An intelligent sleep guidance system

Abstract

The present invention provides an intelligent sleep guidance system. Compared with the prior art, the intelligent sleep guidance system of the present invention further includes an acquisition module for monitoring and acquiring human brain electrical information, a signal processing module for analyzing human brain electrical information to determine the human sleep condition, an intelligent display screen for playing video and audio content, a playback controller for controlling the playback brightness and volume of the intelligent display screen, and an adaptive control module for further controlling the playback processor based on the judgment of the human sleep condition by the signal processing module. The intelligent sleep guidance system of the present invention takes into account both the sleep parameter value and the sleep dynamic value, realizes the precise adjustment of the brightness and volume of the intelligent display screen, ensures that the adjustment process not only reflects the user's current sleep depth, but also dynamically responds to the changing trend of the sleep state, and is flexible and personalized. Adaptive ability to guide users to a more suitable sleeping environment.

Description

Technical Field

[0001] The invention relates to the field of sleep health care equipment, and in particular to an intelligent sleep guidance system. Background Art

[0002] Sleep guidance technologies are designed to help people fall asleep faster and improve sleep quality, including environmental optimization, audio guidance, light control, changing sleep-related thinking and behavior, smart mattresses, sleep trackers, and the use of medications or natural supplements when necessary. Many people feel anxious, nervous, or have difficulty relaxing before bedtime, especially after a stressful workday or facing challenges in life. Playing video or audio content, such as relaxing music, nature sounds, meditation guidance, or soothing TV shows, can help them divert their attention, reduce anxiety, and gradually enter a relaxed state, making it easier to fall asleep.

[0003] The experimental team has been browsing and studying a large number of relevant records and materials on the relevant technologies of intelligent sleep guidance for a long time. At the same time, relying on relevant resources and conducting a large number of relevant experiments, after a large number of searches, it is found that there are existing technologies such as CN107961430B, CN108310587B, CN106178222B, and CN109326309B disclosed in the prior art. For example, a user sleep management system disclosed in the prior art includes a processor, an input device, an output device and a memory. The processor is configured to call the program instructions and execute the following method: receiving the user's sleep The system receives a sleep setting instruction to set the user's sleep cycle, which includes bedtime; receives a music setting instruction from the user to set the user's sleep-aiding music collection, which includes multiple sleep-aiding music; when it is detected that the user's bedtime has arrived, the sleep-aiding music in the sleep-aiding music collection is played, and the preset system sleep time is received; when the system sleep time is reached, a system bedtime reminder message is generated to remind the user. The user can set his or her own sleep cycle and sleep-aiding music collection. When the user's bedtime arrives, the sleep-aiding music is played to help the user fall asleep. The user can also fall asleep through the system to guide the user to go to bed in time. The system uses artificial intelligence technology to manage and accompany the user's sleep.

[0004] The present invention is made to solve the common problems in the art that the sleep guidance for users is single, the guidance cannot be adjusted according to the actual situation of the users, and the efficiency of the sleep guidance for users is low. Summary of the invention

[0005] The purpose of the present invention is to propose an intelligent sleep guidance system in view of the shortcomings existing in the current field.

[0006] In order to overcome the shortcomings of the prior art, the present invention adopts the following technical solutions:

[0007] An intelligent sleep guidance system, characterized in that the intelligent sleep guidance system includes an acquisition module for monitoring and acquiring human brain electrical information, a signal processing module for analyzing human brain electrical information to determine the human sleep condition, an intelligent display screen for playing video and audio content, a playback controller for controlling the playback brightness and volume of the intelligent display screen, and an adaptive control module for further controlling the playback processor based on the judgment of the human sleep condition by the signal processing module.

[0008] Furthermore, the acquisition module includes a headgear for the user to wear, a brain wave sensor arranged inside the headgear for detecting the user's brain wave signals, and a signal transmitter for transmitting the brain wave signals collected by the brain wave sensor to the signal processing module in real time.

[0009] Furthermore, the brain wave sensor and the signal transmitter are connected via a wire embedded in the headgear.

[0010] Furthermore, ventilation holes are designed near the brain wave sensor installation area of ​​the headgear, and the ventilation holes are used to improve the air circulation in the user's headgear and reduce the stuffiness caused by the user wearing the headgear for a long time.

