Multi-sensory medical music therapy system and method based on artificial intelligence

Abstract

The invention discloses a multi-sensory medical music therapy system and method based on artificial intelligence, and is applied to the field of health management. The system comprises an audio generation module, an optical signal module, a tactile feedback module and a control module. The method comprises the following steps: acquiring user health data, and generating an audio frequency, an optical signal and a vibration signal for a disease through an artificial intelligence platform; the signals are output through wearable equipment or hardware, and the sense organ of a user is stimulated synchronously; the parameters are dynamically adjusted based on EEG feedback. The traditional Chinese medicine composition can assist in treating gout, hypertension, hyperglycemia, insomnia, depression, myocardial infarction and other diseases through a multi-sensory synergistic effect, supports application of human and various animals (such as dogs and cats) and the like, remarkably reduces pain and improves the curative effect. The system adopts a vibration template caching technology and an animal behavior feedback module, so that the efficiency and the cross-species applicability are improved.

Description

Technical Field

[0001] The present invention belongs to the field of health management technology, specifically to an artificial intelligence-based multi-sensory medical music therapy system and method. This system aims to provide personalized, non-invasive health management solutions for humans and animals (such as dogs, cats, chickens, and cows) through the synergistic effects of audio, light signals, and tactile feedback. The system integrates an audio generation module, a light signal module, a tactile feedback module, and a control module. It outputs multi-sensory signals through wearable devices (such as MR / AR / VR glasses) or dedicated hardware. These signals can be used to assist in the relief of chronic human diseases (such as gout, insomnia, depression, and hypertension) and improve the behavioral and physiological status of animals. It also supports animal health applications such as pet anxiety relief. The present invention utilizes advanced artificial intelligence technologies, including convolutional neural networks (CNNs) for brainwave signal analysis, vibration template caching technology, a timestamp alignment algorithm, and an animal behavior feedback module. The system supports multi-device collaboration (such as multi-user home treatment) and is suitable for home, hospital, and pet healthcare scenarios. It is efficient, accurate, and widely applicable. It can be combined with traditional medical or drug therapies to significantly reduce medical costs and improve quality of life, providing innovative solutions for the health management field. Background Art

[0002] Traditional music therapy stimulates brain waves through a single audio frequency to assist in the treatment of diseases such as hypertension, depression, and gout. However, due to the lack of multi-sensory coordination, personalized adjustment, and animal application support, its efficacy is limited. Vibration massage and light stimulation in existing technologies have the following shortcomings: First, the real-time synchronization of audio, light signals, and vibrations is poor, the sensory stimulation effect is poor, and the synchronization error is large; second, there is a lack of a dynamic optimization mechanism based on EEG feedback, which cannot adapt to individual differences, resulting in insufficient treatment accuracy; third, the vibration waveform generation efficiency is low, which increases the hardware computing burden and limits real-time performance; in addition, the existing system is not adapted to the brainwave frequency and behavioral characteristics of animals (such as dogs and cats), ignoring the pet medical market; finally, traditional equipment lacks the support of an integrated artificial intelligence platform, and the health data collection, modeling, and multi-device collaboration capabilities are limited, making it difficult to achieve large-scale application in home or hospital scenarios. Existing technologies also do not fully utilize the cognitive enhancement function of 40Hz light signals, and lack quantitative analysis of animal behavioral feedback. The present invention breaks through the above limitations through multi-sensory collaboration (audio, light, vibration), vibration template caching technology, timestamp alignment algorithm and animal behavior feedback module, significantly improves treatment efficiency, and expands to human and animal health management, filling the gap in existing technology and providing an efficient, cross-species solution for non-invasive therapy. Summary of the Invention

[0003] The main purpose of the present application is to provide an artificial intelligence-based multi-sensory medical music therapy system and method, aiming to improve the treatment effect through the synergistic effect of audio, light signal and vibration signal, and support human and animal health management. The main steps include: obtaining user health data, generating multi-sensory signals for diseases through an artificial intelligence platform; outputting signals through wearable devices or hardware to stimulate the user's senses synchronously; dynamically adjusting parameters based on EEG feedback to achieve personalized treatment. The present application optimizes the generation time to within 120 seconds through vibration template caching technology, adds an animal behavior feedback module to support cross-species adaptation, significantly reduces the pain of diseases such as gout, and improves the user and pet experience.

