Intelligent slow wave sleep aiding system based on adaptive adjustment

Abstract

The invention relates to the technical field of sleep aiding, in particular to an intelligent slow wave sleep aiding system based on adaptive adjustment, which comprises a health monitoring bracelet, a multi-mode sleep aiding pillow, a sleep aiding illumination system and a transcranial electrical stimulation system, the problems that a traditional sleep-aiding product is difficult to accurately adapt to the sleep state of a human body, the adjusting effect is poor and the like are solved, physiological and body movement data are collected by means of the health monitoring bracelet and optimized, states such as waking, light sleep and deep sleep can be automatically and accurately recognized in combination with sleep state judgment rules, the states are fed back to the main control unit of the pillow through wireless transmission, and the sleep-aiding function is achieved. Self-adaptive control of music and sound effects, adjustment of ambient light, transcranial electric intensity and the like based on the sleep state of the human body are achieved, scientific and personalized support is provided for sleep improvement, sleep quality improvement is assisted, and the method can be used for reference application in the fields of intelligent sleep product research and development, sleep health management and the like.

Description

Technical Field

[0001] This invention relates to the field of sleep aid technology, specifically to an intelligent slow-wave sleep aid system based on adaptive adjustment. Background Technology

[0002] In modern society, the pace of life is constantly accelerating, and people are experiencing increasing pressure in various aspects of life and work. Declining sleep quality has become a common problem affecting many people. From a physiological health perspective, quality sleep is crucial for maintaining normal metabolism, immune system function, and nervous system repair. From a psychological health perspective, sufficient and high-quality sleep plays an irreplaceable role in mood regulation and cognitive function maintenance. However, as lifestyles shift towards higher frequency, more diverse, and more complex patterns, coupled with increasingly prominent external environmental interference factors such as urban noise and light pollution, many people struggle to obtain sufficient and high-quality sleep, leading to a continuous rise in the incidence of sleep disorders. To improve this situation, various sleep aids have emerged on the market, including light therapy devices, aromatherapy diffusers, and sleep masks integrating sound and light. However, at present, most sleep aids suffer from a significant deficiency in their limited functionality, focusing only on one or a few functions such as light therapy creating a soothing environment or aromatherapy providing sleep-inducing stimulation.

[0003] From an industry development perspective, single-function sleep aids have become a common product form in the early stages of the market due to their relatively low development costs and simple technical implementation. However, this product form brings practical pain points to users: if users expect to achieve better sleep through comprehensive interventions, such as simultaneously utilizing light environment adjustment, white noise masking, and olfactory sleep aids, they have to purchase multiple single-function devices, which are difficult to use in combination. Taking a typical sleep improvement scenario as an example, users need to simultaneously purchase light therapy equipment to create a sleep-aiding light environment, a white noise machine to output masking sounds, and an aromatherapy machine to emit soothing fragrances. This process not only significantly increases users' financial expenditure but also occupies a lot of living space due to the arrangement and coordinated use of multiple devices, causing a crowded living environment. When these problems are not effectively resolved for a long time, users will gradually reduce their willingness to use sleep aids due to the cumbersome operation process of multiple devices, the high overall cost, and the poor effect of sleep aids. They may even abandon using them altogether, ultimately failing to effectively improve sleep quality through these devices. This makes it difficult to meet users' needs for efficient, convenient, and low-cost sleep aid solutions and also limits the further expansion and upgrading of the sleep aid product market.

[0004] To address this, an intelligent slow-wave sleep aid system based on adaptive adjustment is proposed. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent slow-wave sleep aid system based on adaptive adjustment to solve the problems mentioned in the background art.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: an intelligent slow-wave sleep aid system based on adaptive adjustment, the system comprising: a health monitoring bracelet, a multimodal sleep aid pillow, a sleep aid light illumination system, and a transcranial electrical stimulation system;

[0007] The health monitoring bracelet includes multiple physiological signal acquisition modules and an embedded processor;

[0008] The multimodal sleep aid pillow includes a main control unit and an audio subsystem;

[0009] Multiple physiological signal acquisition modules are used to collect physiological data and body movement information of the human body in real time during sleep. The physiological data includes heart rate, blood oxygen and respiratory rate.

