Modular portable brain-computer interface device

Abstract

The present disclosure relates to a modular portable brain-computer interface device, the device comprising: a processing module and an interface for connecting a functional module, the processing module being used to: determine the function of a functional module connected to the processing module; load a target processing function according to the function of an acquisition module and / or the function of an execution module; and process the physiological signal collected by the acquisition module through the target processing function to determine the physiological state of the target object. According to the processing device of an embodiment of the present disclosure, the corresponding target processing function can be loaded in the processing module through the function of the connected functional module, thereby supporting the operation of the functional module. This facilitates the development of functional modules, reduces development costs, and is conducive to improving the richness of the functions of the processing device.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a modular portable brain-computer interface device. Background Art

[0002] The implementation of brain-computer interface technology is mainly through steps such as EEG acquisition, signal acquisition and processing, signal output (execution), and signal feedback. The electrodes for collecting EEG signals are different from the electrodes used to generate electrical stimulation, which results in different ways of acquiring EEG signals. Brain-computer interfaces are divided into invasive brain-computer interfaces and non-invasive brain-computer interfaces. Whether it is an invasive brain-computer interface or a non-invasive brain-computer interface, both require hardware equipment that can support EEG signal acquisition and transmission, and software algorithms that can support EEG signal processing and analysis.

[0003] At present, brain-computer interface devices are mainly based on EEG signal acquisition devices, such as electroencephalographs. Such devices only support the acquisition of EEG signals. Subsequent EEG signal processing and encoding and decoding, execution and regulation and other related functions need to rely on other devices to complete. At the same time, due to different application scenarios, the functional requirements of brain-computer interface devices are also different. For example, when analyzing EEG signals, the function of collecting and processing EEG signals is usually required. When electrically stimulating patients with brain diseases, it is usually necessary to output electrical stimulations of appropriate frequency and intensity at appropriate locations. Therefore, in different scenarios, the functional requirements for brain-computer interface devices are different. In related technologies, the equipment usually has specific processing functions (for example, specific algorithms), which are difficult to adapt to more application scenarios. In addition, the cost of developing customized brain-computer interface devices for each scenario is high, which not only causes a waste of resources, but also greatly restricts its application scenarios, making it difficult to meet actual research needs. Summary of the invention

[0004] According to one aspect of the present disclosure, a processing device is provided, comprising: a processing module and a plurality of interfaces for connecting functional modules, the processing module being used to: determine functions of functional modules connected to the processing module via the interfaces, the functional modules comprising acquisition modules; load a target processing function according to the functions of the acquisition module; and process physiological signals acquired by the acquisition module via the target processing function to determine the physiological state of a target object.

[0005] In a possible implementation, the device further includes an execution module, and the processing module is further used to: generate an execution instruction corresponding to the execution module according to the physiological state, and send the execution instruction to the execution module.

[0006] In a possible implementation, the acquisition module includes an EEG acquisition module, a respiratory signal acquisition module and an ECG acquisition module, and the physiological state includes a sleep state; the processing module is further used to determine the sleep state of the target object based on the EEG signal collected by the EEG acquisition module, the respiratory signal collected by the respiratory signal acquisition module, and the ECG signal collected by the ECG acquisition module.

[0007] In a possible implementation, the acquisition module includes an EEG acquisition module, and the physiological state includes a pathological state; the processing module is further used to determine the pathological state of the target object based on the function of the EEG acquisition module and the EEG signal acquired by the EEG acquisition module.

[0008] In one possible implementation, the execution module includes a stimulation module, which includes an electrical stimulation generating unit connected to the processing module through the interface and a stimulation unit arranged at a preset position in the brain, the execution instruction includes a stimulation instruction, and the processing module is further used to: generate the stimulation instruction according to the pathological state, and send it to the stimulation module through the interface, so that the stimulation module generates a stimulation signal according to the stimulation instruction, and applies the stimulation signal to the preset position of the brain through the stimulation unit.

[0009] In a possible implementation, the stimulation module includes an electrical stimulation module, the stimulation unit includes an electrode, and the stimulation signal includes electrical stimulation.

[0010] In a possible implementation, the stimulation module includes an ultrasound stimulation module and / or a magnetic stimulation module.

[0011] In one possible implementation, the physiological state includes an action requirement state, the execution module includes an action execution mechanism, the execution instruction includes an action instruction, and the processing module is further used to: generate the action instruction according to the action requirement state, and output it to the action execution mechanism, so that the action execution mechanism performs the corresponding action according to the action instruction.

[0012] In a possible implementation, the processing device is further configured to: in response to a plurality of functional modules connected to the interface, perform correction processing on the clocks of the functional modules according to a preset standard clock.

[0013] In a possible implementation, the standard clock includes an Internet clock, and the processing module is further used to: generate a clock correction instruction, the clock correction instruction is used to enable the functional module to obtain the Internet clock, and correct the clock of the functional module based on the Internet clock.

