Health early warning and monitoring system and method based on spatial information perception

Abstract

The invention discloses a health early warning and monitoring system based on spatial information perception. The health early warning and monitoring system comprises a multi-source heterogeneous data fusion module, a data processing module, a data fusion module, a spatial information perception module and a management center, the management center outputs decision information based on output data of the data fusion module, the multi-source heterogeneous data fusion module comprises a wearable sampling unit, an environment sensing unit and a millimeter wave radar array, and the data processing module reads medical record text features of a monitored person based on a BERT-Med entity recognition model; and the data fusion module fuses the collected information of the multi-source heterogeneous data fusion module, the data processing module and the spatial information perception module to generate a comprehensive health portrait. Compared with the prior art, the health early warning and monitoring system based on spatial information perception and the method thereof have the advantages that intelligent use is achieved, all-around safety monitoring is facilitated, and it is guaranteed that a person under guardianship rapidly responds to unforeseen circumstances.

Description

Technical Field

[0001] The present invention relates to the technical field of home safety and health monitoring for social personnel, and specifically to a health early warning monitoring system and method based on spatial information perception. Background Art

[0002] As they age, the elderly will experience memory loss, slower reaction speed, and other conditions, which make them prone to sudden situations that endanger their health. Various chronic diseases will also gradually appear. The problems of health monitoring and disease diagnosis and treatment for the elderly, especially those living alone (empty nesters) and disabled elderly, need to be urgently addressed.

[0003] For example, elderly people cannot receive timely assistance when they fall or suffer a heart attack at home, and it is difficult to control the recurrence or exacerbation of chronic diseases in real time. This will seriously affect the physical and mental health of the elderly, reduce their quality of life, and increase the burden on their families and society.

[0004] Most of the current health monitoring management systems have single functions and can only simply detect body characteristics such as temperature, heart rate, and blood oxygen saturation through smart bracelets and smart watches. However, wearing only existing traditional smart devices still cannot meet the health monitoring and safety warning requirements of the elderly. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to overcome the above technical defects and provide a health warning monitoring system and method based on spatial information perception that is intelligent, convenient for all-round safety monitoring, and ensures rapid response to unexpected situations of the monitored person.

[0006] To solve the above technical problems, the present invention provides a technical solution: a health early warning monitoring system based on spatial information perception, comprising a multi-source heterogeneous data fusion module, a data processing module, a data fusion module, a spatial information perception module and a management center;

[0007] The management center outputs decision information based on the output data of the data fusion module. The multi-source heterogeneous data fusion module includes a wearable sampling unit, an environmental sensing unit, and a millimeter-wave radar array. The data processing module reads the text features of the patient's medical records based on the BERT-Med entity recognition model.

[0008] The data fusion module fuses the collected information of the multi-source heterogeneous data fusion module, the data processing module, and the spatial information perception module to generate a comprehensive health portrait. The spatial information perception module also includes identifying abnormal behavior patterns.

[0009] Preferably, the wearable sampling unit includes any one of a flexible electronic skin patch and a smart bracelet, and the environmental sensing unit includes a non-contact respiratory rate monitoring sensor and a temperature and humidity gas monitoring sensor.

[0010] Preferably, the spatial information perception module includes an array radar unit, an intelligent camera unit, a concealed monitoring unit deployed in furniture, and a floor tile pressure sensor;

[0011] The spatial information perception module outputs information on falling, wandering, and entering dangerous areas.

[0012] Preferably, the millimeter wave radar array is a 60 GHz frequency band dual-channel radar.

[0013] Preferably, the data fusion module includes establishing a spatiotemporal feature mapping model, and performing spatiotemporal alignment based on the waveform data of the wearable sampling unit and the millimeter wave radar spatial coordinates;

[0014] The attention mechanism is used to weightedly fuse multi-source data to generate a comprehensive health index.

