CN117982798A - Nerve stimulation control system, data processing method, device and computer equipment - Google Patents
Nerve stimulation control system, data processing method, device and computer equipment Download PDFInfo
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Abstract
The present application relates to a neural stimulation control system, a data processing method, an apparatus computer device, a storage medium and a computer program product. The system comprises an extracorporeal controller, an implant and at least one edge calculation module, wherein the extracorporeal controller is used for being in communication connection with the at least one edge calculation module, the implant is used for being in inductive connection with the extracorporeal controller through an induction coil, and the extracorporeal controller comprises: the edge calculation module is used for acquiring edge monitoring data of the monitoring part and calculating edge processing data according to the edge monitoring data; the external controller is used for acquiring a plurality of edge processing data and generating a nerve stimulation control signal according to the plurality of edge processing data; the implant is for contacting the peripheral nerve, the implant is for receiving the nerve stimulation control signal, and stimulating the peripheral nerve according to the nerve stimulation control signal. The system can reduce the maintenance and adjustment times of the peripheral nerve stimulation system in the use process.
Description
Technical Field
The present application relates to the technical field of medical devices, and in particular, to a neural stimulation control system, a data processing method, an apparatus computer device, a storage medium and a computer program product.
Background
Peripheral nerve stimulation (PERIPHERAL NERVOUS STIMULATION, PNS) devices are typically devices in which a wire-like electrode is placed alongside the peripheral nerve, the electrode being connected to an external device for the transmission of electrical signals, the electrical energy being able to be delivered from an implantable pulse generator (Implantable pulse generator) to the nerve via one or several electrodes.
At present, the peripheral nerve stimulation system consists of an implantable pulse generator, an electrode lead, a sensor lead and an external parameter program-controlled instrument, wherein the sensor lead is required to be arranged under the body surface of a user through operation so as to acquire data and conduct the data to the pulse generator, so that the pulse generator can provide electric stimulation pulses for a stimulation electrode. At the same time, the stimulation electrode also needs to be surgically placed at the peripheral nerve of the user to deliver the stimulation signal to the peripheral nerve.
However, in the current peripheral nerve stimulation system, due to the problems of limited service life of the power supply battery, the user needs to perform operations for replacing or adjusting the internal equipment many times, so that the peripheral nerve stimulation system needs to be maintained and adjusted many times in the using process, and many injuries are caused to a great extent.
Meanwhile, the sensors of the existing peripheral nerve stimulation system are collected and processed, and accurate nerve regulation and control cannot be achieved due to the reasons of placement positions, morphology and the like.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a neurostimulation control system, a data processing method, an apparatus computer device, a storage medium, and a computer program product that can reduce the number of maintenance adjustments of a peripheral neurostimulation system during use, and increase the accuracy of closed-loop stimulation.
In a first aspect, a neural stimulation control system, the system comprising an extracorporeal controller for communication connection with at least one of the edge calculation modules, an implant for inductive connection with the extracorporeal controller through an inductive coil, and at least one edge calculation module, wherein:
the edge calculation module is used for acquiring edge monitoring data of the monitoring part and calculating edge processing data according to the edge monitoring data;
The external controller is used for acquiring at least one piece of edge processing data and generating a nerve stimulation control signal according to the at least one piece of edge processing data;
the implant is configured to contact the peripheral nerve, the implant is configured to receive the nerve stimulation control signal, and to stimulate the peripheral nerve in accordance with the nerve stimulation control signal.
In one embodiment, the implant comprises an implant body and a stimulation electrode, the implant body comprising an in vivo induction coil, wherein:
the implant body is used for receiving the nerve stimulation control signal and the induction electric energy from the external controller through the internal induction coil and taking the induction electric energy as the power supply electric energy of the stimulation electrode;
The stimulation electrode is used for contacting the peripheral nerve so as to stimulate the peripheral nerve according to the nerve stimulation control signal.
In one embodiment, the implant further comprises an energy storage module for storing the inductive power and supplying power to the stimulation electrode if a preset condition is met.
The nerve stimulation control system comprises an external controller, an implant and at least one edge calculation module, wherein the edge calculation module is arranged at least one monitoring part of a user in a use state, can acquire edge monitoring data of the monitoring part, and calculates edge processing data according to the edge monitoring data, so that the current human body biological signal of the user is obtained, the sensor is prevented from being arranged under the body surface in a surgical mode, and the injury to the user is reduced. The external controller is in communication with the at least one edge calculation module and is capable of acquiring at least one edge processing data and generating a neural stimulation control signal based on the at least one edge processing data. The implant is directly arranged and contacted with the peripheral nerve and is connected with the external controller in an induction way through the induction coil, so that a nerve stimulation control signal is received, and the peripheral nerve is stimulated according to the nerve stimulation control signal. Therefore, the nerve stimulation control system is not affected by the service life of the power supply and other problems in the use process, and needs to be replaced or maintained, so that the maintenance and adjustment times of the peripheral nerve stimulation system in the use process are reduced, the damage to a user is further reduced, and the closed-loop stimulation accuracy is improved.
In a second aspect, a data processing method is applied to an extracorporeal controller, and the method includes:
Generating a reference moment and sending the reference moment to at least one edge calculation module;
acquiring edge processing data from at least one edge computing module, wherein the edge processing data is a data sequence generated according to the reference moment;
obtaining stimulation parameters, and updating the stimulation parameters according to at least one edge processing data under the condition that preset conditions are met;
and generating a neural stimulation control signal according to the edge processing data and the stimulation parameters.