[0004] To achieve the above-mentioned purpose, the present application provides an artificial intelligence-based multi-sensory medical music therapy system, which is applied to the field of health management, and comprises:

[0005] An audio generation module for generating specific audio frequencies for diseases according to user health data;

[0006] A light signal module for generating 40Hz light signals to stimulate the user's vision;

[0007] A tactile feedback module for generating 5Hz vibration signals to assist in relieving diseases such as gout, using pre-computed vibration templates stored as `.h` files to control vibration motors through SPI / I 2C interfaces, and optimizing the generation time to within 120 seconds;

[0008] A control module for dynamically adjusting audio, light signal and vibration parameters based on EEG feedback, outputting through wearable devices or hardware, and using timestamp alignment algorithms to ensure multi-sensory signal synchronization to achieve emergency relief, pain prediction, relaxation route planning and health finding for the disease. Optionally, before the step of generating audio frequencies by the audio generation module, it further comprises:

[0009] Establishing the connection between wearable devices (such as MR / AR / VR glasses) and the artificial intelligence platform, and connecting user health data and the system based on wearable devices, supporting multi-device collaborative connection to achieve home multi-user treatment.

[0010] Optionally, before the step of generating vibration signals by the tactile feedback module, it further comprises:

[0011] The health real-time information is generated by collecting the user health parameters and the environment through a collecting module, and the health real-time information is sent to the system through a wireless network module, wherein the collecting module comprises an EEG module, a sensor module (such as a heart rate sensor and a blood pressure sensor), and an animal behavior camera module for analyzing pet behavior changes (such as barking and tail swing frequency).

[0012] Optionally, the step of controlling the user through the real-time control instruction comprises:

[0013] The real-time control instruction is sent to an artificial intelligence platform, and the real-time control instruction is analyzed through the artificial intelligence platform, the brain wave signal features are analyzed based on a convolutional neural network (CNN), and the user is remotely controlled for relaxation according to the analyzed real-time control instruction.

[0014] Optionally, after the step of remotely controlling the user for relaxation according to the analyzed real-time control instruction, the method further comprises:

[0015] The health information of the user after relaxation is obtained, and whether the user is in a preset health state is determined according to the health information;

[0016] If not, the health information is sent to a wearable device, so that the user can remotely control the health state again based on the health information until the preset health state is reached.

[0017] Optionally, the step of obtaining the real-time control instruction through the wearable device comprises:

[0018] The user is visually stimulated through an evoked pattern in the wearable device, the electroencephalogram signal of the occipital visual area of the brain is collected, the features are extracted to generate the real-time control instruction.

[0019] Optionally, the wearable device comprises a wearable MR device or a wearable AR / VR device, which can be integrated into glasses or a head-mounted display, and is convenient for the user to use at any time.

[0020] Optionally, the system supports animal brain wave frequency adaptation, adjusts the frequency for different animal species, optimizes the treatment effect in combination with an animal behavior feedback module (such as camera analysis of barking and tail swing), and is suitable for a family pet medical scene.

[0021] To achieve the above-mentioned purpose, the present application also provides a multi-sensory medical music therapy method based on artificial intelligence, comprising:

[0022] The light signal and vibration signal modeling module is used for obtaining the user health real-time information detected by the health management system, obtaining target health information by preprocessing the user health real-time information through an artificial intelligence platform, and obtaining a corresponding digital model by modeling the target health information through an artificial intelligence digital twin cloud platform.

[0023] The light signal and vibration signal acquisition module is configured to send the digital model to the wearable device for display and acquire real-time control instructions through the wearable device;

[0024] The light signal and vibration signal control module is configured to control the user according to the digital model through the real-time control instructions, and adopt a timestamp alignment algorithm to ensure synchronization of the multi-sensory signals, so as to realize emergency relief, pain prediction, relaxation route planning and health finding of the user's health state.

[0025] In the present application, each functional module of the multi-sensory medical music therapy device based on artificial intelligence realizes the steps of the multi-sensory medical music therapy method based on artificial intelligence as described above when running.

[0026] To achieve the above-mentioned purpose, the present application further provides a terminal device, which comprises a memory, a processor and a multi-sensory medical music therapy program based on artificial intelligence stored on the memory and executable on the processor, and the program realizes the steps of the multi-sensory medical music therapy method based on artificial intelligence as described above when executed by the processor.