[0014] In a possible implementation, the processing module is further used to: read, through the interface, description information of a functional module connected to the processing module; and determine the target processing function according to the description information.

[0015] In a possible implementation, the device further includes a communication module, and the processing module is further configured to: load the target processing function from the cloud via the communication module.

[0016] In a possible implementation, the device also includes a communication module, and the processing module is further used to: send the physiological signal to the cloud through the communication module, so that the cloud obtains the corresponding execution instruction based on the physiological signal; receive the execution instruction through the communication module and send it to the execution module.

[0017] According to the processing device of the embodiment of the present disclosure, the corresponding target processing function can be loaded in the processing module through the function of the connected functional module, thereby supporting the operation of the functional module, facilitating the development of the functional module, reducing the development cost, and improving the richness of the functions of the processing device.

[0018] It should be understood that the above general description and the following detailed description are exemplary and explanatory only and do not limit the present disclosure. Other features and aspects of the present disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings herein are incorporated into the specification and constitute a part of the specification, and these drawings illustrate embodiments consistent with the present disclosure and are used together with the specification to illustrate the technical solutions of the present disclosure;

[0020] Figure 1 A block diagram showing a processing device according to an embodiment of the present disclosure;

[0021] Figure 2 A block diagram showing a processing device according to an embodiment of the present disclosure;

[0022] Figure 3 A block diagram showing an interface according to an embodiment of the present disclosure;

[0023] Figure 4 A block diagram showing an interface according to an embodiment of the present disclosure;

[0024] Figure 5 A schematic diagram showing a functional module according to an embodiment of the present disclosure;

[0025] Figure 6 A schematic diagram showing an application of a processing device according to an embodiment of the present disclosure;

[0026] Figure 7 A schematic diagram showing an application of a processing device according to an embodiment of the present disclosure;

[0027] Figure 8 A schematic diagram showing an application of a processing device according to an embodiment of the present disclosure;

[0028] Fig. 9 A schematic diagram showing a clock correction process according to an embodiment of the present disclosure;

[0029] Fig.10 A schematic diagram showing a clock correction process according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0030] Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0031] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0032] The term "and / or" herein is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C can represent including any one or more elements selected from the set consisting of A, B, and C.

[0033] In addition, in order to better illustrate the present disclosure, numerous specific details are given in the following specific embodiments. It should be understood by those skilled in the art that the present disclosure can also be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the subject matter of the present disclosure.

[0034] In the related art, brain-computer interface devices mainly include electroencephalographs, which can be used to collect EEG signals for analysis, for example, analyzing EEG signals of patients with brain diseases such as epilepsy and depression. First of all, its function is relatively simple, and a specific software function is fixed in the processor of the electroencephalograph, which can be used to collect and process EEG signals, which is difficult to meet more scenarios. In addition, it is difficult to expand the functions of the electroencephalograph, and it is also difficult to develop peripheral equipment for the electroencephalograph. For example, it is difficult to develop other signal acquisition equipment for use with the electroencephalograph, and it is also difficult to synchronously analyze and comprehensively utilize the signals collected by various devices. For example, it is difficult to develop an electrocardiograph for use with the electroencephalograph, it is difficult to synchronize the signals collected by the two, and it is difficult to comprehensively utilize the signals collected by the two for analysis and health detection.

[0035] In view of the above problems, the present disclosure relates to a processing device, including a processing module, and providing multiple interfaces for connecting with other functional modules, which can call corresponding processing functions (e.g., software functions) according to the functions of the functional modules connected to the interfaces, thereby supporting the connected functional modules, for example, calling the acquisition function to drive the acquisition module, and / or calling the execution function to drive the execution module. This facilitates the development of new functions and peripheral devices, enriches the functions of the processing device, and saves development costs.

[0036] Figure 1 A block diagram of a processing device according to an embodiment of the present disclosure is shown as follows: Figure 1 As shown, the device comprises: a processing module 11 and a plurality of interfaces 12 for connecting functional modules,

[0037] The processing module 11 is used for:

[0038] Determine the function of a functional module connected to the processing module through the interface, the functional module including a collection module;

[0039] According to the function of the acquisition module, load the target processing function;

[0040] The physiological signal collected by the collection module is processed by the target processing function to determine the physiological state of the target object.

[0041] According to the processing device of the embodiment of the present disclosure, the corresponding target processing function can be loaded in the processing module through the function of the connected functional module, thereby supporting the operation of the functional module, facilitating the development of the functional module, reducing the development cost, and improving the richness of the functions of the processing device.

[0042] In a possible implementation, the processing device may be a brain-computer interface device, the processing module in the processing device may be a processor for processing and analyzing physiological signals such as electroencephalogram signals and / or generating execution instructions, and the interface may be used to connect to a collection module for collecting a variety of physiological signals. The device also includes an execution module, the interface may be used to connect to execution modules that perform a variety of functions, and the processing module is further used to: generate an execution instruction corresponding to the execution module according to the physiological state, and send it to the execution module.