[0010] The embedded processor is used to fuse and extract features from the collected physiological data and body movement information, establish a discrimination model based on multi-dimensional signal features to determine the current sleep state and generate a discrimination result, and transmit the discrimination result and respiratory rate to the main control unit.

[0011] The main control unit receives the discrimination result and breathing frequency, and controls the audio subsystem accordingly to dynamically adjust the volume and rhythm of the music and sound effects;

[0012] The sleep-aid lighting system includes a flexible LED light strip with adjustable color temperature and brightness and a PWM dimming circuit. The main control unit controls the dynamic adjustment of the light source brightness and color temperature of the flexible LED light strip.

[0013] The transcranial electrical stimulation system is embedded in the multimodal sleep aid pillow. The transcranial electrical stimulation system includes microelectrodes, a constant current source circuit, current limiting protection, and a safety monitoring module. The main control unit controls the transcranial electrical stimulation system to output low-frequency microcurrents, induce slow-wave brainwave rhythms, and increase the probability of deep sleep.

[0014] According to the above technical solution, the physiological signal acquisition module includes a heart rate and blood oxygen acquisition module and a body motion information acquisition module; the heart rate and blood oxygen acquisition module includes a MAX30102 sensor, which integrates infrared and red light LEDs and a photodetector, and supports the acquisition of PPG signals; the body motion information acquisition module includes an MPU6050 triaxial accelerometer and a gyroscope module.

[0015] According to the above technical solution, the embedded processor is an STM32F411 CEU6 microcontroller, and the embedded processor controls and reads data from the physiological signal acquisition module through the I2C interface.

[0016] According to the above technical solution, the discrimination model is as follows: when the heart rate is stable, the blood oxygen saturation remains stable, the breathing rhythm is slow and the body movement is minimal, it is judged as a deep sleep state; when the physiological signal fluctuations are slight but the rhythm still exists, it is judged as a light sleep state; if the heart rate and breathing fluctuations are significant and the body movement is frequent or irregular, it is judged as a wakeful or critical state.

[0017] Compared with existing technologies, the beneficial effects achieved by this invention are as follows: This invention solves the problems of traditional sleep aids being difficult to accurately adapt to human sleep states and having poor adjustment effects. By collecting and optimizing physiological and physical data with a health monitoring bracelet, and combining it with sleep state judgment rules, it can automatically and accurately identify states such as wakefulness, light sleep, and deep sleep. This data is then wirelessly transmitted to the main control unit of the pillow, enabling adaptive control of music and sound effects, adjustment of ambient light, and transcranial electrical activity based on human sleep states. This provides scientific and personalized support for sleep improvement, helps to improve sleep quality, and can be used as a reference for applications in the fields of intelligent sleep product development and sleep health management. Attached Figure Description

[0018] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0019] Figure 1 This is an overall system block diagram of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Please see Figure 1 The present invention provides a technical solution: an intelligent slow-wave sleep aid system based on adaptive adjustment, the system comprising: a health monitoring bracelet, a multimodal sleep aid pillow, a sleep aid light illumination system and a transcranial electrical stimulation system;

[0022] The health monitoring bracelet includes multiple physiological signal acquisition modules and an embedded processor;

[0023] The health monitoring bracelet worn on the user's wrist continuously collects physiological data (heart rate, blood oxygen, respiratory rate) and body movement information during sleep.

[0024] The physiological signal acquisition module includes a heart rate and blood oxygen acquisition module and a body movement information acquisition module. The heart rate and blood oxygen acquisition module includes a MAX30102 sensor, which integrates infrared and red light LEDs and a photodetector to support the acquisition of PPG signals. The STM32F411 CEU6 controls and reads data from the physiological signal acquisition module through the I2C interface. After the raw PPG signal is processed by multi-stage filtering, the heart rate fluctuation characteristics and SpO2 value are extracted. Then, based on the PPG signal acquired by the MAX30102 sensor, respiratory fluctuations are demodulated. The respiratory rate is estimated based on the PPG signal acquired by the MAX30102 sensor in the wristband. Human breathing causes amplitude modulation, baseline drift, and frequency modulation in the PPG signal. The wristband main controller demodulates these respiratory modulation effects to achieve non-invasive estimation of respiratory rate. The specific method is to perform bandpass filtering and noise reduction on the PPG signal, extract its envelope or baseline trend, and then use frequency domain analysis to extract the main frequency component and convert it into respiratory rate, providing multi-dimensional physiological parameter support for subsequent accurate judgment of sleep status.

