Tongue muscle stimulator and system

Abstract

The invention relates to a tongue muscle stimulator and system. The tongue muscle stimulator includes: a sensor module including one or more sensors that detect parameters related to a user and / or a surrounding environment; the controller generates a control signal at least based on the parameters from the sensor module; the stimulation circuit is used for receiving the control signal from the controller and generating an electrical stimulation waveform; the one or more electrodes are electrically connected with the stimulation circuit and provide electrical stimulation for the tongue muscle of the user; the method is characterized in that each period of the electrical stimulation waveform sequentially comprises a first time period, a second time period and a third time period, in the first time period, the stimulation amplitude is gradually increased to a second amplitude from a first amplitude, and the second amplitude is maintained in the second time period; the stimulation amplitude in the third time period is gradually reduced from the second amplitude to a third amplitude.

Description

Technical Field

[0001] The present disclosure belongs to the technical field of medical devices, and in particular, relates to a tongue muscle stimulator and system. Background Art

[0002] Obstructive sleep apnea (OSA) is a common sleep disorder characterized by recurring complete or partial obstruction of the upper airway during sleep, resulting in interrupted or shallow breathing. It is associated with a variety of chronic diseases, including coronary heart disease, hypertension, arrhythmias, type 2 diabetes, cerebrovascular disease, and cognitive dysfunction. OSA patients often experience sleep disruption and apnea at night, leading to daytime sleepiness and increased risk of traffic accidents. The onset of OSA involves multiple physiological factors, especially dysfunction of the neuro-upper airway dilator muscles, which play a key role in maintaining airway patency during sleep. As the main upper airway dilator muscle, the genioglossus muscle (Genioglossus) has a dysfunctional function that may lead to airway collapse and apnea.

[0003] Snoring originates from the vibration of the soft tissues of the oropharynx and is a common phenomenon in the general population, with some reports suggesting that at least 20% of people snore. It is most common in middle-aged men, although women after menopause become more prone to snoring. Snoring is also associated with adverse health outcomes, including fatigue and hypertension, as well as more serious conditions such as ischemic heart disease and cerebral ischemia. There are many causes of snoring, most of which are caused by airway obstruction, which is connected to the nasal and oral cavities. During sleep, airway tissue can collapse due to muscle relaxation, mandibular retraction, and tongue retraction, leading to airway obstruction. Obese individuals, who often have narrower airways, are particularly susceptible to airway obstruction. One way to open the airway is to pull the mandible forward to increase muscle tone in the throat, tongue, and soft palate, thereby propping up the airway that collapses during sleep. Therefore, snoring caused by this condition can be stopped by pulling the mandible forward to the ideal position to prop up the airway.

[0004] In the prior art, continuous positive airway pressure (CPAP) therapy is one of the standard treatments for OSA and snoring, but due to patient compliance issues, there is an increasing demand for alternative treatments. In recent years, neurostimulation technology has been studied as an emerging treatment method for the treatment of OSA. In particular, electrical stimulation of the tongue muscles has shown potential effects. By stimulating the tongue muscles to activate the tongue muscles, the tongue is prevented from falling back during sleep, thereby maintaining the patency of the upper airway. For example, in the prior art, an instrument for training oral muscle tone is provided, such as an electrical stimulation device, which includes a mouthpiece having at least one electrode device associated with the mouthpiece, and a circuit operably connected to the electrode device, wherein the instrument is configured to provide electrical stimulation to one or more oral muscles (such as the tongue muscles and optional palatal muscles) through the inner membrane of the mouth (such as the oral mucosa) via the at least one electrode device during use, for example, to increase resting muscle tone and / or muscle tone during sleep.

[0005] However, existing technologies for using devices to stimulate the tongue muscles still fail to meet user needs in various ways. For example, stimulation can cause discomfort. Another example is that stimulation cannot be adjusted in real time based on changes in the user's physical condition. These issues can affect the stimulation effect and the user experience. Summary of the Invention

[0006] According to a first aspect of the present application, a tongue muscle stimulator is provided, comprising:

[0007] a sensor module, the sensor module comprising one or more sensors for detecting parameters related to the user and / or the surrounding environment;

[0008] a controller that generates a control signal based at least on the parameter from the sensor module;

[0009] a stimulation circuit, receiving a control signal from the controller and generating an electrical stimulation waveform;

[0010] one or more electrodes electrically connected to the stimulation circuit to provide electrical stimulation to the user's tongue muscles;

[0011] It is characterized in that each cycle of the electrical stimulation waveform includes a first time period, a second time period and a third time period in sequence. During the first time period, the stimulation amplitude of the electrical stimulation waveform gradually increases from a first amplitude to a second amplitude, during the second time period, the stimulation amplitude maintains the second amplitude, and during the third time period, the stimulation amplitude gradually decreases from the second amplitude to a third amplitude.

