Brain-computer interface module, digital skull implant and integration method and related application thereof

Abstract

The embodiment of the invention relates to the technical field of brain-computer interfaces, in particular to a brain-computer interface module, a digital skull implant and an integration method and related application of the digital skull implant. The digital skull implant comprises a skull prosthesis and a brain-computer interface module, wherein the brain-computer interface module and the skull prosthesis are integrated; the brain-computer interface module comprises an ultrasonic transducer used for sending ultrasonic signals to the brain and collecting brain echo signals. The brain-computer interface module comprises an ultrasonic transducer used for sending ultrasonic signals to the brain and collecting brain echo signals. The brain-computer interface module is configured to be integrated with a skull or a skull prosthesis. In this way, the implantation structure integrating the brain-computer interface module in the skull form can have good mechanical strength and biocompatibility, complete implantation and wireless design can be achieved, and ultrasonic waves penetrate through the skull to conduct precise stimulation on the brain area.

Description

Technical Field

[0001] The embodiments disclosed herein generally relate to the field of brain-computer interface technology, and specifically to a brain-computer interface module, a digital cranial implant, an integration method thereof, and related applications. Background Technology

[0002] Brain-computer interface (BCI), sometimes also called "direct neural interface" or "brain-machine interface," is a direct connection pathway established between the brain of a subject (human or animal) and an external device.

[0003] Brain-computer interfaces (BCIs) are classified into three types: non-invasive, semi-invasive, and invasive. Non-invasive or semi-invasive BCIs, in neuromodulation applications, are limited by skull attenuation and acoustic distortion, making it impossible to achieve stable, precise, and repetitive deep brain region stimulation and imaging. While invasive BCIs can achieve high-precision signal acquisition or neural stimulation, they suffer from limited spatial coverage, high invasiveness, poor biocompatibility, and difficulties in cleaning / maintaining. Summary of the Invention

[0004] Embodiments of this disclosure provide a brain-computer interface module, a digital cranial implant, an integration method thereof, and related applications, aimed at solving one or more of the above-mentioned problems and other potential problems.

[0005] According to a first aspect of this disclosure, a digital cranial implant is provided. The digital cranial implant includes a cranial prosthesis and a brain-computer interface module, the brain-computer interface module being integrally integrated with the cranial prosthesis. The brain-computer interface module includes an ultrasound transducer for transmitting ultrasound signals to the brain and acquiring brain echo signals.

[0006] According to a second aspect of this disclosure, a method for integrating a digital cranial implant is provided. The digital cranial implant is the implant described in the first aspect above. The method includes forming a bone groove on the inner surface of the cranial prosthesis. The method further includes securing a brain-computer interface module to the bone groove for integration with the cranial prosthesis into a single structure.

[0007] According to a third aspect of this disclosure, a brain-computer interface module is provided. The brain-computer interface module includes an ultrasound transducer for transmitting ultrasound signals to the brain and acquiring brain echo signals. The brain-computer interface is configured for integrated integration with the skull or a skull prosthesis.

[0008] According to a fourth aspect of this disclosure, a neuromodulation system is provided. The system includes one or more digital cranial implants as described in the first aspect. The system also includes a control module configured on an external electronic device or implantation device, the control module communicating bidirectionally with the digital cranial implant.

[0009] According to a fifth aspect of this disclosure, a neuromodulation system is provided. The system includes one or more brain-computer interface modules as described in the third aspect. The system also includes a control module configured in an external electronic device or implantable device, the control module communicating bidirectionally with the brain-computer interface modules.

[0010] According to a sixth aspect of this disclosure, a method for monitoring the physiological activities of a subject is provided. The method includes transmitting one or more signals to one or more ultrasound transducers in a digital craniotomy implant according to the first aspect. The digital craniotomy implant is replaced and installed at a target skull location in the subject, and the one or more signals are transmitted via the one or more ultrasound transducers to transmit ultrasound waves for altering the physiological activities of the subject. The method also includes receiving data characterizing the physiological activities of the subject from the one or more ultrasound transducers.

[0011] According to a seventh aspect of this disclosure, a method for monitoring the physiological activities of a subject is provided. The method includes sending one or more signals to one or more ultrasound transducers in a brain-computer interface module according to a third aspect, wherein any one of a skull prosthesis and a target skull is integrated with the brain-computer interface module at the location of the target skull in the subject, and the one or more signals are transmitted via the one or more ultrasound transducers to transmit ultrasound waves for altering the physiological activities of the subject. The method also includes receiving data representing the physiological activities of the subject from the one or more ultrasound transducers.

[0012] According to an eighth aspect of this disclosure, a method is provided for determining instructions for the neural modulation of a subject. The method includes receiving data characterizing the physiological state of a subject from one or more digital craniotomy implants according to the first aspect or brain-computer interface modules according to the third aspect, wherein the data characterizing the physiological state of the subject is data processed from ultrasound data acquired by an ultrasound transducer. The method further includes determining instructions for the neural modulation of the subject based on the data characterizing the physiological state of the subject.

[0013] According to a ninth aspect of this disclosure, a method is provided for determining instructions for neuromodulation of a subject. The method includes receiving data characterizing the physiological state of a subject from one or more digital craniotomy implants according to a first aspect or brain-computer interface modules according to a third aspect, wherein the data characterizing the physiological state of the subject is data processed from ultrasound data acquired by an ultrasound transducer. The method further includes determining instructions for neuromodulation of the subject based on the data characterizing the physiological state of the subject. Furthermore, the method includes sending instructions for neuromodulation of the subject to the digital craniotomy implant or the brain-computer interface module to perform ultrasound neuromodulation on the subject by the ultrasound transducer.

[0014] According to a tenth aspect of this disclosure, an electronic device is provided. The electronic device includes at least one processor and a memory. The memory is coupled to the at least one processor and has instructions stored thereon that, when executed by the at least one processor, cause the electronic device to perform the methods provided according to a sixth, seventh, eighth, or ninth aspect of this disclosure.

[0015] According to the eleventh aspect of this disclosure, a computer program product is provided. The computer program product includes a computer program that is executed by a processor to implement the methods provided according to the sixth, seventh, eighth, or ninth aspect of this disclosure.

[0016] According to a twelfth aspect of this disclosure, a machine-readable storage medium is provided. The machine-readable storage medium stores machine-executable instructions, which are executed by a processor to implement the methods provided according to a sixth, seventh, eighth, or ninth aspect of this disclosure.

[0017] It should be understood that the description in the Summary of the Invention section is not intended to limit the key or essential features of the embodiments of this disclosure, nor is it intended to restrict the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0018] The above and other objects, features, and advantages of embodiments of the present disclosure will become readily apparent from the following detailed description taken in conjunction with the accompanying drawings. Several embodiments of the present disclosure are illustrated in the drawings by way of example and not limitation.

[0019] Figure 1 A schematic diagram illustrating an example environment that can be implemented according to embodiments of the present disclosure;

[0020] Figure 2 An exemplary schematic diagram showing a cross-sectional structure of a digital cranial implant according to an embodiment of the present disclosure after implantation in a subject;

[0021] Figure 3 A schematic cross-sectional view of an exemplary brain-computer interface module according to an embodiment of the present disclosure is shown.

[0022] Figure 4 An exemplary block diagram of a brain-computer interface module according to an embodiment of the present disclosure is shown;

[0023] Figure 5 An exemplary principle block diagram of a brain-computer interface module according to an embodiment of the present disclosure is shown;

[0024] Figure 6 This diagram illustrates an exemplary schematic of a brain-computer interface module operating in a circuit board integration manner according to an embodiment of the present disclosure;

[0025] Figure 7A A schematic diagram of an exemplary array arrangement of an ultrasonic transducer according to an embodiment of the present disclosure is shown;

[0026] Figure 7B Another exemplary array arrangement schematic diagram of an ultrasonic transducer according to an embodiment of the present disclosure is shown;

[0027] Figure 8 Another exemplary block diagram of a brain-computer interface module according to an embodiment of the present disclosure is shown;

[0028] Figure 9 Another exemplary principle block diagram of a brain-computer interface module according to an embodiment of the present disclosure is shown;

[0029] Figure 10 A flowchart illustrating an integration method for a digital cranial implant according to an embodiment of the present disclosure is shown;

[0030] Figure 11 A schematic diagram illustrating an exemplary process of an integration method for a digital cranial implant according to an embodiment of the present disclosure is shown;

[0031] Figure 12 A schematic diagram illustrating an exemplary process of integrating a brain-computer interface module with a target skull as a digital skull implant according to an embodiment of the present disclosure is shown;

[0032] Figure 13A An exemplary schematic diagram is shown after a digital skull implant has been implanted in a subject according to an embodiment of the present disclosure;

[0033] Figure 13B An exemplary schematic diagram is shown after multiple digital skull implants according to embodiments of the present disclosure have been implanted in a subject;

[0034] Figure 14A A flowchart of an example method for monitoring the physiological activities of a subject according to an embodiment of the present disclosure is shown;

[0035] Figure 14B A flowchart is shown for another example method for monitoring the physiological activities of a subject according to an embodiment of the present disclosure;

[0036] Figure 15 A flowchart of an example method for determining instructions for neural modulation of a subject according to an embodiment of the present disclosure is shown;

[0037] Figure 16 A flowchart is shown of another example method for determining instructions for neural modulation of a subject according to an embodiment of the present disclosure;

[0038] Figure 17 A schematic diagram illustrating the training process of a machine learning model according to an embodiment of the present disclosure is shown;

[0039] Figure 18 A schematic diagram illustrating the interaction between an external electronic device and a subject based on a brain-computer interface module according to an embodiment of the present disclosure is shown. Detailed Implementation

[0040] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0041] In the description of embodiments of this disclosure, the term "comprising" and similar terms should be understood as open-ended inclusion, i.e., "including but not limited to". The term "based on" should be understood as "at least partially based on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first", "second", etc., may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0042] As mentioned earlier, brain-computer interfaces establish a direct connection pathway between the subject's brain and an external device. They can be applied to neuromodulation, including monitoring the subject's physiological activities (including physical or hemodynamic changes related to neural activity, such as changes in cerebral blood flow, blood volume, and neurons), decoding the subject's physiological state (including emotional state, pathological state, cognitive load, motor intention, etc.), and regulating the subject's physiological activities.

