Centralized multi-user sleep-aiding audio automatic control system and method

Abstract

The invention discloses a centralized multi-user sleep-aiding audio automatic control system and method, and belongs to the technical field of smart home and health monitoring. Dynamically collecting real-time sleep physiological signals of multiple users through sleep monitoring equipment; the first core of the system is that the sleep state analysis central server carries out centralized processing on received physiological signals and rapidly and accurately identifies sleep states of all users; and the core 2 is that the volume control central server performs centralized decision-making on the sleep state change of each user, and accurately distributes instructions: a first control instruction is sent to the audio equipment bound with the user entering deep sleep, and a second control instruction is sent to the audio equipment of the user recovered to be awakened. Through the one-to-one binding of the monitoring equipment and the playing equipment and the centralized management architecture of the central server, the personalized and refined volume control of massive users is realized, the problems that the traditional sleep aiding equipment cannot automatically manage the volume and cannot accurately serve multiple users at the same time and the like are effectively solved, and the intelligent level of sleep aiding and the user experience are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of smart home and health monitoring, and particularly relates to a centralized multi-user sleep-aiding audio automatic control system and method. BACKGROUND

[0002] With the acceleration of social rhythm and the increase of life pressure, sleep disorders have become a common health problem. Sleep-aiding music, as a non-drug intervention method, is widely used to improve sleep quality. However, the existing sleep-aiding audio devices have obvious limitations: (1) simple control method: most devices use a simple timing-off function and cannot dynamically adjust the volume according to the real sleep state of the user; (2) single-user limitation: existing solutions only serve a single user and cannot realize multi-user parallel management; (3) lack of precision: although existing solutions can monitor sleep and automatically adjust the volume, they are mostly locally processed, with simple control logic and poor monitoring accuracy, which leads to poor user experience; (4) high cost limitation: existing solutions are costly and difficult to market; (5) poor scalability: existing solutions cannot effectively support thousands of users to use simultaneously and are difficult to meet the needs of group scenarios such as hotels and nursing homes. For example, Chinese patent CN114366986A discloses a "sleep-aiding method, medium and wearable device", but this solution can only control locally according to the sleep physiological state changes of a single user and does not involve multi-user binding and central server architecture. Moreover, the implementation of this solution has a high single cost and is limited by processor performance, making it difficult to achieve fine audio control, so it is difficult to be marketed on a large scale. Therefore, there is an urgent need in the art for a system and method that can serve a large number of users simultaneously and perform individualized and fine audio control according to the real-time sleep state of each user. SUMMARY

[0003] The present application aims to overcome the shortcomings of the prior art and provide a centralized multi-user sleep-aiding audio automatic control system and method. The main purposes include:

[0004] (1) to realize the unique binding of sleep monitoring devices and audio playback devices and ensure the accurate targeting of control instructions;

[0005] (2) to realize the centralized processing and intelligent decision-making of massive user data through a central server structure and support large-scale user concurrent access

[0006] (3) to automatically and accurately control the playback, pause, volume adjustment and other operations of the audio devices bound to each user according to their real-time sleep state, thereby improving user experience.

[0007] To achieve the above purposes, the present application adopts the following technical solutions:

[0008] 1. In one aspect, the present application provides a system for implementing the above method, comprising:

[0009] (1) A plurality of sleep signal acquisition and transmission devices: for real-time acquisition and transmission of user sleep physiological signals;

[0010] (2) A sleep state analysis central server: in communication connection with the acquisition device, for analyzing and deriving the real-time sleep state of each user;

[0011] (3) A volume control central server: in communication connection with the sleep state analysis server, for generating volume control instructions and sending them to the corresponding user-bound audio devices;

[0012] (4) A plurality of audio playback devices: in communication connection with the volume control server, for receiving volume control instructions and executing operations.

[0013] 2. In another aspect, the present application provides a centralized multi-user sleep-aiding audio automatic control method, comprising the following steps:

[0014] (1) Distributed sleep signal acquisition and transmission: through a plurality of sleep monitoring devices, the sleep physiological signals of each user are respectively acquired and transmitted to a sleep state analysis central server;

[0015] (2) Centralized sleep state analysis and transmission: the sleep state analysis central server receives all user real-time sleep physiological signals, determines the real-time sleep state of each user (including deep sleep, light sleep, rapid eye movement, wakefulness and bed leaving state) through algorithm analysis, and sends the results to a volume control central server;

[0016] (3) Centralized control signal generation and transmission: the volume control central server receives the sleep state analysis results of all users; through a task scheduling module, tasks are allocated; a processing unit consumes tasks, generates specific control instructions according to sleep state changes and accurately distributes them: when the sleep state of a user changes to deep sleep, the first control instruction (pause or lower volume) is generated and sent to the audio device bound to it; when the sleep state of a user changes to wakefulness or bed leaving state, the second control instruction (resume or increase volume) is generated and sent to the audio device bound to it; for any change in the sleep state of a user, the corresponding control instruction can be immediately responded and sent; sending control instructions to any user will not affect the sleep state monitoring of other users, nor will it cause unnecessary impact on the sleep of any other user;

[0017] (4) Distributed playback control: each audio playback device receives control instructions and executes corresponding operations.