[0012] The tongue muscle stimulator of the first aspect can avoid sudden increase or decrease in tongue muscle electrical stimulation, thereby improving the user's experience of using the tongue muscle stimulator.

[0013] Preferably, there is a treatment interval between adjacent cycles of the electrical stimulation waveform, and no electrical stimulation is performed during the treatment interval.

[0014] Preferably, the lengths of the first period, the second period, the third period and the treatment interval are adjusted in real time according to the user's electromyographic signal rhythm.

[0015] Preferably, the electrical stimulation waveform includes a waveform selected from the group consisting of a square wave, a sine wave, a triangle wave, an exponential wave, and a balanced asymmetric wave.

[0016] Among them, more preferably, the power spectrum energy of the user's muscle electrical signal in the second time period is Pt1, and the power spectrum energy of the user's muscle electrical signal in the treatment interval period is Pt2, wherein, by adjusting the electrical stimulation waveform, 1.5≤Pt1 / Pt2≤10.

[0017] Among them, more preferably, by adjusting the electrical stimulation waveform, 2≤Pt1 / Pt2≤6.

[0018] Among them, more preferably, the adjustment of the electrical stimulation waveform includes adjusting at least one of the pulse width, amplitude, frequency, length of the first time period, length of the second time period, length of the third time period, and length of the treatment interval period of the electrical stimulation waveform.

[0019] Preferably, the frequency of the electrical stimulation waveform is changed based on the change of Pt1 / Pt2 over time.

[0020] Preferably, snoring detection is performed based on the parameters from the sensor module, and in the presence of snoring, an electrical stimulation waveform suitable for snoring treatment is generated using a pre-stored algorithm.

[0021] More preferably, snoring detection is performed based on at least one of an electrophysiological signal of the user, a sound signal near the mouth and nose of the user, and a respiratory movement signal of the user.

[0022] Preferably, swallowing training is performed by using a pre-stored algorithm to generate an electrical stimulation waveform suitable for swallowing training based on the user's swallowing movement amplitude.

[0023] Preferably, the stimulation circuit includes a safety resistor connected in series with the load, and the controller calculates the impedance value of the load based on the voltage on the safety resistor, the voltage on the load, and the resistance value of the safety resistor.

[0024] Preferably, calculating the impedance value of the load is performed within the second time period.

[0025] In a second aspect of the present application, a tongue muscle stimulation system is provided, comprising:

[0026] The tongue muscle stimulator of the first aspect; and

[0027] An electronic device is capable of communicating with the tongue muscle stimulator, receiving data from the tongue muscle stimulator, and sending instructions to the tongue muscle stimulator to set the tongue muscle stimulator so that the tongue muscle stimulator performs treatment on the user.

[0028] According to a second aspect of the present application, a tongue muscle stimulation system is provided, which allows a user to operate a tongue muscle stimulator on an electronic device, and the tongue muscle stimulator can upload data to the electronic device.

[0029] Preferably, a cloud device that communicates with the electronic device is further included, and the cloud device can receive and store data from the electronic device, and can transmit data and instructions to the electronic device.

[0030] Compared with the prior art, the tongue muscle stimulator and system of the present application provides a new method for generating an electrical stimulation waveform, generating electrical stimulation that is more user-friendly and improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The present disclosure will now be described, by way of example only, with reference to the accompanying drawings, in which:

[0032] Figure 1 It is a block diagram of a tongue muscle stimulator of the present application.

[0033] Figure 2 Schematic diagram of the sensor module of the tongue muscle stimulator of the present application.

[0034] Figure 3 Schematic diagram of the stimulation circuit of the tongue muscle stimulator of the present application.

[0035] Figure 4 Schematic diagram of an exemplary stimulation waveform generated by the tongue muscle stimulator of the present application.

[0036] Figure 5 This is a flow chart of a method for generating a stimulation waveform of the tongue muscle stimulator of the present application.

[0037] Figure 6 An embodiment of the stimulation circuit of the tongue muscle stimulator of the present application is shown.