[0015] Preferably, the management center includes three levels of warning decision units: level one warning, level two warning and level three warning;

[0016] The management center is also connected to the nursing-side PDA, the family-side APP, and the community warning terminal.

[0017] Another aspect of the present invention discloses a health early warning monitoring method based on spatial information perception, comprising the following steps:

[0018] Step 1: Multi-source data collection;

[0019] Step 2: Spatiotemporal feature alignment;

[0020] Step 3: Abnormal behavior pattern recognition;

[0021] Step 4: Multimodal data fusion decision.

[0022] Preferably, step 1 includes acquiring ECG / PPG physiological signals through a wearable sampling unit, collecting three-dimensional spatial coordinates through a 60GHz millimeter wave radar array, and acquiring temperature, humidity, and air quality parameters through environmental sensors.

[0023] Preferably, step 2 includes establishing a spatiotemporal mapping model of physiological signals and spatial trajectories, and step 3 obtains spatial information perception data by analyzing continuous spatial trajectory features through an LSTM neural network to identify falls, wandering, and staying in dangerous areas.

[0024] Preferably, in step 4, the attention mechanism is used to calculate the weight of each data source, generate a user health profile, and output decision information through a three-level early warning decision unit.

[0025] The advantages of the present invention over the existing technology are: in the present invention, multi-modal data collection is performed through wearable sampling units, environmental sensing units and array radars, and spatial information perception is performed through a spatial information perception module, thereby performing all-round posture and behavior monitoring of the monitored person, and the intelligent hierarchical early warning response facilitates the monitoring end to quickly understand the current situation and meet application needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a structural diagram of a health early warning monitoring system based on spatial information perception.

[0027] Figure 2 It is a schematic diagram of a health early warning monitoring method based on spatial information perception. DETAILED DESCRIPTION

[0028] The present invention will be described in further detail below with reference to the accompanying drawings.

[0029] Combined with attachment Figure 1-2 As shown, a health early warning monitoring system based on spatial information perception includes a multi-source heterogeneous data fusion module, a data processing module, a data fusion module, a spatial information perception module and a management center; the management center outputs decision information based on the output data of the data fusion module, the multi-source heterogeneous data fusion module includes a wearable sampling unit, an environmental sensing unit, and a millimeter wave radar array, and the data processing module reads the text features of the medical records of the monitored person based on the BERT-Med entity recognition model; the data fusion module fuses the collected information of the multi-source heterogeneous data fusion module, the data processing module, and the spatial information perception module to generate a comprehensive health portrait, and the spatial information perception module also includes the ability to identify abnormal behavior patterns.

[0030] When in use, the wearable sampling unit includes any one of a flexible electronic skin patch and a smart bracelet, the environmental sensing unit includes a non-contact respiratory rate monitoring sensor and a temperature and humidity gas monitoring sensor, and the spatial information perception module includes an array radar unit, an intelligent camera unit, a concealed monitoring unit deployed in furniture, and a floor tile pressure sensor; the spatial information perception module outputs information on falls, wandering, and intrusion into dangerous areas.

[0031] The millimeter-wave radar array is a dual-channel radar in the 60GHz frequency band. The data fusion module includes establishing a spatiotemporal feature mapping model, performing spatiotemporal alignment based on the waveform data of the wearable sampling unit and the millimeter-wave radar spatial coordinates; and using the attention mechanism to weightedly fuse multi-source data to generate a comprehensive health index.

[0032] The management center includes three levels of warning decision-making units: level one warning, level two warning and level three warning; the management center is also connected to the nursing-side PDA, the family-side APP, and the community warning terminal.

[0033] The present invention, when implemented, includes the following steps: Step 1: multi-source data acquisition; Step 2: spatiotemporal feature alignment;

[0034] Step 3: Abnormal behavior pattern recognition; Step 4: Multimodal data fusion decision-making.

