nerve stimulation of the tested object based on the stimulation parameters. The hypoglossal nerve stimulation control system is the hypoglossal nerve stimulation control system described in any one of claims 1-9.

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