In one embodiment, the generating the neural stimulation control signal based on the edge processing data and the stimulation parameters includes:
acquiring a preset stimulation mode, and monitoring a target state signal according to at least one edge processing data;
If the preset stimulation mode is a continuous stimulation mode, generating a nerve stimulation control signal for continuous stimulation within a first preset time period according to the stimulation parameter under the condition that the target state signal is monitored to be characterized as a preset state;
If the preset stimulation mode is the accurate stimulation mode, generating a nerve stimulation control signal which is continuously stimulated in a second preset time period according to the stimulation parameter under the condition that the target state signal is monitored to be characterized as an abnormal state.
In one embodiment, the updating the stimulation parameters according to at least one of the edge processing data when a preset condition is satisfied includes:
Acquiring a preset updating period and a preset threshold value, and measuring a characteristic value of a stimulation electrode according to the preset updating period;
and under the condition that the characteristic value of the stimulation electrode exceeds the preset threshold value, updating the stimulation parameter according to at least one of the edge processing data and the characteristic value of the stimulation electrode.
In a third aspect, the present application also provides a data processing apparatus for use in an extracorporeal controller, the apparatus comprising:
The time synchronization module is used for generating a reference moment and sending the reference moment to at least one edge calculation module;
The data acquisition module is used for acquiring edge processing data from at least one edge calculation module, wherein the edge processing data is a data sequence generated according to the reference moment;
The parameter determining module is used for acquiring the stimulation parameters and updating the stimulation parameters according to at least one edge processing data under the condition that the preset conditions are met;
and the signal generation module is used for generating a nerve stimulation control signal according to the edge processing data and the stimulation parameters.
In a fourth aspect, the present application also provides a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
Generating a reference moment and sending the reference moment to at least one edge calculation module;
acquiring edge processing data from at least one edge computing module, wherein the edge processing data is a data sequence generated according to the reference moment;
obtaining stimulation parameters, and updating the stimulation parameters according to at least one edge processing data under the condition that preset conditions are met;
and generating a neural stimulation control signal according to the edge processing data and the stimulation parameters.
In a fifth aspect, the present application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
Generating a reference moment and sending the reference moment to at least one edge calculation module;
acquiring edge processing data from at least one edge computing module, wherein the edge processing data is a data sequence generated according to the reference moment;
obtaining stimulation parameters, and updating the stimulation parameters according to at least one edge processing data under the condition that preset conditions are met;
and generating a neural stimulation control signal according to the edge processing data and the stimulation parameters.
In a sixth aspect, the application also provides a computer program product comprising a computer program which, when executed by a processor, performs the steps of:
Generating a reference moment and sending the reference moment to at least one edge calculation module;
acquiring edge processing data from at least one edge computing module, wherein the edge processing data is a data sequence generated according to the reference moment;
obtaining stimulation parameters, and updating the stimulation parameters according to at least one edge processing data under the condition that preset conditions are met;
and generating a neural stimulation control signal according to the edge processing data and the stimulation parameters.
The data processing method, the device computer equipment, the storage medium and the computer program product are applied to the external controller, and the generated reference moment is sent to the at least one edge computing module to instruct the at least one edge computing module to synchronously acquire and compute the state data of the user, and then the edge processing data from the at least one edge computing module is acquired, so that at least one data sequence generated according to the reference moment is obtained. Because the data sequences are all generated according to the reference time sent in the steps, the corresponding time of different edge processing data is synchronous, and the current state of a user can be analyzed through the acquired edge processing data. And finally, generating a nerve stimulation control signal according to the edge processing data and the stimulation parameters, and automatically and dynamically adjusting the stimulation parameters according to the state of a user in the use process, so that the manual titration of the stimulation parameters is not needed, the maintenance and adjustment times of the peripheral nerve stimulation system in the use process are reduced in the aspect of the stimulation parameters, the closed-loop stimulation accuracy is increased, and the use experience of the user is further improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the drawings that are required to be used in the embodiments or the related technical descriptions will be briefly described, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort for those skilled in the art.
FIG. 1 is a schematic diagram of a neural stimulation control system in one embodiment;
FIG. 2 is a schematic diagram of an in vitro controller 102 of a neural stimulation control system, in one embodiment;
FIG. 3 is a schematic diagram of an implant 104 of a neural stimulation control system, in one embodiment;
FIG. 4 is a schematic diagram of an edge calculation module 106 of a neural stimulation control system, in one embodiment;
FIG. 5 is a schematic diagram illustrating a data transmission process of the edge calculation module 106 according to one embodiment;
FIG. 6 is a diagram of an application environment for a data processing method in one embodiment;
FIG. 7 is a flow chart of a method of data processing according to one embodiment;
FIG. 8 is a flowchart of a data processing method step S708 in one embodiment;
FIG. 9 is a block diagram of a data processing apparatus in one embodiment;
FIG. 10 is an internal block diagram of a computer device in one embodiment;
fig. 11 is an internal structural view of a computer device in another embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The neural stimulation control system provided by the embodiment of the application can be used for accurate tongue position control, as shown in fig. 1, the neural stimulation control system comprises an external controller 102, an implant 104 and at least one edge calculation module 106, the external controller 102 is used for being in communication connection with the at least one edge calculation module 106, and the implant 104 is used for being in inductive connection with the external controller 102 through an induction coil. The edge calculation module 106 is configured to obtain edge monitoring data of the monitored portion, and calculate edge processing data according to the edge monitoring data; the external controller 102 is configured to obtain a plurality of edge processing data, and generate a neural stimulation control signal according to the plurality of edge processing data; the implant 104 is configured to contact the peripheral nerve, and the implant 104 is configured to receive the nerve stimulation control signal and to stimulate the peripheral nerve in accordance with the nerve stimulation control signal.