[0027] In addition, to achieve the above-mentioned purpose, the present application further provides a computer readable storage medium, which stores a multi-sensory medical music therapy program based on artificial intelligence, and the program realizes the steps of the multi-sensory medical music therapy method based on artificial intelligence as described above when executed by the processor.

[0028] In addition, to achieve the above-mentioned purpose, the present application further provides a computer program product, which comprises a computer program, and the computer program realizes the steps of the multi-sensory medical music therapy method based on artificial intelligence as described above when executed by the processor.

[0029] Compared with the single audio treatment mode in the prior art, the present application collects user health data through a wearable device, generates multi-sensory signals (audio, light, vibration) through an artificial intelligence platform, outputs signals through the device, synchronously stimulates the user's senses, and dynamically adjusts parameters based on EEG feedback. The present application adopts vibration template caching technology, optimizes the signal generation time from 178 seconds to within 120 seconds, adds an animal behavior feedback module to support cross-species adaptation, significantly improves the treatment efficiency, and improves the user and pet experience. BRIEF DESCRIPTION OF DRAWINGS

[0030] Figure 1 The structural diagram of the hardware running environment involved in the embodiment of the present application;

[0031] Figure 2This is a flow chart of an embodiment of the multi-sensory medical music therapy method based on artificial intelligence of the present invention;

[0032] Figure 3 Schematic diagram of the functional modules of an embodiment of an artificial intelligence-based multi-sensory medical music therapy device of the present invention.

[0033] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0034] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0035] like Figure 1 As shown, Figure 1 It is a schematic diagram of the device structure of the hardware operating environment involved in the embodiment of the present invention.

[0036] It should be noted that the terminal device of the embodiment of the present invention can be a terminal device for realizing data extraction from multiple types of health data sources. The terminal device can specifically be a wearable device (such as MR / AR / VR glasses), a smart phone, a personal computer, and a server.

[0037] like Figure 1 As shown, the device may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, and a communication bus 1002. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a Wi-Fi interface). The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0038] The hardware interface uses SPI / I2C protocol to control the vibration motor and light LED, supporting high-precision signal output (such as 5Hz PWM waveform, 40Hz light flashing).

[0039] Those skilled in the art will understand that Figure 1 The device structure shown in the figure does not constitute a limitation of the device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0040] like Figure 1As shown, the memory 1005 as a computer storage medium can include an operating system, a network communication module, a user interface module, and an artificial intelligence-based multi-sensory medical music therapy program. The operating system is a program that manages and controls device hardware and software resources, supports the running of the artificial intelligence-based multi-sensory medical music therapy program and other software or programs. In Figure 1 In the device shown, the user interface 1003 is mainly used for data communication with the client; the network interface 1004 is mainly used for establishing a communication connection with the server; and the processor 1001 can be used to call the artificial intelligence-based multi-sensory medical music therapy program stored in the memory 1005, and perform the following operations:

[0041] Obtain user health real-time information detected by the health management system, preprocess the user health real-time information through an artificial intelligence platform to obtain target health information, and model the target health information through an artificial intelligence digital twin cloud platform to obtain a corresponding digital model;

[0042] Send the digital model to a wearable device for display, and obtain real-time control instructions through the wearable device;

[0043] According to the digital model, control the user through the real-time control instructions, and use a timestamp alignment algorithm to ensure synchronization of multi-sensory signals, so as to realize emergency relief, pain prediction, relaxation route planning, and health finding of the user's health state.

[0044] Send the digital model to a wearable device for display, and obtain real-time control instructions through the wearable device;

[0045] According to the digital model, control the user through the real-time control instructions, so as to realize emergency relief, pain prediction, relaxation route planning, and health finding of the user's health state.

[0046] Further, before the step of obtaining user health real-time information detected by the health management system, the processor 1001 can also be used to call the artificial intelligence-based multi-sensory medical music therapy program stored in the memory 1005, and further perform the following operations:

[0047] Establish a connection between the wearable device and the artificial intelligence platform, and establish a connection between the user health data and the system based on the wearable device.