[0011] Furthermore, the signal processing module implements the following operation steps:

[0012] S101: Filter the collected raw EEG signals to retain EEG signals within the range of 0.5 Hz to 30 Hz.

[0013] S102: Segment the filtered continuous signal into several unit signals according to a fixed time window, each unit signal is 5 seconds.

[0014] S103: Perform discrete Fourier transform on each signal unit signal to obtain a processed signal X, where the horizontal coordinate k of the processed signal is the frequency, and the vertical coordinate is the amplitude value, k∈[0.5Hz, 30Hz], |X[k]| is the amplitude value corresponding to the k frequency in the processed signal,

[0015] S104: respectively obtain the total power Pδ of the δ spectrum segment, the total power Pθ of the θ spectrum segment, the total power Pα of the α spectrum segment, and the total power Pβ of the β spectrum segment in the processed signal:

[0016]

[0017] Among them, N=30Hz-0.5Hz=29.5Hz, the δ spectrum segment is the spectrum segment with power in the range of 0.5Hz to 4Hz in the processing signal, the θ spectrum segment is the spectrum segment with power in the range of 4Hz to 8Hz in the processing signal, the α spectrum segment is the spectrum segment with power in the range of 8Hz to 13Hz in the processing signal, and the β spectrum segment is the spectrum segment with power in the range of 13Hz to 30Hz in the processing signal.

[0018] The β spectrum band is related to the user's active thinking activities, concentration and awake state, the α frequency band is related to the user's relaxed, awake but closed eyes state, the θ frequency band is related to the user's light sleep when falling asleep or relaxing, and the δ frequency band is related to the user's deep sleep.

[0019] S105: Obtain the user's sleep parameter value RS:

[0020]

[0021] Among them, P all is the total power value of the processed signal, P all =Pδ+Pθ+Pα+Pβ, C is the actual sleep parameter value of the user, u is the user correction coefficient, w1, w2, w3, w4 are weight coefficients, w1+w2+w3+w4=1, and w1<w2<w3<w4, the RS value is proportional to the sleep depth of the user, RC is the preset control value, and 0.5≤RC≤2.0.

[0022] The calculation method of the user's actual sleep parameter value C includes the following steps:

[0023] S201: Obtain the user's age value Uage according to human input,

[0024] S202: Obtaining the average daily sleep duration value AL for the most recent week based on human input,

[0025] S203:

[0026] The C value reflects the individual differences of different users. When the C value is large, it corresponds to the user's age and sleep duration being close to the standard value. The user is in an ideal state and the correction amplitude is small.

[0027] A smaller C value reflects that the user's age or sleep duration deviates far from the standard value, indicating that a larger correction is needed.

[0028] Furthermore, the steps of guiding the user's sleep by the intelligent sleep guidance system include:

[0029] Step 1: The user wears the headgear and the EEG sensor contacts the user's head.

[0030] Step 2: The EEG sensor starts to collect the user's brain wave signals, and the collected brain wave signals are transmitted to the signal processing module through the wires embedded in the headgear.

[0031] Step 3: The signal processing module calculates the sleep parameter value that is positively correlated with the user's sleep depth.

[0032] Step 4: The adaptation control module calculates and obtains a sleep dynamic value that reflects changes in the user's sleep state, and adjusts the brightness and volume of the smart display based on the user's sleep parameter value and the sleep dynamic value.

[0033] The beneficial effects achieved by the present invention are:

[0034] 1. The intelligent sleep guidance system of the present invention accurately calculates the RS value that is positively correlated with the sleep depth through comprehensive analysis and weight adjustment of multi-spectral band brain wave signals, which can comprehensively cover the user's entire sleep cycle and ensure effective monitoring of the sleep state at each stage, thereby accurately guiding the user's sleep and significantly improving the user's sleep quality.

[0035] 2. The intelligent sleep guidance system of the present invention calculates the user's actual sleep parameter value C by comprehensively considering the user's age and the average sleep duration in the past week, thereby providing the system with a personalized basis for sleep status evaluation. The correction amplitude of RS is smoothly and moderately adjusted through the design of C, ensuring the wide applicability to different user groups and the stability of the system, which helps to achieve more effective sleep guidance.