[0038] Figure 7 A tongue muscle stimulation system according to the present application is shown. DETAILED DESCRIPTION

[0039] In order to enable those skilled in the art to better understand the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Moreover, based on the embodiments in the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0040] Figure 1 This is a block diagram of a tongue muscle stimulator of the present application. Figure 1 As shown, the tongue muscle stimulator 1 involved in the present application includes a sensor module 11, a controller 13, a stimulation circuit 15 and an electrode array 17. Optionally, a communication module 19 may also be included.

[0041] Figure 2 Schematic diagram of the sensor module of the tongue muscle stimulator of the present application. Figure 2 As shown, the sensor module 11 may include one or more sensors with detection functions. For example, it may include an electrode 111 for collecting electrophysiological signals. The electrophysiological signal is, for example, the electromyographic signal of the tongue muscle. In order to detect the user's oral movement, a motion sensor 113 may be included to collect the oral movement waveform. The sensor module 11 may also include a breathing detection device 115 for collecting the user's breathing signal. In addition, the microphone 117 can collect the sound near the user's mouth. Further, it may also include a pressure sensor 119 for detecting the respiratory airway pressure. Of course, the sensors described herein are not limited to a specific form as long as they can detect the relevant parameters. In addition, more or fewer sensors may be included as needed, as long as the predetermined function can be achieved. Of course, those skilled in the art should understand that in order to obtain the corresponding digital signal, other auxiliary devices may also need to be included, such as electromyographic signal acquisition circuits, analog-to-digital conversion devices, etc., which are not listed here one by one.

[0042] The controller 13 generates control signals based on the detection data from the sensor module 11. The controller 13 can be any computing device with logical computing capabilities, such as a microcontroller unit (MCU), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), etc. Obviously, the specific type of the controller 13 does not constitute a limitation on the technical content of this application.

[0043] Figure 3: is a schematic diagram of the stimulation circuit of the tongue muscle stimulator of the present application. The stimulation circuit 15 generates an electrical stimulation waveform signal according to the control signal from the controller 13. The stimulation circuit 15 may include a boost module for providing sufficient stimulation output voltage. In addition, the stimulation circuit 15 may operate in a constant voltage, constant current or constant charge output mode to adapt to different treatment needs. In addition, the stimulation circuit may also include an impedance measurement module for measuring the impedance of the load. The impedance measurement results can be used to determine whether the user is wearing the stimulator correctly, whether the electrodes are working properly, etc. The specific impedance measurement method will be described in detail later.

[0044] The electrode array 17 includes one or more electrodes, which are arranged to contact the tongue muscles so as to stimulate the tongue muscles. In the tongue muscle stimulator 1 of the present application, one or more electrodes of the electrode array 17 can be distributed symmetrically or asymmetrically. Thus, different treatment modes and treatment effects can be produced according to the different distribution of electrodes. As needed, one or more electrodes can be replaced by the user. For example, when the result of the impedance measurement shows that the electrode is abnormal, an alarm can be issued to remind the user to replace the electrode or hand it over to a professional for repair.

[0045] The tongue muscle stimulator 1 of the present application can communicate with electronic devices through the communication module 19, receive data or instructions from these electronic devices, and transfer data related to treatment to these electronic devices. For example, other electronic devices can be electronic devices such as smart phones, tablet computers, desktop computers, etc. The wireless communication connection can be near field communication (NFC), Bluetooth, WIFI, mobile network, etc. The wired communication connection can include common wired networks, such as optical fibers or other optical networks, cable networks, power lines, etc.