[0018] 1.1 Further, the step (1) distributed sleep signal collection and sending includes the following specific steps (taking a user C as an example):

[0019] 1.1.1. The sleep monitoring device a equipped by the user C collects the sleep physiological signals of the user, and the playing device of the user is b; when the user C prepares to go to bed, the devices a and b are turned on;

[0020] 1.1.2. The devices a and b automatically complete pairing and binding;

[0021] 1.1.3. The devices a and b start to work separately, the device a starts to collect the sleep physiological signals of the user, and the device b starts to play the sleep-aiding audio set by the user;

[0022] 1.1.3.1. The device a collects the sleep basic data of the user C, such as in-bed state, heart rate, respiration rate, body movement, eye movement, and bed temperature, every second;

[0023] 1.1.4. The device a uploads the real-time sleep basic data of the user C to the cloud sleep state analysis central server s1;

[0024] 2.1 Further, the step (2) centralized sleep state analysis and sending includes the following specific steps:

[0025] 2.1.1. After the central server s1 receives the sleep basic data of the user C, the PSO-SVM sleep staging model algorithm is called to calculate the current sleep state (including deep sleep, light sleep, rapid eye movement, wakefulness, and out-of-bed state) of the user C;

[0026] 2.1.2. The current sleep state of the user C is sent to the cloud volume control central server s2;

[0027] 3.1 Further, the step (3) centralized control signal generation and sending includes the following specific steps:

[0028] 3.1.1. If the current sleep state of the user C is wakefulness, light sleep, or out-of-bed state after going to bed, the central server s2 does not generate a control signal;

[0029] 3.1.2. If the current sleep state of the user C changes to deep sleep or rapid eye movement, the central server s2 generates a first control signal, i.e., stopping playing or reducing the volume;

[0030] 3.1.3. If the current sleep state of the user C changes to wakefulness or out-of-bed state again, the central server s2 generates a second control signal, i.e., resuming playing or increasing the volume;

[0031] 3.1.4. The central server s2 sends the generated control signal to the device b bound by the device a;

[0032] 4.1 Further, the step (4) distributed play control includes the following specific steps:

[0033] 4.1.1. Device b receives the first control signal sent by the central server s2, and immediately stops playing or lowers the volume;

[0034] 4.1.2. Device b receives the second control signal sent by the central server s2, and immediately resumes playing or increases the volume; Advantages

[0035] Compared with the prior art, the present application has the following obvious advantages:

[0036] (1) High precision personalized service: through the "one-to-one" device binding mechanism, it is ensured that the play volume of each user is completely based on the real-time change of its own sleep state, realizing truly personalized service;

[0037] (2) Large-scale efficient management: the central server architecture can manage more than ten thousand device pairs at the same time, effectively cope with high concurrency scenarios through load balancing, task scheduling and other technologies, and has elastic expansion capability;

[0038] (3) Intelligent decision: the sleep staging accuracy based on the improved algorithm (such as PSO-SVM model) is high, the task scheduling module and instruction unit processing mechanism are introduced, the instructions are accurately distributed, and the sleep aid effect is effectively improved;

[0039] (4) Strong system reliability: the design of access gateway, firewall and the like ensures the safety and stability of the system, and the distributed control logic reduces the risk of single point failure;

[0040] (5) Low cost advantage: the central server architecture greatly reduces the use cost of each user, providing a solid economic foundation for marketization;

[0041] (6) Wide application scenarios: suitable for families, hotels, medical institutions, old-age communities and other scenarios that need group sleep quality management. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 The overall architecture diagram of the centralized multi-user sleep aid audio automatic control system is shown.

[0043] Figure 2 The logic diagram of the internal task scheduling and processing of the volume control central server is shown.

[0044] Figure 3 The application flowchart of the large-scale hotel sleep aid system based on the cloud platform is shown in Embodiment 1 of the present application.

[0045] Figure 4 The application flow chart of the personalized health management of the high-end pension community according to Embodiment 2 of the present application. DETAILED DESCRIPTION

[0046] The specific embodiments will be described in detail below in combination with the characteristics of the technical solutions of the present application. The following embodiments are only used to more clearly illustrate the technical solutions of the present application, and therefore only serve as examples, but cannot limit the protection scope of the present application.