[0048] Further, before the step of obtaining user health real-time information detected by the health management system, the processor 1001 can also be used to call the artificial intelligence-based multi-sensory medical music therapy program stored in the memory 1005, and further perform the following operations:

[0049] The health real-time information is generated by collecting the user health parameters and the environment in real time through a collection module, and the health real-time information is sent to the system through a wireless network module, wherein the collection module comprises an EEG module and / or a sensor module.

[0050] Further, the processor 1001 can also be configured to invoke the multi-sensory medical music therapy program based on artificial intelligence stored in the memory 1005, and further perform the following operations:

[0051] The real-time control instruction is sent to an artificial intelligence platform, and the real-time control instruction is analyzed through the artificial intelligence platform, and the user is remotely relaxed according to the analyzed real-time control instruction.

[0052] Further, after the step of remotely relaxing the user according to the analyzed real-time control instruction, the processor 1001 can also be configured to invoke the multi-sensory medical music therapy program based on artificial intelligence stored in the memory 1005, and further perform the following operations:

[0053] The position information of the relaxed user is obtained, and whether the user is in a preset health state is determined according to the position information.

[0054] If not, the position information is sent to the wearable device, so that the user can remotely control the health state again based on the position information until the preset health state is reached.

[0055] Further, the processor 1001 can also be configured to invoke the multi-sensory medical music therapy program based on artificial intelligence stored in the memory 1005, and further perform the following operations:

[0056] The user is visually stimulated through an evoked pattern in the wearable device to obtain a real-time control instruction.

[0057] Further, the wearable device comprises a wearable MR device or a wearable AR / VR device. For details, refer to Figure 2 , Figure 2 The flowchart of the first embodiment of the multi-sensory medical music therapy method based on artificial intelligence.

[0058] In this embodiment, an embodiment of the multi-sensory medical music therapy method based on artificial intelligence is provided. It should be noted that although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0059] In the embodiment, the multi-sensory medical music therapy method based on artificial intelligence comprises the following steps: step S10, acquiring user health real-time information detected by a health management system, preprocessing the user health real-time information through an artificial intelligence platform to obtain target health information, and modeling the target health information through an artificial intelligence digital twin cloud platform to obtain a corresponding digital model;

[0060] Step S20, sending the digital model to a wearable device for display, and acquiring real-time control instructions through the wearable device;

[0061] Step S30, controlling the user according to the digital model through the real-time control instructions to achieve emergency relief, pain prediction, relaxation route planning and health finding of the user's health state.

[0062] Further, before the step S10 of "acquiring user health real-time information detected by a health management system", the method further comprises:

[0063] Step S40, establishing a connection between the wearable device and the artificial intelligence platform, and establishing a connection between the user health data and the system based on the wearable device.

[0064] When the user needs health management, a connection instruction is sent through the wearable device, the connection instruction is sent to the artificial intelligence platform through the wearable device, the artificial intelligence platform establishes a connection with the wearable device after receiving the connection instruction, and the connection instruction is sent to the health management system through the artificial intelligence platform, and the connection instruction is sent to the user equipment through the wireless module in the health management system. The user equipment establishes a connection with the nearest health management system after receiving the connection instruction, so as to realize the connection between the user equipment and the health management system.

[0065] Further, before the step S10 of "acquiring user health real-time information detected by a health management system", the method further comprises:

[0066] Step S50, generating health real-time information by collecting user health parameters and environment through a collecting module, and sending the health real-time information to the system through a wireless network module, wherein the collecting module comprises an EEG module and / or a sensor module.

[0067] It should be noted that in the embodiment, the collecting module carried by the user equipment can include an EEG module and a sensor module. The EEG module can be used to scan the user's brain waves to form brain wave data, and the sensor module can be used to capture the user's physiological indicators and identify abnormalities contained in the indicators through deep learning, such as blood pressure abnormalities, blood sugar abnormalities, etc.

[0068] Specifically, for example, when managing the user's health, it is necessary to pre-acquire the user's brain wave data and physiological indicators and other real-time health information through the EEG module and / or sensor module, and send the user's real-time health information to the health management system through the wireless network module in the user's device. The health management system can receive the user's real-time health information through the wireless module, and after receiving the user's real-time health information, send the user's real-time health information to the artificial intelligence platform and the artificial intelligence digital twin cloud platform to obtain a digital model corresponding to the user's real-time health information, and display the digital model on the wearable device, so that the user can control his health status based on the wearable device, such as relaxation, pain relief, etc.

