CN117159925A

CN117159925A - Nerve stimulator control method and device based on human sleep state

Info

Publication number: CN117159925A
Application number: CN202311168179.7A
Authority: CN
Inventors: 徐天睿; 杨飞
Original assignee: Beijing Lingchuang Yigu Technology Development Co ltd
Current assignee: Beijing Lingchuang Yigu Technology Development Co ltd
Priority date: 2023-09-11
Filing date: 2023-09-11
Publication date: 2023-12-05

Abstract

The embodiment of the application discloses a method and a device for controlling a nerve stimulator based on a sleeping state of a human body, wherein the method comprises the following steps: acquiring sleep information of the patient in a first time period by sleep monitoring equipment; determining a target working mode of the nerve stimulator according to the sleep information, wherein the target working mode comprises a first working mode and a second working mode, the first working mode comprises an active balance mode and a passive balance mode, and the second working mode comprises a constant current mode and a constant voltage mode; and generating a stimulation instruction corresponding to the target working mode, and sending the stimulation instruction to the nerve stimulator so that the nerve stimulator outputs stimulation current to the treatment part of the patient according to the stimulation instruction. By adopting the embodiment of the application, the influence on the sleep of the patient can be avoided when the patient is treated.

Description

Nerve stimulator control method and device based on human sleep state

Technical Field

The application relates to the technical field of medical equipment, in particular to a neural stimulator control method and device based on a human sleep state.

Background

Currently, implantable neurostimulation systems mainly include neurostimulators placed in the body and energy controllers placed in the body. The energy controller and the nerve stimulator can carry out radio frequency communication and energy transmission, and the energy controller provides radio frequency electric energy for the nerve stimulator. On the basis, the energy controller provides a stimulation pulse instruction in real time to drive the stimulation electrode of the nerve stimulator, so that the nerve stimulator applies stimulation current to the treatment part of the patient.

In the process of outputting the stimulation current by the nerve stimulator, the first working mode and the second working mode work simultaneously, wherein the first working mode is divided into an active balance mode and a passive balance mode according to frequency. The higher frequency of the stimulation current output by the neurostimulator when in the active balance mode causes less nerve stimulation to the patient, but more power is consumed. In addition, the second operation mode is divided into a constant current mode and a constant voltage mode according to an output mode. The stimulation current output by the nerve stimulator in the constant current mode is more power-consuming than that output by the nerve stimulator in the constant voltage mode, and has less stimulation to the patient.

In order to save the electric quantity of the energy controller, the mode of the output current of the stimulator is generally set to be a first stimulation mode as a passive balance mode by default, and a second stimulation mode as a constant voltage mode. But control of the stimulus intensity is a matter of concern when the patient is in a sleep state. If the stimulus intensity is too high, the sleeping quality of the patient can be directly influenced, so that the patient can feel uncomfortable stimulus, and the sleeping quality of the patient is influenced.

Disclosure of Invention

The application provides a neural stimulator control method and device based on a human sleep state, which can avoid influencing the sleep of a patient when the patient is treated.

In a first aspect of the present application, the present application provides a neural stimulator control method based on a sleep state of a human body, applied to an energy controller disposed outside a patient, the energy controller being connected to a stimulator disposed inside the patient, the energy controller providing rf power to the stimulator, the neural stimulator control method based on the sleep state of the human body comprising:

acquiring sleep information of the patient in a first time period by sleep monitoring equipment;

determining a target working mode of the nerve stimulator according to the sleep information, wherein the target working mode comprises a first working mode and a second working mode, the first working mode comprises an active balance mode and a passive balance mode, and the second working mode comprises a constant current mode and a constant voltage mode;

and generating a stimulation instruction corresponding to the target working mode, and sending the stimulation instruction to the nerve stimulator so that the nerve stimulator outputs stimulation current to the treatment part of the patient according to the stimulation instruction.

By adopting the technical scheme, the sleep state of the patient can be known in real time by the sleep information of the patient acquired in the first time period. And determining a target working mode based on the sleep information, wherein the target working mode comprehensively considers the requirement of adopting different stimulation strategies aiming at different sleep states. The above process can monitor and determine the instantaneous sleep state of the patient. Different stimulation modes are adopted aiming at different sleep states, symptomatic drug delivery can be realized, and the treatment effect is improved. Meanwhile, the application of the constant-current mode and the constant-voltage mode can ensure the stability of stimulation or reduce the energy consumption. In summary, the scheme can realize real-time monitoring and response to the sleep state of the patient and symptomatically select the working mode, so that the influence on the sleep of the patient is avoided when the patient is treated.

Optionally, the determining, according to the sleep information, a target working mode of the neurostimulator includes:

determining a sleep stage of the patient according to the sleep information, and determining the target working mode according to the sleep stage; or alternatively, the first and second heat exchangers may be,

and calculating a sleep coefficient according to the sleep information, and determining the target working mode according to the sleep coefficient.

By adopting the technical scheme, the working mode is selected according to different sleep stages, so that the stimulation parameters can be better adapted to the treatment requirements of the stage. The sleep quality can be quantitatively evaluated by calculating the sleep coefficient, and coefficient values of different orders of magnitude correspond to different optimal working modes. Depending on the sleep coefficient selection mode, quantitative personalized therapy may be achieved. Both modes can realize individual mode selection according to the actual sleep state of a patient, so that the adjustment of the stimulation treatment parameters is more accurate.

Optionally, the sleep stage includes a wake stage, a shallow sleep stage, and a deep sleep stage, and the determining the target working mode according to the sleep stage includes:

when the sleep stage is the awake stage, determining that the first working mode is an active balance mode, and the second working mode is a constant current mode;

when the sleep stage is the shallow sleep stage, determining that the first working mode is an active balance mode, and the second working mode is a constant pressure mode;

and when the sleep stage is the deep sleep stage, determining that the first working mode is a passive balance mode, and the second working mode is a constant pressure mode.