[0043] The present disclosure does not limit the application field of the processing device.

[0044] In a possible implementation, the processing module may include a controller and a computing unit, the controller is used to call various interfaces and call various functions, and the computing unit can be used to execute the called functions, that is, to provide computing power, for example, according to the called EEG signal analysis function, the EEG signal is analyzed and processed. The processing device may include multiple interfaces, which can be used to connect multiple functional modules to realize multiple functions. The interface may include a wired interface and / or a wireless interface, which can be used to connect to the functional module by wire and / or wirelessly, and to interact with the functional module for data, so as to control the functional module to perform various functions. The processing device may also include a basic communication unit, which is used to support the communication function of the interface, for example, the wired communication function and / or the wireless communication function. For example, the basic communication unit includes a Bluetooth unit, which can support the function of the Bluetooth interface, so as to connect to other functional modules by Bluetooth. For another example, the basic communication unit includes a USB unit, which can be used to support the function of the USB interface, so as to connect to other functional modules by USB. Furthermore, the processing device may also include a power management module for providing power to the processing device and to the connected functional modules. Furthermore, when it is necessary to output an electrical signal (for example, when the electrode needs to output electrical stimulation), it can also provide the power required to output the electrical signal, for example, to provide various types of level signals.

[0045] Figure 2 A block diagram of a processing device according to an embodiment of the present disclosure is shown as follows: Figure 2 As shown, the processing device may include a controller, a computing unit, a power management module, a basic communication unit and n (n is a positive integer) interfaces. The interface may include a wired interface or a wireless interface, and the basic communication unit may be a functional unit supporting a wired interface and / or a functional unit supporting a wireless interface.

[0046] In a possible implementation, the interface can be connected to various functional modules, and the processing module (e.g., a controller in the processing module) can scan each interface and determine whether each interface is connected to other functional modules. If one or some interfaces are connected to one or some functional modules, the function of the connected functional module can be determined. In an example, the functional module can include a collection module and an execution module.

[0047] In an example, the acquisition module may include an acquisition module for acquiring physiological signals, such as an EEG acquisition module, a respiratory signal acquisition module, an ECG signal acquisition module, etc., and the execution module may include a module for executing certain instructions, such as an electrical stimulation module for outputting electrical stimulation, an execution mechanism for executing certain actions, etc. The present disclosure does not limit the types of acquisition modules and execution modules.

[0048] Figure 3 A block diagram showing an interface according to an embodiment of the present disclosure is shown as follows: Figure 3 As shown, taking a wired interface as an example, the interface may include multiple groups of data lines connected to the functional modules, such as a power line, a ground line (GND), and differential data lines (data+, data-), and the number of differential data lines may be determined according to the data protocol. For example, the minimum number of differential data lines in the USB protocol is 1 group of differential data lines, etc.

[0049] Figure 4 A block diagram showing an interface according to an embodiment of the present disclosure is shown as follows: Figure 4 As shown, if the number of interfaces is insufficient, the interfaces can be expanded. For example, a USB interface can be expanded into multiple interfaces, for example, k (k is a positive integer greater than 1) interfaces, through hardware devices such as an expander.

[0050] In a possible implementation, the functions in the processing module may not be fixed. For example, a specific algorithm may not be fixed in the controller, but the algorithm may be written / updated to the controller from an external device through a communication interface according to actual functional requirements. For example, the required target processing function may be determined according to the function of the functional module connected to the processing module through the interface. The processing module is further used to: read the description information of the functional module connected to the processing module through the interface; and determine the target processing function according to the description information.

[0051] In the example, the processing module can read the description information of the functional module through the interface, for example, the information describing the function of the functional module, so as to determine the required target processing function. The description information can be pre-set in the functional module, provided by the functional module to the processing module, or read from the functional module by the processing module. For example, through the description information of the functional module, it can be determined that the functional module is an EEG acquisition module for collecting EEG signals, then the required target processing function is a function that can support the acquisition and processing of the EEG acquisition module, for example, the driving function of the electrodes in the EEG acquisition module, the function of signal processing and analysis of the collected EEG signals, etc. For another example, through the description information of the functional module, it can be determined that the functional module is an EEG acquisition module for collecting EEG signals and an electrical stimulation module for implementing electrical stimulation, then the required target processing function is a function that can support the acquisition and processing of the EEG acquisition module and a function that can support the output of electrical stimulation by the electrical stimulation module, for example, the function of signal processing and analysis of the collected EEG signals, and the function of generating appropriate electrical stimulation instructions according to the results of processing and analysis, so as to drive the electrical stimulation module to generate appropriate electrical stimulation. The present disclosure does not limit the type of target processing function.