[0025] The body movement information acquisition module includes an MPU6050 triaxial accelerometer and a gyroscope module for acquiring body movement information. It records the frequency and amplitude of body movements during sleep in real time, capturing postural characteristics such as turning over, limb twitching, and lying flat or on one's side. The body movement signals are processed using low-pass filtering and dynamic thresholding to remove minor interference. Combined with the duration and rhythmic changes of the movements, this serves as a key input for sleep stage determination. Since some people exhibit behaviors such as turning over even during deep sleep, the amplitude of these movements is not very meaningful. Further algorithm optimization primarily uses the frequency of body movements to determine sleep state. Considering the influence of skin contact and wrist movement on wearable devices, this invention employs a multi-channel signal fusion algorithm and adaptive filtering strategy to dynamically correct and denoise heart rate, blood oxygen, respiration, and body movement data, outputting stable, continuous physiological parameters with high temporal resolution. Through this hardware and software co-design, the health monitoring bracelet of this invention can accurately monitor the user's core sleep physiological indicators, laying the foundation for subsequent sleep state analysis and personalized adjustments to sleep-aid stimulation programs.

[0026] The embedded processor is an STM32F411CEU6 microcontroller. The STM32F411 CEU6 has a high-performance ARM Cortex-M4 core with a main frequency of up to 100MHz. It has a built-in floating-point unit and rich peripheral interfaces, which can meet the real-time acquisition and processing requirements of multi-sensor data. Its low power consumption characteristics are also suitable for the long-term operation requirements of wearable devices such as wristbands.

[0027] The embedded processor is used to fuse and extract features from the collected physiological data and body movement information. First, it preprocesses the heart rate, blood oxygen, respiratory value and body movement information obtained by the physiological signal acquisition module. Within a 10-second sliding window, it calculates feature parameters such as mean and standard deviation of heart rate, coefficient of variation of blood oxygen, number and amplitude of body movements, and coefficient of variation of respiratory rate and rhythm. It comprehensively analyzes heart rate, blood oxygen, respiratory rate and body movement information, and establishes a discrimination model based on multi-dimensional signal features to determine the current sleep state and generate discrimination results. The discrimination results and respiratory rate are transmitted to the main control unit, thereby providing a reliable physiological basis for subsequent sleep state assessment and sleep aid regulation.

[0028] The specific discrimination model is as follows: when the heart rate is stable, the blood oxygen saturation remains stable, the breathing rhythm is slow and the body movement is minimal, it is judged as a deep sleep state; when the physiological signal fluctuations are slight but the rhythm still exists, it is judged as a light sleep state; if the heart rate and breathing fluctuate significantly and the body movement is frequent or irregular, it is judged as a wakeful or borderline state.

[0029] The multimodal sleep aid pillow includes a main control unit and an audio subsystem;

[0030] The main control unit receives the discrimination results and breathing frequency, and controls the audio subsystem to dynamically adjust the volume and rhythm of the music and sound effects accordingly.

[0031] The main control unit receives and identifies current sleep state and respiratory rate characteristics, and accordingly performs real-time adaptive control of the audio subsystem. The audio subsystem employs a self-developed HiFi-grade high-fidelity audio module and DSP sound processing chip, supporting low-frequency enhancement, rhythm synchronization, and varied playback functions. The main control unit dynamically adjusts the volume and rhythm of the music and sound effects based on the real-time respiratory rate. Utilizing specially designed IMAGINCE digital audio technology, the frequency fluctuations of the music or sound effects are adjusted to have a strong inducing effect on the human brain, perfectly matching the breathing state before falling asleep, during early sleep, and in deep sleep, helping users achieve high-quality sleep. Furthermore, the sleep-aid music or sound effects played by the audio subsystem are specially designed slow-wave music and sound effects. The sound effects mainly consist of white noise and natural sounds, allowing users to feel a sense of spaciousness and relaxation. The music selection primarily features instrumental pieces, including instruments with soft timbres such as the guqin, chime bells, chime stones, cello, viola, and morin khuur. The melodies are characterized by their distant, ethereal, and tranquil style. The music is also selected or original pieces are created based on the user's sleep-aid needs. Furthermore, the music and sound effects are intelligently selected based on information from the health monitoring bracelet to enhance the effectiveness of the sleep aid.