[0069] In this embodiment, when a user needs to perform health management, a connection instruction can be sent through a wearable device. After receiving the connection instruction through the artificial intelligence platform, the connection instruction is sent to the health management system through the artificial intelligence platform, and the connection instruction is sent to the signal receiving module of the user device through the wireless module in the health management system. After receiving the connection signal, the user device is connected to the nearest health management system. When performing health management for the user, it is necessary to pre-acquire the user's brain wave data and physiological indicators and other real-time health information of the user through the EEG module and / or sensor module carried by the user device, and send the real-time health information of the user to the health management system; send the real-time health information of the user to the artificial intelligence platform through the health management system for preprocessing to obtain the target health information; send the target health information to the artificial intelligence digital twin cloud platform through the artificial intelligence platform, and model the target health information through the artificial intelligence digital twin cloud platform to obtain the corresponding digital model; transmit the digital model wirelessly to the wearable device worn by the user through the artificial intelligence digital twin cloud platform, and receive the real-time control instructions triggered by the user through the wearable device to control the user's health status according to the real-time control instructions.

[0070] Compared to existing single-audio therapies, this invention uses wearable devices to collect user health data, generates multisensory signals (audio, light, and vibration) through an artificial intelligence platform, outputs these signals to simultaneously stimulate the user's senses, and dynamically adjusts parameters based on EEG feedback. Therefore, this invention implements multisensory medical music therapy based on an artificial intelligence platform and wearable devices, improving treatment efficiency and enhancing the user experience.

[0071] Further, based on the first embodiment of the multi-sensory medical music therapy method based on artificial intelligence of the present application, a second embodiment of the multi-sensory medical music therapy method based on artificial intelligence of the present application is proposed. The difference between this embodiment and the first embodiment is that in this embodiment, in the step of "controlling the user through the real-time control instruction" in the step S30, it includes:

[0072] In step S301, the real-time control instruction is sent to the artificial intelligence platform, and the real-time control instruction is analyzed by the artificial intelligence platform, and the user is remotely relaxed according to the analyzed real-time control instruction.

[0073] After the terminal device obtains the real-time control instruction triggered by the user through the wearable device, the real-time control instruction is sent to the artificial intelligence platform through the wearable device in a wireless transmission manner, and the real-time control instruction is analyzed by the artificial intelligence platform, so that the analyzed real-time control instruction can control the health status of the user, and then realize the remote control of health management.

[0074] It should be noted that in this embodiment, when the user triggers the real-time control instruction through the wearable device, the real-time control instruction is actually based on the visual evoked electrical signal, so the artificial intelligence platform is needed to analyze the real-time control instruction to obtain a signal that can control the health status of the user.

[0075] Further, after the step S301 of "controlling the user remotely according to the analyzed real-time control instruction", it further includes:

[0076] In step S302, the position information of the relaxed user is obtained, and whether the user is in a preset health state is judged according to the position information;

[0077] Step S303, if no, the position information is returned to the wearable device, so that the user can remotely control the health state again based on the position information until the preset health state is reached. It should be noted that in the embodiment, since the user may make errors when remotely controlling the health state, therefore, after each remote relaxation control by the wearable device, the current information of the user needs to be collected again by the collection module to ensure that the user is in the preset health state. Specifically, for example, after remotely relaxing the user once, the current position information of the user is obtained again through the sensor module, and then the current position information of the user is compared with the preset health state to determine whether the user is currently in the preset health state. If it is determined that the user is still not in the preset health state, the current position information of the user is sent to the artificial intelligence digital twin cloud platform for modeling to obtain a digital model through the artificial intelligence platform, and the digital model corresponding to the current position information of the user is sent to the wearable device for display through the artificial intelligence digital twin cloud platform, so that the user can obtain the current state of the user through the wearable device, and then control the health state again based on the current state of the user until the user is adjusted to the preset health state.

[0078] Further, in the above step S20, "obtaining real-time control instructions through the wearable device", can include:

[0079] Step S201, the user is visually stimulated through the evoked pattern in the wearable device to obtain real-time control instructions.

[0080] It should be noted that in the embodiment, the wearable device is configured with a visual interactive interface, in which the digital model corresponding to the user information can be displayed, and can also be displayed in 3D holographic image or three-dimensional manner. The user can browse the real-time health information in the visual interface, and the user can also trigger the real-time control instructions through the visual interface to realize remote control of the health state.