[0047] Embodiment 1: Large-scale hotel sleep-aid system application based on cloud platform

[0048] In this embodiment, the system is deployed on a public cloud to provide sleep-aid services for a large chain hotel.

[0049] 1. Hardware configuration:

[0050] Sleep signal acquisition and transmission device (100, 200): a 60G millimeter wave high-precision radar detector is built in each guest room bedside cabinet, which is used to non-contact acquisition of user heart rate, respiration rate, eye movement and body movement signals; the detector transmits data to the cloud through the hotel's Wi-Fi network for encryption;

[0051] Sleep state analysis central server (300): deployed on a cloud server cluster, using a sleep staging model based on an improved particle swarm algorithm optimized support vector machine (PSO-SVM) to analyze the received original sleep physiological signals in real time and output sleep state results;

[0052] Volume control central server (400): also deployed on the cloud, using a microservice architecture, its core includes:

[0053] (1) Central task scheduling module: receiving state results from the analysis module, according to the room number (i.e. device binding relationship) to publish control instruction generation tasks to the message queue;

[0054] (2) Multiple audio instruction processing units: deployed in a containerized manner, consuming tasks from the message queue, generating specific control instructions according to sleep state changes, and issuing them to the specified room audio device through the hotel's network;

[0055] Audio playback device (500): each room is equipped with a smart speaker, which has been uniquely bound to the 60G millimeter wave radar in the room. It subscribes to cloud instructions and performs operations such as playing, pausing, and volume adjustment.

[0056] 2. System workflow:

[0057] After guest c checks in, the system automatically activates the radar a--smart speaker b device pair in the room;

[0058] After the guest c goes to bed, the 60G millimeter wave radar a continues to collect the sleep physiological signals of the guest c and uploads them to the cloud, and the smart audio box b starts to play sleep-aiding audio;

[0059] The sleep state analysis central server s1 in the cloud analyzes the sleep state of the guest c in real time, and notifies the volume control central server s2 of the analysis result;

[0060] The volume control central server s2 in the cloud calls a task scheduling module, generates a sleep state generation task of the guest c, and assigns the task to an idle instruction processing unit;

[0061] The unit compares the sleep state of the guest c at the previous moment, and if it is found that there is no change, it is ignored and continues to be monitored; if there is a change, a corresponding control instruction is generated;

[0062] If the sleep state of the guest c changes from wakefulness, light sleep or bed leaving to deep sleep or rapid eye movement, the unit generates a “pause playing” instruction, and accurately issues the instruction to the smart audio box b in the guest room through the network;

[0063] The audio box b executes the instruction to stop playing sleep-aiding music, so as to avoid the interference of the music on the deep sleep of the guest c;

[0064] If the sleep state of the guest c changes from deep sleep or rapid eye movement to wakefulness or bed leaving (the millimeter wave radar a detects a large movement), the unit generates a “resume playing” instruction, and accurately issues the instruction to the smart audio box b in the guest room through the network, and the audio box b automatically resumes playing sleep-aiding music to help the guest c quickly enter the sleep state.

[0065] Embodiment 2: Application of personalized health management in high-end pension communities

[0066] In this embodiment, the system is deployed on a private cloud in a pension community, focuses on health monitoring and personalized care, and the hardware configuration is slightly different, and the overall work flow does not change significantly.

[0067] 1. Differences in hardware and software configuration:

[0068] The collection device a: a flexible graphene piezoelectric sensor sleep monitoring pad is provided for each old person c, which is laid under the bed sheet, and is used to collect sleep state physiological signals such as heart rate, respiration rate, bed temperature and bed leaving;

[0069] The audio device b: the old person's mobile phone + high-performance active Bluetooth audio box;

[0070] A dedicated sleep-aiding applet: the old person c can order the sleep-aiding audio that he likes through the mobile phone, provide personalized sleep-aiding effect, and provide high-quality audio experience.

[0071] Function extension:

[0072] The central server not only controls the audio, but also pushes the sleep report (such as deep sleep duration, bed leaving times) of the old man c to the caregiver workstation and related relatives. The system supports setting different volume adjustment strategies for different old people, for example, for the old people with weak hearing, the system will automatically adjust the volume to a preset higher level after they wake up. Industrial applicability

[0073] The system and method described in the present application have clear industrial applicability and can be widely applied to:

[0074] Hotel industry: improve guest room service quality and create "intelligent sleep" theme guest rooms;

[0075] Elderly care and medical monitoring: real-time monitoring of sleep safety and quality of the elderly or patients, and timely alarm for abnormal conditions such as high heart rate, rapid breathing, long time leaving bed at night, etc.