The neural stimulation control system is composed of an external controller 102, an implant 104 and at least one edge calculation module 106, wherein "at least one" means "one or more", that is, the edge calculation module in the embodiment of the application may be one or more, and in a use state, the edge calculation module 106 is disposed at a plurality of monitoring positions of a user, so as to obtain edge monitoring data of the monitoring positions, and calculate edge processing data according to the edge monitoring data, thereby obtaining the current state of the user, avoiding the sensor from being disposed under the body surface in a surgical mode, and reducing injury to the user. The extracorporeal controller 102 is communicatively coupled to at least one edge calculation module 106, and is capable of acquiring a plurality of edge processing data and generating a neural stimulation control signal based on the plurality of edge processing data. The implant 104 is disposed under the body surface to contact the peripheral nerve, and inductively connected with the external controller 102 through an induction coil, thereby receiving a neural stimulation control signal, and stimulating the peripheral nerve according to the neural stimulation control signal, and it is apparent that the implant 104 can directly obtain electric energy by forming a magnetic resonance loop with the external controller 102 without using an additional power supply, thereby completing the electric stimulation. Therefore, the nerve stimulation control system is not affected by the service life of the power supply and other problems in the use process, and the condition that the nerve stimulation control system needs to be replaced or maintained is avoided, so that the maintenance and adjustment times of the peripheral nerve stimulation system in the use process are reduced, and the damage to a user is further reduced.
In an exemplary embodiment, as shown in fig. 2, the extracorporeal controller 102 may include an extracorporeal controller body 202 and a patch 204, wherein the patch 204 may be a disposable patch 204. In use, the disposable patch 204 may be placed over a body surface where the implant 104 is positioned. The patch 204 includes a custom coil 2041 and a connection bayonet 2042. The extracorporeal controller body 202 is connected to the disposable patch 204 by corresponding connection bayonets 2042, forming a magnetic induction link.
With continued reference to fig. 2, further, the extracorporeal controller body 202 may include a controller power module 206, a controller circuit module 208, and a controller communication module 210. The controller communication module 210 is configured to receive energy and data information from the edge calculation module 106. The circuit module is used for processing the received energy and information to generate corresponding stimulation pulses. The controller Communication module 210 inputs the high frequency electrical signal generated by the controller circuit module 208 to the custom coil 2041 on the disposable patch 204 in a wireless manner through different protocols, such as custom protocols, wireless charging Qi protocol, air-Fuel protocol, short range wireless Communication (NFC) protocol, etc. In use, the custom coil 2041 on the external controller 102 and the internal induction coil 306 (see fig. 3) in the implant 104 form a magnetic resonance circuit to provide electrical power to the implant 104. And the electrical signals processed by the controller circuit module 208 are input to the custom coil 2041 on the disposable patch 204 via the controller communication module 210 using a communication protocol. Custom coil 2041 forms a communication loop with in-vivo induction coil 306 in implant 104 to electrically stimulate the peripheral nerve.
Illustratively, as shown in fig. 3, the implant 104 may include an implant body 302 and a stimulation electrode 304, the implant body 302 including an in-vivo induction coil 306, the implant body 302 being configured to receive the neural stimulation control signal and the inductive power from the in-vitro controller 102 via the in-vivo induction coil 306, and to use the inductive power as the power supply power for the stimulation electrode 304; the stimulation electrode 304 is used to contact the peripheral nerve to stimulate the peripheral nerve according to the nerve stimulation control signal. Further, the implant body 302 may further include an implant circuit module 308 and an implant communication module 310, wherein the implant circuit module 308 is configured to rectify and filter the energy received by the in-vivo induction coil 306 to generate a stimulation pulse to complete the stimulation pulse conversion required by the stimulation electrode 304; the implant communication module 310 is configured to receive the stimulation signal without using the extracorporeal controller 102, thereby achieving electrical stimulation. The wireless communication received by the implant 104 may be decoded and encoded by a demodulator and modulator module in the implant 104. The stimulation electrodes 304 can be used to deliver stimulation pulses to peripheral nerves such as spinal nerves, sacral nerves, hypoglossal nerve lamps, and the like.
With continued reference to fig. 3, in one exemplary embodiment, the implant 104 further includes an energy storage module 312, the energy storage module 312 being configured to store inductive power and to provide power to the stimulation electrode 304 if a predetermined condition is met. In some specific use scenarios (e.g., travel, business trip, etc.), the user may directly use the implant 104 for stimulation without wearing the external controller body 202 and the disposable patch 204 for control.
Illustratively, the above-described neural stimulation control system further includes a charging base 108, the charging base 108 being configured to provide power to the external controller 102, the charging base 108 and the external controller 102 being configured to provide power via contact. Further, the charging base 108 may be provided separately or integrated into the edge computing module 106, and the charging base 108 may be one or more. In the case where the charging base 108 is integrated in the edge calculation module 106 described above, the following relationships may be set between the charging base 108 and the edge calculation module 106:
Illustratively, a set of neural stimulation control systems includes an edge calculation module 106 integrated with a charging base 108, the edge calculation module 106 having the function of powering the extracorporeal controller 102.