[0046] Figure 4 Schematic diagram of an exemplary stimulation waveform generated by the tongue muscle stimulator 1 of the present application. Figure 4 As shown in (b), the tongue muscle stimulator 1 includes one or more treatment cycles during operation, and there is a treatment interval t2 between adjacent treatment cycles. Each treatment cycle can be roughly divided into three stages, namely, the gradual increase period t0, the constant output period t1, and the gradual decrease period t3. Figure 4 As shown in (c), at the treatment start-up stage of each treatment cycle, that is, in the gradual increase period t0, the amplitude of the stimulation waveform shows a gradually increasing characteristic until it reaches the maximum value A of the period at the end of the period t0. For example, the initial amplitude can be 0 or not. Using a gradually increasing waveform helps to reduce the user's discomfort caused by the sudden application of the electrical stimulation signal at the beginning of the treatment cycle. After the gradual increase period t0, in the constant output period t1, the amplitude of the stimulation waveform remains A. The constant output period t1 is the main treatment period. As shown in Figure 4As shown in (a), during the time period t1, the stimulation waveform presents a conventional basic treatment waveform. The stimulation waveform is composed of a basic waveform with a pulse width of T, a stimulation amplitude of A, and a frequency of f. During the fading period t3 before the end of the treatment cycle, the stimulation amplitude gradually decreases until the end. The amplitude can be 0 or not at the end. The advantage of setting the fading period t3 is that it can avoid the user's abnormal feeling caused by a sudden decrease in the stimulation waveform, thereby improving the user experience. Basic waveforms include but are not limited to: symmetrical square waves, sine waves, triangle waves, exponential waves, balanced asymmetric waves, etc. The pulse width T and frequency f of the fading period t0 and the fading period t3 can be the same as the basic waveform in the constant output period t1, but the amplitude is gradually changed. Therefore, by utilizing the three-period waveform control of the present application, muscle spasms caused by sudden increase / sudden decrease stimulation can be avoided, and the treatment comfort and compliance can be improved, thereby significantly improving the user experience.

[0047] By manipulating the aforementioned parameters T, f, A, t0, t1, t2, and t3, a variety of stimulation waveforms can be achieved. For example, within a constant output period t1, varying f can achieve variable-frequency stimulation within the treatment cycle. Another example is adjusting the lengths of periods t0, t1, t2, and t3 to modulate the envelope of the base stimulation waveform.

[0048] Generally speaking, the myoelectric signals generated by muscle movement are accompanied by muscle contraction and relaxation, and present a rhythmic characteristic of gradually increasing and decreasing amplitude in the time domain. In the stimulation waveform of the present application, by adjusting the duration lengths of t0, t1, t2, and t3, synchronization with the rhythm of muscle movement can be achieved. The acquisition of muscle signal rhythm mainly adopts electromyographic electrophysiological sensors, which directly collect muscle electrical signals at both ends of the electrodes, and calculate the amplitude change cycle and other movement rhythms through amplitude analysis in the time domain; the muscle rhythm can also be obtained through analysis of the power spectrum energy in the frequency domain. The advantage of electrical stimulation with the same muscle movement rhythm is that it can fully train the muscles and make the patient more comfortable. For example, if the stimulation rhythm is faster than the muscle movement rhythm itself, it is easy to cause muscle fatigue and may even damage the effect. Generally speaking, the stimulation rhythm is best synchronized with the muscle movement rhythm.

[0049] Generally speaking, the length of t0+t1+t3 and t2 is related to the type of movement (slow control / fast burst), which is on the order of several hundred milliseconds to several seconds, and can be synchronized with the rhythm of muscle movement. In addition, the frequency component of the electromyographic signal is usually between 0 and 500 Hz, and is typically concentrated in the range of 20 Hz to 150 Hz. Therefore, in the stimulation waveform of the present application, the range of f can be 0 to 500 Hz, and is preferably set between 20 Hz and 150 Hz. In addition, under certain circumstances, explosive high-frequency stimulation can cause muscles (such as the genioglossus muscle) to contract violently, which is suitable for short-term intensive treatment of patients with severe OSA. For this reason, f can also be a high-frequency model greater than 1 kHz, and typical values may include 10 kHz, 20 kHz, etc. The pulse width T is usually between 0.01% and 50% of 1 / f. A = 0 to 60 mA (current amplitude) or 0 to 30 V (voltage amplitude). As an example of a typical set of parameters, T=100 μs, f=20 Hz, A=10 mA, t0=1 s, t1=4 s, t2=4 s, t3=1 s.

[0050] In the tongue muscle stimulator 1 of the present application, a set of basic stimulation parameters and adjustable ranges predetermined according to clinical experiments, etc. can be pre-set. Since each user has different perceptions and tolerances for stimulation, the user is allowed to make appropriate adjustments during use to meet the best individual usage experience. This corresponds to open-loop operation. In addition, the controller 13 can also automatically calculate the stimulation waveform based on a predetermined algorithm according to the parameters from the sensor module 11. This corresponds to closed-loop operation. Of course, in addition to the calculation of the stimulation waveform by the controller 13, it can also be completed on an electronic device or in the cloud. This will be described in detail later.