[0076] High-end residential and community: provide personalized smart home sleep solutions for family users;

[0077] Research institutions: provide large-scale, long-time data collection and analysis platform for sleep research.

[0078] The scheme of the present application is based on general network architecture and hardware devices, which is mature in technology, easy to implement, and has the prospect of large-scale production and application.

[0079] The above is only the preferred specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can make equivalent replacement or change according to the technical scheme and the inventive concept of the present application within the technical range disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A centralized multi-user sleep-aiding audio automatic control method, characterized in that, It comprises the following steps: (1) Distributed sleep signal collection and sending step: a plurality of sleep monitoring devices collect the sleep physiological signals of each user respectively, and send the sleep physiological signals to a sleep state analysis central server; (2) Centralized sleep state analysis and sending step: the sleep state analysis central server receives all user sleep physiological signals in real time, determines the sleep state of each user through algorithm analysis, and the sleep state includes deep sleep, light sleep, rapid eye movement, wakefulness and out-of-bed state, and sends the analysis result to a volume control central server; (3) Centralized control signal generation and sending step: the volume control central server receives the sleep state analysis results of all users, allocates tasks through a task scheduling module; the processing unit consumes tasks, generates specific control instructions according to the change of sleep state and accurately distributes: when the sleep state analysis result of a user changes to deep sleep, the first control instruction is generated and sent to the audio playback device bound to the user; when the sleep state analysis result of a user changes to wakefulness or out-of-bed state, the second control instruction is generated and sent to the audio playback device bound to the user; (4) Distributed playback control step: each audio playback device receives the first control instruction or the second control instruction from the volume control central server, and performs corresponding operation; Wherein, the first control instruction is a pause playing instruction or a volume down instruction, and the second control instruction is a resume playing instruction or a volume up instruction.

2. The method of claim 1, wherein: Each user's sleep monitoring device has a unique corresponding binding relationship with an audio playback device.

3. The method according to claim 1 or 2, characterized in that: The sleep monitoring device is a sleep monitoring bracelet, a sleep monitoring ring, a millimeter wave radar, a sleep monitoring pad or a sleep monitoring polygraph, etc.

4. The method of claim 1, wherein: The transmission of the sleep physiological signals is realized through Wi-Fi combined with a mobile terminal, or 4G / 5G direct connection device.

5. A centralized multi-user sleep-aiding audio automated control system for implementing the method of any one of claims 1 to 4, characterized in that, It comprises: (1) A plurality of sleep signal collection and transmission devices (100, 200) for collecting and transmitting the sleep physiological signals of each user; (2) A sleep state analysis central server (300) in communication connection with the sleep signal collection and transmission device, for receiving the physiological signals and analyzing the sleep state of each user; (3) A volume control central server (400) in communication connection with the sleep state analysis central server, for generating corresponding playback control signals according to the sleep state of each user, and sending them to the audio playback device bound to the corresponding user; (4) A plurality of audio playback devices (500) in communication connection with the volume control central server respectively, for receiving the playback control signals and performing corresponding operation.

6. The system of claim 5, wherein: The sleep signal collection device is equipped with high-precision signal collection sensors, such as three-axis acceleration sensor, optical heart rate sensor, infrared wearing detection sensor, flexible piezoelectric sensor and millimeter wave radar detector, etc.

7. The system of claim 5, wherein: The sleep state analysis central server adopts the sleep staging model based on improved particle swarm optimization support vector machine (PSO-SVM).

8. The system of claim 5, wherein: (1) The volume control central server is configured to manage more than ten thousand user-bound device pairs simultaneously and can flexibly increase server configuration according to actual needs to improve large-scale user service capability; (2) The volume control central server includes a task scheduling module and a plurality of audio instruction processing units connected in communication; (3) The task scheduling module is configured to receive sleep state data from the sleep state analysis central server and distribute tasks for generating control instructions to designated audio instruction processing units based on the binding relationship; (4) The audio instruction processing unit is deployed in a containerized manner, consumes tasks from a message queue, generates specific control instructions according to sleep state changes, and sends them to the designated room audio equipment through the hotel network (5) The system further includes an access gateway, which includes a load balancer configured to receive data streams from a plurality of sleep signal acquisition and transmission devices and send them to the sleep state analysis central server instance.

9. The system of claim 5, wherein: The audio playback device is a mobile terminal or a computer equipped with a source audio amplifier or a passive audio amplifier, or a smart audio amplifier capable of performing device binding and instruction operation.

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