Digital insomnia treatment system based on artificial intelligence and playing control method thereof

Abstract

The invention provides a digital insomnia treatment system based on artificial intelligence and a playing control method thereof, the system comprises a VR audio and video playing module, a main control module and a sharing platform, the VR audio and video playing module is used for playing audio and video contents pushed by the main control module, a brain wave collector is embedded in the VR audio and video playing module, and the brain wave collector is used for collecting brain waves. The brain wave collector is used for collecting brain wave data of an insomnia person and sending the brain wave data to the main control module, the main control module is provided with an audio-video content screening model, and the audio-video content screening model pushes audio-video content according to the brain wave data. The traditional Chinese medicine composition can assist an insomnia person to mildly and quickly switch from a highly excited mania state to a deep sleep state.

Description

Technical Field

[0001] The present invention relates to the technical field of digital treatment of insomnia, and in particular to an artificial intelligence-based digital treatment of insomnia system and a playback control method thereof. Background Art

[0002] Insomnia refers to the disorder of initiation and maintenance of sleep, which makes the quality and quantity of sleep unable to meet the individual's physiological needs and has obvious adverse effects on the patient's daytime activities, and objective detection shows abnormal syndrome. In addition to the significantly higher incidence of serious accidents and trauma than those with normal sleep, long-term insomniacs can also induce more than 80 diseases such as anxiety, depression, hypertension, diabetes, etc., which seriously affect people's physical and mental health and hinder social functions. Therefore, scholars have made many attempts and developed many drugs to treat insomnia. However, although the direction and goal of new drug development are very clear, sleeping pills are constantly being innovated, and each new drug can overcome some shortcomings of the previous generation, at present, both first-line and second-line sleeping pills have always been difficult to solve the side effects such as hangover reaction and addiction, resulting in many restrictions on their application, which has also prompted people to turn the research and development of single drugs to other sleep-promoting therapies. Using acupuncture (puncture) to treat insomnia is another contribution of traditional Chinese medicine. Many scholars have conducted excavation research and clinical trials on this, and achieved good results. With the development of science and technology, people have combined modern electronic technology with traditional acupuncture, and new treatment methods such as electroacupuncture for insomnia and music electroacupuncture for insomnia have emerged. Electroacupuncture is a treatment method that uses electric pulses to replace manual stimulation after traditional filiform needles stimulate the acupoints of the human body to achieve treatment or pain relief. However, ordinary pulse electroacupuncture is easy to produce tolerance to the body; music electroacupuncture is to convert and amplify the music signal to generate low-medium frequency current pulses synchronized with the music, and output them to the electroacupuncture. The waveform, frequency, and amplitude of this current pulse change with the music, which can not only input the music melody to the acupoints, but also overcome the human body adaptability that is easily caused by ordinary electroacupuncture. However, it should be pointed out that the pulse converted from music and output to the electroacupuncture cannot have a frequency that is too high, generally less than 100Hz, and the frequency band of the music signal is relatively wide. According to Shannon's sampling theorem, some music components will inevitably be lost, which is the shortcoming of music electroacupuncture. EEG biofeedback is a new method for relieving physical and psychological discomfort. It collects the EEG signals of the subjects and displays them in some way, and uses the operant conditioning model to make the subjects consciously control their own EEG patterns through rewards and reinforcement, so as to relieve physical and psychological discomfort. Researchers and medical workers are committed to using this technology to relieve people's anxiety and tension, and to treat diseases such as brain injuries, alcoholism, and mental disorders, and have achieved certain results in clinical applications.

[0003] However, the above methods directly stimulate the brain, have unknown side effects, and pose certain safety risks. They may not be suitable for the weak, those with heart disease, cerebrovascular disease, and pregnant women. Therefore, the existing hypnosis methods cannot induce hypnosis gently and harmlessly. Summary of the invention

[0004] The present invention solves the problem that the prior art cannot provide hypnosis gently and harmlessly, and proposes a digital treatment method and system for insomnia based on artificial intelligence, which can assist insomniacs to gently and quickly transition from a highly excited manic state to a deep sleep state.

[0005] In order to achieve the above objectives, the following technical solutions are proposed:

[0007] A digital treatment system for insomnia based on artificial intelligence includes a VR audio and video playback module, a main control module and a sharing platform. The VR audio and video playback module is used to play the audio and video content pushed by the main control module. The VR audio and video playback module is embedded with a brain wave collector, which is used to collect brain wave data of insomniacs and send the brain wave data to the main control module. The main control module is provided with an audio and video content screening model, and the audio and video content screening model pushes audio and video content according to the brain wave data.