[0036] 3. The intelligent sleep guidance system of the present invention takes into account both the sleep parameter values ​​and the sleep dynamic values, and realizes precise adjustment of the brightness and volume of the intelligent display screen, ensuring that the adjustment process not only reflects the user's current sleep depth, but also dynamically responds to the changing trend of the sleep state. With flexibility and personalized adaptability, the system can gently adjust environmental parameters to avoid abrupt changes, ensuring that users are guided to a more suitable sleeping environment without being disturbed. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The present invention can be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily drawn to scale, but the emphasis is placed on illustrating the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0038] Figure 1 It is a modular schematic diagram of the intelligent sleep guidance system of the present invention.

[0039] Figure 2 The figure is a schematic diagram of the operation flow of the intelligent sleep guidance system of the present invention.

[0040] Figure 3It is a modular schematic diagram of the acquisition module of the present invention. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention is further described in detail in combination with its embodiments below; it should be pointed out that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present case. For those skilled in the art, after reviewing the following detailed description, other systems, methods and / or features of this embodiment will become apparent. And the terms describing the positional relationship in the accompanying drawings are only used for illustrative purposes and cannot be understood as limitations on this patent. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to the specific circumstances.

[0042] Embodiment 1: Combining with Figure 1 , Attachment Figure 2 and attached Figure 3 This embodiment constructs an intelligent sleep guidance system, which includes an acquisition module for monitoring and acquiring human brain electrical information, a signal processing module for analyzing human brain electrical information to determine the human sleep condition, an intelligent display screen for playing video and audio content, a playback controller for controlling the playback brightness and volume of the intelligent display screen, and an adaptive control module for further controlling the playback processor based on the judgment of the human sleep condition by the signal processing module.

[0043] The acquisition module includes a headgear for the user to wear, a brain wave sensor installed inside the headgear for detecting the user's brain wave signals, and a signal transmitter for transmitting the brain wave signals collected by the brain wave sensor to the signal processing module in real time.

[0044] The brainwave sensor and the signal transmitter are connected via wires embedded inside the headgear. There are ventilation holes designed near the installation area of ​​the brainwave sensor of the headgear to improve the air circulation inside the user's headgear and avoid the stuffiness caused by the user wearing the headgear for a long time.

[0045] The signal processing module implements the following operation steps:

[0046] S101: Filter the collected raw EEG signals to retain EEG signals within the range of 0.5 Hz to 30 Hz.

[0047] S102: Segment the filtered continuous signal into several unit signals according to a fixed time window, each unit signal is 5 seconds.

[0048] S103: Perform discrete Fourier transform on each signal unit signal to obtain a processed signal X, where the horizontal coordinate k of the processed signal is the frequency, and the vertical coordinate is the amplitude value, k∈[0.5Hz, 30Hz], |X[k]| is the amplitude value corresponding to the k frequency in the processed signal,

[0049] S104: respectively obtain the total power Pδ of the δ spectrum segment, the total power Pθ of the θ spectrum segment, the total power Pα of the α spectrum segment, and the total power Pβ of the β spectrum segment in the processed signal:

[0050]

[0051] Among them, N=30Hz-0.5Hz=29.5Hz, the δ spectrum segment is the spectrum segment with power in the range of 0.5Hz to 4Hz in the processing signal, the θ spectrum segment is the spectrum segment with power in the range of 4Hz to 8Hz in the processing signal, the α spectrum segment is the spectrum segment with power in the range of 8Hz to 13Hz in the processing signal, and the β spectrum segment is the spectrum segment with power in the range of 13Hz to 30Hz in the processing signal.

[0052] The β spectrum band is related to the user's active thinking activities, concentration and awake state, the α frequency band is related to the user's relaxed, awake but closed eyes state, the θ frequency band is related to the user's light sleep when falling asleep or relaxing, and the δ frequency band is related to the user's deep sleep.