[0052] In a possible implementation, the target processing function may also be determined by other means, for example, the target processing function may be manually selected. In the example, the functional module may be manually connected to the interface, and the target processing function corresponding to the connected functional module may be manually selected. In another example, the functional modules may also be matched one-to-one with the interfaces, for example, the ECG acquisition module may be matched with the interface 1, and the EEG acquisition module may be matched with the interface 2. In this case, as long as the processing module detects that the interface 1 is connected to a certain functional module, the target processing function corresponding to the ECG acquisition module is automatically called, and as long as the processing module detects that the interface 2 is connected to a certain functional module, the target processing function corresponding to the EEG acquisition module is automatically called. The present disclosure does not limit the method of selecting the target processing function.

[0053] In a possible implementation, after determining the target processing function, the target processing function can be loaded. In the example, the processing device may include a storage module that can be used to store algorithms (e.g., software packages) and data, etc. The present disclosure does not limit the function of the storage module. After the processing module determines the required target function, the target processing function can be called and loaded from the storage module, for example, the corresponding algorithm is called and written into the processing module, so that the processing module can control the functional module through the algorithm, and / or process the signal obtained by the functional module.

[0054] In a possible implementation, the processing device may not include a storage module, but may include a communication module, and the processing module is further used to: load the target processing function from the cloud through the communication module. In the example, the cloud may store processing functions that support multiple functional modules, for example, a software package storing multiple algorithms, and after determining the target processing function, the target processing function may be loaded from the cloud through the communication module, for example, the software package may be downloaded, so that the functions in the software package may be executed to support the functional module.

[0055] In one possible implementation, the processing function may be modified or added. For example, various processing functions (e.g., algorithms) in the storage module may be modified or added, and processing functions stored in the cloud may also be modified or added, so as to adapt to more functional modules.

[0056] Figure 5 A schematic diagram showing a functional module according to an embodiment of the present disclosure is shown as follows: Figure 5 As shown, the functional module may include an interface unit, which can be used to connect with the interface of the processing device, for example, to make a wired connection or a wireless connection. The functional module may include an interface conversion and driving unit, which can be used to convert and drive the interface. For example, when the interface of the functional module does not match the interface of the processing device, it can be used to convert the interface of the functional module to adapt to the interface of the processing device, and can provide a driving function for the interface, for example, the function of driving the USB interface. The functional module may include a functional unit for realizing the function of the functional module. For example, in the EEG acquisition module, the functional unit may include a signal amplification and analog-to-digital conversion unit, which can perform signal amplification and analog-to-digital conversion processing on the collected EEG signal to obtain the digital signal of the EEG. The functional module may also include an auxiliary unit for assisting in realizing the function of the functional module. For example, the auxiliary unit may include a data cache, which can be used to cache the digital signal of the EEG, and the processing module of the processing device can call the digital signal of the EEG in the data cache through the interface. In addition, the functional module may also include other execution units, for example, the electrodes in the EEG acquisition module are used to be set at a preset position of the brain, so that the function of EEG acquisition can be executed, that is, the EEG signal at the preset position is collected. The present disclosure does not limit the units included in the functional modules.

[0057] In a possible implementation, after the target processing function is loaded, the connected functional modules can be driven by the target processing function to perform corresponding processing. In the example, the acquisition module includes an EEG acquisition module, a respiratory signal acquisition module and an ECG acquisition module, and the physiological state includes a sleep state; the processing module is further used to determine the sleep state of the target object based on the EEG signal acquired by the EEG acquisition module, the respiratory signal acquired by the respiratory signal acquisition module, and the ECG signal acquired by the ECG acquisition module.

[0058] Figure 6 A schematic diagram of an application of a processing device according to an embodiment of the present disclosure is shown. Figure 6 As shown, the processing module can be connected to the EEG acquisition module, the respiratory signal acquisition module and the ECG acquisition module through different interfaces, and load the target processing function of detecting the sleep state of the target object. In the example, the EEG acquisition module may include an 8-channel EEG acquisition module, which may include multiple electrodes arranged in the brain, and may collect 8-channel EEG signals through multiple electrodes. The present disclosure does not limit the number of channels of EEG signals. The ECG signal acquisition module can be used to collect ECG signals. For example, the ECG signal acquisition module may include multiple electrodes arranged in the heart to collect multiple ECG signals. The respiratory signal acquisition module may include a respiratory sensor, which may be arranged in the respiratory tract, lungs, etc., and can be used to collect respiratory signals, such as respiratory frequency, blood oxygen content and other signals. Multiple modules can be collected simultaneously, and the processing module can process the three signals at the same time, so as to analyze the sleep state of the target object, such as shallow sleep or deep sleep state, or whether the sleep quality is good, etc. The present disclosure does not limit the type of sleep state and the specific method of determining the sleep state.