[0006] In the present invention, when the VR audio and video playback module plays audio and video content to the insomniac, the brain wave data of the insomniac is collected in real time, and the audio and video content played by the VR audio and video playback module is adjusted by the audio and video content screening model and the frequency change of the insomniac's brain waves, and the audio and video content is used to gradually reduce the frequency of the insomniac's brain waves, so that the insomniac can be transferred from a highly excited manic state to a deep sleep state. The audio and video content screening model in the present invention is set with a playback library of different priorities, and the playback library can update the playback library according to the insomniac's personal changes in the brain wave frequency of the audio and video content, and it will be more in line with the needs of the insomniac after long-term use. The present invention is completely different from the prior art in assisting hypnosis. It uses an external visual stimulus to reduce the brain wave frequency of the insomniac and achieve hypnosis without causing damage to the body.

[0007] Preferably, the VR video and audio playback module includes VR visual glasses and plug-in headphones, the VR visual glasses are provided with a fixing ring for fixing on the head of the insomniac, and the brain wave collector is nested in the fixing ring.

[0008] Preferably, an elastic band is provided between the VR visual glasses and the fixing ring.

[0009] Preferably, the VR audio and video playback module is provided with a handheld controller, which is electrically connected to the main control module. The handheld controller is used to obtain operating instructions from the insomniac and input the operating instructions into the main control module.

[0010] Preferably, the main control module is electrically connected to a sharing platform, the sharing platform is regularly updated with a number of audio and video contents, and the main control module pre-downloads the audio and video contents from the sharing platform.

[0011] Preferably, the sharing platform is provided with a real-name authentication system, and the insomniac logs in through the real-name authentication system. The sharing platform is provided with a content review module, and the content review module is used to review the audio and video content and text content uploaded by the insomniac. Only the audio and video content and text content that pass the review can be displayed on the sharing platform, and the insomniac can download the audio and video content displayed on the sharing platform.

[0012] Preferably, insomniacs can set permissions when uploading audio and video content, and choose whether the audio and video content is public or private. When the audio and video content is selected to be public, the audio and video content will be displayed on the sharing platform after the review is passed. When the audio and video content is selected to be private, the audio and video content will not be displayed on the sharing platform after the review is passed.

[0013] A playback control method of a digital insomnia treatment system based on artificial intelligence, using the above-mentioned digital insomnia treatment system based on artificial intelligence, comprises the following steps: S1, play the audio and video content in sequence according to the preset first-level push library, second-level push library and selection library, and obtain the brain wave frequency at a certain time interval t within the set time T; S2, judging whether the brain wave frequency decreases within the time T and the decrease value is greater than the set value, if so, continue playing until the current audio and video content is finished, and then play the next audio and video content, if not, directly play the next audio and video content; S3, determine whether the playback completion signal is received, if not, return to S2, if yes, obtain the brain wave frequency according to a certain time interval t, fit the brain wave frequency change curve of the played audio and video content, and reclassify the played audio and video content into the first-level push library, the second-level push library and the selection library according to the brain wave frequency change curve. When all the played audio and video content are classified, the order of the audio and video content of the newly classified first-level push library, the second-level push library and the selection library is disrupted.

[0014] As a preferred method, the specific process of reclassifying the played audio and video content into the primary push library, the secondary push library and the selection library according to the brain wave frequency change curve is as follows: S31, determining whether the maximum drop value of the brain wave frequency when the audio-visual content is played is greater than b, if not, deleting the audio-visual content from the selection library, if so, proceeding to S32; S32, determining whether the maximum drop value of the brain wave frequency when the audio-visual content is played is greater than c, if not, putting the audio-visual content into the selection library; if so, proceeding to S33; S33, obtaining the slope k of the brain wave frequency change curve of the video content at a time interval s. i , i = 1, 2, 3, ..., n, where i is the nth time interval, and the statistical change slope k i The median k of z , judge k z Is it greater than the set threshold? If so, put the audio and video content into the first-level push library; if not, put the audio and video content into the second-level push library.

[0015] The beneficial effects of the present invention are as follows: when the VR audio and video playback module plays audio and video content to the insomniac, the brain wave data of the insomniac is collected in real time, and the audio and video content played by the VR audio and video playback module is adjusted by the audio and video content screening model and the frequency change of the insomniac's brain waves, and the audio and video content is used to gradually reduce the frequency of the insomniac's brain waves, so that the insomniac can be transferred from a highly excited manic state to a deep sleep state. The audio and video content screening model in the present invention is set with a playback library of different priorities, and the playback library can update the playback library according to the insomniac's personal changes in the brain wave frequency of the audio and video content, and it will be more in line with the needs of the insomniac after long-term use. The present invention is completely different from the prior art in assisting hypnosis. It uses an external visual stimulus to reduce the brain wave frequency of the insomniac to achieve hypnosis without causing damage to the body. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a system configuration diagram of an embodiment; Figure 2 is a method flow chart of an embodiment; Among them: 1. VR visual glasses; 2. Brain wave collector; 3. Fixed ring; 4. Elastic band; 5. Plug-in earphones. DETAILED DESCRIPTION