[0053] S105: Obtain the user's sleep parameter value RS:

[0054]

[0055] Among them, P all is the total power value of the processed signal, P all =Pδ+Pθ+Pα+Pβ, C is the actual sleep parameter value of the user, u is the user correction coefficient, w1, w2, w3, w4 are weight coefficients, w1+w2+w3+w4=1, and w1<w2<w3<w4, RS value is proportional to the sleep depth of the user, RC is the preset control value, and 0.5≤RC≤2.0,

[0056] The process of obtaining parameter u: The initial value of the user correction coefficient u is preliminarily set by technicians in this field based on the individual differences in the user's age and average daily sleep duration. In order to ensure that the system can fully adapt to the personalized needs of different users, the technicians have conducted a large number of experiments and actual applications, and calibrated and adjusted u many times based on the user's long-term sleep data and feedback, and gradually optimized the value of u so that it can accurately reflect the user's individual characteristics, thereby improving the system's adaptability to the user's sleep state and the guiding effect.

[0057] The intelligent sleep guidance system of the present invention accurately calculates the RS value which is positively correlated with the sleep depth through comprehensive analysis and weight adjustment of multi-spectral band brain wave signals. It can comprehensively cover the user's entire sleep cycle and ensure effective monitoring of the sleep state at each stage, thereby accurately guiding the user's sleep and significantly improving the user's sleep quality.

[0058] Embodiment 2: Combining with Figure 1 , Attachment Figure 2 and attached Figure 3 In addition to the contents of the above embodiments, the method for calculating the actual sleep parameter value C of the user includes the following steps:

[0059] S201: Obtain the user's age value Uage according to human input,

[0060] S202: Obtaining the average daily sleep duration value AL for the most recent week based on human input,

[0061] S203:

[0062] The C value reflects the individual differences of different users. When the C value is large, it corresponds to the user's age and sleep duration being close to the standard value. The user is in an ideal state and the correction amplitude is small.

[0063] A small C value indicates that the user's age or sleep duration deviates far from the standard value, indicating that a larger correction is needed.

[0064] The intelligent sleep guidance system of the present invention calculates the user's actual sleep parameter value C by comprehensively considering the user's age and the average sleep duration in the past week, thereby providing the system with a personalized basis for sleep state evaluation. The correction amplitude of RS is smoothly and moderately adjusted through the design of C, ensuring the wide applicability to different user groups and the stability of the system, which helps to achieve more effective sleep guidance.

[0065] Embodiment 3: Combining with Figure 1 , Attachment Figure 2 and attached Figure 3 In addition to the contents of the above embodiments, the adaptive control module implements the following operation steps:

[0066] S301: The processed signals are sequentially represented as X1, X2, X3, ... Xn according to the acquisition timing, and RS Xn Represented as the RS value corresponding to the Xn processed signal, RS Xn-2 , RS Xn-1 , RS Xn It is three processing signals in a continuous time series, and calculates the user's sleep dynamic value RSDT after Xn monitoring is completed XN :

[0067] Where, Δt = 10 seconds,

[0068] S302: In RSDT XN ≤tr, it is determined that the user may be waking up from a deep sleep state or the user's sleep state remains stable, and the current playback brightness and playback sound of the smart display are maintained.

[0069] In RSDT XN >tr, it is determined that the user is entering a deeper sleep state, and a command signal is sent to the playback controller to adjust the playback brightness of the smart display to Bne, and at the same time adjust the playback volume of the smart display to Vne;

[0070] Among them, tr is the preset judgment threshold, and 0.05≤tr≤0.3,

[0071] Vne=Vcur-(E1×RSDT Xn +P1×RS XN ),

[0072] Vcur is the playback volume of the smart display before adjustment, and E1 is the control RSDT XN The first volume adjustment coefficient of the volume adjustment intensity, P1 is RS Xn A second volume adjustment coefficient that affects the intensity of volume adjustment,

[0073] Bne=Bcur-(E2×RSDT Xn +P2×RS XN ),

[0074] Bcur is the playback brightness of the smart display before adjustment, and E2 is the control RSDT Xn The first brightness adjustment coefficient of the intensity of the brightness adjustment, P2 is RS Xn A second brightness adjustment coefficient that affects the brightness adjustment intensity,

[0075] The initial values ​​of u, w1, w2, w3, w4, E1, E2, P1 and P2 in the present invention are set by technicians in this field based on their rich practical experience, and are gradually adjusted and optimized through multiple experiments and practical application feedback to ensure that the intelligent sleep guidance system can accurately monitor and adjust the user's sleep state in actual applications.