[0059] In one possible implementation, after determining the sleep state, a corresponding execution instruction may be generated according to the sleep state. For example, the functional module may also include an electrical stimulation module, which may be used to output electrical stimulation of corresponding frequency and / or intensity according to the electrical stimulation instruction. The functional module may include an electrode arranged at the position of a nerve center, which may be used to adjust the sleep state. For example, an execution instruction may be generated based on the sleep state and the current time to adjust the sleep quality of the target object. For example, if it is detected that the target object cannot enter deep sleep for a long time after falling asleep, and the current time is midnight, an execution instruction (e.g., an electrical stimulation instruction) may be generated to stimulate the nerve center, assist the target object in sleeping, make it easier for the target object to enter deep sleep, and improve the sleep quality of the target object. In another example, if it is detected that the target object is in deep sleep for a long time, and the current time is dawn, an execution instruction (e.g., an electrical stimulation instruction) may be generated to stimulate the nerve center, assist the target object in sleeping, and make the target object go from deep sleep to shallow sleep, so that the target object will feel less tired after waking up, thereby improving the sleep quality of the target object.

[0060] In another example, the acquisition module includes an EEG acquisition module, and the physiological state includes a pathological state; the processing module is further used to determine the pathological state of the target object according to the function of the EEG acquisition module and the EEG signal acquired by the EEG acquisition module. Furthermore, appropriate execution instructions can be generated based on the pathological state of the target object, so that the pathological state of the target object can be adjusted by outputting electrical stimulation through the electrical stimulation module. The execution module includes a stimulation module, and the stimulation module includes a stimulation generation unit connected to the processing module through the interface and a stimulation unit set at a preset position of the brain. The execution instruction includes a stimulation instruction, and the processing module is further used to generate the stimulation instruction according to the pathological state, and send it to the stimulation module through the interface, so that the electrical stimulation module generates a stimulation signal according to the electrical stimulation instruction, and applies the stimulation signal to the preset position of the brain through the stimulation unit.

[0061] In an example, the stimulation module comprises an electrical stimulation module, the stimulation unit comprises an electrode, and the stimulation signal comprises electrical stimulation.

[0062] Figure 7 A schematic diagram of an application of a processing device according to an embodiment of the present disclosure is shown. Figure 7As shown, the processing module can be connected to multiple EEG acquisition modules and electrical stimulation modules respectively through different interfaces, and load the target processing function of detecting the pathological state of the target object and / or applying electrical stimulation to the target object. In the example, the EEG acquisition module may include a 64-channel EEG acquisition module, which may include electrodes set at multiple preset positions in the brain, and may collect 64-channel EEG signals through multiple electrodes. The present disclosure does not limit the number of channels of EEG signals. The electrical stimulation module can be used to output electrical stimulation, and the electrical stimulation module may include a 16-channel electrical stimulation module, which may include electrodes set at multiple preset positions in the brain, and may apply 16-channel electrical stimulation to preset positions of the brain through multiple electrodes. The present disclosure does not limit the number of channels of the EEG acquisition module and the electrical stimulation module.

[0063] In the example, when detecting the pathological state of the target object (for example, brain diseases such as epilepsy and depression), a large number of data channels are required. For example, multiple 64-channel EEG acquisition modules are required to jointly collect EEG signals of multiple channels, for example, EEG signals of hundreds of data channels, and the sampling frequency of the data is relatively high, for example, the sampling frequency is 2kSps. And the pathological state of the target object can be comprehensively judged by the EEG signals of multiple channels. For example, the target processing function (for example, an algorithm for processing EEG signals) can comprehensively process the EEG signals of multiple channels to determine the pathological state of the target object, for example, identify the category of brain diseases of the target object (for example, brain diseases such as epilepsy and depression are not limited to the specific category of brain diseases, and the present disclosure does not limit the specific category of brain diseases), the location of the onset, and the severity of the disease.

[0064] In the example, the corresponding electrical stimulation can also be output according to the pathological state determined above, so as to reduce the severity of the disease. For example, brain diseases such as epilepsy and depression are related to abnormal electrical signals in the brain. Appropriate electrical stimulation can be performed on preset locations of the brain to adjust the electrical signals in the brain, thereby reducing the severity of the brain disease. For example, a comprehensive analysis can be performed based on the category, severity, and location of the brain disease identified above to generate an electrical stimulation instruction, which is transmitted to the electrical stimulation module so that the electrical stimulation module applies electrical stimulation of appropriate frequency and intensity to the appropriate location of the brain, thereby adjusting the electrical signals in the brain and reducing the severity of the brain disease.

[0065] In the example, after applying electrical stimulation, the EEG signal of the brain can be collected again through the EEG acquisition module to determine the pathological state after applying electrical stimulation, and then electrical stimulation can be further applied according to the pathological state at this time, so as to further adjust the electrical signal of the brain and reduce the severity of the disease. The above process can be executed repeatedly, and the generated electrical stimulation instructions are continuously feedback-adjusted through the collected EEG signals, so as to continuously generate more appropriate electrical stimulation to adjust the electrical signal of the brain, so that the electrical signal of the brain returns to a normal state or a near-normal state, and the severity of the brain disease is reduced.