[0051] Figure 5 FIG. 1 shows a method for generating a stimulation waveform in the tongue muscle stimulator 1 of the present application. Figure 5 As shown, the method starts in step S101. In step S102, the configured basic parameters and adjustment range are used as default parameters. This corresponds to open-loop operation. At the same time, in step S103, data is collected by the sensor module. In step S104, the data is processed by a data processing device (such as an analog-to-digital conversion device, etc.), for example, analog-to-digital conversion is performed. In step S105, the user's settings are accepted to determine whether to execute the closed-loop operation mode. If the judgment is yes, the step proceeds to S106 to determine whether closed-loop parameter adjustment is performed. If not, the step proceeds to step S108 to generate a stimulation waveform based on the default parameters. In step S106, if closed-loop adjustment parameters are required, parameter adjustment is performed in step S107 according to the corresponding algorithm. Then in step S108, a stimulation waveform is generated based on the adjusted parameters. If closed-loop adjustment parameters are not required in step S106, the step proceeds directly to step S108 to generate a stimulation waveform based on the default parameters.

[0052] Application Example 1

[0053] Example 1 is the application of the tongue muscle stimulator 1 of the present application in genioglossus muscle training. Genioglossus muscle training is a common method for treating obstructive sleep apnea. In application, the electrophysiological signal sensor of the sensor module 11, such as an electrode, collects the electrophysiological signal of the genioglossus muscle. The analog-to-digital conversion module converts the collected electrophysiological analog signal into a digital signal. In addition, a sliding window can be used to filter and perform power spectrum conversion on the digital signal.

[0054] Assume that the power spectrum energy of the muscle electrical signal in the constant output period t1 of the treatment cycle is Pt1, and the power spectrum energy of the muscle electrical signal in the treatment interval period t2 is Pt2. The ratio of Pt1 / Pt2 can be used to indicate the intensity of muscle training. Typically, if the power spectrum energy ratio Pt1 / Pt2 is greater than 1.5, it can be considered effective training. The larger the power spectrum energy ratio value, the more sufficient the training. However, in order to avoid fatigue caused by excessive muscle training, the value of Pt1 / Pt2 should not exceed 10. It is more preferred that the value of Pt1 / Pt2 is controlled between 2 and 6. Therefore, by dynamically adjusting Pt1 / Pt2 within a reasonable range, it is possible to balance training intensity and muscle recovery and reduce adaptive attenuation.

[0055] In closed-loop control, the stimulation pulse width T, stimulation amplitude A, frequency f, and t0-t3 of the next treatment cycle can be adjusted by the value of Pt1 / Pt2 of the previous treatment cycle. According to practice, long-term use of the method of increasing the stimulation amplitude to increase training intensity will lead to muscle fatigue. Specifically, during the treatment process, the ratio of Pt1 / Pt2 will gradually decrease. In response to this situation, the rate of change of the Pt1 / Pt2 ratio over time, for example, the ratio of the values of Pt1_1 / Pt2_1 (the most recent treatment) and Pt1_0 / Pt2_0 (the previous treatment), is used as the frequency conversion coefficient to adjust the stimulation frequency f in the next treatment cycle, increase the treatment intensity, and achieve variable frequency stimulation.

[0056] Application Example 2

[0057] Example 2 is an application of the tongue muscle stimulator 1 of the present application in the treatment of snoring. The sensor module 11 of the tongue muscle stimulator 1 may include an electrophysiological acquisition sensor, a sound acquisition sensor, and may also include a respiratory acquisition sensor, a motion sensor, or any other sensor that can detect snoring, apnea events, or airway obstruction.

[0058] Snoring detection algorithms vary depending on the sensor used to collect data. For example, snoring detection based on electrophysiological signals primarily uses surface electromyography (SEM) to assess muscle tension. The sensor records changes in muscle tension, and the data undergoes preprocessing such as filtering, denoising, and artifact removal to obtain clean EMG signals. Based on the real-time requirements of the detection, an appropriate sliding time window is determined and the data is sliced. Typically, the sliding time window can be on the order of milliseconds to seconds. Simultaneously, the data is processed using wavelet transforms and short-time Fourier transforms to extract features in the time, frequency, and time-frequency domains. Typically, the root mean square (RMS) metric is used to reflect muscle activity intensity. Snoring typically causes a decrease in the RMS value. When the RMS falls below a predetermined threshold, snoring is detected. Similar to RMS, integrated electromyography (iEMG) and mean amplitude (MAV) can also reflect overall muscle activity intensity and use similar determination methods. The zero-crossing rate (ZCR) and EMG burst rate exhibit a continuous downward trend during snoring, so these can also be used as criteria for detection. In addition, classification algorithms based on machine learning and deep learning can also be used to determine snoring, such as SVM, KNN, logistic regression, random forest, CNN, long short-term memory network, etc.