[0081] Specifically, for example, in the visual interface of the wearable device, the user can be visually stimulated through the stimulation module in the visual interface. When the user receives a certain frequency of graphic flicker stimulation, the occipital visual area of the brain generates a brain electrical signal response related to the stimulation frequency, and the brain electrical signal is collected for feature extraction and analysis to identify the user's intention, that is, to obtain the real-time control instructions triggered by the user, to remotely adjust the health state according to the real-time control instructions.

[0082] Further, the wearable device comprises a wearable MR device or a wearable AR / VR device. It should be noted that in the present embodiment, in order to enable the user to remotely control the health state at any time, the wearable device can be a wearable MR (mixed reality) device or a wearable AR (augmented reality) / VR (virtual reality) device, specifically, the wearable MR device or the wearable AR / VR device can be integrated into glasses or sunglasses, so that the user can remotely adjust the health state at any time through the wearable MR device or the wearable AR / VR device.

[0083] In the present embodiment, after the terminal device obtains the real-time control instruction triggered by the user through the wearable device, the terminal device sends the real-time control instruction to the artificial intelligence platform in a wireless transmission manner, and the artificial intelligence platform analyzes the real-time control instruction, so that the analyzed real-time control instruction can control the health state of the user. After the user is remotely adjusted once, the current health information of the user is obtained again through the sensor module, and then the current information of the user is compared with the preset health state to determine whether the user is currently in the preset health state. If it is determined that the user is still not in the preset health state, the current information of the user is processed through the artificial intelligence platform and the artificial intelligence digital twin cloud platform to obtain a corresponding digital model, and the digital model is sent to the wearable device for display through the artificial intelligence digital twin cloud platform, so that the user can obtain the current state of the user through the wearable device, and then adjust the health state based on the current state of the user until the user is adjusted to the preset health state. The wearable device comprises a wearable MR device or a wearable AR / VR device, and the wearable MR device or the wearable AR / VR device can be integrated into glasses or sunglasses, so that the user can remotely adjust the health state at any time through the wearable MR device or the wearable AR / VR device.

[0084] In the present application, the user real-time health information sent by the artificial intelligence platform is displayed in the visualization interface of the wearable MR device or the wearable AR / VR device in real time, so that the user adjusts the health state based on the user real-time health information multiple times until the health state is adjusted to the preset target state. Therefore, the present application realizes remote adjustment of the health state based on the user, the wearable device, the artificial intelligence platform and the artificial intelligence digital twin cloud platform, improves the efficiency of health management, and enables the user to perform emergency health relief operation or health state adjustment operation.

[0085] In addition, the embodiment of the present application also proposes an artificial intelligence-based multi-sensory medical music therapy device, which is described with reference to Figure 3 , Figure 3It is an embodiment of the function module schematic diagram of the multi-sensory medical music therapy device based on artificial intelligence of the present application. As shown in Figure 3 The multi-sensory medical music therapy device based on artificial intelligence of the present application comprises:

[0086] The modeling module 10 is used to acquire the user health real-time information detected by the health management system, to obtain target health information by preprocessing the user health real-time information through the artificial intelligence platform, and to obtain the corresponding digital model by modeling the target health information through the artificial intelligence digital twin cloud platform.

[0087] The acquisition module 20 is used to send the digital model to the wearable device for display, and to acquire real-time control instructions through the wearable device.

[0088] The control module 30 is used to control the user according to the digital model through the real-time control instructions, so as to realize the emergency relief, pain prediction, relaxation route planning and health finding of the user health state.

[0089] Further, the multi-sensory medical music therapy device based on artificial intelligence of the present application further comprises:

[0090] The connection establishing module is used to establish the connection between the wearable device and the artificial intelligence platform, and to establish the connection between the user health data and the system based on the wearable device.

[0091] Further, the multi-sensory medical music therapy device based on artificial intelligence of the present application further comprises:

[0092] The real-time acquisition module is used to acquire the user health parameters and the environment through the acquisition module to generate health real-time information, and to send the health real-time information to the system through the wireless network module, wherein the acquisition module comprises an EEG module and / or a sensor module.