By adopting the technical scheme, different mode combinations are adopted for different sleep stages, so that the treatment effect is ensured, and the personalized accurate treatment is realized. Strong stimulation during waking and weak stimulation during deep sleep, thus avoiding interference with sleep quality and simultaneously taking into account energy consumption control.

Optionally, the sleep information includes a heart rate, a body movement amplitude and a respiratory rate, the calculating a sleep coefficient according to the sleep information, and determining the target working mode according to the sleep coefficient includes:

determining a sleep coefficient based on the heart rate, the body movement amplitude, and the respiratory rate;

if the sleep coefficient is greater than a first threshold, determining that the first working mode of the nerve stimulator is an active balance mode and the second working mode is a constant current mode;

if the sleep coefficient is smaller than or equal to the first threshold value and larger than a second threshold value, determining that the first working mode of the nerve stimulator is a passive balance mode and the second working mode is a constant current mode, wherein the first threshold value is larger than the second threshold value;

if the sleep coefficient is smaller than or equal to the second threshold and larger than a third threshold, determining that the first working mode of the nerve stimulator is an active balance mode and the second working mode is a constant current mode, wherein the second threshold is larger than the third threshold;

And if the sleep coefficient is smaller than or equal to the third threshold value, determining that the first working mode of the nerve stimulator is a passive balance mode and the second working mode is a constant pressure mode.

By adopting the technical scheme, when the sleep coefficient is larger than the first threshold value, the patient is shown to be in a waking or shallow sleep state, at the moment, the active balance mode is selected to provide higher stimulation frequency, and meanwhile, the constant current mode is selected to ensure stable intensity. When the sleep coefficient is below the first threshold and above the second threshold, indicating that the patient is going to deeper sleep, a passive balance mode is selected to reduce the stimulation frequency while maintaining the constant current mode. If the sleep coefficient continues to drop but still is higher than the third threshold, the active balance and constant current mode is temporarily restored at this time, considering that the sleep unstable phase may be in. When the sleep coefficient eventually falls below the third threshold, the patient is instructed to go to deep sleep, at which time a passive balance and constant pressure mode is selected, providing a steady and weak stimulus. Therefore, through judging the sleep coefficient, the stimulation parameters can be customized according to the needs, the treatment effect is ensured, and the sleep quality can be minimally influenced. Realizing accurate individualized sleep treatment.

Optionally, the determining a sleep coefficient according to the heart rate, the body movement amplitude and the respiratory frequency includes:

substituting the heart rate, the body movement amplitude and the respiratory frequency into a preset formula to obtain the sleep coefficient;

wherein, the preset formula is:

SC＝A*(HR1-HR2) ² +B*log((MA1-MA2)+1)+C*(RR1-RR2)；

where SC represents a sleep coefficient, HR1 represents a heart rate, HR2 represents a standard heart rate, a represents a coefficient corresponding to the heart rate, MA1 represents a body movement amplitude, MA2 represents a standard body movement amplitude, B represents a coefficient corresponding to the body movement amplitude, RR1 represents a respiratory rate, RR2 represents a standard respiratory rate, and C represents a coefficient corresponding to the respiratory rate.

By adopting the technical scheme, the larger the heart rate deviation from the normal value is, the lighter the sleep is, the slight change can be reflected by the body movement amplitude by using the logarithmic relationship, and the sleep state is also prompted by the respiratory rate deviation from the normal state. The calculated sleep coefficients may numerically quantify the sleep quality. By calculating the sleep coefficient and comparing the sleep coefficient with the threshold value, the sleeping depth of the patient can be judged, and therefore the optimal stimulation mode is selected correspondingly.

Optionally, the method further comprises:

when the patient is in a waking stage, receiving feedback information of the patient, adjusting the target working mode according to the feedback information, generating an adjusting instruction of the adjusted target working mode, and sending the adjusting instruction to the nerve stimulator so that the nerve stimulator outputs stimulation current to a treatment part of the patient according to the adjusting instruction.

Through adopting above-mentioned technical scheme, when the state of waking up appears, can fix a position the problem reason fast, in time adjust the stimulation mode parameter, avoid the treatment to descend, improve patient's travelling comfort.

Optionally, the method further comprises:

according to the sleep information, adjusting target stimulation parameters of the target working mode;

generating an adjusting instruction corresponding to the target stimulation parameter, and sending the adjusting instruction to the nerve stimulator so that the nerve stimulator outputs stimulation current to the treatment part of the patient according to the adjusting instruction.

By adopting the technical scheme, the function of dynamically adjusting the target stimulation parameters based on the sleep information is realized by the alternative scheme. Since the optimal stimulation parameters are also different in different sleep states, the target stimulation parameters need to be optimized according to the detected sleep information to adapt to the specific sleep state of the patient.

In a second aspect of the present application, there is provided a neural stimulator control device based on a sleep state of a human body, the device comprising:

in a third aspect the application provides a computer storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform the above-described method steps.

In a fourth aspect of the application there is provided an energy controller comprising: a processor, a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the above-mentioned method steps.

In summary, one or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:

by adopting the technical scheme of the application, the sleep state of the patient can be known in real time by the sleep information of the patient acquired in the first time period. And determining a target working mode based on the sleep information, wherein the target working mode comprehensively considers the requirement of adopting different stimulation strategies aiming at different sleep states. The above process can monitor and determine the instantaneous sleep state of the patient. Different stimulation modes are adopted aiming at different sleep states, symptomatic drug delivery can be realized, and the treatment effect is improved. Meanwhile, the application of the constant-current mode and the constant-voltage mode can ensure the stability of stimulation or reduce the energy consumption. In summary, the scheme can realize real-time monitoring and response to the sleep state of the patient and symptomatically select the working mode, so that the influence on the sleep of the patient is avoided when the patient is treated.