[0043] In some related technologies, brain-computer interface (BCI) stimulators (such as electrodes and ultrasound transducers) are implanted into a bone window in the skull by drilling a hole in the skull. An external controller is placed outside the body, and the implanted and external components are connected by wires. This semi-invasive BCI requires invasive implantation in the subject, followed by assembly of the BCI via wires after implantation. This method involves drilling holes from the outer to the inner surface of the skull to create an implantation bone window, which not only compromises the overall mechanical strength of the skull but also affects the seal between the implanted skull and the brain. Furthermore, the BCI components are connected via wires that pass through the scalp and skull, creating a skin-intracranial channel that disrupts the integrity of the blood-brain barrier. Additionally, the implanted stimulators are prone to displacement due to the pull of the external wires, leading to friction between the wires and tissues, causing local inflammation, granulomas, or fibrous encapsulation, thus affecting signal quality and device stability. In particular, the displacement of the stimulators affects the focusing accuracy and stimulation / imaging effect on the target brain region. In addition, this semi-invasive brain-computer interface has a poor user experience. Exposed connecting wires cause scalp bulges at the implantation site, affecting aesthetics. Furthermore, the stimulation components are easily pulled by the peripheral controller, causing pain to the user or damage to the device.

[0044] Therefore, embodiments of this disclosure propose an implant scheme that integrates a brain-computer interface module with the target skull (hereinafter referred to as the skull prosthesis or the subject's own skull) into a single unit. In embodiments of this disclosure, the brain-computer interface module (including an ultrasonic transducer and other functional components) is integrated with the target skull. The brain-computer interface module has an ultrasonic transducer capable of sending ultrasonic signals to the brain and acquiring echo signals to establish a read / write pathway for communication with external devices.

[0045] By integrating the brain-computer interface (BCI) module entirely with the target skull, the entire BCI can be implanted into the subject's head. The scalp can smoothly cover the skull implant (i.e., the integrated structure of the BCI module and the target skull), enabling wireless communication with external devices. This method integrates the skull implant externally and implants it into the subject's head, essentially achieving non-invasive implantation. It can replace the subject's skull with either a skull implant consisting of a skull prosthesis integrated with the BCI module, or a skull implant consisting of the BCI module integrated into the subject's own skull. This not only avoids penetrating damage to the skull but also ensures a tight seal between the skull and brain, maintaining the integrity of the blood-brain barrier. The brain-computer interface module can be used stably on the subject's head (including stable physical support, accurate and unbiased focusing on the target area, and stable signal transmission and reception). Ultrasound can penetrate the skull to precisely stimulate deep brain regions (such as the thalamus, hippocampus, and basal ganglia). It also uses wireless communication to achieve two-way communication between the external device and the brain, thus realizing the digital capability of "the skull as a device". It integrates biomechanical substitution, acoustic transparency, ultrasound transmission and reception capabilities, and intelligent control interface.

[0046] Figure 1 A schematic diagram of an example environment 100 that can be implemented according to embodiments of the present disclosure is shown. Figure 1 As shown, environment 100 includes subject 102 (only a human head is shown, but it could also be an animal head). The subject's head shows a scalp 102-2, a brain, and a skull 102-1 located between the scalp 102-2 and the brain. Environment 100 also includes a digital cranial implant 104, which can be an integrated structure combining a brain-computer interface module and a cranial prosthesis, or an integrated structure combining a brain-computer interface module and the subject's own skull. The digital cranial implant 104 is implanted into the head of subject 102. After implantation, the outer surface of the implant is flatly covered by the scalp 102. The ultrasound transducer of the brain-computer interface module acts on the brain, typically outside the brain parenchyma.

[0047] like Figure 1 As shown, environment 100 also includes a control module 106-1, which is communicatively connected to the brain-computer interface module in the digital cranial implant 104, enabling interaction between the control module 106-1 and the brain via a read / write channel. In some embodiments, the control module 106-1 is configured in an external electronic device / implanted device 106. The external electronic device can be a mobile device, such as a mobile tablet, mobile phone, laptop, handheld device, wearable device, etc., or a non-mobile device such as a desktop computer. The implanted device can be an electronic device implanted in the subject's body, such as a controller implanted in the subject's chest.

[0048] In some implementations, such as Figure 1 As shown, the digital cranial implant 104 includes a cranial prosthesis 104-1 and a brain-computer interface module 104-2. The cranial prosthesis 104-1 is biomimeticly fabricated based on any single cranial bone from the subject's skull. This cranial prosthesis 104-1 can be made from any of the following: titanium alloy, polyetheretherketone (PEEK), polyaryletherketone (PAEK), or hydroxyapatite. It can also be made from PEEK and bioactive ceramics (such as hydroxyapatite, β-TCP, or bioglass), polyaryletherketone and bioactive ceramics (such as hydroxyapatite, β-TCP, or bioglass), or a composite of hydroxyapatite and other bioactive ceramics (bioactive ceramics other than hydroxyapatite, such as bioglass or porous ceramics / tricalcium phosphate). Alternatively, it can be a composite of hydroxyapatite and a metal / polymer. The metal can be titanium or titanium alloy, and the polymer can be PLLA, PCL, or collagen. Figure 1 A skull prosthesis 104-1 based on parietal bone biomimicry is shown. A brain-computer interface module 104-2 is integrated into the inner surface of the skull prosthesis 104-1, meaning there is no visible incision on the outer surface of the skull prosthesis 104-1, and the brain-computer interface module 104-2 partially exposes the skull prosthesis 104-1, with one end having an ultrasonic transducer that acts on the brain. The user can send external commands to the brain-computer interface module 104-2 via an external electronic device / implanted device 106 through the control module 106-1. The brain-computer interface module 104-2 interprets the commands and drives the ultrasonic transducer within it to send ultrasound waves to the target area of ​​the brain 108. Furthermore, the ultrasonic transducer can also collect echoes from the target area of ​​the brain and send them from the brain-computer interface module 104-2 to the control module 106-1. The control module 106-1 acquires data on the subject's physiological activities, can further analyze the subject's physiological state, and can also provide feedback to adjust stimulation parameters, achieving closed-loop neuromodulation of the subject.

[0049] In some implementations, the brain-computer interface (BCI) module is integrated into the skull of the subject, such as the parietal bone. The BCI module is integrated into the inner surface of the skull, meaning there is no visible incision on the outer surface, and part of the BCI module is exposed above the skull, with one end having an ultrasound transducer that acts on the brain. The skull implant with the integrated BCI module communicates bidirectionally with the control module and can send ultrasound waves to the brain and collect the echoes.

[0050] In this way, the digital cranial implant can be implanted into the subject in a virtually non-invasive manner. It not only has a certain mechanical strength to stably support the brain-computer interface module placed in the brain and accurately focus on the target area, but also has good biocompatibility and sealing. It can ensure the biological safety of the subject while achieving millimeter-level or even sub-millimeter-level targeted stimulation, reducing interference with adjacent brain regions, improving the accuracy of neuromodulation, and can also use wireless communication to control the transmission and reception of ultrasonic transducers to achieve read and write control, and even read and write closed-loop regulation.

[0051] Figure 2 An exemplary schematic diagram shows a cross-sectional structure 200 of a digital cranial implant after implantation in a subject according to an embodiment of the present disclosure. Figure 2 As shown, the structure 200 includes a scalp 202, a skull prosthesis 204 (which can also be considered as the skull of the subject to be integrated with the brain-computer interface module), a dura mater 208, a brain 210, and a brain-computer interface module 206 integrated within the skull prosthesis 204. In some embodiments, a bone groove 204-1 is formed on the inner surface of the skull prosthesis 204, and the brain-computer interface module 206 is fixed to the bone groove 204-1, for example, by using clavicle screws to fix the brain-computer interface module 206, after which the brain-computer interface module 206 is at least partially exposed outside the bone groove 204-1. The end of the brain-computer interface module 206 is generally equipped with an ultrasonic transducer, which contacts the dura mater 208. In one example, the acoustically transparent portion of the end of the brain-computer interface module 206 contacts the dura mater and exerts slight, negligible pressure on the dura mater (this pressure will not cause damage or tearing of the dura mater).

[0052] like Figure 2 As shown, a sound-permeable and biocompatible intermediate layer is also provided within the bone groove 204-1. In some embodiments, this intermediate layer includes an absorption plate and a ceramic connection structure. The absorption plate is used to absorb the ultrasonic energy generated on the back of the ultrasonic transducer, preventing it from being reflected back and causing interference. The brain-computer interface module is rigidly connected to the bone groove 204-1 through the ceramic connection structure and the absorption plate. The intermediate layer also includes a sealant filling the gap between the brain-computer interface module 206 and the bone groove 204-1. This sealant is a biocompatible adhesive, such as medical-grade silicone, medical-grade epoxy resin, or polyurethane adhesive. In some embodiments, the absorption plate and the ceramic connection structure are encapsulated within the brain-computer interface module, and the brain-computer interface module forms a rigid connection body through the absorption plate and the ceramic connection structure, thereby rigidly connecting to the bone groove 204-1. The intermediate layer includes a sealant filling the gap between the brain-computer interface module 206 and the bone groove 204-1. This sealant is a biocompatible adhesive.

[0053] In this way, the brain-computer interface module is integrated with a skull prosthesis (or the subject's own skull) into a skull-shaped implant structure, which is then implanted into the subject's head. Wireless communication is used to achieve bidirectional communication between the external control module and the brain-computer interface module. This results in a smooth scalp covering the skull implant, with corresponding scalp growth between the skull bones being flat and without protruding openings. This achieves wire-free, low-interference-risk implantation, and is aesthetically pleasing, convenient to use, and provides a good user experience. Furthermore, while ensuring good mechanical strength of the skull, the brain-computer interface module possesses high spatial resolution, accurately focusing on target brain regions for precise targeted stimulation and signal acquisition.

[0054] Figure 3 A schematic cross-sectional view of an exemplary brain-computer interface module 300 according to an embodiment of the present disclosure is shown. Figure 3 As shown, the brain-computer interface module 300 includes a module body 302 and brain-computer interface functional devices / units integrated within the module body 302 (including an ultrasonic transducer, an ultrasonic transceiver and beamforming unit, a data processing and communication unit, a power management unit, etc.). An acoustic window 304 is provided at the end of the module body 302, and an ultrasonic transducer 306 is positioned close to the acoustic window 304. The ultrasonic transducer 306 is configured to transmit ultrasonic signals to the brain through the acoustic window and to acquire brain echo signals through the acoustic window. In some embodiments, the ultrasonic transducer is configured to cover one or more brain regions. In some embodiments, the ultrasonic transducer includes any one or more of a capacitive micromechanical ultrasonic transducer array, a piezoelectric micromechanical ultrasonic transducer array, and a lead zirconate titanate piezoelectric transducer array (e.g., multiple arrays of the same type, or multiple combinations of different types of arrays, such as two or three types as described above, with one or more of each type).