Illustratively, a set of neural stimulation control systems includes a plurality of integrated edge calculation modules 106, wherein one of the edge calculation modules 106 has a charging base 108 integrated therein, and the edge calculation module 106 has the function of powering the extracorporeal controller 102 and the other edge calculation modules 106.
Illustratively, a set of neural stimulation control systems includes a plurality of integrated edge calculation modules 106, each of the edge calculation modules 106 having a charging base 108 integrated therein, the plurality of edge calculation modules 106 each having the functionality to power the extracorporeal controller 102 and other edge calculation modules 106.
Illustratively, the charging dock 108 includes a display module, which may be a led display screen or a respiratory light. When the charging base 108 starts the charging function, the display module starts to display charging, and the external controller 102 contacts the charging interface of the charging base 108 for charging. When the charging base 108 is used as a program control function, the display module displays the current regulation Mode, and the current regulation Mode is controlled through a Mode key. The up key "+" and down key "-" control the values of the programming mode. The charger base may also be coupled to the edge computing modules 106 to provide power to at least one of the edge computing modules 106.
In an exemplary embodiment, as shown in fig. 4, the edge calculation module 106 is configured to collect various physiological signals of a human body, and obtain a result through an algorithm and a computing force of edge calculation. The edge calculation module 106 may be a wireless acquisition device, and is in communication connection with the external controller 102 through a communication protocol, where at least one edge calculation module 106 may be placed at different monitoring positions of the human body, such as a chest, an abdomen, a finger, a lower leg, etc., and may respectively acquire various physiological signals of the human body by using an acceleration sensor, a blood oxygen sensor, an impedance sensor, etc. Further, the edge computing module 106 may include a power supply unit 402, a monitoring unit 404, a circuit unit 406, a computing unit 408, and a communication unit 410, where the power supply unit 402 is configured to obtain power to other external devices or the charging base 108 described above to supply power to other functional units in the edge computing module 106; the monitoring unit 404 may be a variety of sensors for monitoring user status data; the circuit unit 406 is configured to convert the information acquired by the monitoring unit 404 and transmit the converted information to the calculating unit; the computing unit 408 is configured to perform corresponding computing processing on the received edge monitoring data to obtain edge processing data; the communication unit 410 is configured to send out edge processing data.
Further, the calculation unit 408 of the edge calculation module 106 disposed at different monitoring locations may use model parameters (such as a linear regression model, a deep neural network, a sequence-to-sequence model, etc.) obtained by different mathematical models, so as to calculate the obtained edge monitoring data and obtain edge processing data.
For example, as shown in fig. 5, the edge calculation module 106 disposed at the monitoring site of abdomen, chest, etc. may use a linear regression model to obtain corresponding fitting curve relations Z1 (chest acceleration fitting curve function) and Z2 (abdomen angular velocity fitting curve function) by fitting the accelerometer XYZ and the gyroscope XYZ, for judging respiratory rhythm, arrhythmia, etc.
Z = a1 * acc.X + b1 * acc.Y + c1 * acc.Z + a2 * gyr.X + b2 * gyr.Y + c2 * gyr.Z
Wherein a1, a2, b1, b2, c1, c2 are edge monitoring data acquired by an edge calculation module 106 arranged on the abdomen and the chest, respectively, and model parameters can be calculated by using the mathematical model after the edge monitoring data are input. Z represents the calculation result by the calculation force of the edge calculation module 106.
For example, with continued reference to fig. 5, the edge calculation module 106 disposed at the monitoring site of the finger, the lower leg, or the like may calculate Z3 (blood oxygen depth learning model) and Z4 (pulse depth learning model) from the acquired input sensor Data data_in by the model M of the advanced depth learning, by z=m×data_in.
The data processing method provided by the embodiment of the application can be applied to the extracorporeal controller 102, and can be applied to an application environment as shown in fig. 6. The terminal 602 communicates with the server 604 through a network, and is configured to receive a control instruction and display a control result. The data storage system may store data that the server 604 needs to process. The data storage system may be integrated on the server 604 or may be located on the cloud or other network server 604. The data storage system may be used to store acquired edge processing data, etc. The terminal 602 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices and portable wearable devices, where the internet of things devices may be smart speakers, smart televisions, smart air conditioners, smart vehicle devices, and the like. The portable wearable device may be a smart watch, smart bracelet, headset, or the like. The server 604 may be implemented as a stand-alone server 604 or as a cluster of servers 604 comprising a plurality of servers 604.
In an exemplary embodiment, as shown in fig. 7, a data processing method is provided, and the method is applied to the server 604 in fig. 6 for illustration, and includes the following steps S702 to S708. Wherein:
In step S702, a reference time is generated and sent to the at least one edge calculation module 106.
The reference time is determined by the extracorporeal controller 102, and indicates a time when the at least one edge calculation module 106 collects and processes data according to the synchronized time information.
For example, the server 604 may generate a reference time from the response to the data processing instructions and send the reference time to the edge calculation module 106; the reference time may also be automatically generated periodically and sent to the edge calculation module 106.
In step S704, edge processing data from at least one edge calculation module 106 is acquired.
Wherein the edge processing data is a data sequence generated from the reference time instant. Further, the data sequence as edge processing data contains a time stamp.