Drawings

Fig. 1 is a schematic diagram of an application scenario of a neural stimulation system according to an embodiment of the present application;

FIG. 2 is a schematic diagram of a neural stimulation system according to an embodiment of the present application;

fig. 3 is a schematic flow chart of a neural stimulator control method based on a sleep state of a human body according to an embodiment of the present application;

fig. 4 is a schematic diagram of a neural stimulator control device according to an embodiment of the present application, which is based on a sleep state of a human body;

fig. 5 is a schematic structural diagram of a disclosed energy controller according to an embodiment of the present application.

Reference numerals illustrate: 500. an energy controller; 501. a processor; 502. a memory; 503. a user interface; 504. a network interface; 505. a communication bus.

Detailed Description

In order that those skilled in the art will better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments.

In describing embodiments of the present application, words such as "for example" or "for example" are used to mean serving as examples, illustrations, or descriptions. Any embodiment or design described herein as "such as" or "for example" in embodiments of the application should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "or" for example "is intended to present related concepts in a concrete fashion.

In the description of embodiments of the application, the term "plurality" means two or more. For example, a plurality of systems means two or more systems, and a plurality of screen terminals means two or more screen terminals. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating an indicated technical feature. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.

With aging population and changing lifestyle, the incidence of nervous system diseases such as parkinson's disease, epilepsy, depression, anxiety, etc. has a great influence on physical and mental health and quality of life of patients. The traditional treatment method has certain limitations, such as drug treatment, operation treatment and the like, and has the conditions of large side effect, unstable effect, difficult control and the like. Thus, new treatments are needed to improve the symptoms and quality of life of patients.

Along with the development of biomedical engineering, neuroscience and other fields, the implanted medical system is continuously improved and innovated, the treatment effect and the safety are continuously improved, and the implanted medical system becomes an important means for treating nervous system diseases, and the implanted electrical stimulation technology is used as a novel treatment means, and has wide application prospect and important clinical significance.

Implantable medical systems generally include: an implantable nerve electrical stimulation system (Deep Brain Stimulation, DBS), an implantable cerebral cortex electrical stimulation system (Cortical Neural Stimulation, CNS), an implantable spinal cord electrical stimulation system (Spinal Cord Stimulation, SCS), an implantable sacral nerve electrical stimulation system (Sacral Nerve Stimulation, SNS), an implantable vagal nerve electrical stimulation system (Vagus Nerve Stimulation, VNS), an implantable cardiac electrical stimulation system (Implantable Cardiac Stimulation System, ICSS) and the like, and a nerve stimulator plays a vital role as a core component of the electrical stimulation system.

On the basis of the above, the embodiment of the application provides a neural stimulator control method based on a sleep state of a human body, please refer to fig. 1, which shows an application scene schematic diagram of a neural stimulation system provided by an embodiment of the application, for example, the neural stimulation system can comprise a neural stimulator, an energy controller, a terminal and a server, the neural stimulator is in wireless connection with the energy controller through a bluetooth module, the energy controller outputs radio frequency energy to the neural stimulator through a radio frequency antenna so as to provide electric energy for the neural stimulator during working, and in addition, the energy controller is also internally provided with a communication module which can be directly or indirectly connected with the terminal and the server through a wired or wireless network.

Illustratively, as shown in fig. 1, a neurostimulator is disposed at an a site in a patient, and a stimulating electrode is disposed in the neurostimulator and outputs stimulating current to a treatment site, b treatment site, and c treatment site via a lead wire for electrical stimulation treatment.

The terminal may be, for example, an energy controller with a neural stimulation-type target application installed, typically for use by doctors and patients. The doctor and the patient can control the energy controller through the terminal, thereby indirectly controlling the work of the nerve stimulator, and also can acquire the real-time operation data of the nerve stimulator collected by the energy controller and visually displayed on the doctor or the patient. The terminal includes, but is not limited to: android (Android) system Devices, mobile operating system (IOS) Devices developed by apple corporation, personal Computers (PCs), world Wide Web (Web) Devices, smart Wearable Devices (WD), and the like.

The server may be, for example, a background server of the neural stimulation class target application for providing background services for the energy controllers and terminals. The server may receive and store various aspects of the data of the neurostimulator and the energy controller during treatment, so that the patient's condition may be summarized and analyzed. The server can be a server, a server cluster formed by a plurality of servers, or a cloud computing service center, and the server can communicate with the energy controller and the terminal through a wired or wireless network.

It should be noted that, fig. 1 illustrates the implantation position of the neurostimulator in the human body, and the exemplary manner of each treatment site is only exemplary, and in a possible embodiment, the specific implantation position of the neurostimulator in the human body, and the treatment position corresponding to the stimulation current output by the stimulation electrode need to be determined according to the specific type of the neurostimulator and the condition of the patient.

The above embodiments correspondingly describe the application scenario of the neural stimulation system provided by the embodiments of the present application, so that, in order to enable those skilled in the art to better understand the principle of the neural stimulation method provided by the embodiments of the present application, the following describes the information transmission process between the neural stimulators, please refer to fig. 2, fig. 2 shows a structure diagram of the neural stimulation system provided by the embodiments of the present application.

As shown in fig. 2, the energy controller includes a first processor, an accelerometer, and a gyroscope. The accelerometer and gyroscope are used to collect the activity status data of the user in real time and transmit to the first processor when the energy controller is worn on the patient. The first processor is used for determining the posture of the patient according to the collected activity state data. The second processor in the nerve stimulator is mainly used for receiving the control instruction input by the energy controller, converting the control instruction into corresponding parameters and controlling the stimulation electrode to output stimulation current by the parameters.