[0055] The acoustic window, acting as a gateway for ultrasound waves, ensures that the transmitted ultrasound waves are not significantly attenuated or distorted. It also serves as a barrier between the brain and the brain-computer interface module, preventing cerebrospinal fluid and other brain tissue from entering the module and affecting its electronic components. Furthermore, it prevents biological damage to the brain and dura mater, reducing brain tissue injury and lowering the risk of infection. In some embodiments, the acoustic window is made of a biocompatible polymer. In some examples, the biocompatible polymer is any one or more combinations of polymethyl methacrylate, polyetheretherketone, polychlorotrifluoroethylene, polytetrafluoroethylene, ultra-high molecular weight polyethylene, polyethylene terephthalate, low-density polyethylene, polyether block amide, and high-density polyethylene. In some implementations, the module body can be made of any one of titanium alloy, polyetheretherketone (PEEK), polyaryletherketone (PAEK), or hydroxyapatite. It can also be made of PEEK and bioactive ceramics (such as hydroxyapatite, β-TCP, or bioglass), polyaryletherketone and bioactive ceramics (such as hydroxyapatite, β-TCP, or bioglass), or a composite of hydroxyapatite and other bioactive ceramics (bioactive ceramics other than hydroxyapatite, such as bioglass or porous ceramics / tricalcium phosphate). Alternatively, it can be a composite of hydroxyapatite and a metal / polymer. The metal can be titanium or titanium alloy, and the polymer can be PLLA, PCL, or collagen.

[0056] Figure 4 An exemplary block diagram of a brain-computer interface module 400 according to an embodiment of the present disclosure is shown. Figure 4 As shown, the brain-computer interface module 400 includes an ultrasonic transducer 402, an ultrasonic transceiver and beamforming unit 404, a power management unit 406, and a data processing and communication unit 408. The ultrasonic transducer 402 is located near the end of the brain-computer interface module (e.g., [missing information]). Figure 3(See indicated location). The ultrasonic transceiver and beamforming unit 404 is used to drive the ultrasonic transducer 402 to transmit ultrasonic waves, and also to amplify and convert the received echoes from analog to digital. In some examples, the ultrasonic transceiver and beamforming unit 404 is positioned close to the ultrasonic transducer 402 to shorten the signal path, reduce noise, and achieve local high-speed beam control. The data processing and communication unit 408 has wireless communication capabilities and can communicate bidirectionally with an external control module. In some embodiments, the communication portion of the data processing and communication unit 408 can achieve bidirectional communication between the inside and outside of the unit via ultrasonic echo signals (acoustic return), radio frequency signals (such as UWB ultra-wideband signals, BLE low-power Bluetooth signals), or magnetic induction signals. On one hand, it receives instructions sent by the external control module, processes them, and sends them to the ultrasonic transceiver and beamforming unit; on the other hand, it receives the output signals of the ultrasonic transceiver and beamforming unit 404 and sends them to the external control module. The power management unit 406 is used to supply power to the ultrasonic transducer 402 and other units. The data processing and communication unit 408 and the power management unit 406 are positioned near the brain-computer interface module facing the scalp to facilitate heat dissipation. In some examples, the data processing and communication unit 408 and the power management unit 406 may be located at the edge of the skull or near the suture between adjacent skull bones or at the interface between the skull and the scalp.

[0057] Figure 5 An exemplary principle block diagram of a brain-computer interface module according to an embodiment of the present disclosure is shown. Figure 5 As shown, the brain-computer interface module includes a data processing and communication unit 502, an ultrasound transceiver and beamforming unit 504, an ultrasound transducer 506, and a power management unit 508. In some embodiments, the data processing and communication unit 502 includes a SoC (System-on-a-Chip) with wireless communication capabilities, enabling parameter setting (e.g., configuring SoC operating parameters such as sampling rate, channel selection, gain, and filter frequency range), remote control (e.g., adjusting system operating status, starting / stopping recording, etc.), and signal uplink. In some examples, the SoC integrates a lightweight neural network inference engine for feature extraction to achieve decoding. In some embodiments, the ultrasound transceiver and beamforming unit 504 includes a waveform generator 504-1, a drive circuit 504-2, a feedback amplifier 504-3, and an analog-to-digital conversion circuit 504-4. In some embodiments, the power management unit 508 includes a wireless charging coil 508-1 and / or a dry cell battery 508-2. Furthermore, the power management unit 508 also includes a magnetic resonance coil, a capacitor energy storage module, etc.

[0058] Figure 5The interaction process 500 between the brain-computer interface module and the control module is illustrated. This process 500 includes the control module sending external commands to a data processing and communication unit 502. The data processing and communication unit parses the external commands and sends them to a waveform generator 504-1. The waveform generator generates electrical signal waveforms (such as sine waves or pulse sequences) of specific frequency, amplitude, and phase according to the external commands. Then, a drive circuit 504-2 amplifies the output signal of the waveform generator to a high-power electrical signal to drive an ultrasonic transducer 506. The ultrasonic transducer 506 converts the electrical signal into ultrasound waves and emits ultrasound signals towards the target area 510 of the brain. This process 500 includes the ultrasonic transducer 506 acquiring brain echo signals from the target area 510 (i.e., backscattered echoes after ultrasound waves are emitted into the target area). The ultrasonic transducer 506 converts the acquired echo signals into electrical signals and sends them to a feedback amplifier 504-3 for amplification. Feedback amplifier 504-3 sends the amplified electrical signal to analog-to-digital converter 504-4. Analog-to-digital converter 504-4 outputs a digital signal to data processing and communication unit 502. Data processing and communication unit 502 uploads data representing physiological activity (i.e., physiological activity data in the figure, which can be understood as data after processing the acquired ultrasound echo data) to the control module. In some implementations, the control module monitors the physiological activity of the subject through the data representing physiological activity acquired by the brain-computer interface module, such as the subject's electrocardiogram (ECG), electroencephalogram (EEG), and electromyogram (EMG). In some implementations, the control module reconstructs brain structures or blood flow distribution through the data representing physiological activity acquired by the brain-computer interface module. In some implementations, the control module decodes the data representing physiological activity acquired by the brain-computer interface module to obtain the subject's physiological state. In one example, the intention of an ALS patient is decoded to determine the motor intention, thereby enabling thought control, such as controlling external devices to assist limb movements or sending stimuli to trigger the subject's limbs to perform actions. In some implementations, the control module sends stimulation signals to the target area via a brain-computer interface module to modulate abnormal neural activity. For example, by sending ultrasound stimulation signals to specific brain regions (such as the amygdala or nucleus accumbens), abnormal neural activity can be modulated to treat tremors in Parkinson's disease, seizures, and major depressive disorder. In some implementations, the control module sends stimulation signals to the target area via a brain-computer interface module, obtains feedback from the brain after stimulation, and readjusts the stimulation parameters. In one example, when using neurostimulation to treat depression, the doctor sends stimulation signals to a specific area of ​​the patient's brain, detects the brain's feedback signals to determine if the stimulation parameters are appropriate, adjusts the parameters, and resends the stimulation signals to achieve an ideal or better neural state. Accordingly, the ultrasound transceiver and beamforming unit is also configured to achieve adaptive focusing or beam self-calibration based on feedback signals.

[0059] Figure 6 An exemplary schematic diagram illustrating a brain-computer interface module operating in a circuit board integrated manner according to an embodiment of the present disclosure is shown, illustrating an example process 600 of communication and interaction between the brain and an external control module. Figure 6 As shown, the brain-computer interface module 602 integrates one or more circuit boards 602-1, ..., 602-N. In some embodiments, the ultrasound transducer is generally integrated on a circuit board 602-1 closest to the brain 604. In some examples, the ultrasound transducer is arranged on a dedicated complementary metal-oxide-semiconductor integrated circuit. In some examples, the ultrasound transducer has a separate integrated circuit board. Other units are integrated on different circuit boards or some of their electronic components are integrated on a single circuit board. For example, the ultrasound transceiver and beamforming unit, the data processing and communication unit, and the power management unit are all arranged on a single circuit board, or they are arranged on different circuit boards, or the electronic components in any two units are at least partially arranged on the same circuit board. In some examples, the ultrasound transducer and some electronic components in other units are integrated on a single circuit board. For example, the electronic components in any one of the ultrasound transceiver and beamforming unit, the data processing and communication unit, and the power management unit are at least partially arranged on the same circuit board as the ultrasound transducer. In some examples, the ultrasonic transducer, ultrasonic transceiver and beamforming unit, data processing and communication unit, and power management unit are all arranged on a single circuit board. For example... Figure 6 As shown, to shorten the signal path, reduce noise, and achieve local high-speed beam control, the ultrasonic transceiver and beamforming unit 404 can be arranged on a circuit board close to the ultrasonic transducer 402 for heat dissipation. For heat dissipation, the data processing and communication unit 408 and the power management unit can be arranged near the scalp, as shown on circuit board 602-N in the figure. Figure 6 In the example shown, the brain-computer interface module has three circuit boards. The top layer can accommodate a data processing and communication unit and a power management unit; the middle layer can accommodate an ultrasound transceiver and beamforming unit; and the bottom layer, near the acoustic window, can accommodate an ultrasound transducer. Figure 6 As shown, the process 600 includes a control module 606 performing bidirectional wireless communication with a brain-computer interface module 602, and the brain-computer interface module 602 sending ultrasound waves to the brain 604 and collecting echoes to achieve neuromodulation in multiple ways such as reading, writing, and reading and writing.