[0076] In this embodiment, those skilled in the art can refer to the above value examples and make adjustments according to actual conditions. In short, the specific value ranges and trends of tr, u, E1, E2, P1 and P2 will be determined by the designers or operators of the intelligent sleep guidance system according to the actual sleep guidance processing requirements and system response, and will not be repeated here.

[0077] The steps of guiding the user's sleep by the intelligent sleep guidance system include:

[0078] Step 1: The user wears the headgear and the EEG sensor contacts the user's head.

[0079] Step 2: The EEG sensor starts to collect the user's brain wave signals, and the collected brain wave signals are transmitted to the signal processing module through the wires embedded in the headgear.

[0080] Step 3: The signal processing module calculates the sleep parameter value that is positively correlated with the user's sleep depth.

[0081] Step 4: The adaptation control module calculates and obtains a sleep dynamic value reflecting the change in the user's sleep state, and adjusts the brightness and volume of the smart display screen based on the user's sleep parameter value and the sleep dynamic value.

[0082] The intelligent sleep guidance system of the present invention takes into account both the sleep parameter values ​​and the sleep dynamic values, and realizes precise adjustment of the brightness and volume of the intelligent display screen, ensuring that the adjustment process not only reflects the user's current sleep depth, but also dynamically responds to the changing trend of the sleep state. With flexibility and personalized adaptability, the system can gently adjust environmental parameters to avoid abrupt changes, ensuring that users are guided to a more suitable sleeping environment without being disturbed.

[0083] Although the present invention has been described above with reference to various embodiments, it should be understood that many changes and modifications may be made without departing from the scope of the present invention. That is, the methods, systems and devices discussed above are examples. Various configurations may appropriately omit, replace or add various processes or components. For example, in alternative configurations, the method may be performed in an order different from that described, and / or various components may be added, omitted and / or combined. Moreover, the features described with respect to certain configurations may be combined in various other configurations, such as different aspects and elements of the configuration may be combined in a similar manner. In addition, as technology develops, the elements therein may be updated, i.e., many elements are examples and do not limit the scope of the present disclosure or claims. And it should be understood that after reading the contents of the record of the present invention, the technician may make various changes or modifications to the present invention, and these equivalent changes and modifications also fall within the scope defined by the claims of the present invention.