The second processor in the nerve stimulator receives a stimulation instruction sent by the energy controller through the second Bluetooth module through the first Bluetooth module, and the second processor can convert the stimulation instruction from analog quantity to digital quantity through a self-contained analog-to-digital converter, so that data processing analysis is carried out on the stimulation pulse instruction, a stimulation waveform is generated, and the stimulation waveform is converted from digital voltage signals to analog voltage signals through a self-contained digital-to-analog conversion circuit. When the stimulation instruction is a voltage parameter, the second processor outputs the analog voltage signal to the proportional amplifying circuit so as to adjust the voltage parameter, obtain a voltage stimulation waveform and output the voltage stimulation waveform to the electrode control circuit; when the stimulation instruction is a current parameter, the second processor converts the analog voltage signal into an analog current signal to obtain a current stimulation waveform, and outputs the current stimulation waveform to the electrode control circuit. The electrode control circuit can configure the switching state and the electrode direction of the stimulation electrode according to the stimulation waveform, so as to control the stimulation electrode to output stimulation current to the treatment part.

Further, the nerve stimulator is further provided with a detection module, the detection module can acquire the operation parameters of the stimulation electrode, the operation parameters are transmitted to the energy controller through a transmission path between the second processor, the first Bluetooth module, the second Bluetooth module and the first processor, the energy controller can transmit the operation parameters to the terminal and/or the server through the external communication module, and then the operation information of the nerve stimulator can be fed back to the terminal and the server through the energy controller.

In addition, the nerve stimulator in the nerve stimulation system provided by the embodiment of the application does not need to be additionally provided with a battery for power supply, and only needs to be provided with a radio frequency signal by the energy controller, so that the working electric energy of the nerve stimulator can be met, and the volume of the nerve stimulator is further reduced.

Specifically, the energy controller sends radio frequency signals to a first radio frequency antenna in the nerve stimulator through a second radio frequency antenna, and the first radio frequency antenna inputs the received radio frequency signals to the impedance matching circuit. The impedance matching circuit is used for adjusting the impedance in the circuit, so that the impedance between the radio frequency signal and the circuit is matched, thereby reducing the energy loss caused by signal reflection in the transmission process of the signal, and further improving the efficiency and quality of signal transmission. The radio frequency signal is input to the rectifying and energy-storing circuit after passing through the impedance matching circuit. The rectification energy storage circuit is used for converting the radio frequency signal into electric energy and storing the electric energy so as to continuously provide the electric energy for the second processor.

The above description is made on the architecture of the neural stimulation system provided by the embodiment of the present application and the operation principle of each end under the architecture, and further, please refer to fig. 3, specifically, a flow chart of a neural stimulator control method based on a sleep state of a human body is provided, the method may be implemented by a computer program, may be implemented by a single chip microcomputer, may also be operated on the neural stimulation system, and the computer program may be integrated in the target application programs of the neural stimulator, the energy controller, the terminal and the server, or may also be operated as independent tool applications, and specifically, the method includes steps 301 to 304, where the steps are as follows:

Step 301: the sleep monitoring device acquires sleep information of a patient in a first time period.

To dynamically monitor the sleep state of a patient, it is necessary to acquire sleep information of the patient in real time. The patient may be configured with a sleep monitoring device that may include sensors for detecting physiological indicators of the patient during sleep, such as heart rate, respiratory rate, amplitude of motion, etc.

Specifically, the sleep monitoring device is connected with the energy controller, and after the patient falls asleep, the sleep monitoring device starts working and configures working time length, namely first time length. The first time period may be preset or may be set according to different patients. And in the first time period, the sleep monitoring equipment continuously collects sleep information such as heart rate, respiratory rate, action amplitude and the like of the patient and transmits the sleep information to the energy controller in real time. The energy controller receives the sleep information and stores and processes the sleep information. By collecting the sleep information of the patient in a continuous period of time, the change condition of the physiological indexes of the patient from falling asleep to different sleep stages can be monitored, and a basis is provided for the follow-up determination of the working mode of the stimulator, so that the dynamic adjustment of the working mode of the nerve stimulator is realized.

Step 302: according to the sleeping information, determining a target working mode of the nerve stimulator, wherein the target working mode comprises a first working mode and a second working mode, the first working mode comprises an active balancing mode and a passive balancing mode, and the second working mode comprises a constant current mode and a constant voltage mode.

In the process of outputting the stimulation current by the nerve stimulator, the energy controller mainly sends a stimulation instruction to the nerve stimulator. The second processor in the neural stimulator can read the stimulation parameters in the stimulation instructions, so that a stimulation waveform is generated according to the stimulation parameters, and then a stimulation current can be output to the treatment part of the patient according to the stimulation waveform by controlling the stimulation electrode. The energy controller can acquire the current residual electric quantity and the residual treatment duration of the patient every a period of time, so that the working mode of the controller for outputting the stimulation current is adjusted according to the residual treatment duration.

Specifically, from the viewpoint of the shape of the stimulus waveform, the stimulus waveform mainly consists of a forward waveform and a backward waveform, wherein the forward waveform refers to an electric signal waveform for generating a therapeutic effect in nerve electric stimulation treatment, and since charges are released in the process, the backward waveform opposite to the forward waveform needs to be output for charge neutralization, so that the charge balance in the patient is achieved.