[0060] In one or more embodiments of this disclosure, the ultrasonic transducer is configured with multiple functional arrays, which can be implemented by any one or more of capacitive micromechanical ultrasonic transducer arrays (CMUT), piezoelectric micromechanical ultrasonic transducer arrays (PMUT), and lead zirconate titanate piezoelectric transducer arrays (PZT). The CMUT and PMUT are flexible ultrasonic transducer arrays with a thickness of 0.1-0.5 mm, enabling miniaturized integration and implantation outside the dura mater, avoiding compression damage to brain tissue. Furthermore, the elastic modulus of the flexible transducer array can match that of the brain tissue and dura mater, reducing chronic inflammatory responses and scratches to the brain tissue. The PZT can be bonded to a flexible polymer substrate or integrated in the form of a thin film (nanoscale). In one or more embodiments of this disclosure, the arrangement of the ultrasonic transducer arrays can be a one-dimensional linear array, a two-dimensional planar array (e.g., ... Figure 7B 700B in the middle) or curved surface array (such as Figure 7A The 700A curved array can match the curved surface of the skull or dura mater for better contact with the skull or dura mater. Figure 7A Multiple functional arrays are shown, at least for achieving functional ultrasound imaging and focused ultrasound transcranial stimulation. Each functional array is used to achieve a specific function (imaging or stimulation) on a target region and can correspond to different brain regions, including F area (frontal motor area), C area (central sulcus area), L / R area (superior temporal gyrus-lateral perischisis area), and P area (posterior parietal cortex area), with each area configured with 200-500 array elements. In some examples, array elements can be shared between multiple functional arrays, such as... Figure 7A The 702-1 and 702-2 are examples of functional arrays. For instance... Figure 7B Functional arrays 704-1 and 704-2 are provided. In some examples, multiple functional arrays are composed of different array elements. In one or more embodiments of this disclosure, the element spacing of the ultrasonic transducer may be less than half the wavelength to avoid beam sidelobe interference. Figure 7A and Figure 7B This is only an example of array arrangement; the actual number of array elements and array structure are not limited to what is shown in the figure.

[0061] Figure 8 Another exemplary block diagram of a brain-computer interface module 800 according to an embodiment of the present disclosure is shown. Figure 8 As shown, the brain-computer interface module 800 includes an ultrasonic transducer 802, an ultrasonic transceiver and beamforming unit 804, a power management unit 806, a data processing and communication unit 808, an electrophysiological signal acquisition unit 810, and an optical sensing unit 812. The ultrasonic transducer 802 is located near the end of the brain-computer interface module (e.g., ...). Figure 3(See indicated location). The ultrasonic transceiver and beamforming unit 804 is used to drive the ultrasonic transducer 802 to transmit ultrasonic waves, and also to amplify and convert the received echoes from analog to digital. In some examples, the ultrasonic transceiver and beamforming unit 804 is positioned close to the ultrasonic transducer 802 to shorten the signal path, reduce noise, and achieve local high-speed beam control. The data processing and communication unit 808 has wireless communication capabilities and can communicate bidirectionally with an external control module. In some implementations, the communication portion of the data processing and communication unit 808 can achieve bidirectional communication between the inside and outside of the unit via ultrasonic echo signals (acoustic return), radio frequency signals (such as UWB ultra-wideband signals, BLE low-power Bluetooth signals), or magnetic induction signals. On one hand, it receives instructions sent by the external control module, processes them, and sends them to the ultrasonic transceiver and beamforming unit; on the other hand, it receives the output signals of the ultrasonic transceiver and beamforming unit 804 and sends them to the external control module. The power management unit 806 is used to supply power to the ultrasonic transducer 802 and other units. The data processing and communication unit 808 and the power management unit 806 are positioned near the brain-computer interface module, facing the scalp, for heat dissipation. In some examples, the data processing and communication unit 808 and the power management unit 806 may be located at the edge of the skull, near adjacent cranial sutures, or at the interface between the skull and the scalp. The electrophysiological signal acquisition unit 810 is configured to record local field potentials or individual neuronal potentials via an electrode array to cooperate with the ultrasound channel for electroacoustic fusion. The optical sensing unit 821 extracts changes in hemoglobin concentration by controlling the illumination of the cerebral cortex with a light source and detecting changes in the intensity of reflected light, to be fused with the ultrasound channel for optical fusion. In some implementations, multimodal fusion is achieved using electroacoustic fusion, optical fusion, and electroacoustic fusion schemes to identify pathological events from multiple dimensions or to perform neuromodulation from multiple dimensions.

[0062] Figure 9 Another exemplary block diagram of a brain-computer interface module according to an embodiment of this disclosure is shown. Figure 9As shown, the brain-computer interface module includes a data processing and communication unit 902, an ultrasound transceiver and beamforming unit 904, an ultrasound transducer 906, a power management unit 908, an electrophysiological signal acquisition unit 912, and an optical sensing unit 914. In some embodiments, the data processing and communication unit 902 includes a SoC (System-on-a-Chip) with wireless communication capabilities, enabling parameter setting (e.g., configuring SoC operating parameters, sampling rate, channel selection, gain, filter frequency range, etc.), remote control (e.g., adjusting system operating status, starting / stopping recording, etc.), and signal uplink. In some examples, the SoC integrates a lightweight neural network inference engine for feature extraction to achieve decoding. In some embodiments, the ultrasound transceiver and beamforming unit 904 includes an ultrasound generator 904-1, a first drive circuit 904-2, a first feedback amplifier 904-3, and a first analog-to-digital conversion circuit 904-4. In some embodiments, the power management unit 908 includes a wireless charging coil and / or a dry cell battery. In addition, the power management unit 908 also includes a magnetic resonance coil, a capacitor energy storage module, etc. In some embodiments, the electrophysiological signal acquisition unit 912 includes an electrode array (which can be used to acquire electrical signal feedback), a second feedback amplifier, and a second analog-to-digital conversion circuit. In some embodiments, the optical sensing unit 914 includes a sensor, a light source, a third driving circuit, a third feedback amplifier, and a third analog-to-digital conversion circuit.

[0063] Figure 9The diagram illustrates the interaction process 900 between the brain-computer interface module and the control module. This process 900 includes the control module sending external commands to a data processing and communication unit 902. The data processing and communication unit parses the external commands and sends them to an ultrasound generator 904-1. The ultrasound generator generates electrical signal waveforms (such as sine waves or pulse sequences) with specific frequency, amplitude, and phase according to the external commands. Then, a first drive circuit 904-2 amplifies the output signal of the ultrasound generator to a high-power electrical signal to drive an ultrasound transducer 906. The ultrasound transducer 906 converts the electrical signal into ultrasound waves and emits the ultrasound signal towards a target area 910 of the brain. This process 900 also includes the ultrasound transducer 906 acquiring brain echo signals from the target area 910 (i.e., backscattered echoes after ultrasound waves are emitted into the target area). The ultrasound transducer 906 converts the acquired echo signals into electrical signals and sends them to a first feedback amplifier 904-3 for amplification. The first feedback amplifier 904-3 sends the enhanced electrical signal to the first analog-to-digital converter 904-4. The first analog-to-digital converter 904-4 outputs a digital signal to the data processing and communication unit 902. The data processing and communication unit 902 uploads the data representing physiological activity (i.e., the physiological activity data in the figure, which can be understood as the data after processing the collected ultrasound echo data) to the control module. In some implementations, the control module monitors the physiological activities of the subject through the data representing physiological activity acquired by the brain-computer interface module, such as the subject's electrocardiogram, electroencephalogram, and electromyogram. In some implementations, the control module reconstructs brain structures or blood flow distribution through the data representing physiological activity acquired by the brain-computer interface module. In some implementations, the control module decodes the data representing physiological activity acquired by the brain-computer interface module to obtain the subject's physiological state. In one example, the intention of an ALS patient is decoded to determine the motor intention, thereby enabling thought control, such as controlling external devices to assist limb movements or sending stimuli to trigger the subject's limbs to perform actions. In some implementations, the control module sends stimulation signals to the target area via a brain-computer interface module to modulate abnormal neural activity. For example, by sending ultrasound stimulation signals to specific brain regions (such as the amygdala or nucleus accumbens), abnormal neural activity can be modulated to treat tremors in Parkinson's disease, seizures, and major depressive disorder. In some implementations, the control module sends stimulation signals to the target area via a brain-computer interface module, obtains feedback from the brain after stimulation, and readjusts the stimulation parameters. In one example, when using neurostimulation to treat depression, the doctor sends stimulation signals to a specific area of ​​the patient's brain, detects the brain's feedback signals to determine if the stimulation parameters are appropriate, adjusts the parameters, and resends the stimulation signals to achieve an ideal or better neural state. Accordingly, the ultrasound transceiver and beamforming unit is also configured to achieve adaptive focusing or beam self-calibration based on feedback signals.

[0064] like Figure 9 As shown, the process 900 includes an electrode array acquiring brain echo signals (which may be neuronal potentials, field potentials, etc.) from the target region 910. The electrode array converts the acquired echo signals into electrical signals and sends them to a second feedback amplifier for amplification. The second feedback amplifier sends the amplified electrical signals to a second analog-to-digital conversion circuit. The second analog-to-digital conversion circuit outputs digital signals to a data processing and communication unit 902. The data processing and communication unit 902 uploads the data characterizing physiological activity to the control module.

[0065] like Figure 9 As shown, process 900 includes a control module sending external commands to a data processing and communication unit 902. The data processing and communication unit parses the external commands and sends them to a light source and a third driving circuit to emit the desired light wave to the target area 910. The light source can be a wavelength capable of penetrating tissue and being absorbed or reflected by specific biomolecules, such as near-infrared light. Process 900 includes a collector (such as a near-infrared spectrometer) collecting brain echo signals from the target area 910 (which can be diffuse reflection signals received by the collector after light is absorbed by hemoglobin (HbO and HbR)). The collector converts the collected echo signals into small electrical signals and sends them to a third feedback amplifier for amplification. The third feedback amplifier sends the filtered and amplified electrical signals to a third analog-to-digital conversion circuit. The third analog-to-digital conversion circuit outputs a digital signal to the data processing and communication unit 902. The data processing and communication unit 902 uploads data characterizing physiological activity to the control module.

[0066] In one or more embodiments of this disclosure, multimodal recognition of different brain activity patterns or multimodal modulation of brain activity is achieved using sound waves and radio waves (or sound waves and light waves, or sound waves, light waves, and radio waves). In some examples, transcranial ultrasound stimulation of the left inferior frontal gyrus (Broca's area) enhances language production excitability; simultaneously, an electrode array acquires high-frequency gamma (70–150 Hz) signals to decode vocabulary. This significantly improves the efficiency of intent decoding and recognition. In some examples, changes in prefrontal HbO are monitored using optical stimulation and photodetector feedback to determine anxiety levels; when the anxiety level exceeds a threshold, targeted ultrasound stimulation of the amygdala is used to modulate the subject's emotions. In some examples, ultrasound stimulation of a target brain region is used, with electrophysiological acquisition units and photosensing units acquiring electrical and optical signal feedback, respectively, to utilize multimodal feedback modulation.