[0066] In the example, the processing device may be a portable terminal device, and the computing power of its processing module is limited. Therefore, when encountering large-scale computing, part or all of the collected data may be sent to the cloud, so that the computing power of the cloud can be used for computing. The device also includes a communication module, and the processing module is also used to: send the physiological signal to the cloud through the communication module, so that the cloud obtains the corresponding execution instruction according to the physiological signal; receive the execution instruction through the communication module and send it to the execution module.

[0067] In the example, in the process of determining the pathological state of the target object, if the data size of the EEG signal to be collected is large, the processing device can be connected to the communication module through an interface, so that all or part of the EEG signal can be sent to the cloud for calculation through the communication module. In the example, the calculation can be performed through the computing power node in the cloud to determine the pathological state of the target object, and the pathological state can be sent to the processing device, and then the electrical stimulation instruction can be generated based on the pathological state. Alternatively, all processing can be performed directly through the cloud, that is, the pathological state can be directly determined through the cloud, and the electrical stimulation instruction can be determined based on the pathological state, and the electrical stimulation instruction can be sent to the processing device, and the processing device can send the electrical stimulation instruction to the electrical stimulation module, so that electrical stimulation can be output.

[0068] In a possible implementation, the stimulation module may include an ultrasound stimulation module and / or a magnetic stimulation module.

[0069] In the example, the ultrasonic stimulation module may include a module capable of generating transcranial focused ultrasound stimulation (TUS), and the stimulation unit may include an ultrasonic generating unit, which may regulate neural circuits through acoustic mechanisms, and may generate ultrasonic waves through stimulation units such as piezoelectric devices outside the skull (for example, current may flow through a crystal and cause vibration, and the energy generated by the vibration may be released through an ultrasonic transducer, thereby generating ultrasonic stimulation). Based on the shape of the transducer, array arrangement and other features, the ultrasonic wave may be accurately focused to a point space, allowing the sound wave to be focused on the deep brain below the cortical surface, thereby stimulating a specific location of the brain. Ultrasound, as a mechanical wave, may interact with biological mechanosensitive units (for example, mechanosensitive channels, cytoskeleton, etc.) in the nervous system, thereby converting mechanical wave energy into neuroelectrochemical signals, thereby achieving the purpose of stimulating and regulating the brain and neurons.

[0070] In the example, the magnetic stimulation module may include a module capable of generating transcranial magnetic stimulation (TMS), which uses a pulsed magnetic field to act on the central nervous system of the brain, change the membrane potential of the cerebral cortical nerve cells, generate induced currents, affect brain metabolism and neural electrical activity, and thus induce a series of physiological and biochemical reactions to achieve the purpose of stimulating and regulating the brain and neurons. Based on the principles of electromagnetic induction and electromagnetic conversion, the magnetic field generated by the transient current in the stimulation coil can penetrate the skull, and the dynamic magnetic field is converted into an induced current in the opposite direction of the stimulation coil current in the intracranial conductor. This endogenous induced current stimulates neurons to produce a series of physiological and biochemical reactions. The magnetic stimulation module can stimulate the cerebral cortical nerves through the current caused by the electromagnetic induction effect, and can stimulate the nerves non-invasively.

[0071] In another example, the acquisition module includes an EEG acquisition module, the physiological state includes an action requirement state, the execution module includes an action execution mechanism, the execution instruction includes an action instruction, and the processing module is further used to: generate the action instruction according to the action requirement state, and output it to the action execution mechanism, so that the action execution mechanism performs the corresponding action according to the action instruction. The action requirement state can represent the action that the target object needs to be executed by the execution mechanism. For example, when the target object generates a certain action requirement, its brain can generate a corresponding electrical signal, which can be analyzed to determine the action requirement of the target object, and the execution mechanism can be controlled based on the action requirement to perform the action corresponding to the action requirement. For example, if the target object is a target object whose limbs have lost their motor ability or whose motor ability has been damaged to a certain extent, its action requirement can be determined by analyzing the EEG signal of the target object, so as to control the execution mechanism such as the prosthesis to make the corresponding action. Alternatively, the execution mechanism includes a robot and other mechanisms, and its action requirement can be determined by analyzing the EEG signal of the target object, so as to control the robot to perform the corresponding action, so as to achieve the purpose of controlling the robot action through the EEG signal of the target object.