Illustratively, the server 604 of the extracorporeal controller 102 sends the reference time to the trailing edge calculation module 106, and the data collected by the edge calculation module 106 is time-sequential. The edge calculation module 106 may send the resulting data sequence of the edge calculation to the server 604 of the extracorporeal controller 102 at a preset interval with the reference time as a start time. Next, the server 604 of the extracorporeal controller 102 may calculate the physiological state of the human body at each moment in time using a sequence-to-sequence model based on the received data series.
The Sequence-to-Sequence (Seq 2 Seq) model is a deep learning model, and is used for processing tasks of which input and output are variable-length sequences. The Seq2Seq model consists of two main components: an encoder (Encoder) and a Decoder (Decoder). Wherein the encoder is arranged to accept the input sequence and convert it into a fixed length vector representation. This vector contains the information digest of the input sequence. Common encoders are recurrent neural networks or long and short term memory networks. The fixed length vector generated by the encoder is passed to the decoder as context information for the input sequence. The decoder is configured to accept the context vector and generate a target sequence. The decoder is also typically a recurrent neural network or a long and short term memory network. During training, the goal of the model is to minimize the gap between the actual output and the desired output. This is typically measured using a loss function (e.g., cross entropy loss).
The server 604 may transmit several edge processing data (data sequences) to the extracorporeal controller 102 after time synchronization, for example, by distributed edge calculation. The algorithm computation is performed again by the sequence-to-sequence model. The external controller 102 sends the stimulation waveform related information to the implant 104 in the body by an algorithm (e.g., table look-up, deep neural network model, etc.). The implant 104 receives the stimulation waveform information, can stimulate the peripheral nerve pulse, and can play a role in accurately controlling the tongue position in the process of controlling the tongue position through the peripheral nerve stimulation.
Step S706, obtaining the stimulation parameters, and updating the stimulation parameters according to the plurality of edge processing data under the condition that the preset conditions are met.
For example, the server 604 may acquire the initial stimulation parameters first, and then update the stimulation parameters according to a number of edge processing data if the preset condition is satisfied. The preset condition may be an instruction for adjusting and updating the stimulation parameters in response to active initiation of the user, or may be that the update time for periodically updating the stimulation parameters arrives.
Further, the server 604 may analyze the current user state according to the edge processing data, so as to update the dynamic stimulation parameters that are effective for the single use process, or may update the static stimulation parameters that are effective for the multiple use processes according to the edge processing data and in combination with the active test step for the user body state.
Step S708, generating a neural stimulation control signal according to the edge processing data and the stimulation parameters.
For example, the server 604 may correspondingly generate the stimulation instructions according to the user status and the current stimulation parameters obtained by the above steps. In the process of generating the stimulation instruction, the server 604 may receive the preference instruction of the user through the terminal 602, and then determine the type of the current stimulation according to the preference instruction, so as to generate a corresponding stimulation instruction, and then generate the neural stimulation control signal according to a preset rule for converting the stimulation instruction into the neural stimulation control signal.
In the above data processing method, the generated reference time is sent to the at least one edge computing module 106, so as to instruct the at least one edge computing module 106 to synchronously acquire and compute the state data of the user, and then acquire the edge processing data from the at least one edge computing module 106, thereby obtaining a plurality of data sequences generated according to the reference time. Because the data sequences are all generated according to the reference time sent in the steps, the corresponding time of different edge processing data is synchronous, and the current state of a user can be analyzed through the acquired edge processing data. Then, the initial stimulation parameters are acquired, the stimulation parameters are updated according to a plurality of edge processing data under the condition that preset conditions are met, and finally, the nerve stimulation control signals are generated according to the edge processing data and the stimulation parameters, so that the stimulation parameters can be automatically and dynamically adjusted according to the state of a user in the use process, and the manual titration of the stimulation parameters is not needed, the maintenance adjustment times of the peripheral nerve stimulation system in the use process are reduced in the aspect of the stimulation parameters, and the use experience of the user is further improved.
In an exemplary embodiment, as shown in fig. 8, step S708 includes steps S802 to S806. Wherein:
Step S802, a preset stimulation mode is obtained, and a target state signal is monitored according to a plurality of edge processing data.
The target state signal is a human body biological signal characterized by edge processing data. For example, the sensors of each edge calculation module 106 may be used to detect physiological states of the user's respiratory rhythm, blood oxygen, heart rate, etc.
The preset stimulation mode can be a continuous stimulation mode or a precise stimulation mode. The continuous stimulation mode refers to a mode in which continuous stimulation can be started without monitoring the abnormal state of a user when basic stimulation conditions are met; accurate electrical stimulation refers to a mode in which stimulation is initiated only if an abnormal state of the user is detected.
For example, the server 604 may analyze the current respiration status of the user through several edge processing data together, and send the status data as edge processing data to the server 604 of the external controller 102 for unified analysis after performing calculation processing, so as to effectively monitor the sleep apnea phenomenon of the user.
In step S804, if the preset stimulation mode is the continuous stimulation mode, if it is detected that the target state signal is characterized as the preset state, a neural stimulation control signal for continuous stimulation in the first preset time period is generated according to the stimulation parameter.
For example, the preset state may be an inhalation state, and when the preset stimulus mode is the continuous stimulus mode, the server 604 determines that the total stimulus time is n and the current timer time is t. The start time is ts, i.e. the time at which stimulation is started. When t < = ts, the current stimulus task is in an inactive state. When t < n and t > ts, the current stimulus task is in an active state. The server 604 analyzes the breathing rhythm from the breathing waveform data for a period of time in the edge processing data. When the inspiratory state is monitored, the stimulation function is activated, at which point stimulation energy and signals generated by the external controller 102 may be transmitted to the implant 104 by means of magnetic resonance for stimulation. In the continuous stimulation mode, peripheral nerve stimulation will continue until stimulation is stopped when the current timing time t is greater than the total stimulation time n.