Claims

1. An intelligent sleep guidance system, It is characterized in that The intelligent sleep guidance system includes an acquisition module for monitoring and acquiring human brain electrical information, a signal processing module for analyzing human brain electrical information to determine the human sleep condition, an intelligent display screen for playing video and audio content, a playback controller for controlling the playback brightness and volume of the intelligent display screen, and an adaptive control module for further controlling the playback processor based on the judgment of the human sleep condition by the signal processing module. The signal processing module implements the following operation steps: S101: Filter the collected raw EEG signals to retain the signals in the range of 0.5 Hz to 30 Hz. Brain wave signals, S102: Segment the filtered continuous signal into several unit signals according to a fixed time window, each unit signal is 5 seconds. S103: Perform discrete Fourier transform on each signal unit signal to obtain a processed signal X, where the horizontal coordinate k of the processed signal is the frequency, and the vertical coordinate is the amplitude value, k∈[0.5Hz, 30Hz], |X[k]| is the amplitude value corresponding to the k frequency in the processed signal, S104: respectively obtain the total power Pδ of the δ spectrum segment, the total power Pθ of the θ spectrum segment, the total power Pα of the α spectrum segment, and the total power Pβ of the β spectrum segment in the processed signal: ， ， ， ， Among them, N=30Hz-0.5Hz=29.5Hz, the δ spectrum segment is the spectrum segment with power in the range of 0.5Hz to 4Hz in the processing signal, the θ spectrum segment is the spectrum segment with power in the range of 4Hz to 8Hz in the processing signal, the α spectrum segment is the spectrum segment with power in the range of 8Hz to 13Hz in the processing signal, and the β spectrum segment is the spectrum segment with power in the range of 13Hz to 30Hz in the processing signal. The β spectrum band is related to the user's active thinking activities, concentration and awake state, the α frequency band is related to the user's relaxed, awake but closed eyes state, the θ frequency band is related to the user's light sleep when falling asleep or relaxing, and the δ frequency band is related to the user's deep sleep. S105: Obtain the user's sleep parameter value RS: ， Among them, P all is the total power value of the processed signal, P all =Pδ+Pθ+Pα+Pβ, C is the actual sleep parameter value of the user, u is the user correction coefficient, w1, w2, w3, w4 are weight coefficients, w1+w2+w3+w4=1, and w1<w2<w3<w4, RS value is proportional to the sleep depth of the user, RC is the preset control value, and 0.5≤RC≤2.0; The calculation method of the user's actual sleep parameter value C includes the following steps: S201: Obtain the user's age value Uage according to human input, S202: Obtaining the average daily sleep duration value AL for the most recent week based on human input, S203:C= , The C value reflects the individual differences of different users. When the C value is large, it corresponds to the user's age and sleep duration being close to the standard value. The user is in an ideal state and the correction amplitude is small. A small C value corresponds to a deviation of the user's age or sleep duration from the standard value, indicating that a larger correction is needed; The adaptive control module implements the following operation steps: S301: The processed signals are sequentially represented as X1, X2, X3, ... Xn according to the acquisition timing, and RS Xn Represented as the RS value corresponding to the Xn processed signal, RS Xn-2 , RS Xn-1 , RS Xn It is three processing signals in a continuous time series, and calculates the user's sleep dynamic value RSDT after Xn monitoring is completed XN : , where Δt=10 seconds, S302: In RSDT XN ≤tr, it is determined that the user may be waking up from a deep sleep state or the user's sleep state remains stable, and the current playback brightness and playback sound of the smart display are maintained. In RSDT XN >tr, it is determined that the user is entering a deeper sleep state, and a command signal is sent to the playback controller to adjust the playback brightness of the smart display to Bne, and at the same time adjust the playback volume of the smart display to Vne; Among them, tr is the preset judgment threshold, and 0.05≤tr≤0.3, , Vcur is the playback volume of the smart display before adjustment, and E1 is the control RSDT XN The first volume adjustment coefficient of the volume adjustment intensity, P1 is RS Xn A second volume adjustment coefficient that affects the intensity of volume adjustment, ， Bcur is the playback brightness of the smart display before adjustment, and E2 is the control RSDT Xn The first brightness adjustment coefficient of the intensity of the brightness adjustment, P2 is RS Xn A second brightness adjustment coefficient that affects the intensity of brightness adjustment.

2. The intelligent sleep guidance system according to claim 1, It is characterized in that The acquisition module includes a headgear for the user to wear, a brain wave sensor arranged inside the headgear for detecting the user's brain wave signals, and a signal transmitter for transmitting the brain wave signals collected by the brain wave sensor to the signal processing module in real time.

3. The intelligent sleep guidance system according to claim 2, It is characterized in that The brain wave sensor and signal transmitter are connected via wires embedded inside the headgear.

4. The intelligent sleep guidance system according to claim 3, It is characterized in that There are ventilation holes designed near the brain wave sensor installation area of ​​the headgear. The ventilation holes are used to improve the air circulation inside the user's headgear and reduce the stuffiness caused by the user wearing the headgear for a long time.

5. The intelligent sleep guidance system according to claim 4, It is characterized in that The steps of guiding the user's sleep by the intelligent sleep guidance system include: Step 1: The user wears the headgear and the EEG sensor contacts the user's head. Step 2: The EEG sensor starts to collect the user's brain wave signals, and the collected brain wave signals are transmitted to the signal processing module through the wires embedded in the headgear. Step 3: The signal processing module calculates the sleep parameter value that is positively correlated with the user's sleep depth. Step 4: The adaptation control module calculates and obtains a sleep dynamic value that reflects changes in the user's sleep state, and adjusts the brightness and volume of the smart display based on the user's sleep parameter value and the sleep dynamic value.

Images