The waveform is mainly composed of two parameters, namely waveform amplitude and waveform pulse width, the waveform amplitude refers to the magnitude of the stimulation current output by the stimulation electrode, and the waveform pulse width refers to the time width of the output stimulation current. In the embodiment of the application, parameters of a forward waveform are respectively defined as forward waveform amplitude and forward waveform pulse width; correspondingly, parameters of the backward waveform are respectively defined as backward waveform amplitude and backward waveform pulse width. Assuming that a stimulus waveform is composed of only one forward waveform and one backward waveform, the stimulus period of the stimulus waveform is the sum of the forward waveform pulse width and the backward waveform pulse width. Since the backward waveform needs to neutralize the charge released by the forward waveform, it can be inferred that the forward waveform pulse width=the backward waveform amplitude.

Further, by changing the forward waveform pulse width and the backward waveform pulse width, the frequency of the stimulation current output by the neural stimulator can be changed, and in the embodiment of the application, the working mode of the neural stimulator can be divided into an active balance mode and a passive balance mode according to the frequency of the stimulation current output by the neural stimulator.

In the active balance mode, the frequency of the output stimulation current of the nerve stimulator is controllable, namely, the electric charge generated by the forward waveform can be neutralized by adjusting the pulse width of the backward waveform and the amplitude of the backward waveform; in the passive balance mode of the nerve stimulator, the electrodes in the stimulating electrode group can be controlled to be in short circuit with the electrodes, so that the electric charges generated by the forward waveform are automatically eliminated. Thus, the frequency of the neural stimulator output stimulation current in the passive balance mode is low and uncontrollable.

In addition, the constant current mode and the constant voltage mode may be classified according to the manner in which the stimulation current is output.

When the nerve stimulator is in a constant current mode, the nerve stimulator can maintain constant current output without being blocked and influenced. Thus, if the impedance of the stimulation electrode to the treatment site changes, the intensity of the stimulation current will remain unchanged. Making the stimulation more stable and reducing pain or discomfort due to impedance changes. However, constant current mode generally requires a higher voltage to drive the current, which may result in faster battery consumption.

When the neurostimulator is in constant voltage mode, the neurostimulator maintains a constant voltage output. If the impedance changes, the current will change accordingly, possibly resulting in increased pain or discomfort to the patient. However, the constant voltage mode generally requires a lower voltage to drive the current, and thus consumes less power than the constant current mode.

Under different sleep states, the sensitivity degree of the patient to the stimulation is different, and the working mode of the nerve stimulator needs to be correspondingly adjusted so as to ensure the treatment effect. Based on the above embodiment, as an alternative embodiment, in step 302: this step of determining a target operating mode of the neurostimulator based on the sleep information may specifically further comprise the steps of:

step 401: and determining a sleep stage of the patient according to the sleep information, and determining a target working mode according to the sleep stage.

During sleep, the human body can undergo different sleep stages such as wakefulness, light sleep, deep sleep and the like. The degree of sensitivity of the human body to external stimuli is also different in different sleep stages. For example, during a deep sleep phase, the human body is less sensitive to external stimuli. If the stimulation intensity cannot be adjusted according to the sleep stage, the stimulation effect may be poor in the deep sleep stage. It is therefore necessary to detect sleep stages and to determine the mode of operation of the stimulator accordingly.

The current sleep stage can be judged through processing according to the sleep information such as the heart rate, the respiratory rate, the action amplitude and the like acquired in the previous step. For example, the light sleep stage has a stable heart rate and a low respiratory rate; the heart rate is further reduced in the deep sleep stage, the respiratory rate is reduced and uniform, and the action amplitude is minimum. From these characteristics, the current sleep stage can be determined. And then selecting a corresponding stimulator working mode according to the judged sleep stage.

The optimal stimulator mode of operation may be selected based on the actual sleep stage of the patient, providing the most appropriate stimulation intensity at the different stages. Ensures that sufficient stimulating effect is provided during light sleep without overstimulation during deep sleep. Thus, the treatment effect can be improved, and the comfort level of the patient can be improved.

Based on the above embodiment, as an alternative embodiment, step 401: the step of determining the target working mode according to the sleep stage may specifically further include the following steps:

step 501: when the sleep stage is the awake stage, the first working mode is determined to be an active balance mode, and the second working mode is determined to be a constant current mode.

In the awake stage, the cognitive and perceptual functions of the patient are stronger and can bear stronger stimulation. If a stimulus of sufficient intensity is not provided, the therapeutic effect is affected. At the same time, the physical activity is frequent in the awake stage, and the stimulus intensity needs to be controllable to avoid discomfort.

Specifically, after determining that the patient is in an awake phase, the first mode of operation of the stimulator is configured to be an active balance mode, such that the stimulation frequency can be adjusted by controlling the backward waveform parameters. The second working mode is set to be a constant current mode, so that stable stimulation current can be provided, interference resistance is avoided, and stimulation intensity fluctuation is avoided in the process of activity.

The active balance mode may provide a strong and controllable stimulation frequency depending on the needs of the awake phase. The constant current mode can keep the stimulation current stable. The combination of the two modes can improve the stimulation treatment effect and comfort in the awake stage.

Step 502: when the sleep stage is a shallow sleep stage, the first working mode is determined to be an active balance mode, and the second working mode is determined to be a constant voltage mode.

In the light sleep stage, the patient is sensitive to external stimuli and cannot use too strong stimuli. Meanwhile, the energy-saving mode is required to be adopted in consideration of long light sleep time.

Specifically, after determining that the patient is in a light sleep stage, the first mode of operation of the stimulator is configured to be an active balance mode, providing a moderate stimulation intensity by controlling the stimulation frequency. The second working mode is set to be a constant-voltage mode, so that energy consumption can be reduced compared with a constant-current mode, and the device is more suitable for long-time working.

The active balance mode may provide a modest stimulation frequency depending on the requirements of the light sleep stage. The constant voltage mode may reduce battery consumption. The combination of the two modes allows for a safe and energy efficient stimulation therapy during the light sleep stage.