[0017] Example: This embodiment proposes a digital treatment system for insomnia based on artificial intelligence. Figure 2 , including a VR audio and video playback module, a main control module and a sharing platform. The VR audio and video playback module is used to play the audio and video content pushed by the main control module. The VR audio and video playback module is embedded with a brain wave collector 2. The brain wave collector 2 is used to collect brain wave data of insomniacs and send the brain wave data to the main control module. The main control module is provided with an audio and video content screening model, and the audio and video content screening model pushes audio and video content according to brain wave data. The VR audio and video playback module includes VR visual glasses 1 and plug-in headphones 5. The VR visual glasses 1 are provided with a fixing ring 3 for fixing on the head of the insomniac, and the brain wave collector 2 is nested in the fixing ring 3. An elastic band 4 is provided between the VR visual glasses 1 and the fixing ring 3. The elastic band 4 can be adjusted accordingly according to the head size of different insomniacs, increasing the wearing stability while improving the wearing comfort.

[0018] The VR video and audio playback module is provided with a handheld controller, which is electrically connected to the main control module. The handheld controller is used to obtain operation instructions from the insomniac and input the operation instructions into the main control module.

[0019] The main control module is electrically connected to a sharing platform, and the sharing platform is regularly updated with a number of audio and video contents. The main control module pre-downloads the audio and video contents from the sharing platform.

[0020] The sharing platform is equipped with a real-name authentication system, and the insomniac logs in through the real-name authentication system. The sharing platform is equipped with a content review module, which is used to review the audio and video content and text content uploaded by the insomniac. Only the audio and video content and text content that have passed the review can be displayed on the sharing platform, and the insomniac can download the audio and video content displayed on the sharing platform. In this embodiment, the content review module is equivalent to building a firewall to prevent unhealthy audio and video content from being uploaded and shared on the sharing platform.

[0021] When uploading audio and video content, Insomniacs can set permissions and choose whether to make the audio and video content public or private. When the audio and video content is chosen to be public, the audio and video content will be displayed on the sharing platform after passing the review. When the audio and video content is chosen to be private, the audio and video content will not be displayed on the sharing platform after passing the review.

[0022] This embodiment also proposes a digital treatment method for insomnia based on artificial intelligence, referring to Figure 2 , specifically including the following steps: S1, play the audio and video content in sequence according to the preset first-level push library, second-level push library and selection library, and obtain the brain wave frequency at a certain time interval t within the set time T; in this embodiment, T = 120s, t = 1s; S2, judging whether the brain wave frequency decreases within 120s and the decrease value is greater than the set value. If so, continue playing until the current audio and video content is finished, and then play the next audio and video content. If not, directly play the next audio and video content; S3, determine whether the playback completion signal is received, if not, return to S2, if yes, obtain the brain wave frequency according to a certain time interval t, fit the brain wave frequency change curve of the played audio and video content, and reclassify the played audio and video content into the first-level push library, the second-level push library and the selection library according to the brain wave frequency change curve. When all the played audio and video content are classified, the order of the audio and video content of the newly classified first-level push library, the second-level push library and the selection library is disrupted.

[0023] Since the stimulation of audio and video content requires a certain reaction time for the brain, the present invention first determines within 120 seconds whether the audio and video content will reduce the brain wave frequency. If so, it will continue to play, otherwise it will switch to the next audio and video content. The first-level push library, the second-level push library and the selection library are all stored with audio and video content that has been screened countless times and is suitable for insomniacs to reduce brain wave frequency. Therefore, it can achieve a targeted and efficient auxiliary drug detoxification effect for a specific person.

[0024] The specific process of reclassifying the played audio and video content into the primary push library, the secondary push library and the selection library according to the brain wave frequency change curve is as follows: S31, determining whether the maximum drop value of the brain wave frequency when the audio-visual content is played is greater than b, if not, deleting the audio-visual content from the selection library, if so, proceeding to S32; S32, determining whether the maximum drop value of the brain wave frequency when the audio-visual content is played is greater than c, if not, putting the audio-visual content into the selection library; if so, proceeding to S33; S33, obtaining the slope k of the brain wave frequency change curve of the video content at a time interval s. i , i = 1, 2, 3, ..., n, where i is the nth time interval, and the statistical change slope k i The median k of z , judge k z Is it greater than the set threshold? If so, put the video content into the first-level push library; if not, put the video content into the second-level push library. Median k z It can represent the general rate at which the video content causes the brain waves to decrease, which can generally reflect the effect of the video content.