[0067] Figure 10A flowchart illustrating an integration method 1000 for a digital cranial implant according to an embodiment of the present disclosure is shown. In some embodiments, the method 1000 may be implemented via 3D printing, CNC machining, or other custom equipment processes. It should be understood that the method 1000 may also include additional actions not shown and / or the actions shown may be omitted, and the scope of the present disclosure is not limited in this respect. Figure 10 As shown in block 1002, method 1000 can form a bone groove 1002 on the inner surface of the skull prosthesis. In some embodiments, the skull prosthesis is biomimetically fabricated based on the target skull of the test subject. For example, after acquiring CT / MR images of the target skull, the images are processed and modeled, and the skull prosthesis is fabricated using 3D printing technology (such as FDM or SLM). Then, a groove is ground on the inner surface of the fabricated skull prosthesis according to the dimensions of the integrated brain-computer interface module. In block 1004, method 1000 can fix the brain-computer interface module to the bone groove to integrate it with the skull prosthesis into a single structure. In some embodiments, the brain-computer interface module is fixed to the bone groove through an acoustically permeable and biocompatible intermediate layer, which improves ultrasound transmission efficiency and prevents tissue fluid inflow. In one example, the brain-computer interface module is rigidly connected to the bone groove by an absorbent plate and a ceramic connecting structure disposed in the intermediate layer. The brain-computer interface module can also be fixed to the bone groove using clavicle screws. Glue is applied to the gap between the brain-computer interface module and the bone groove. The aforementioned gaps are filled with biocompatible adhesives, such as medical-grade silicone, medical-grade epoxy resin, and polyurethane adhesive. Furthermore, bone cement or an osteointegration coating can be filled into the gap between the skull prosthesis and the bone groove to improve sealing, prevent tissue fluid leakage, subcutaneous fluid accumulation, and bacterial backflow, and provide sufficient strength to ensure the stable integration of the brain-computer interface module.

[0068] Figure 11 A schematic diagram of an exemplary process 1110 of an integration method for a digital cranial implant according to an embodiment of the present disclosure is shown. Figure 11As shown, in box 1102, the process 1100 can determine the target skull 1102 of the subject. In some embodiments, the target skull is determined from a region of the skull with high mechanical strength, such as the parietal bone, frontal bone, or skull around the central coronal suture. In box 1104, the process 1100 can fabricate a skull prosthesis based on the target skull of the subject. The implantation morphology is customized to achieve a high degree of conformity with the natural curvature of the skull. In box 1106, the process 1100 can groove the skull prosthesis so that the space within the groove can accommodate the brain-computer interface module. In some embodiments, a groove is cut into the skull prosthesis from its inner surface to its outer surface to form a bone groove (the bone groove is not visible on the outer surface of the skull prosthesis). In one or more embodiments of this disclosure, the ultrasonic transducer of the brain-computer interface module is at least partially located outside the bone groove to contact the dura mater of the subject. In block 1120, process 1100 may integrate electronics into the module body to fabricate the brain-computer interface module in block 1122. The electronics may be those constituting an ultrasonic transducer, a power management unit, an ultrasonic transceiver and beamforming unit, a data processing and communication unit, etc. In some embodiments, the skull prosthesis fabrication process and the brain-computer interface module fabrication process are performed independently. In process 1100, the brain-computer interface module can also be placed within the bone groove of the skull prosthesis, with the two rigidly connected to form the rigid connector of frame 1108. In some embodiments, the brain-computer interface module is rigidly connected to the bone groove via a ceramic connecting structure and an absorbent plate. Furthermore, the brain-computer interface module is also fixed to the bone groove via clavicle screws. In addition, process 1100 can also pot the rigid connector with adhesive, thereby integrating the brain-computer interface module into the skull prosthesis to form the digital skull implant of frame 1110. In some embodiments, adhesive is potted between the brain-computer interface module and the bone groove; this adhesive can be a biocompatible adhesive, such as medical-grade silicone, medical-grade epoxy resin, or polyurethane adhesive.

[0069] In this way, a personalized and adaptable skull prosthesis can be customized for the subject's skull, and the brain-computer interface module and the skull prosthesis can be integrated in vitro. During the operation, the original skull is replaced by an implant in the shape of the skull. Because the implantable structure has good mechanical strength and biocompatibility, the implant can fit the subject well and has good biological safety. Furthermore, the implant is stably fixed in the subject's head and has "digital capabilities", which can accurately focus on the target area of ​​the brain and accurately achieve targeted stimulation and signal acquisition.

[0070] Figure 12 A schematic diagram illustrating an exemplary process 1200 of integrating a brain-computer interface module with a target skull as a digital cranial implant according to an embodiment of the present disclosure is shown. Figure 12As shown, in block 1202, process 1200 can identify the target skull 1202 of the subject. In some embodiments, the target skull is identified as a region of the skull with high mechanical strength, such as the parietal bone, frontal bone, or skull around the central coronal suture. In block 1206, process 1200 can surgically groove the target skull such that the space within the groove can accommodate the brain-computer interface module. In some embodiments, the target skull is surgically removed and grooved on its inner surface to form a bone groove (the bone groove is not visible on the outer surface of the skull). In one or more embodiments of this disclosure, the ultrasonic transducer of the brain-computer interface module is at least partially located outside the bone groove to contact the dura mater of the subject. In block 1220, process 1200 can integrate electronics into the module body to fabricate the brain-computer interface module in block 1222. The electronics may be those constituting an ultrasonic transducer, a power management unit, an ultrasonic transceiver and beamforming unit, a data processing and communication unit, etc. In some implementations, the brain-computer interface (BCI) module fabrication process is completed preoperatively. During the procedure 1200, the BCI module can also be placed intraoperatively within a bone groove in the target skull, with the two rigidly connected to form a rigid connector of frame 1208. In some implementations, the BCI module is rigidly connected to the bone groove via a ceramic connection structure and an absorbent plate. The BCI module is also fixed to the bone groove using clavicle screws. Furthermore, the rigid connector can be glued during the procedure 1200, thereby integrating the BCI module into the target skull to form the digital cranial implant of frame 1310. In some implementations, glue is injected into the gap between the BCI module and the bone groove; this glue can be a biocompatible adhesive, such as medical-grade silicone, medical-grade epoxy resin, or polyurethane glue.

[0071] In this way, the brain-computer interface module can be integrated into the original skull of the subject during the operation. Because the implantable structure has good mechanical strength and biocompatibility, the implant can fit the subject well and has good biological safety. Furthermore, the implant is stably fixed in the subject's head and has "digital capabilities", which can accurately focus on the target area of ​​the brain and accurately achieve targeted stimulation and signal acquisition.

[0072] Figure 13A An exemplary schematic diagram is shown after a digital skull implant according to an embodiment of the present disclosure has been implanted in a subject. Figure 13AAs shown, the test subject has multiple skull fragments, one of which can be used as the target skull region for implanting a digital skull implant. For example, a skull prosthesis is fabricated based on parietal bone biomimicry, and the parietal bone skull prosthesis is integrated with the brain-computer interface module in vitro into a single skull implant structure. The skull implant is then placed in the corresponding location, replacing the target skull. To ensure complete integration, bone-inspired biomaterials (such as polyetheretherketone (PEEK) and polyaryletherketone (PEKK)) are used to match the coefficient of thermal expansion with the original bone edge. Microporous roughening treatment, medical bone putty, or bone integration coating at the joint promotes bone tissue creeping and growing towards the edge of the digital skull, thereby achieving continuous integral fusion of the original bone and digital skull in terms of mechanics, stability, and long-term biocompatibility. In some implementations, a brain-computer interface module can be integrated onto the skull prosthesis. In one example, such as... Figure 13A The parietal prosthesis 1301 in the figure integrates a brain-computer interface module 1302-1. A bone groove is opened on the inner surface of the parietal prosthesis, and the brain-computer interface module 1302-1 is not visible on the outer surface of the parietal prosthesis 1301.

[0073] In other implementations, the target skull (i.e., the native skull) of the subject can be removed intraoperatively, and the brain-computer interface module can be integrated onto the target skull during the procedure. The integrated skull implant is then placed into the location of the target skull. To ensure complete integration, a bone-like biomaterial (such as polyetheretherketone (PEEK) or polyaryletherketone (PEKK)) is used to match the coefficient of thermal expansion with the edge of the original bone. Microporous roughening treatment, medical bone putty, or an osteointegration coating are applied at the joint to promote bone tissue creeping and growing towards the edge of the digital skull, thereby achieving continuous integral fusion of the original and digital skulls in terms of mechanics, stability, and long-term biocompatibility. It is important to note that the process of removing the target skull from the body for in vitro integration is controlled within a reasonable timeframe to ensure the biosafety of the subject. In one example, a bone groove is created on the inner surface of the target skull, and the brain-computer interface module is not visible on the outer surface of the skull.

[0074] Figure 13B An exemplary schematic diagram is shown after multiple digital skull implants according to embodiments of the present disclosure have been implanted in a subject. Figure 13BAs shown, the test subject has multiple skull fragments, and digital skull implants can be implanted in each of the target skull regions, enabling intracranial wireless communication across multiple brain regions. In some implementations, multiple skull prostheses are biomimeticly fabricated based on the multiple skull fragments, and a brain-computer interface module is integrated with each skull prosthesis in vitro into a single skull implant structure. The number of integrations (generally no more than four) is determined based on the mechanical strength of the skull, with each brain-computer interface module distributed at the location of the skull prosthesis to correspond to different brain regions. The skull implant is then inserted into the corresponding location, replacing the target skull. To ensure complete integration, bone-inspired biomaterials (such as polyetheretherketone (PEEK) or polyaryletherketone (PEKK)) are used to match the coefficient of thermal expansion with the original bone edge. Microporous roughening treatment, medical bone putty, or bone integration coating at the joint promotes bone tissue creeping and growing towards the edge of the digital skull, thereby achieving continuous integral fusion of the original bone and digital skull in terms of mechanics, stability, and long-term biocompatibility. In one example, multiple brain-computer interface modules are integrated onto different cranial prostheses. For example, such as... Figure 13B In the figure, a brain-computer interface module 1304-1 is integrated on the frontal bone prosthesis 1304, and a brain-computer interface module 1303-1 is integrated on the parietal bone prosthesis 1303. Bone grooves are formed on the inner surfaces of the parietal and frontal bones of the test subjects, and the brain-computer interface modules are not visible on the outer surfaces of the frontal and parietal bone prostheses.