Step 503: when the sleep stage is a deep sleep stage, the first working mode is determined to be a passive balance mode, and the second working mode is determined to be a constant pressure mode.

During the deep sleep phase, the patient is least sensitive to external stimuli and needs to provide a minimum stimulus intensity. Meanwhile, the deep sleep time is considered to be longer, and a more energy-saving mode needs to be adopted.

Specifically, after the patient is determined to enter a deep sleep stage, the first working mode of the stimulator is configured to be a passive balance mode, and the minimum stimulation frequency is provided through electrode short circuit. The second mode of operation still employs a constant voltage mode to conserve battery power.

The passive balance mode may provide the lowest stimulation frequency depending on the characteristics of the deep sleep phase. The constant voltage mode can greatly reduce battery consumption. The combination of the two modes allows for a safe and efficient stimulation therapy during the deep sleep phase.

Step 402: and calculating a sleep coefficient according to the sleep information, and determining a target working mode according to the sleep coefficient.

The sleep coefficient is an important real-time index for evaluating sleep quality, and can reflect the sleep state of the current patient. Different sleep coefficients represent different current sleep quality, and different stimulator operating modes should be selected accordingly to dynamically adapt to the change of sleep quality.

According to the sleep information such as heart rate, respiration, action and the like acquired in real time, the proportion of deep sleep at the current moment can be dynamically calculated, and a real-time sleep coefficient is generated. The real-time sleep coefficients can dynamically reflect the changes in sleep quality. Based on the method, the dynamic switching of the working mode can be realized, and the instantaneous sleep state of the patient can be accurately docked, so that the individualized current state stimulation treatment can be carried out.

Based on the above embodiment, as an alternative embodiment, in step 402: the step of calculating the sleep coefficient according to the sleep information may specifically further include the steps of:

step 601: sleep coefficients are determined based on heart rate, body movement amplitude, and respiratory rate.

In one possible implementation, the heart rate, body movement amplitude and respiratory rate can be substituted into a preset formula to obtain a sleep coefficient;

wherein, the preset formula is:

SC＝A*(HR1-HR2) ² +B*log((MA1-MA2)+1)+C*(RR1-RR2)；

In particular, heart rate, body movement amplitude and respiratory rate are key physiological parameters for assessing sleep states. The sleep state can be reflected more comprehensively and accurately by combining and utilizing the three parameters. An objective sleep coefficient can be obtained through a quantitative calculation formula, and errors caused by subjective judgment are avoided.

Further, the preset formula comprehensively considers three key physiological signals affecting sleep quality: heart rate, body movement amplitude and respiratory rate. Heart rate: the difference from the standard heart rate reflects the depth of sleep, with a heart rate closer to the standard heart rate indicating deeper sleep. Body movement amplitude: a logarithmic relationship is used because the influence of body movement amplitude on sleep quality is not linear. Smaller body movements indicate deeper sleep. Respiratory rate: the difference from the standard breathing rate also reflects the depth of sleep, with closer breathing rates to the standard indicating deeper sleep.

Step 602: if the sleep coefficient is greater than the first threshold, determining that the first working mode of the nerve stimulator is an active balance mode and the second working mode is a constant current mode.

Step 603: if the sleep coefficient is smaller than or equal to the first threshold value and larger than the second threshold value, determining that the first working mode of the nerve stimulator is a passive balance mode and the second working mode is a constant current mode, wherein the first threshold value is larger than the second threshold value.

Step 604: if the sleep coefficient is smaller than or equal to the second threshold value and larger than the third threshold value, determining that the first working mode of the nerve stimulator is an active balance mode and the second working mode is a constant current mode, wherein the second threshold value is larger than the third threshold value.

Step 605: if the sleep coefficient is smaller than or equal to the third threshold value, the first working mode of the nerve stimulator is determined to be a passive balance mode, and the second working mode is determined to be a constant pressure mode.

In particular, because of the differences in physiological conditions and therapeutic needs of patients in different sleep states, if a single stimulation pattern is used, the need for personalized therapy cannot be met. By setting a plurality of sleep coefficient threshold intervals, the fine change of the sleep state can be detected more finely, so that the optimal stimulation mode is selected correspondingly, and accurate adjustment of the medicine under symptoms is realized.

And according to the previously acquired sleep physiological information and a preset calculation formula, calculating the sleep coefficient of the patient in real time. Comparing the calculated sleep coefficient with a preset threshold value, and judging a numerical interval in which the sleep coefficient is located, wherein the method comprises the following steps of: four sections that are greater than a first threshold, equal to or less than the first threshold and greater than a second threshold, equal to or less than the second threshold and greater than a third threshold, and equal to or less than the third threshold.

According to the interval judgment result of the sleep coefficient, the working mode of the nerve stimulator is correspondingly determined:

if the sleep coefficient is greater than the first threshold, determining that the sleep coefficient is in a wake state and a shallow sleep state, and determining that the first working mode is an active balance mode at the moment so as to provide a strong and controllable stimulation frequency; and simultaneously determining the second working mode as a constant current mode so as to provide stable stimulation intensity.

If the sleep coefficient is smaller than or equal to the first threshold value and larger than the second threshold value, judging a moderate sleep state, and determining the first working mode to be a passive balance mode at the moment so as to provide lower stimulation frequency; and simultaneously, a constant current mode is kept to ensure the stability of the stimulus intensity.

If the sleep coefficient is smaller than or equal to the second threshold value and larger than the third threshold value, the deep sleep is judged to be early, and at the moment, the active balance and constant current mode is restored, and stronger stimulation is provided.

If the sleep coefficient is smaller than or equal to the third threshold, the sleep coefficient is judged to be the middle and later stage of deep sleep, at the moment, the first working mode is determined to be a passive balance mode so as to provide the minimum stimulus, and the first working mode is switched to a constant pressure mode so as to reduce energy consumption.