Step S806, if the preset stimulation mode is the accurate stimulation mode, generating a neural stimulation control signal for continuous stimulation within a second preset time period according to the stimulation parameter under the condition that the target state signal is detected to be characterized as an abnormal state.
For example, when the preset stimulus mode is the precise stimulus mode, the server 604 analyzes the data monitored by the respiration sensor, the blood oxygen sensor, and the sleep posture sensor together from the edge processing data, determines that the abnormal waveform at the time of apnea and the blood oxygen SpO2 are lower than p1 (preset threshold, unit%), and starts to precisely stimulate the peripheral nerve at the inhalation stage at this time.
Further, the current stimulation task will set the total stimulation time to n and the current timing time to t. The activation time ts is the time at which stimulation is started after setting. When t < = ts, the current stimulus task is in an inactive state. When t < n and t > ts, the current stimulus task is in an active state. At this time, when the respiratory state is judged to be an abnormal state, the stimulus function is effective. At this point the stimulation function is activated and stimulation energy and signals are transferred to the implant 104 by means of magnetic resonance for stimulation. If the respiration waveform is monitored normal and blood oxygen spo2> =p1, the neural stimulation task is not activated.
In the precise stimulation mode, peripheral nerve stimulation will selectively and precisely stimulate until the end of the current timing time is greater than the total stimulation time. The peripheral nerve can be accurately stimulated at the stage that the user is in the abnormal breathing state, fatigue caused by continuous stimulation to the peripheral nerve and damage to the nerve blocking interface are effectively avoided, and the electrical stimulation safety and the user experience of the user are greatly improved.
In an exemplary embodiment, the step of updating the stimulation parameters according to the several edge processing data in step S706 if the preset condition is satisfied includes: acquiring a preset updating period and a preset threshold value, and measuring the characteristic value of the stimulation electrode 304 according to the preset updating period; in case the stimulus electrode 304 characteristic value exceeds a preset threshold value, the stimulus parameters are updated according to the stimulus electrode 304 characteristic value and the edge processing data according to several edges.
By way of example, the stimulation parameters (amplitude, pulse width and frequency) can be deduced from the linear relationship between electrode configuration, neural interface impedance and stimulation threshold. For example, the initial impedance is Zo, and the initial stimulation parameters acquired by the server 604 include: amplitude Vo, pulse width wo, and frequency ro, the initial values being single titration completed before first use. After a period of use, during the non-stimulation phase of the implant 104, the server 604 may control the electrode configuration of the implant 104 to be a single cathode at intervals and automatically measure the current impedance Z'. If Z' is within Z (1.+ -. P2) of the initial impedance Z0 (p 2 is a preset threshold in%) then the current stimulation parameters are not changed. When Z' exceeds the Z (1±p2) range, the server 604 derives the desired stimulation voltage threshold according to the linear relationship between the interface impedance and the stimulation threshold voltage in the single cathode electrode configuration.
Further, the server 604 updates the stimulation parameters according to the different threshold impedances by table look-up; the stimulation waveform parameters (amplitude v=v ', pulse width w=w', frequency r=r ') and initial impedance z=z' may also be updated according to a look-up table of different threshold voltages. The method can automatically and periodically adjust the stimulation parameters, can effectively solve the problem that the peripheral nerve stimulation generated by a user in the using process is too strong or too weak, improves the usability of equipment, and reduces the frequency of readjusting the stimulation parameters.
In another exemplary embodiment, the server 604 first periodically automatically generates a reference time and sends the reference time to the at least one edge calculation module 106. The at least one edge calculation module 106 may send the resulting data sequence of the edge calculation to the server 604 of the extracorporeal controller 102 at a preset interval with the reference time as a start time.
The server 604 then time synchronizes the edge processing data (data sequence) to the extracorporeal controller 102 via distributed edge calculation. The server 604 performs algorithm calculation again through the sequence-to-sequence model, and generates stimulation waveform related information through algorithm correspondence. And then acquiring initial stimulation parameters, acquiring a preset updating period and a preset threshold value under the condition that preset conditions are met, measuring the characteristic value of the stimulation electrode 304 according to the preset updating period, and updating the stimulation parameters according to a plurality of edge processing data and the characteristic value of the stimulation electrode 304 under the condition that the characteristic value of the stimulation electrode 304 exceeds the preset threshold value.
The server 604 then analyzes the user's current respiration state together via several edge-processed data. The sensors of each edge calculation module 106 are used for detecting physiological states such as respiratory rhythm, blood oxygen, heart rate and the like of the user, and after the state data are calculated and processed, the state data are transmitted to the server 604 of the external controller 102 as edge processing data for unified analysis, so that the phenomenon of apnea during sleeping of the user is effectively monitored.
When the preset stimulation mode is the continuous stimulation mode, the server 604 determines that the total stimulation time is n and the current timing time is t. The start time is ts, i.e. the time at which stimulation is started. When t < n and t > ts, the current stimulus task is in an active state. The server 604 analyzes the breathing rhythm from the breathing waveform data for a period of time in the edge processing data. When the inspiratory state is monitored, the stimulation function is activated, at which point stimulation energy and signals generated by the external controller 102 may be transmitted to the implant 104 by means of magnetic resonance for stimulation. In the continuous stimulation mode, peripheral nerve stimulation will continue until stimulation is stopped when the current timing time t is greater than the total stimulation time n.