[0072] Figure 8 A schematic diagram of an application of a processing device according to an embodiment of the present disclosure is shown. Figure 8 As shown, the processing module can be connected to multiple EEG acquisition modules and actuators through different interfaces, and load the target processing function of detecting the action requirement state of the target object and / or generating action instructions based on the action requirement state. In the example, the EEG acquisition module may include a 64-channel EEG acquisition module, which may include electrodes arranged at multiple preset positions in the brain, and may collect 64-channel EEG signals through multiple electrodes. The present disclosure does not limit the number of channels of EEG signals. The actuator may include an actuator such as a prosthesis or a robot, which can be used to perform corresponding actions based on action instructions. The present disclosure does not limit the number of channels of the EEG acquisition module.

[0073] In the example, when detecting the action requirement state of the target object, multiple data channels may be required, for example, multiple 64-channel EEG acquisition modules are required to jointly collect EEG signals of multiple channels. Each channel can be connected to electrodes arranged at different positions of the brain, so that EEG signals at various positions of the brain can be obtained, so that the action requirement state of the target object can be comprehensively analyzed. For example, the action requirement state of the target object can be analyzed based on a variety of information such as the position where the EEG signal is generated, the amplitude of the EEG signal, the frequency of the EEG signal, and the phase of the EEG signal. In the example, the analysis and processing can be performed by the computing unit of the processing module, or the EEG signal can be sent to the cloud and performed by the cloud computing node, which is not limited by the present disclosure. After obtaining the action requirement state, the processing module or the cloud computing node can generate corresponding action instructions based on the action requirement state, such as walking, grabbing, etc. The cloud computing node can send the action instruction to the processing module. After the processing module obtains the action instruction (receives the action instruction sent by the cloud, or generates the action instruction through its own computing unit), the processing module can send the action instruction to the actuator, so that the corresponding action can be executed.

[0074] In a possible implementation, the processing device can be connected to multiple functional modules. Since the real-time requirements of physiological signals are high, the clocks of multiple functional modules can be unified so that the clocks of multiple functional modules remain consistent, thereby collecting physiological signals such as electroencephalogram signals with the same clock, reducing signal phase errors caused by inconsistent clocks, and reducing deviations in physiological states. The processing device is also used to: respond to the number of functional modules connected to the interface being multiple, and calibrate the clocks of the functional modules according to a preset standard clock.

[0075] Fig. 9 A schematic diagram showing a clock correction process according to an embodiment of the present disclosure is shown as follows: Fig. 9 As shown, for multiple functional modules connected by wire (for example, m functional modules, m is a positive integer greater than 1), a standard clock can be set. For example, the clock of the processing device can be set to the standard clock, and the clock signal of the standard clock can be used to correct the clock signals of other functional modules, so that the clock signals of each functional module and the processing device are the same frequency clock signals, that is, the clocks of each functional module and the processing device are unified, thereby reducing the signal phase error caused by clock inconsistency and reducing the deviation caused by physiological state.

[0076] In a possible implementation, the functional module may also be wirelessly connected to the processing device. For example, multiple EEG acquisition modules for simultaneously acquiring EEG signals from multiple people may be connected to the processing device by wireless connection, which can reduce restrictions on the activities of multiple people, and can also detect EEG signals of multiple people in different environments at the same time, or detect whether the EEG signals of multiple people facing the same situation are the same or similar, etc. In this case, each independent EEG acquisition module has its own clock, and the clock unit is usually a quartz crystal, etc. Due to the timely error of the quartz crystal, time deviation may occur after a long period of work, resulting in inconsistent clocks of various functional modules, and due to the transmission time difference, it is difficult for each functional module to be corrected by the clock signal of the quartz crystal of the processing device.

[0077] In a possible implementation, to address the above problem, the Internet clock can be set as a standard clock, and the processing module is also used to: generate a clock correction instruction, the clock correction instruction is used to enable the above functional module to obtain the Internet clock, and correct the clock of the functional module based on the Internet clock.

[0078] Fig.10 A schematic diagram showing a clock correction process according to an embodiment of the present disclosure is shown as follows: Fig.10 As shown, in each functional module, a unified Internet clock can be used as a standard clock to calibrate its own clock. Each functional module may have a crystal oscillator. Due to the error of the crystal oscillator, the clock signal frequencies on each functional module may be inconsistent. Therefore, the processing module may send a clock correction instruction to each functional module every preset time (for example, every 1 second). Multiple functional modules (for example, i acquisition modules and j execution modules, i and j are both positive integers) can access the Internet wirelessly and use the Internet clock as the standard clock. After determining the standard clock, each functional module can compare its own clock signal with the Internet clock. If its own clock is too fast, the clock frequency of the device is reduced in the clock synchronization process, otherwise, the clock frequency of the device is increased. Each functional module is compared and proofread with the Internet clock, so that the clocks of each functional module are consistent, thereby reducing the signal phase error caused by inconsistent clocks and reducing the deviation of physiological state.