Step 303: and generating a stimulation instruction corresponding to the target working mode, and sending the stimulation instruction to the nerve stimulator so that the nerve stimulator outputs stimulation current to the treatment part of the patient according to the stimulation instruction.

On the basis of the above embodiment, as an optional embodiment, the neural stimulator control method based on the sleep state of the human body may further include the steps of:

step 701: and adjusting target stimulation parameters of the target working mode according to the sleep information.

Because the physiological conditions under different sleep states are different, after the working mode of the nerve stimulator is adjusted, the stimulation parameters are also required to be individually adjusted to achieve the optimal treatment effect.

Specifically, sleep information of the patient, such as heart rate, respiratory rate, body movement amplitude and the like, is continuously acquired, and the information is analyzed in real time to judge the current sleep state of the patient. According to the judged sleep state, inquiring a stored big data statistical model, and searching the optimal stimulation parameters under the sleep state, including the optimal value ranges of the parameters such as stimulation intensity, pulse width, frequency and the like. And combining the optimal parameter range given by the model and the experience of doctors, determining the optimal stimulation parameters of the specific patient in the current sleep state, and updating the optimal stimulation parameters serving as target stimulation parameters into the working mode configuration of the stimulator.

Step 702: and generating an adjusting instruction corresponding to the target stimulation parameter, and sending the adjusting instruction to the nerve stimulator so that the nerve stimulator outputs stimulation current to the treatment part of the patient according to the adjusting instruction.

In one possible embodiment, when the patient is in a waking stage, feedback information of the patient is received, a target working mode is adjusted according to the feedback information, an adjustment instruction of the adjusted target working mode is generated, and the adjustment instruction is sent to the neurostimulator, so that the neurostimulator outputs stimulation current to a treatment site of the patient according to the adjustment instruction.

When the patient is awake, indicating that there may be discomfort to the current stimulation pattern, immediate adjustment is required to avoid a decrease in the therapeutic effect. By analyzing the feedback information of the patient, the cause of the arousal can be judged and the mode can be adjusted accordingly.

Specifically, when a patient is monitored to be awake, the patient feedback module is activated immediately. Thereby collecting patient feedback information, including mainly pain level, discomfort location, etc. The feedback information is analyzed to find out the parameters of the stimulation pattern, such as excessive intensity, which may cause arousal. And adjusting parameters causing discomfort, and generating an adjusted target stimulation mode. Such as decreasing the stimulus intensity. And sending the adjusted mode instruction to a stimulator, and immediately adjusting the mode output by the stimulator.

By collecting and analyzing the patient feedback in time, the cause of discomfort can be found out and the mode can be adjusted, so that the reduction of the treatment effect is avoided and the comfort of the patient is improved.

The embodiment of the application also provides a neural stimulator control device based on the human sleep state, please refer to fig. 4, fig. 4 is a schematic diagram of the neural stimulator control device based on the human sleep state disclosed in the embodiment of the application. The device comprises: sleep information acquisition module, target working mode confirm the module and stimulate the instruction generation module, wherein:

the sleep information acquisition module is used for acquiring sleep information of the patient in a first time period by the sleep monitoring equipment;

the target working mode determining module is used for determining a target working mode of the nerve stimulator according to the sleeping information, wherein the target working mode comprises a first working mode and a second working mode, the first working mode comprises an active balancing mode and a passive balancing mode, and the second working mode comprises a constant-current mode and a constant-voltage mode;

and the stimulation instruction generation module is used for generating a stimulation instruction corresponding to the target working mode and sending the stimulation instruction to the nerve stimulator so that the nerve stimulator outputs stimulation current to the treatment part of the patient according to the stimulation instruction.

On the basis of the above embodiment, as an optional embodiment, the target operation mode determining module may further include:

a sleep stage determining unit configured to determine a sleep stage of the patient according to the sleep information, and determine the target working mode according to the sleep stage;

and the sleep coefficient calculation unit is used for calculating a sleep coefficient according to the sleep information and determining the target working mode according to the sleep coefficient.

On the basis of the above embodiment, as an alternative embodiment, the sleep stage determining unit may further include:

the first target working mode determining subunit is used for determining that the first working mode is an active balance mode when the sleep stage is the awake stage, and the second working mode is a constant current mode;

the second target working mode determining subunit is used for determining that the first working mode is an active balance mode when the sleep stage is the shallow sleep stage, and the second working mode is a constant pressure mode;

and the third target working mode determining subunit is used for determining that the first working mode is a passive balance mode and the second working mode is a constant pressure mode when the sleep stage is the deep sleep stage.

On the basis of the above embodiment, as an optional embodiment, the sleep coefficient calculating unit may specifically further include:

the sleep coefficient calculating subunit is used for substituting the heart rate, the body movement amplitude and the respiratory frequency into a preset formula to obtain the sleep coefficient;

wherein, the preset formula is:

SC＝A*(HR1-HR2) ² +B*log((MA1-MA2)+1)+C*(RR1-RR2)；

A first target working mode determining subunit, configured to determine that the first working mode of the neurostimulator is an active balance mode and the second working mode is a constant current mode if the sleep coefficient is greater than a first threshold;

a second target working mode determining subunit, configured to determine that, if the sleep coefficient is less than or equal to the first threshold and greater than a second threshold, the first working mode of the neurostimulator is a passive balance mode, and the second working mode is a constant current mode, where the first threshold is greater than the second threshold;

A third target working mode determining subunit, configured to determine that, if the sleep coefficient is less than or equal to the second threshold and greater than a third threshold, the first working mode of the neurostimulator is an active balance mode, and the second working mode is a constant current mode, where the second threshold is greater than the third threshold;

and the fourth target working mode determining subunit is configured to determine that the first working mode of the neurostimulator is a passive balance mode and the second working mode is a constant voltage mode if the sleep coefficient is less than or equal to the third threshold.