[0075] In other implementations, the target skull (i.e., the native skull) of the subject can be removed intraoperatively, and the brain-computer interface module can be integrated onto the target skull during the procedure. The integrated skull implant is then placed into the location of the target skull. To ensure complete integration, a bone-like biomaterial (such as polyetheretherketone (PEEK) or polyaryletherketone (PEKK)) is used to match the coefficient of thermal expansion with the edge of the original bone. Microporous roughening treatment, medical bone putty, or an osteointegration coating are applied at the joint to promote bone tissue creeping and growing towards the edge of the digital skull, thereby achieving continuous integral fusion of the original and digital skulls in terms of mechanics, stability, and long-term biocompatibility. It is important to note that the process of removing the target skull from the body for in vitro integration is controlled within a reasonable timeframe to ensure the biosafety of the subject. In one example, a bone groove is created on the inner surface of the target skull, and the brain-computer interface module is not visible on the outer surface of the skull.

[0076] Figure 14A A flowchart of an example method 1400A for monitoring the physiological activities of a subject according to an embodiment of the present disclosure is shown. Method 1400A may, for example, be derived from... Figure 1 The external electronic device or implanted device 106 in the environment 100 shown performs the operation. For example... Figure 14AAs shown in block 1402, method 1400A can send one or more signals to ultrasound transducers in one or more digital cranial implants, which are installed in place of a target skull in a subject. The one or more signals are transmitted via the one or more ultrasound transducers to alter the physiological activity of the subject. In one or more embodiments of this disclosure, the digital cranial implant is an integral structure integrating a brain-computer interface module with a cranial prosthesis. In some examples, a signal is sent to an ultrasound transducer in one digital cranial implant to instruct the transducer to transmit ultrasound waves that alter the physiological activity of the subject. In some examples, signals are sent to ultrasound transducers in multiple digital cranial implants to instruct them to transmit ultrasound waves that alter the physiological activity of the subject. The signals in the above examples may contain electrical signals of stimulation parameters, which are converted into ultrasound waves by the ultrasound transducers and applied to a target brain region. The physiological activity is the neural activity of the subject, which may be neural activity of the central nervous system or neural activity of the brain. In block 1404, method 1400A can receive data characterizing the physiological activities of a subject from one or more ultrasound transducers. In some embodiments, the ultrasound transducers receive echo signals and convert them into electrical signals, which are then converted into digital signals and sent to a control module. The control module receives data characterizing the physiological activities of the subject, such as data on neural electrical activity (e.g., electroencephalogram waves, cortical potentials, etc.), data on cerebral blood flow and metabolic activity (e.g., changes in hemoglobin concentration), and data on electromyographic activity (e.g., electromyographic waves).

[0077] In this embodiment, an external electronic device or implanted device 106 uses a control module to wirelessly control a brain-computer interface module to apply ultrasonic stimulation to a target area of ​​the subject's brain to alter the subject's physiological activity. The subject's physiological activity is then monitored by acquiring feedback data from the ultrasonic waves (i.e., data characterizing the subject's physiological activity). This method allows for accurate focusing of the target area and obtaining accurate feedback on changes in physiological activity, significantly improving the efficiency and accuracy of monitoring the subject's physiological activity.

[0078] Figure 14B A flowchart of another example method for monitoring the physiological activities of a subject according to an embodiment of this disclosure is shown. Method 1400B may, for example, be... Figure 1 The external electronic device or implanted device 106 in the environment 100 shown performs the operation. For example... Figure 14BAs shown in block 1412, method 1400B can send one or more signals to ultrasound transducers in one or more brain-computer interface modules. Either a skull prosthesis or a target skull is integrated with the brain-computer interface module in a single structure and installed at the location of the target skull in the subject. The one or more signals are transmitted via one or more ultrasound transducers to alter the physiological activity of the subject. In one or more embodiments of this disclosure, the brain-computer interface module is integrated with the skull prosthesis in vitro and replaces the original skull implant intraoperatively. In one or more embodiments of this disclosure, the brain-computer interface module is integrated with the target skull intraoperatively and implanted. In some examples, a signal is sent to one ultrasound transducer to instruct it to transmit ultrasound waves that alter the physiological activity of the subject. In some examples, signals are sent to multiple ultrasound transducers to instruct them to transmit ultrasound waves that alter the physiological activity of the subject. The signals in the above examples may contain electrical signals of stimulation parameters, which are converted into ultrasound waves by the ultrasound transducers and applied to the target brain region. The aforementioned physiological activities refer to the neural activities of the test subject, which can be neural activities of the central nervous system or neural activities of the brain. In block 1414, method 1400B can receive data characterizing the physiological activities of the test subject from one or more ultrasound transducers. In some embodiments, the ultrasound transducer receives echo signals and converts them into electrical signals, which are then converted into digital signals and sent to the control module. The control module receives data characterizing the physiological activities of the test subject, such as data on neural electrical activity (e.g., electroencephalogram (EEG), cortical potentials, etc.), data on cerebral blood flow and metabolic activity (e.g., changes in hemoglobin concentration), and data on electromyographic activity (e.g., electromyographic waves).

[0079] In this embodiment, an external electronic device or implanted device 106 uses a control module to wirelessly control a brain-computer interface module to apply ultrasonic stimulation to a target area of ​​the subject's brain to alter the subject's physiological activity. The subject's physiological activity is then monitored by acquiring feedback data from the ultrasonic waves (i.e., data characterizing the subject's physiological activity). This method allows for accurate focusing of the target area and obtaining accurate feedback on changes in physiological activity, significantly improving the efficiency and accuracy of monitoring the subject's physiological activity.

[0080] Figure 15 A flowchart of an example method 1500 for determining neural modulation of a subject according to an embodiment of the present disclosure is shown. Method 1500 may, for example, be derived by... Figure 1 The external electronic device or implanted device 106 in the environment 100 shown performs the operation. For example... Figure 15As shown in block 1502, method 1500 can receive data characterizing the physiological state of a subject from one or more digital cranial implants or brain-computer interface modules. This data characterizing the subject's physiological state is processed data from ultrasound data acquired by an ultrasound transducer. In one or more embodiments of this disclosure, the digital cranial implant is an integrated structure that combines the brain-computer interface module with a cranial prosthesis. In some examples, a control module in an external electronic device or implanted device 106 reads physiological activity data acquired by the ultrasound transducer in the digital cranial implant. This physiological activity data is converted into electrical signals by the ultrasound transducer, then converted into digital signals by the brain-computer interface module and sent to the control module. The control module decodes this data characterizing the subject's physiological state to obtain the subject's physiological state. In other words, the control module learns the subject's physiological state based on the collected physiological activity data. Physiological activity refers to the subject's neural activity, which can be neural activity of the central nervous system or neural activity of the brain. Physiological state refers to the neural activity state of a subject (including motor state, cognitive state, emotional state, state of consciousness, intention state, pathological state, etc.). This state is determined based on physiological activity. By extracting and classifying features from processed ultrasound data, the physiological state corresponding to different physiological activities can be identified. For example, the state of consciousness of a subject, such as wakefulness or sleep, can be determined using electroencephalogram (EEG) data. Another example is the motor state of a subject, which can be determined using cortical potential data.

[0081] In one or more embodiments of this invention, the brain-computer interface module may be integrated into a single structure with the native skull. In some examples, a control module in an external electronic device or implanted device 106 reads physiological activity data acquired by an ultrasound transducer in the brain-computer interface module. This physiological activity data is converted into electrical signals by the ultrasound transducer, and then converted into digital signals by the brain-computer interface module and sent to the control module. The control module then decodes this data characterizing the physiological state of the subject to obtain the subject's physiological state.

[0082] like Figure 15 As shown in block 1504, method 1500 can determine instructions for the subject's neural modulation based on data characterizing the subject's physiological state. These instructions can be used to modulate the subject's physiological state. These instructions can be sent to an ultrasound transducer to provide feedback modulation to the subject (e.g.,...). Figure 16 This instruction contains stimulus parameters. It can also be sent to external devices for targeted neuromodulation of the subject, containing modulation parameters. These external devices can be assistive neuromodulation devices, such as sleep aids and cognitive enhancement devices used in various scenarios.

[0083] Figure 16A flowchart of another example method 1600 for determining the neural modulation of a subject according to an embodiment of this disclosure is shown. Method 1600 may, for example, be derived by... Figure 1 The external electronic device or implanted device 106 in the environment 100 shown performs the operation. For example... Figure 16 As shown in block 1602, method 1600 can receive data characterizing the physiological state of a subject from one or more digital cranial implants or brain-computer interface modules. This data characterizing the subject's physiological state is processed data from ultrasound data acquired by an ultrasound transducer. In one or more embodiments of this disclosure, the digital cranial implant is an integrated structure that combines a brain-computer interface module with a cranial prosthesis. In some examples, a control module in an external electronic device or implanted device 106 reads physiological activity data acquired by the ultrasound transducer in the digital cranial implant. This physiological activity data is converted into electrical signals by the ultrasound transducer, then converted into digital signals by the brain-computer interface module and sent to the control module. The control module decodes this data characterizing the subject's physiological state to obtain the subject's physiological state. In other words, the control module learns the subject's physiological state based on the collected physiological activity data. Physiological activity refers to the subject's neural activity, which can be neural activity of the central nervous system or neural activity of the brain. Physiological state refers to the neural activity state of a subject (including motor state, cognitive state, emotional state, state of consciousness, intention state, pathological state, etc.). This state is determined based on physiological activity. By extracting and classifying features from processed ultrasound data, the physiological state corresponding to different physiological activities can be identified. For example, the state of consciousness of a subject, such as wakefulness or sleep, can be determined using electroencephalogram (EEG) data. Another example is the motor state of a subject, which can be determined using cortical potential data.