When the preset stimulation mode is the accurate stimulation mode, the server 604 analyzes the data monitored by the respiration sensor, the blood oxygen sensor and the sleeping posture sensor together in the edge processing data, and determines that the abnormal respiration state is present by combining the abnormal waveform and the blood oxygen SpO2 of the apnea being lower than p1 (preset threshold value, unit%), and starts to accurately stimulate the peripheral nerve in the inspiration phase at this time.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a data processing device for realizing the above related data processing method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation of one or more embodiments of the data processing device provided below may refer to the limitation of the data processing method hereinabove, and will not be repeated herein.
In one exemplary embodiment, as shown in FIG. 9, a data processing apparatus is provided for use with an extracorporeal controller 102, comprising: a time synchronization module 902, a data acquisition module 904, a parameter determination module 906, and a signal generation module 908, wherein:
A time synchronization module 902, configured to generate a reference time, and send the reference time to the at least one edge calculation module 106;
A data acquisition module 904, configured to acquire edge processing data from the at least one edge calculation module 106, where the edge processing data is a data sequence generated according to a reference time;
The parameter determining module 906 is configured to obtain a stimulus parameter, and update the stimulus parameter according to a plurality of edge processing data when a preset condition is satisfied;
The signal generation module 908 is configured to generate a neural stimulation control signal according to the edge processing data and the stimulation parameters.
In one embodiment, the signal generation module 908 comprises:
The state acquisition unit is used for acquiring a preset stimulation mode and monitoring a target state signal according to a plurality of edge processing data;
The first processing unit is used for generating a nerve stimulation control signal for continuous stimulation in a first preset time period according to the stimulation parameters under the condition that the target state signal is monitored to be characterized as a preset state if the preset stimulation mode is the continuous stimulation mode;
And the second processing unit is used for generating a nerve stimulation control signal which is continuously stimulated in a second preset time period according to the stimulation parameter under the condition that the target state signal is monitored to be characterized as an abnormal state if the preset stimulation mode is the accurate stimulation mode.
In one embodiment, the parameter determination module 906 includes:
The data acquisition unit is used for acquiring a preset updating period and a preset threshold value and measuring the characteristic value of the stimulation electrode 304 according to the preset updating period;
The parameter updating unit is configured to update the stimulation parameter according to the edge processing data and the feature values of the stimulation electrode 304 when the feature values of the stimulation electrode 304 exceed a preset threshold.
Each of the modules in the above-described data processing apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one exemplary embodiment, a computer device is provided, which may be a server 604, the internal structure of which may be as shown in FIG. 10. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is for storing edge processing data. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is for communicating with an external terminal 602 via a network connection. The computer program is executed by a processor to implement a data processing method.
In an exemplary embodiment, a computer device is provided, which may be a terminal 602, the internal structure of which may be as shown in fig. 11. The computer device includes a processor, a memory, an input/output interface, a communication interface, a display unit, and an input means. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communication with an external terminal 602 in a wired or wireless manner, which may be implemented by WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a data processing method. The display unit of the computer device is used for forming a visual picture, and can be a display screen, a projection device or a virtual reality imaging device. The display screen may be a liquid crystal display screen or an electronic ink display screen and the input means of the computer device may be a touch layer overlaying the display screen. It will be appreciated by those skilled in the art that the structure shown in FIG. 11 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one exemplary embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of: generating a reference time and transmitting the reference time to at least one edge calculation module 106; acquiring edge processing data from at least one edge calculation module 106, wherein the edge processing data is a data sequence generated according to a reference moment; obtaining stimulation parameters, and updating the stimulation parameters according to a plurality of edge processing data under the condition that preset conditions are met; a neural stimulation control signal is generated based on the edge processing data and the stimulation parameters.
In one embodiment, the processor when executing the computer program further performs the steps of: acquiring a preset stimulation mode, and monitoring a target state signal according to a plurality of edge processing data; if the preset stimulation mode is the continuous stimulation mode, generating a nerve stimulation control signal for continuous stimulation within a first preset time period according to the stimulation parameters under the condition that the target state signal is monitored to be characterized as the preset state; if the preset stimulation mode is the accurate stimulation mode, generating a nerve stimulation control signal which continuously stimulates in a second preset time period according to the stimulation parameter under the condition that the target state signal is monitored to be characterized as an abnormal state.
In one embodiment, the processor when executing the computer program further performs the steps of: acquiring a preset updating period and a preset threshold value, and measuring the characteristic value of the stimulation electrode 304 according to the preset updating period; in case the stimulus electrode 304 characteristic value exceeds a preset threshold value, the stimulus parameters are updated according to the stimulus electrode 304 characteristic value and the edge processing data according to several edges.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of: generating a reference time and transmitting the reference time to at least one edge calculation module 106; acquiring edge processing data from at least one edge calculation module 106, wherein the edge processing data is a data sequence generated according to a reference moment; obtaining stimulation parameters, and updating the stimulation parameters according to a plurality of edge processing data under the condition that preset conditions are met; a neural stimulation control signal is generated based on the edge processing data and the stimulation parameters.