On the basis of the above embodiment, as an optional embodiment, the neural stimulator control device based on the sleep state of the human body may further include:

the system comprises a waking stage feedback module, a neural stimulator and a control module, wherein the waking stage feedback module is used for receiving feedback information of a patient when the patient is in a waking stage, adjusting the target working mode according to the feedback information, generating an adjusting instruction of the adjusted target working mode, and sending the adjusting instruction to the neural stimulator so that the neural stimulator outputs stimulation current to a treatment part of the patient according to the adjusting instruction;

The target stimulation parameter adjusting module is used for adjusting target stimulation parameters of the target working mode according to the sleep information; and the adjusting instruction generation module is used for generating an adjusting instruction corresponding to the target stimulation parameter and sending the adjusting instruction to the nerve stimulator so that the nerve stimulator outputs stimulation current to the treatment part of the patient according to the adjusting instruction.

It should be noted that: in the device provided in the above embodiment, when implementing the functions thereof, only the division of the above functional modules is used as an example, in practical application, the above functional allocation may be implemented by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to implement all or part of the functions described above. In addition, the embodiments of the apparatus and the method provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the embodiments of the method are detailed in the method embodiments, which are not repeated herein.

The application also discloses an energy controller. Referring to fig. 5, fig. 5 is a schematic structural diagram of an energy controller according to an embodiment of the present disclosure. The energy controller 500 may include: at least one processor 501, at least one network interface 504, a user interface 503, a memory 502, at least one communication bus 505.

Wherein a communication bus 505 is used to enable the connected communication between these components.

The user interface 503 may include a Display screen (Display) and a Camera (Camera), and the optional user interface 503 may further include a standard wired interface and a standard wireless interface.

The network interface 504 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.

Wherein the processor 501 may include one or more processing cores. The processor 501 utilizes various interfaces and lines to connect various portions of the overall server, perform various functions of the server and process data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 502, and invoking data stored in the memory 502. Alternatively, the processor 501 may be implemented in hardware in at least one of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 501 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), and a modem, etc. The CPU mainly processes an operating system, a user interface diagram, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 501 and may be implemented by a single chip.

The Memory 502 may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 502 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). Memory 502 may be used to store instructions, programs, code sets, or instruction sets. The memory 502 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described various method embodiments, etc.; the storage data area may store data or the like involved in the above respective method embodiments. The memory 502 may also optionally be at least one storage device located remotely from the processor 501. Referring to fig. 5, an operating system, a network communication module, a user interface module, and an application program of a neural stimulator control method based on a sleep state of a human body may be included in a memory 502, which is a computer storage medium.

In the energy controller 500 shown in fig. 5, the user interface 503 is mainly used for providing an input interface for a user, and acquiring data input by the user; and the processor 501 may be configured to invoke the memory 502 to store an application program of a neural stimulator control method based on a sleep state of the human body, which when executed by the one or more processors 501, causes the controller 500 to perform the method as described in one or more of the above embodiments. It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present application is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all of the preferred embodiments, and that the acts and modules referred to are not necessarily required for the present application.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.

In the several embodiments provided by the present application, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, such as a division of units, merely a division of logic functions, and there may be additional divisions in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some service interface, device or unit indirect coupling or communication connection, electrical or otherwise.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in whole or in part in the form of a software product stored in a memory, comprising several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method of the various embodiments of the present application. And the aforementioned memory includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a magnetic disk or an optical disk.

The foregoing is merely exemplary embodiments of the present disclosure and is not intended to limit the scope of the present disclosure. That is, equivalent changes and modifications are contemplated by the teachings of this disclosure, which fall within the scope of the present disclosure. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure.

This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a scope and spirit of the disclosure being indicated by the claims.

Claims

1. A neural stimulator control method based on a sleep state of a human body, which is characterized by being applied to a controller arranged outside a patient, wherein the controller is connected with a stimulator arranged in the patient, a state detection device arranged outside the patient and a user terminal, the controller supplies radio frequency electric energy to the stimulator, and the neural stimulator control method based on the sleep state of the human body comprises the following steps:

2. The method for controlling a neurostimulator based on a sleep state of a human body according to claim 1, wherein said determining a target operation mode of the neurostimulator according to the sleep information comprises:

3. The method of claim 2, wherein the sleep stages include a awake stage, a light sleep stage, and a deep sleep stage, the determining the target operation mode according to the sleep stage comprising:

4. The method of claim 2, wherein the sleep information includes heart rate, body movement amplitude, and respiratory rate, the calculating a sleep coefficient from the sleep information, and determining the target operation mode from the sleep coefficient comprises:

5. The method of claim 4, wherein determining the sleep coefficient based on the heart rate, the body movement amplitude, and the respiratory rate comprises:

wherein, the preset formula is:

SC＝A*(HR1-HR2) ² +B*log((MA1-MA2)+1)+C*(RR1-RR2)；

6. The method of controlling a neurostimulator based on sleep states of a human body of claim 1, further comprising:

7. The method of controlling a neurostimulator based on sleep states of a human body of claim 1, further comprising:

8. A neurostimulator control device based on a sleep state of a human body, the device comprising:

9. An energy controller comprising a processor, a memory, a user interface and a network interface, the memory for storing instructions, the user interface and the network interface for communicating to other devices, the processor for executing the instructions stored in the memory to cause the energy controller to perform the method of any of claims 1-7.

10. A computer readable storage medium storing instructions which, when executed, perform the method of any one of claims 1-7.