[0084] In one or more embodiments of this invention, the brain-computer interface module may be integrated into a single structure with the native skull. In some examples, a control module in an external electronic device or implanted device 106 reads physiological activity data acquired by an ultrasound transducer in the brain-computer interface module. This physiological activity data is converted into electrical signals by the ultrasound transducer, and then converted into digital signals by the brain-computer interface module and sent to the control module. The control module then decodes this data characterizing the physiological state of the subject to obtain the subject's physiological state.

[0085] In box 1604, method 1600 can determine instructions for the subject's neural modulation based on data characterizing the subject's physiological state. These instructions can be for modulating the subject's physiological state. The instructions can be sent to an ultrasound transducer for feedback modulation of the subject, and the instructions include stimulation parameters.

[0086] In block 1606, method 1600 can send instructions for subject neuromodulation to a digital cranial implant or brain-computer interface module to perform ultrasound neuromodulation on the subject by an ultrasound transducer.

[0087] In this way, by reading data representing the physiological state of the subject, the subject's physiological state is determined, and then instructions to regulate that physiological state are determined, enabling closed-loop neural modulation through reading and writing. In some implementations, the brain-computer interface module monitors the subject's physiological activities, and the control module extracts and classifies the features of this data to determine the subject's physiological state. Based on this physiological state, it then determines neural modulation instructions, including stimulation parameters. For example, monitoring the cortical electrical activity and cerebral blood flow changes in epilepsy patients, when an abnormal physiological state is detected, sends an instruction containing a pulse sequence to the ultrasound transducer to trigger the ultrasound transducer to send short-duration ultrasound pulse stimulation to the deep brain regions. This allows for proactive intervention before seizures occur, reducing the frequency of attacks. In some examples, the control module is equipped with a machine learning model to identify the received data representing the physiological state, which may be filtered, amplified, and analog-to-digital converted physiological activity data. Machine learning models extract features from data representing physiological states and output predictions of physiological states. These predictions can be classification labels (e.g., labels representing brain states), arrays (e.g., arrays of stimulus parameters), abnormal probabilities (e.g., the probability of abnormal brain states), or multi-source data composed of combinations of the above data types.

[0088] Figure 17 A schematic diagram of a training process 1700 for a machine learning model according to an embodiment of the present disclosure is shown. Method 1700 may, for example, be performed by... Figure 1 The external electronic device or implanted device 106 in the environment 100 shown can perform the training, or it can be performed by other electronic devices, and the machine learning model is deployed after training is completed. Figure 1 External electronic devices or implanted devices 106 in the environment 100 shown. For example... Figure 17As shown, process 1700 includes training the machine learning model 1704 based on training samples 1702. The diagram illustrates this using the prediction results of output stimulus parameters as an example. This machine learning model can employ models such as Support Vector Machine (SVM), Random Forest, or Deep Learning Network. The machine learning model includes a feature extraction module 1704-1 and a prediction module 1704-2. The feature extraction module 1704-1 extracts data based on sample ultrasound data 1702-2. In this process, sample ultrasound data 1702-2 is data collected by an ultrasound transducer. It requires processing such as converting the ultrasound signal to an electrical signal, amplification, analog-to-digital conversion, and filtering before being sent to the feature extraction module for feature extraction, obtaining the feature vector of the physiological state in box 1706. The prediction module 1704-2 determines the stimulus parameters related to this physiological state based on the feature vector, i.e., the predicted stimulus parameters for box 1708. Subsequently, the loss module 1710 calculates the loss based on the predicted stimulus parameters and the sample stimulus parameters (stimulation parameters that have shown good effects on neural modulation as determined by clinical trials, under which the subject's brain state reaches a relatively ideal state or a better target state). When the loss value is large, the parameters of the machine learning model 1704 are adjusted inversely until convergence. In one example, the loss module 1710 calls the cross-entropy algorithm to calculate the loss value. The loss module 1710 can also calculate the loss value using mean squared error, and can also introduce multi-task losses including cross-entropy loss and mean squared error.

[0089] The machine learning model is trained through the above process and then deployed in the control module. The control module uses the machine learning model to predict data representing the physiological state of the subject, predicting stimulus parameters and feeding these parameters back to the brain-computer interface module for real-time closed-loop control (e.g., applying the machine learning model to...). Figure 16 The example shown is used to determine the instructions for the subject's neural regulation in order to effectively control the subject's brain neural state.

[0090] In addition, machine learning models can predict other data formats; the training process can be referenced. Figure 17 Example implementation. For instance, the prediction model outputs labels for physiological states. The control module, based on these labels, invokes the predicted regulatory instructions and sends them to an external assistive device or brain-computer interface module to provide feedback regulation to the subject. Another example is that the prediction model outputs the probability of abnormal physiological states. The control module determines regulatory instructions related to different degrees of abnormality by comparing predicted probabilities exceeding a threshold, and sends these instructions to an external assistive device or brain-computer interface module to provide feedback regulation to the subject.

[0091] Figure 18 A schematic diagram illustrating the interaction between an external electronic device and a subject based on a brain-computer interface module according to an embodiment of the present disclosure is shown. Figure 18 As shown, the subject's head 1802 has a digital craniotomy implant 1804 or an integrated structure combining the native skull and a brain-computer interface module. A control module is located on an external computer 1806, which communicates bidirectionally with the brain-computer interface module in the digital craniotomy implant 1804 or integrated on the native skull. The external computer 1806 displays data related to the subject's physiological activities (e.g., electrocardiogram, electroencephalogram, electromyography, etc., are shown in the figure as examples of detecting the subject's physiological activities), or data related to physiological state, or imaging data (such as anatomical ultrasound imaging data, power Doppler imaging data, etc.).

[0092] This disclosure also provides an electronic device including a processor that can perform various appropriate actions and processes based on computer program instructions loaded into random access memory (RAM) according to computer program instructions stored in read-only memory (ROM). Various programs and data required for device operation may also be stored in the RAM. The processor, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0093] The various processes and procedures described above, such as methods 1400A, 1400B, 1500, and 1600, can be executed by a processor. For example, in some embodiments, methods 1400A, 1400B, 1500, and 1600 can be implemented as software programs tangibly contained in a machine-readable medium. In some embodiments, part or all of the software program can be loaded into and / or installed onto the device via ROM. When the software program is loaded into RAM and executed by a processor, one or more actions of methods 1400A, 1400B, 1500, and 1600 described above can be performed.

[0094] Embodiments of this disclosure also provide a computer-readable storage medium storing instructions that, when executed on a computer or processor, cause the computer or processor to perform one or more steps in the above-described method embodiments. If the constituent modules of the above-described electronic device are implemented as software functional units and sold or used as independent products, they can be stored in the computer-readable storage medium.

[0095] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this specification are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., Digital Versatile Discs (DVDs)), or semiconductor media (e.g., Solid State Disks (SSDs)).

[0096] The embodiments described above are merely preferred embodiments of this specification and are not intended to limit the scope of this specification. Any modifications and improvements made by those skilled in the art to the technical solutions of this specification without departing from the spirit of this specification should fall within the protection scope defined by the claims of this specification.

Claims

1. A digital cranial implant, characterized in that, The invention includes a skull prosthesis and a brain-computer interface module, wherein the brain-computer interface module is integrated with the skull prosthesis; the brain-computer interface module includes an ultrasound transducer for sending ultrasound signals to the brain and acquiring brain echo signals.

2. The digital cranial implant according to claim 1, characterized in that, The inner surface of the skull prosthesis has a bone groove, and the brain-computer interface module is fixed to the bone groove.

3. The digital cranial implant according to claim 2, characterized in that, An intermediate layer with sound permeability and biocompatibility is provided between the bone groove and the brain-computer interface module.

4. The digital cranial implant according to claim 3, characterized in that, The intermediate layer is provided with an absorption plate and a ceramic connecting structure to rigidly connect the brain-computer interface module to the bone groove, and the intermediate layer is provided with sealant to fill the gap between the brain-computer interface module and the bone groove.

5. The digital cranial implant according to claim 1, characterized in that, The cranial prosthesis is made of any one of titanium alloy, polyetheretherketone, polyaryletherketone, and hydroxyapatite; or, the cranial prosthesis is made of polyetheretherketone and bioactive ceramics; or, the cranial prosthesis is made of polyaryletherketone and bioactive ceramics; or, the cranial prosthesis is made of hydroxyapatite and other bioactive ceramics; or, the cranial prosthesis is made of hydroxyapatite and metal / polymer composite.

6. The digital cranial implant according to claim 1 or 5, characterized in that, The skull prosthesis is made by biomimicking any one part of the skull in the subject's brain.

7. The digital cranial implant according to claim 1, characterized in that, The brain-computer interface module includes a module body, an ultrasonic transducer integrated in the module body, and an acoustic window located at the end of the module body; the ultrasonic transducer is configured to transmit ultrasonic signals to the brain through the acoustic window and to collect brain echo signals through the acoustic window.

8. The digital cranial implant according to claim 1 or 7, characterized in that, The brain-computer interface module also includes an ultrasound transceiver and beamforming unit, a data processing and communication unit, and a power management unit.

9. The digital cranial implant according to claim 8, characterized in that, The ultrasonic transceiver and beamforming unit is configured to achieve adaptive focusing or beam self-calibration based on feedback signals.

10. The digital cranial implant according to claim 8, characterized in that, The data processing and communication unit is configured to achieve bidirectional communication between the body and the outside via ultrasonic echo signals, radio frequency signals, or magnetic induction signals.

11. The digital cranial implant according to claim 8, characterized in that, The brain-computer interface module also includes one or more circuit boards. The ultrasound transceiver and beamforming unit, the data processing and communication unit, and the power management unit are all arranged on one circuit board, or they are arranged on different circuit boards, or the electronic devices in any two units are at least partially arranged on the same circuit board.

12. The digital cranial implant according to claim 11, characterized in that, The ultrasonic transducer, the ultrasonic transceiver and beamforming unit, the data processing and communication unit, and the power management unit are all arranged on a single circuit board, or they are arranged on different circuit boards, or at least some of the electronic components in any one of the ultrasonic transceiver and beamforming unit, the data processing and communication unit, and the power management unit are arranged on the same circuit board as the ultrasonic transducer.

13. The digital cranial implant according to claim 8, characterized in that, The ultrasonic transducer is located near the end of the brain-computer interface module.

14. The digital cranial implant according to claim 13, characterized in that, The ultrasound transceiver and beamforming unit is located near the ultrasound transducer, and the data processing and communication unit and the power management unit are located near the brain-computer interface module facing the scalp.