[0059] In snoring detection based on sound collection, high-sensitivity MEMS microphones or capacitive microphones are used to adapt to low-frequency snoring sounds (usually concentrated in the range of 20Hz-1.5kHz). The snoring signal spectrum range can be met by 8-16kHz. In order to balance performance and data volume, the sound collection sensor is usually close to the bedside, pillow, etc. to ensure the quality of the sound signal and suppress environmental noise. Active noise reduction microphone arrays or beamforming technology can also be added to enhance the signal from the user's direction. In the data processing flow, first, the collected audio signal is preprocessed, mainly including: (1) Noise reduction: Using Wiener filtering, wavelet threshold noise reduction, spectral subtraction and other methods to remove background noise and other interference; (2) Endpoint detection: Using energy threshold, short-time energy and zero crossing rate to determine whether it is a valid sound segment; (3) Frame segmentation and windowing: The commonly used frame length is 20-40ms, with an overlap rate of 50%, such as Hamming window. Secondly, the sound signal is feature extracted: time domain features (short time energy (STE), zero crossing rate (ZCR), autocorrelation coefficient (ACF)), frequency domain features (power spectral density (PSD), peak frequency, spectrum centroid, bandwidth, skewness, kurtosis), time-frequency features (Mel-frequency cepstral coefficients (MFCC), wavelet packet power distribution (WPD)). Snoring is then detected through threshold judgment, machine learning classification algorithms, deep learning and other methods. Generally speaking, when computing power is relatively low, especially when the algorithm is integrated with wearable devices, threshold judgment is mainly used. Specifically, if the energy is greater than the threshold and the main frequency falls within the range of 80Hz-500Hz, accompanied by a repetitive rhythm (for example, 0.5 to 1.5 times / second), and the duration is greater than 0.3 seconds, it can usually be determined as snoring.

[0060] Respiratory motion can be detected using airflow sensors, strain sensors, accelerometers, radar sensors, fiber optic sensors, and other sensors. Snoring can then be detected based on respiratory motion. Preprocessing of these collected signals typically involves applying a bandpass filter (typically 0.1–0.5 Hz) to remove baseline drift and high-frequency interference, and segmenting / sliding windowing the data according to analysis windows of approximately 10–30 seconds. Feature extraction primarily involves extracting features such as respiratory cycle (abnormally prolonged or interrupted), respiratory rate (abnormally significantly decreased / intermittent), respiratory amplitude (abnormally decreased or asymmetric), I / O ratio (abnormally large variations), and apnea duration (abnormally significantly prolonged). For low-computing and low-power devices, threshold-based detection methods are primarily used. For example, if the respiratory amplitude is less than a set threshold for n consecutive seconds (e.g., more than 10 seconds), snoring may be detected. For scenarios with sufficient computing power, algorithms such as machine learning can be used.

[0061] Motion sensors generally play an auxiliary role, usually helping to detect changes in body position, etc., and are used for dynamic correction to improve detection accuracy.

[0062] Furthermore, the aforementioned methods enable multimodal snoring detection. By fusing electrophysiological, acoustic, and respiratory signals, they reduce the false positive rate of a single sensor (e.g., due to environmental noise interference) and can be used simultaneously to improve detection accuracy. During the specific algorithm analysis process, the signal preprocessing stage requires time synchronization of the different signals before subsequent calculations.

[0063] After confirming the presence of snoring, the stimulator is applied to the user. The parameters of the stimulation waveform can be controlled in an open-loop manner, and the parameters can be configured by a doctor or manufacturer based on clinical trials. If closed-loop stimulation is selected, the stimulator 1 will operate in real time while the patient sleeps, with the sensor module collecting various data and simultaneously performing real-time snoring detection. If snoring is detected, electrical stimulation is immediately initiated. The stimulation parameters can be adjusted in real time based on the intensity and frequency of snoring.