[0079] In a possible implementation, one of the functional modules or the processing device can be connected to the Internet to obtain the Internet clock as the standard clock, and wireless broadcasting can be performed in each functional module at the same time, so that each functional module obtains the standard clock, and then can compare and calibrate with its own clock. If multiple functional modules form a local area network and are not connected to the Internet, the clock of a functional module or processing device can be randomly selected as the standard clock and broadcast to other functional modules for clock comparison and calibration. In addition, the above-mentioned preset time can be adjusted, and the preset time can be lowered to increase the frequency of clock correction processing, thereby further improving the consistency of the clock. If the preset time is increased, the frequency of clock correction processing is reduced, which can save processing resources.

[0080] According to the processing device of the embodiment of the present disclosure, the corresponding target processing function can be loaded in the processing module through the function of the connected functional module, thereby supporting the operation of the functional module. It is convenient for the development of functional modules, reduces development costs, and is conducive to improving the richness of the functions of the processing device. It is also possible to integrate the functions of various functional modules to obtain a variety of physiological signals, so as to achieve the purposes of monitoring the sleep state, monitoring and regulating the pathological state, and controlling the actuator through EEG signals. Furthermore, the clocks of each functional module can be corrected based on the standard clock, so that the clocks of each functional module are unified, reducing the signal phase error caused by clock inconsistency, and reducing the deviation caused by the physiological state.

[0081] It can be understood that the above-mentioned various device embodiments mentioned in the present disclosure can be combined with each other to form a combined embodiment without violating the principle logic. Due to space limitations, the present disclosure will not repeat them. It can be understood by those skilled in the art that in the above-mentioned method of the specific implementation method, the specific execution order of each step should be determined according to its function and possible internal logic.

[0082] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A processing device, characterized in that: include: Processing module and multiple interfaces for connecting functional modules, The processing module is used for: Determine the function of a functional module connected to the processing module through the interface, the functional module including an acquisition module; read description information of the functional module connected to the processing module through the interface, the description information is used to describe the function of the functional module; determine the target processing function according to the description information; According to the function of the acquisition module, load the target processing function; Processing the physiological signals collected by the acquisition module through the target processing function to determine the physiological state of the target object; Among them, the device also includes a communication module, through which the target processing function is loaded from the cloud; the cloud stores processing functions that support multiple functional modules. After determining the target processing function, the software package is downloaded from the cloud through the communication module, thereby executing the functions in the software package.

2. The device according to claim 1, characterized in that The device further includes an execution module, and the processing module is used for: According to the physiological state, an execution instruction corresponding to the execution module is generated and sent to the execution module.

3. The device according to claim 1, characterized in that The acquisition module includes an EEG acquisition module, a respiratory signal acquisition module and an ECG acquisition module, and the physiological state includes a sleep state; The processing module is used for: The sleep state of the target object is determined according to the EEG signal collected by the EEG collection module, the respiratory signal collected by the respiratory signal collection module, and the ECG signal collected by the ECG collection module.

4. The device according to claim 2, characterized in that The acquisition module includes an EEG acquisition module, and the physiological state includes a pathological state; The processing module is used for: The pathological state of the target object is determined according to the function of the EEG acquisition module and the EEG signal acquired by the EEG acquisition module.

5. The device according to claim 4, characterized in that The execution module includes a stimulation module, the stimulation module includes a stimulation generation unit connected to the processing module through the interface and a stimulation unit arranged at a preset position of the brain, the execution instruction includes a stimulation instruction, The processing module is used for: According to the pathological state, the stimulation instruction is generated and sent to the stimulation module through the interface, so that the stimulation module generates a stimulation signal according to the stimulation instruction and applies the stimulation signal to a preset position of the brain through the stimulation unit.

6. The device according to claim 5, characterized in that The stimulation module includes an electrical stimulation module, the stimulation unit includes electrodes, and the stimulation signal includes electrical stimulation.

7. The device according to claim 5, characterized in that The stimulation module includes an ultrasound stimulation module and / or a magnetic stimulation module.

8. The device according to claim 2, characterized in that The physiological state includes an action demand state, the execution module includes an action execution mechanism, and the execution instruction includes an action instruction. The processing module is used for: The action instruction is generated according to the action requirement state and output to the action execution mechanism, so that the action execution mechanism executes the corresponding action according to the action instruction.

9. The device according to claim 1, characterized in that The processing device is used for: In response to the number of functional modules connected to the interface being multiple, the clocks of the functional modules are calibrated according to a preset standard clock.

10. The device according to claim 9, characterized in that The standard clock includes an Internet clock, The processing module is used for: Generate a clock correction instruction, wherein the clock correction instruction is used to enable the functional module to obtain an Internet clock and perform correction processing on the clock of the functional module based on the Internet clock.

11. The device according to claim 2, characterized in that The device also includes a communication module, The processing module is used for: Sending the physiological signal to the cloud through the communication module, so that the cloud obtains the corresponding execution instruction according to the physiological signal; The execution instruction is received through the communication module and sent to the execution module.

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