15. The digital cranial implant according to claim 7, characterized in that, The module body is made of any one of titanium alloy, polyetheretherketone, polyaryletherketone, and hydroxyapatite; or, the module body is made of polyetheretherketone and bioactive ceramics; or, the module body is made of polyaryletherketone and bioactive ceramics; or, the cranial prosthesis is made of hydroxyapatite and other bioactive ceramics; or, the cranial prosthesis is made of hydroxyapatite and metal / polymer composite.

16. The digital cranial implant according to claim 7, characterized in that, The acoustic window is made of a biocompatible polymer.

17. The digital cranial implant according to claim 16, characterized in that, The biocompatible polymer is any one or a combination of polymethyl methacrylate, polyether ether ketone, polychlorotrifluoroethylene, polytetrafluoroethylene, ultra-high molecular weight polyethylene, polyethylene terephthalate, low-density polyethylene, polyether block amide, and high-density polyethylene.

18. The digital cranial implant according to claim 1 or 7, characterized in that, The ultrasound transducer is configured to cover one or more brain regions.

19. The digital cranial implant according to claim 1 or 7, characterized in that, The ultrasound transducer is configured with multiple functional arrays, which are used at least to achieve functional ultrasound imaging and focused ultrasound transcranial stimulation.

20. The digital cranial implant according to claim 19, characterized in that, The brain-computer interface module also includes an electrophysiological signal acquisition unit and / or an optical sensing unit, which are configured to work in conjunction with the ultrasound transducer to achieve multimodal signal acquisition and modulation.

21. The digital cranial implant according to claim 1 or 7, characterized in that, The ultrasonic transducer includes any one or more of the following: capacitive micromechanical ultrasonic transducer array, piezoelectric micromechanical ultrasonic transducer array, and lead zirconate titanate piezoelectric transducer array.

22. The digital cranial implant according to claim 1 or 7, characterized in that, The ultrasonic transducer is mounted on a dedicated integrated circuit for complementary metal-oxide-semiconductor.

23. The digital cranial implant according to claim 1 or 7, characterized in that, The ultrasonic transducer is configured to contact the dura mater of the subject.

24. A method for integrating digital cranial implants, characterized in that, The digital cranial implant is an implant according to any one of claims 1-23, and the method includes: The bone groove is formed on the inner surface of the skull prosthesis; and The brain-computer interface module is fixed to the bone groove to integrate it with the skull prosthesis into a single structure.

25. The method according to claim 24, characterized in that, The process of integrating the brain-computer interface module with the skull prosthesis into a single structure includes: The brain-computer interface module is fixed to the bone groove through an intermediate layer that is acoustically permeable and biocompatible.

26. The method according to claim 25, characterized in that, The brain-computer interface module is fixed to the bone groove via an intermediate layer, including: The brain-computer interface module is rigidly connected to the bone groove via an absorption plate and a ceramic connection structure disposed in the intermediate layer; and Glue was injected into the gap between the brain-computer interface module and the bone groove.

27. The method according to claim 24, 25, or 26, characterized in that, The brain-computer interface module is fixedly connected to the bone groove via clavicle screws.

28. The method according to claim 27, characterized in that, Also includes: Bone cement or osseointegration coating is used to fill the gap between the skull prosthesis and the bone groove.

29. The method according to claim 24, 25, or 26, characterized in that, Fixing the brain-computer interface module to the bone groove includes: The ultrasonic transducer of the brain-computer interface module is located at least partially outside the bone groove to contact the dura mater of the subject.

30. The method according to claim 24, characterized in that, Also includes: The skull prosthesis was biomimeticly fabricated based on the target skull of the test subject.

31. The method according to claim 24, 25, 26, or 30, characterized in that, The method is achieved through 3D printing or CNC molding processes.

32. A brain-computer interface module, comprising an ultrasound transducer for sending ultrasound signals to the brain and acquiring brain echo signals, characterized in that, The brain-computer interface module is configured to be integrated with the skull or a skull prosthesis.

33. The brain-computer interface module according to claim 32, characterized in that, The brain-computer interface module includes a module body, an ultrasonic transducer integrated in the module body, and an acoustic window located at the end of the module body; the ultrasonic transducer is configured to transmit ultrasonic signals to the brain through the acoustic window and to collect brain echo signals through the acoustic window.

34. The brain-computer interface module according to claim 32 or 33, characterized in that, The brain-computer interface module also includes an ultrasound transceiver and beamforming unit, a data processing and communication unit, and a power management unit.

35. The brain-computer interface module according to claim 34, characterized in that, The ultrasonic transceiver and beamforming unit is configured to achieve adaptive focusing or beam self-calibration based on feedback signals.

36. The brain-computer interface module according to claim 34, characterized in that, The data processing and communication unit is configured to achieve bidirectional communication between the body and the outside via ultrasonic echo signals, radio frequency signals, or magnetic induction signals.

37. The brain-computer interface module according to claim 34, characterized in that, The brain-computer interface module also includes one or more circuit boards. The ultrasound transceiver and beamforming unit, the data processing and communication unit, and the power management unit are all arranged on one circuit board, or they are arranged on different circuit boards, or the electronic devices in any two units are at least partially arranged on the same circuit board.

38. The brain-computer interface module according to claim 37, characterized in that, The ultrasonic transducer, the ultrasonic transceiver and beamforming unit, the data processing and communication unit, and the power management unit are all arranged on a single circuit board, or they are arranged on different circuit boards, or at least some of the electronic components in any one of the ultrasonic transceiver and beamforming unit, the data processing and communication unit, and the power management unit are arranged on the same circuit board as the ultrasonic transducer.

39. The brain-computer interface module according to claim 34, characterized in that, The ultrasonic transducer is positioned near the end of the brain-computer interface module.

40. The brain-computer interface module according to claim 39, characterized in that, The ultrasound transceiver and beamforming unit is located near the ultrasound transducer, and the data processing and communication unit and the power management unit are located near the brain-computer interface module facing the scalp.

41. The brain-computer interface module according to claim 33, characterized in that, The module body is made of any one of titanium alloy, polyetheretherketone, polyaryletherketone, and hydroxyapatite; or, the module body is made of polyetheretherketone and bioactive ceramics; or, the module body is made of polyaryletherketone and bioactive ceramics; or, the cranial prosthesis is made of hydroxyapatite and other bioactive ceramics; or, the cranial prosthesis is made of hydroxyapatite and metal / polymer composite.

42. The brain-computer interface module according to claim 33, characterized in that, The acoustic window is made of a biocompatible polymer.

43. The brain-computer interface module according to claim 42, characterized in that, The biocompatible polymer is any one or more of polymethyl methacrylate, polyether ether ketone, polychlorotrifluoroethylene, polytetrafluoroethylene, ultra-high molecular weight polyethylene, polyethylene terephthalate, low-density polyethylene, polyether block amide, and high-density polyethylene.

44. The brain-computer interface module according to claim 32 or 33, characterized in that, The ultrasound transducer is configured to cover one or more brain regions.

45. The brain-computer interface module according to claim 32 or 33, characterized in that, The ultrasound transducer is configured with multiple functional arrays, which are used at least to achieve functional ultrasound imaging and focused ultrasound transcranial stimulation.

46. ​​The brain-computer interface module according to claim 45, characterized in that, The brain-computer interface module also includes an electrophysiological signal acquisition unit and / or an optical sensing unit, which are configured to work in conjunction with the ultrasound transducer to achieve multimodal signal acquisition and modulation.

47. The brain-computer interface module according to claim 32 or 33, characterized in that, The ultrasonic transducer includes any one or more of the following: capacitive micromechanical ultrasonic transducer array, piezoelectric micromechanical ultrasonic transducer array, and lead zirconate titanate piezoelectric transducer array.

48. The brain-computer interface module according to claim 32 or 33, characterized in that, The ultrasonic transducer is mounted on a dedicated integrated circuit for complementary metal-oxide-semiconductor.

49. The brain-computer interface module according to claim 32 or 33, characterized in that, The ultrasonic transducer is configured to contact the dura mater of the subject.

50. A neural modulation system, characterized in that, include: One or more digital cranial implants according to any one of claims 1-23; And a control module, configured in an external electronic device or implantable device, the control module communicating bidirectionally with the digital cranial implant; or, One or more brain-computer interface modules according to any one of claims 32-49; and a control module configured on an external electronic device or implantable device, the control module communicating bidirectionally with the brain-computer interface module.

51. A method for monitoring the physiological activities of a test subject, characterized in that, include: One or more signals are sent to one or more ultrasound transducers in a digital cranial implant according to any one of claims 1-23, the digital cranial implant being replaced and installed at the location of a target skull in a subject, the one or more signals being transmitted via one or more of the ultrasound transducers to transmit ultrasound waves for altering the physiological activity of the subject. as well as Receive data characterizing the physiological activities of the subject from one or more of the ultrasonic transducers; or, One or more signals are sent to one or more ultrasound transducers in a brain-computer interface module according to any one of claims 32-49, and any one of the skull prosthesis and the target skull is installed in an integrated structure with the brain-computer interface module at the location of the target skull of the subject, and the one or more signals are sent via one or more of the ultrasound transducers to transmit ultrasound waves for changing the physiological activities of the subject. as well as Data characterizing the physiological activities of the subject are received from one or more of the ultrasonic transducers.

52. A method for determining instructions for neural modulation in a subject, characterized in that, include: Data characterizing the physiological state of a subject is received from one or more digital cranial implants according to any one of claims 1-23 or brain-computer interface modules according to any one of claims 32-49, wherein the data characterizing the physiological state of the subject is data after processing of ultrasound data acquired by an ultrasound transducer; as well as Based on the data characterizing the physiological state of the test subjects, the instructions for neural regulation of the test subjects are determined.

53. The method according to claim 52, characterized in that, Also includes: The subject's neuromodulation instructions are sent to the digital cranial implant or the brain-computer interface module so that the ultrasonic transducer can perform ultrasonic neuromodulation on the subject.

54. The method according to claim 52 or 53, characterized in that, Based on the data characterizing the physiological state of the test subjects, the instructions for determining the neural regulation of the test subjects include: Based on the data representing the physiological state of the test subjects, a machine learning model generates prediction results; and Based on the prediction results, instructions for the neural regulation of the test subjects are generated.

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