[0064] Application Example 3

[0065] Example 3 is the application of the tongue muscle stimulator 1 of the present application in swallowing training. In the application, the motion sensor is used to detect the movement amplitude during the swallowing process. The electrophysiological acquisition module is mainly used to collect muscle movement intensity. When the movement amplitude collected by the motion sensor is low, the electrical stimulation module actively stimulates the swallowing to assist swallowing during the swallowing process, and adjusts the treatment intensity through the muscle movement intensity collected by the electrophysiological acquisition module.

[0066] Figure 6 An embodiment of the stimulation circuit of the tongue muscle stimulator of the present application is shown. In the stimulation circuit, a safety resistor is set in series with the load. Under this setting mode, the safety resistor avoids overload short circuit caused by too low load, which can ensure that the equipment and the patient are in a safe state. Amplifier circuit 1 and amplifier circuit 2 are connected in parallel to the safety resistor and the load respectively. The voltages on amplifier circuit 1 and amplifier circuit 2 are measured by analog-to-digital converters ADC1 and ADC2 respectively. That is, ADC1 and ADC2 measure the voltages on the safety resistor and the load respectively.

[0067] In constant current or constant voltage stimulation mode, the voltage on the safety resistor and the voltage on the load are measured by ADC1 and ADC2. The current value flowing through the safety resistor is obtained by dividing the measured voltage on the safety resistor by the known safety resistor value. Since the load is connected in series with the safety resistor, the current value flowing through the load is also obtained. The impedance value of the load can be obtained by dividing the measured voltage value on the load by the current value. Traditional impedance testing requires the emission of a specific stimulation waveform for measurement, which may cause discomfort to the patient. The impedance test using this method can be measured in real time during the stimulation process, and can achieve the effect of non-inductive impedance measurement.

[0068] Furthermore, in the stimulation waveform of the present application, the execution period of the impedance measurement can be further limited to the t1 time of the stimulation waveform. By setting it in this way, it is possible to ensure that the voltage signal is measured in a stable output state, further improving the accuracy of the impedance measurement. In addition, it is also possible to take an average value of multiple measurements to further improve the accuracy of the impedance measurement. For example, multiple measurements can be taken within the t1 period, with the sampling measurement frequency equal to the frequency f of the stimulation waveform. Then, the average value of the multiple measurements is taken to obtain the final value.

[0069] Figure 7 A tongue muscle stimulation system 100 involved in the present application is shown. As shown in the figure, the tongue muscle stimulator 1 can communicate with the electronic device 2 through the communication module, receive data or instructions from the electronic device 2, and transmit treatment-related data to the electronic device 2. For example, the electronic device 2 can be an electronic device such as a smart phone, a tablet computer, or a desktop computer. The wireless communication connection can be near field communication (NFC), Bluetooth, WIFI, a mobile network, etc. The wired communication connection can include a common wired network, such as an optical fiber or other optical network, a cable network, a power line, etc.

[0070] A computer program, such as an application program specially developed for the tongue muscle stimulator 1 , can be run on the electronic device 2 . Figure 6 Screen shots 3 and 4 show the operating interface of the application. Through the operating interface, the user can operate the tongue muscle stimulator 1, such as setting parameters, performing treatment operations, etc.

[0071] The system 100 may also include a cloud device 5. The cloud device 5 is, for example, a server device that can receive and store data from the electronic device 2 and can transmit data and instructions to the electronic device 2. At least a portion of the calculations of the electronic device 2 can be performed on the cloud device 5. For example, when the computing power requirement is high, the electronic device 2 can send data to the cloud device 5, which performs the calculation and returns the result to the electronic device 2. The electronic device 2 can also upload and store data in the cloud device 5, which can be accessed by other terminals 6. For example, alternatively, the algorithm used for closed-loop control can be executed by the cloud device 5. The electronic device 2 uploads the data collected by the sensor to the cloud device, which then processes the uploaded data, calculates the optimized parameters, and sends them back to the tongue muscle stimulator 1. Of course, other terminals 6 can also send data and instructions to the electronic device 2 through the cloud device 5, thereby performing related operations on the tongue muscle stimulator 1. For example, doctors and equipment manufacturers with access rights can use other terminals 6 to understand the patient's treatment plan, treatment progress, and other related information, and can also retrieve and study the patient's physical parameters.

[0072] It is understandable that in order to implement the above functions, the electronic device includes hardware and / or software modules that perform the corresponding functions. In combination with the algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in a hardware or computer software driven hardware manner depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application in combination with the embodiments, but such implementation should not be considered to be beyond the scope of this application.