[0093] Further, the control module 30 comprises

[0094] The remote control unit is used to send the real-time control instructions to the artificial intelligence platform, to analyze the real-time control instructions through the artificial intelligence platform, and to remotely control the user according to the analyzed real-time control instructions.

[0095] Further, the multi-sensory medical music therapy device based on artificial intelligence of the present application further comprises:

[0096] The judgment module is used to acquire the position information of the user after relaxation, and to judge whether the user is in a preset health state according to the position information.

[0097] The sending module is configured to send the position information to the wearable device if the answer is no, so that the user can remotely control the health state again based on the position information until the preset health state is reached.

[0098] Further, the acquisition module 20 comprises

[0099] The visual stimulation unit is configured to stimulate the user visually through an evoked pattern in the wearable device to obtain the real-time control instruction.

[0100] Further, the wearable device comprises a wearable MR device or a wearable AR / VR device. The specific embodiments of the various functional modules of the artificial intelligence-based multi-sensory medical music therapy system are basically the same as the above-mentioned various embodiments of the artificial intelligence-based multi-sensory medical music therapy method, and will not be repeated here.

[0101] In addition, an embodiment of the present application also provides a computer readable storage medium, and the computer readable storage medium stores an artificial intelligence-based multi-sensory medical music therapy program. When the artificial intelligence-based multi-sensory medical music therapy program is executed by a processor, the steps of the artificial intelligence-based multi-sensory medical music therapy method described above are implemented.

[0102] The various embodiments of the artificial intelligence-based multi-sensory medical music therapy system and the computer readable storage medium of the present application can refer to the various embodiments of the artificial intelligence-based multi-sensory medical music therapy method of the present application, and will not be repeated here.

[0103] In addition, an embodiment of the present application also provides a computer program product, and the computer program product comprises a computer program. When the computer program is executed by a processor, the steps of the artificial intelligence-based multi-sensory medical music therapy method described above are implemented.

[0104] The specific embodiments of the computer program product of the present application are basically the same as the above-mentioned various embodiments of the artificial intelligence-based multi-sensory medical music therapy method, and will not be repeated here.

[0105] It should be noted that in this paper, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of another identical element in the process, method, article or device including the element.

[0106] The above-mentioned embodiment numbers of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0107] Through the above description of the embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be realized by means of software and the necessary general hardware platform, of course, can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a plurality of instructions for making a terminal device (which can be a smart phone, a personal computer, and a server, etc.) execute the methods described in various embodiments of the present application.

[0108] The above is only the preferred embodiment of the present application, and does not limit the patent scope of the present application, and any equivalent structure or equivalent flow transformation made by using the content of the specification and drawings of the present application, or directly or indirectly applied to other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. An artificial intelligence-based multi-sensory medical music therapy system applied to the field of health management, the system comprising an audio generation module, a light signal module, a tactile feedback module, and a control module; The system is characterized by: The audio generation module generates specific audio frequencies for diseases according to user health data (such as brain waves, heart rate, blood pressure), supports personalized treatment for diseases such as gout, hypertension, hyperglycemia, insomnia, depression, and myocardial infarction, and the frequency accuracy is 0.1 Hz; The light signal module generates light signals to stimulate the user's vision through wearable devices (such as MR / AR / VR glasses) or dedicated hardware (such as LED lights) to enhance cognitive function, with a flicker error of less than 1 ms; The tactile feedback module generates a 5Hz vibration signal to assist in relieving diseases such as gout and arthritis, uses pre-computed vibration templates stored as `.h` files, controls the vibration motor through SPI / I 2C interface, optimizes the generation time to within 120 seconds, reduces hardware computing overhead, and the PWM waveform resolution is 8 bits; The control module is based on EEG feedback, uses a convolutional neural network (CNN) to analyze brain wave signal features (such as theta waves, alpha waves, and beta waves), dynamically adjusts audio, light signal, and vibration parameters, and realizes real-time synchronization of multi-sensory signals through a timestamp alignment algorithm (synchronization error <10 ms), supports multi-device collaborative treatment (such as a multi-user home scenario), and achieves emergency relief, pain prediction, relaxation route planning, and health status optimization for diseases.

2. The system of claim 1, wherein, Before the step of generating audio frequencies in the audio generation module, it also includes: Establishing a wireless connection between the wearable device and the artificial intelligence platform based on Wi-Fi or Bluetooth protocol (supporting BLE 5.0) to realize real-time interaction of user health data and the system, with a data transmission rate ≥1 Mbps, supporting a multi-user collaborative treatment scenario at home (such as multiple MR glasses operating synchronously).