[0025] In the present invention, when the VR audio and video playback module plays audio and video content to the insomniac, the brain wave data of the insomniac is collected in real time, and the audio and video content played by the VR audio and video playback module is adjusted by the audio and video content screening model and the frequency change of the insomniac's brain waves, and the audio and video content is used to gradually reduce the frequency of the insomniac's brain waves, so that the insomniac can be transferred from a highly excited manic state to a deep sleep state. The audio and video content screening model in the present invention is set with a playback library of different priorities, and the playback library can update the playback library according to the insomniac's personal changes in the brain wave frequency of the audio and video content, and it will be more in line with the needs of the insomniac after long-term use. The present invention is completely different from the prior art in assisting hypnosis. It uses an external visual stimulus to reduce the brain wave frequency of the insomniac and achieve hypnosis without causing damage to the body.

Claims

1. A digital insomnia treatment system based on artificial intelligence, characterized by: The invention comprises a VR audio and video playback module, a main control module and a sharing platform, wherein the VR audio and video playback module is used to play the audio and video content pushed by the main control module, the VR audio and video playback module is embedded with a brain wave collector (2), the brain wave collector (2) is used to collect brain wave data of insomniacs and send the brain wave data to the main control module, the main control module is provided with an audio and video content screening model, and the audio and video content screening model pushes the audio and video content according to the brain wave data.

2. According to claim 1, a digital treatment system for insomnia based on artificial intelligence is characterized in that: The VR video and audio playback module comprises VR visual glasses (1) and plug-in headphones (5); the VR visual glasses (1) are provided with a fixing ring (3) for fixing on the head of an insomniac; and the brain wave collector (2) is nested in the fixing ring (3).

3. The artificial intelligence-based digital insomnia treatment system according to claim 2 is characterized in that: An elastic band (4) is provided between the VR visual glasses (1) and the fixing ring (3).

4. The artificial intelligence-based digital insomnia treatment system according to claim 1 is characterized in that: The VR audio and video playback module is provided with a handheld controller, which is electrically connected to the main control module. The handheld controller is used to obtain operation instructions from the insomniac and input the operation instructions into the main control module.

5. The artificial intelligence-based digital insomnia treatment system according to claim 1 is characterized in that: The main control module is electrically connected to a sharing platform, the sharing platform is regularly updated with a number of audio and video contents, and the main control module pre-downloads the audio and video contents from the sharing platform.

6. The artificial intelligence-based digital insomnia treatment system according to claim 5 is characterized in that: The sharing platform is provided with a real-name authentication system, and insomniacs log in through the real-name authentication system. The sharing platform is provided with a content review module, and the content review module is used to review the audio and video content and text content uploaded by insomniacs. Only the audio and video content and text content that pass the review can be displayed on the sharing platform, and insomniacs can download the audio and video content displayed on the sharing platform.

7. The artificial intelligence-based digital insomnia treatment system according to claim 6 is characterized in that: When uploading audio and video content, Insomniacs can set permissions and choose whether to make the audio and video content public or private. When the audio and video content is chosen to be public, the audio and video content will be displayed on the sharing platform after passing the review. When the audio and video content is chosen to be private, the audio and video content will not be displayed on the sharing platform after passing the review.

8. A playback control method of a digital insomnia treatment system based on artificial intelligence, using the artificial intelligence-based system according to claim 1, characterized in that: The following steps are involved: S1, play the audio and video content in sequence according to the preset first-level push library, second-level push library and selection library, and obtain the brain wave frequency at a certain time interval t within the set time T; S2, judging whether the brain wave frequency decreases within the time T and the decrease value is greater than the set value, if so, continue playing until the current audio and video content is finished, and then play the next audio and video content, if not, directly play the next audio and video content; S3, determine whether the playback completion signal is received, if not, return to S2, if yes, obtain the brain wave frequency according to a certain time interval t, fit the brain wave frequency change curve of the played audio and video content, and reclassify the played audio and video content into the first-level push library, the second-level push library and the selection library according to the brain wave frequency change curve. When all the played audio and video content are classified, the order of the audio and video content of the newly classified first-level push library, the second-level push library and the selection library is disrupted.

9. The method for treating insomnia based on artificial intelligence according to claim 2, characterized in that: The specific process of reclassifying the played audio and video content into the primary push library, the secondary push library and the selection library according to the brain wave frequency change curve is as follows: S31, determining whether the maximum drop value of the brain wave frequency when the audio-visual content is played is greater than b, if not, deleting the audio-visual content from the selection library, if so, proceeding to S32; S32, determining whether the maximum drop value of the brain wave frequency when the audio-visual content is played is greater than c, if not, putting the audio-visual content into the selection library; if so, proceeding to S33; S33, obtaining the slope k of the brain wave frequency change curve of the video content at a time interval s. i , i = 1, 2, 3, ..., n, where i is the nth time interval, and the statistical change slope k i The median k of z , judge k z Is it greater than the set threshold? If so, put the audio and video content into the first-level push library; if not, put the audio and video content into the second-level push library.

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