[0073] In this embodiment, the electronic device can be divided into functional modules according to the above-mentioned method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into a single processing module. The above-mentioned integrated modules can be implemented in the form of hardware. It should be noted that the module division in this embodiment is illustrative and is only a logical functional division. In actual implementation, other division methods may be used.

[0074] The above is only a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or replacements that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the scope of protection of the present application. In the absence of mutual contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples. These modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of each embodiment of the present application.

Claims

1. A tongue muscle stimulator, comprising: a sensor module, the sensor module comprising one or more sensors for detecting parameters related to the user and / or the surrounding environment; a controller that generates a control signal based at least on the parameter from the sensor module; a stimulation circuit, receiving a control signal from the controller and generating an electrical stimulation waveform; as well as one or more electrodes electrically connected to the stimulation circuit to provide electrical stimulation to the user's tongue muscles; It is characterized in that each cycle of the electrical stimulation waveform includes a first time period, a second time period and a third time period in sequence. During the first time period, the stimulation amplitude of the electrical stimulation waveform gradually increases from a first amplitude to a second amplitude, during the second time period, the stimulation amplitude maintains the second amplitude, and during the third time period, the stimulation amplitude gradually decreases from the second amplitude to a third amplitude.

2. The tongue muscle stimulator according to claim 1, wherein There is a treatment interval between adjacent cycles of the electrical stimulation waveform, during which no electrical stimulation is performed.

3. The tongue muscle stimulator according to claim 2, wherein The lengths of the first period, the second period, the third period and the treatment interval period are adjusted in real time according to the user's electromyographic signal rhythm.

4. The tongue muscle stimulator according to any one of claims 1 to 3, wherein The electrical stimulation waveform includes a waveform selected from the group consisting of a square wave, a sine wave, a triangle wave, an exponential wave, and a balanced asymmetric wave.

5. The tongue muscle stimulator according to claim 2 or 3, wherein: The power spectrum energy of the user's muscle electrical signal in the second time period is Pt1, and the power spectrum energy of the user's muscle electrical signal in the treatment interval period is Pt2, wherein the electrical stimulation waveform is adjusted so that 1.5≤Pt1 / Pt2≤10.

6. The tongue muscle stimulator according to claim 5, wherein The electrical stimulation waveform is adjusted so that 2≤Pt1 / Pt2≤6.

7. The tongue muscle stimulator according to claim 5, wherein Adjusting the electrical stimulation waveform includes adjusting at least one of the pulse width, amplitude, frequency, length of the first period, length of the second period, length of the third period, and length of the treatment interval period of the electrical stimulation waveform.

8. The tongue muscle stimulator according to claim 5, wherein The frequency of the electrical stimulation waveform is varied based on the change in Pt1 / Pt2 over time.

9. The tongue muscle stimulator according to any one of claims 1 to 3, characterized in that Snoring detection is performed based on the parameters from the sensor module, and in the presence of snoring, an electrical stimulation waveform suitable for snoring treatment is generated using a pre-stored algorithm.

10. The tongue muscle stimulator according to claim 9, wherein Snoring is detected based on at least one of an electrophysiological signal of the user, a sound signal near the mouth and nose of the user, and a respiratory movement signal of the user.

11. The tongue muscle stimulator according to any one of claims 1 to 3, characterized in that Based on the user's swallowing movement amplitude, a pre-stored algorithm is used to generate an electrical stimulation waveform suitable for swallowing training for swallowing training.

12. The tongue muscle stimulator according to any one of claims 1 to 3, characterized in that The stimulation circuit includes a safety resistor connected in series with a load, and the controller calculates an impedance value of the load based on a voltage across the safety resistor, a voltage across the load, and a resistance value of the safety resistor.

13. The tongue muscle stimulator according to claim 12, wherein Calculating the impedance value of the load is performed during the second time period.

14. A tongue muscle stimulation system comprising: The tongue muscle stimulator according to any one of claims 1 to 13; and An electronic device is capable of communicating with the tongue muscle stimulator, receiving data from the tongue muscle stimulator, and sending instructions to the tongue muscle stimulator to set the tongue muscle stimulator so that the tongue muscle stimulator performs treatment on the user.

15. The tongue muscle stimulation system according to claim 14, wherein: It also includes a cloud device that communicates with the electronic device, and the cloud device can receive and store data from the electronic device, and can transmit data and instructions to the electronic device.

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