3. The system of claim 1, wherein, Before the step of generating vibration signals in the tactile feedback module, it also includes: Real-time acquisition of user health parameters (such as brain waves, heart rate, and blood pressure) and environmental data through the acquisition module to generate real-time health information and transmit it to the system through the wireless network module; the acquisition module includes an EEG module (sampling rate 256 Hz), a sensor module (heart rate and blood pressure sensors with an accuracy of ±2%), and an animal behavior camera module (resolution 1080p, frame rate 30 fps) for analyzing pet behavior changes (such as barking frequency and tail swing speed), supporting health management for humans and various animals (such as dogs and cats).

4. The system of claim 1, wherein, The step of controlling the user through real-time control instructions includes: Sending real-time control instructions to the artificial intelligence platform, analyzing brain wave signal features based on the CNN model through the artificial intelligence platform, the CNN model containing at least 3 convolution layers and 2 fully connected layers, the feature extraction time <500 ms, generating adjustment parameters for the user's health status (such as audio frequency ±0.5 Hz and vibration intensity ±10 units), and realizing remote relaxation control according to the analyzed instructions to optimize treatment effect.

5. The system of claim 4, wherein, After the step of remote relaxation control according to the analyzed real-time control instructions, it also includes: Obtaining the user's health information after relaxation, determining whether the user has reached the preset health state based on the artificial intelligence platform, such as a 15% increase in theta wave proportion or a 10bpm decrease in heart rate; if not, the health information is fed back to the wearable device for the user to adjust again until the preset health state is reached, and the adjustment period is ≤1 minute.

6. The system of claim 1, wherein, The step of obtaining real-time control instructions through the wearable device comprises: Stimulating the occipital visual area of the user's brain through a visual evoked pattern (such as a 40Hz flickering pattern, refresh rate 60Hz) in the wearable device, collecting electroencephalogram signals (sampling rate 256Hz), extracting features to generate real-time control instructions, and the feature extraction algorithm is based on fast Fourier transform (FFT) with a response time <200ms, supporting personalized interaction.

7. The system of claim 1, wherein, The wearable device includes a wearable MR device or an AR / VR device, which can be integrated into glasses or a head-mounted device, weighs ≤200g, and has a battery life ≥8 hours, suitable for portable health management.

8. The system of claim 1, wherein, The system supports animal brain wave frequency adaptation, adjusts audio and vibration frequency for different animal species (such as dog 4-12Hz, cat 4-8Hz), and optimizes treatment effect in combination with animal behavior feedback module (analyzing barking frequency and tail swing frequency through 1080p camera, recognition accuracy ≥90%) suitable for home pet medical scenarios, treatment period 5-7 days.

9. An artificial intelligence-based multi-sensory medical music therapy device applied to a health management system, the health management system comprising an artificial intelligence platform, a digital twin cloud platform, a wearable device, and a health management system; The device comprises: A modeling module for obtaining real-time user health information detected by the health management system, obtaining target health information through artificial intelligence platform preprocessing, preprocessing including denoising (signal-to-noise ratio ≥20dB) and feature extraction (based on wavelet transform), and generating corresponding digital models through digital twin cloud platform modeling with modeling time <1 second; An acquisition module for sending digital models to wearable devices for 3D visual display (resolution ≥720p) and obtaining real-time control instructions through visual stimulation; A control module for controlling user health status by using timestamp alignment algorithm (error <10ms) to ensure multi-sensory signal synchronization based on digital models and real-time control instructions, realizing emergency relief, pain prediction, relaxation route planning, and health seeking.

10. A terminal device, comprising: The terminal device comprises a memory, a processor, and an artificial intelligence-based multi-sensory medical music therapy program stored on the memory and executable on the processor, the program being executed by the processor to realize the method steps of any one of claims 1 to 8, the processor performance ≥1GHz, and the memory capacity ≥4GB.

11. A computer readable storage medium, characterized in that, The storage medium stores an artificial intelligence-based multi-sensory medical music therapy program, which is executed by the processor to realize the method steps of any one of claims 1 to 8, and the storage medium supports a read / write speed ≥100MB / s.

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