In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring a preset stimulation mode, and monitoring a target state signal according to a plurality of edge processing data; if the preset stimulation mode is the continuous stimulation mode, generating a nerve stimulation control signal for continuous stimulation within a first preset time period according to the stimulation parameters under the condition that the target state signal is monitored to be characterized as the preset state; if the preset stimulation mode is the accurate stimulation mode, generating a nerve stimulation control signal which continuously stimulates in a second preset time period according to the stimulation parameter under the condition that the target state signal is monitored to be characterized as an abnormal state.
In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring a preset updating period and a preset threshold value, and measuring the characteristic value of the stimulation electrode 304 according to the preset updating period; in case the stimulus electrode 304 characteristic value exceeds a preset threshold value, the stimulus parameters are updated according to the stimulus electrode 304 characteristic value and the edge processing data according to several edges.
In one embodiment, a computer program product is provided comprising a computer program which, when executed by a processor, performs the steps of: generating a reference time and transmitting the reference time to at least one edge calculation module 106; acquiring edge processing data from at least one edge calculation module 106, wherein the edge processing data is a data sequence generated according to a reference moment; obtaining stimulation parameters, and updating the stimulation parameters according to a plurality of edge processing data under the condition that preset conditions are met; a neural stimulation control signal is generated based on the edge processing data and the stimulation parameters.
In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring a preset stimulation mode, and monitoring the current respiratory state according to a plurality of edge processing data; acquiring a preset stimulation mode, and monitoring a target state signal according to a plurality of edge processing data; if the preset stimulation mode is the continuous stimulation mode, generating a nerve stimulation control signal for continuous stimulation within a first preset time period according to the stimulation parameters under the condition that the target state signal is monitored to be characterized as the preset state; if the preset stimulation mode is the accurate stimulation mode, generating a nerve stimulation control signal which continuously stimulates in a second preset time period according to the stimulation parameter under the condition that the target state signal is monitored to be characterized as an abnormal state.
In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring a preset updating period and a preset threshold value, and measuring the characteristic value of the stimulation electrode 304 according to the preset updating period; in case the stimulus electrode 304 characteristic value exceeds a preset threshold value, the stimulus parameters are updated according to the stimulus electrode 304 characteristic value and the edge processing data according to several edges.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magneto-resistive random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (PHASE CHANGE Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in various forms such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.
Claims (10)
1. A nerve stimulation control system, the system comprising an extracorporeal controller for communication with at least one of the edge calculation modules, an implant for inductive connection with the extracorporeal controller via an inductive coil, and at least one edge calculation module, wherein:
the edge calculation module is used for acquiring edge monitoring data of the monitoring part and calculating edge processing data according to the edge monitoring data;
The external controller is used for acquiring at least one piece of edge processing data and generating a nerve stimulation control signal according to the at least one piece of edge processing data;
the implant is configured to contact the peripheral nerve, the implant is configured to receive the nerve stimulation control signal, and to stimulate the peripheral nerve in accordance with the nerve stimulation control signal.
2. The system of claim 1, wherein the implant comprises an implant body and a stimulation electrode, the implant body comprising an in vivo induction coil, wherein:
the implant body is used for receiving the nerve stimulation control signal and the induction electric energy from the external controller through the internal induction coil and taking the induction electric energy as the power supply electric energy of the stimulation electrode;
The stimulation electrode is used for contacting the peripheral nerve so as to stimulate the peripheral nerve according to the nerve stimulation control signal.
3. The method of claim 2, wherein the implant further comprises an energy storage module for storing the inductive power and powering the stimulation electrode if a preset condition is met.
4. A data processing method for application to an extracorporeal controller, the method comprising:
Generating a reference moment and sending the reference moment to at least one edge calculation module;
acquiring edge processing data from at least one edge computing module, wherein the edge processing data is a data sequence generated according to the reference moment;
obtaining stimulation parameters, and updating the stimulation parameters according to at least one edge processing data under the condition that preset conditions are met;
and generating a neural stimulation control signal according to the edge processing data and the stimulation parameters.
5. The method of claim 4, wherein generating a neural stimulation control signal based on the edge processing data and the stimulation parameters comprises:
acquiring a preset stimulation mode, and monitoring a target state signal according to at least one edge processing data;
If the preset stimulation mode is a continuous stimulation mode, generating a nerve stimulation control signal for continuous stimulation within a first preset time period according to the stimulation parameter under the condition that the target state signal is monitored to be characterized as a preset state;
If the preset stimulation mode is the accurate stimulation mode, generating a nerve stimulation control signal which is continuously stimulated in a second preset time period according to the stimulation parameter under the condition that the target state signal is monitored to be characterized as an abnormal state.
6. The method according to claim 4, wherein updating the stimulation parameters according to at least one of the edge processing data if a preset condition is met comprises:
Acquiring a preset updating period and a preset threshold value, and measuring a characteristic value of a stimulation electrode according to the preset updating period;
and under the condition that the characteristic value of the stimulation electrode exceeds the preset threshold value, updating the stimulation parameter according to at least one of the edge processing data and the characteristic value of the stimulation electrode.
7. A data processing device for use in an extracorporeal controller, the device comprising:
The time synchronization module is used for generating a reference moment and sending the reference moment to at least one edge calculation module;
The data acquisition module is used for acquiring edge processing data from at least one edge calculation module, wherein the edge processing data is a data sequence generated according to the reference moment;
The parameter determining module is used for acquiring the stimulation parameters and updating the stimulation parameters according to at least one edge processing data under the condition that the preset conditions are met;
and the signal generation module is used for generating a nerve stimulation control signal according to the edge processing data and the stimulation parameters.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 4 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 4 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the steps of the method of any of claims 4 to 6.
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