[0032] The sleep-aid lighting system includes a flexible LED light strip with adjustable color temperature and brightness, and a PWM dimming circuit. The main control unit controls the dynamic adjustment of the light source brightness and color temperature of the flexible LED light strip. For example, it outputs low color temperature and warm light to promote relaxation in the early stage of falling asleep, and turns off the light source to reduce interference during deep sleep.

[0033] The transcranial electrical stimulation system is embedded in the multimodal sleep aid pillow. The transcranial electrical stimulation system includes microelectrodes, constant current source circuit, current limiting protection and safety monitoring module. The main control unit controls the output of low-frequency microcurrent of the transcranial electrical stimulation system to induce slow wave rhythm of brain electricity and increase the probability of deep sleep.

[0034] Under the coordination of the main control unit, the above subsystems realize the synchronization and personalized adjustment of multimodal intervention rhythms of sound, light, electricity and electricity, forming a closed-loop intelligent sleep aid system to improve sleep efficiency and sleep quality.

[0035] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An intelligent slow wave sleep facilitating system based on adaptive adjustment, characterized in that, The system comprises a health monitoring bracelet, a multi-modal sleep-aiding pillow, a sleep-aiding lighting system and a transcranial electrical stimulation system. The health monitoring bracelet comprises a plurality of physiological signal acquisition modules and an embedded processor. The multi-modal sleep-aiding pillow comprises a master control unit and an audio subsystem. The plurality of physiological signal acquisition modules are used to acquire physiological data and body movement information of a human body in real time when sleeping, wherein the physiological data comprises heart rate, blood oxygen and breathing frequency. The embedded processor is used to perform fusion processing and feature extraction on the acquired physiological data and body movement information, establish a discriminant model according to multi-dimensional signal features to determine the current sleep state and generate a discriminant result, and transmit the discriminant result and the breathing frequency to the master control unit. The master control unit receives the discriminant result and the breathing frequency, and controls the audio subsystem to dynamically adjust the volume and rhythm of music and sound effects. The sleep-aiding lighting system comprises a flexible LED light strip with adjustable color temperature and brightness and a PWM dimming circuit, and the master control unit controls the dynamic regulation of the light source brightness and color temperature of the flexible LED light strip. The transcranial electrical stimulation system is embedded in the multi-modal sleep-aiding pillow, and comprises a microelectrode, a constant current source circuit, a current limiting protection and a safety monitoring module. 2.The intelligent slow wave sleep facilitating system based on adaptive adjustment according to claim 1, characterized in that: The master control unit controls the transcranial electrical stimulation system to output low-frequency microcurrent to induce brain slow wave rhythm and improve deep sleep probability. 3.The intelligent slow wave sleep facilitating system based on adaptive adjustment according to claim 1, characterized in that: The physiological signal acquisition module comprises a heart rate and blood oxygen acquisition module and a body movement information acquisition module. 4.The intelligent slow wave sleep facilitating system based on adaptive adjustment of claim 1, wherein: The heart rate and blood oxygen acquisition module comprises a MAX30102 sensor, integrated infrared and red light LEDs and a photodetector, and supports PPG signal acquisition. The body movement information acquisition module comprises an MPU6050 three-axis accelerometer and a gyroscope module. The embedded processor is an STM32F411 CEU6 microcontroller, which controls and reads data from the physiological signal acquisition module through an I 2C interface. The discriminant model is as follows: when heart rate is stable, blood oxygen saturation remains stable, breathing rhythm is slow and body movement is less, it is determined as deep sleep state; when physiological signal fluctuation is slight but rhythm still exists, it is determined as light sleep state; if heart rate and breathing fluctuate obviously and body movement is frequent or irregular, it is determined as wake or critical state.

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