[0035] Step 1 includes acquiring ECG / PPG physiological signals through a wearable sampling unit, collecting three-dimensional spatial coordinates through a 60GHz millimeter-wave radar array, and obtaining temperature, humidity, and air quality parameters through environmental sensors. Step 2 includes establishing a spatiotemporal mapping model between physiological signals and spatial trajectories. Step 3 includes analyzing continuous spatial trajectory features through an LSTM neural network to obtain spatial information perception data to identify falls, wandering, and staying in dangerous areas. Step 4 uses an attention mechanism to calculate the weights of each data source, generate a user health profile, and output decision information through a three-level early warning decision unit.

[0036] When in use, the multi-source heterogeneous data fusion module builds a three-dimensional dynamic perception network of the living space through wearable sampling units, environmental sensor arrays and 60GHz millimeter-wave radars. The millimeter-wave radar array tracks human movement trajectories in real time and combines the ECG / PPG data of wearable devices to achieve non-contact synchronous monitoring of vital signs.

[0037] The floor tile pressure sensor can also construct a heat map of human activity, identify abnormal gait and determine the risk level of falling. The intelligent camera unit analyzes environmental images in real time and detects dangerous behavior.

[0038] Based on the spatiotemporal feature mapping model, the temporal physiological data of the wearable device is aligned with the spatial coordinates of the millimeter-wave radar, and the weights are dynamically allocated through the attention mechanism.

[0039] When an elderly person leaves the bed at night, triggering the floor tile pressure sensor and the radar detecting an unstable gait, the system automatically plays a voice query and simultaneously notifies the family to monitor muscle electrical activity (EMG) through flexible electronic skin, combine gait analysis to evaluate rehabilitation progress, and dynamically perceive the physical condition of the monitored person.

[0040] The contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0041] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative work shall fall within the scope of protection of the present invention.

[0042] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not require further definition or explanation in subsequent drawings.

[0043] In the present invention, unless otherwise expressly specified or limited, terms such as "mounted," "connected," "connect," and "fixed" should be understood broadly. For example, they may refer to fixed connection, detachable connection, or integration; they may refer to direct connection or indirect connection through an intermediate medium; they may refer to internal communication between two components or interaction between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0044] In the present invention, unless otherwise expressly specified or limited, a first feature being "above" or "below" a second feature may include the first and second features being in direct contact, or may include the first and second features being in contact not directly but through another feature between them. Moreover, a first feature being "above," "above," and "above" a second feature includes the first feature being directly above and obliquely above the second feature, or simply indicates that the first feature is higher in level than the second feature. A first feature being "below," "below," and "below" a second feature includes the first feature being directly below and obliquely below the second feature, or simply indicates that the first feature is lower in level than the second feature.

[0045] The present invention and its embodiments are described above. This description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. In short, if a person skilled in the art is inspired by this and, without departing from the purpose of the present invention, designs structures and embodiments similar to this technical solution without inventiveness, they shall fall within the scope of protection of the present invention.

Claims

1. A health early warning monitoring system based on spatial information perception, characterized by: It includes multi-source heterogeneous data fusion module, data processing module, data fusion module, spatial information perception module and management center; The management center outputs decision information based on the output data of the data fusion module. The multi-source heterogeneous data fusion module includes a wearable sampling unit, an environmental sensing unit, and a millimeter-wave radar array. The data processing module reads the text features of the patient's medical records based on the BERT-Med entity recognition model. The data fusion module fuses the collected information of the multi-source heterogeneous data fusion module, the data processing module, and the spatial information perception module to generate a comprehensive health portrait. The spatial information perception module also includes identifying abnormal behavior patterns.

2. The health early warning monitoring system based on spatial information perception according to claim 1, characterized in that: The wearable sampling unit includes any one of a flexible electronic skin patch and a smart bracelet, and the environmental sensing unit includes a non-contact respiratory rate monitoring sensor and a temperature and humidity gas monitoring sensor.

3. The health early warning monitoring system based on spatial information perception according to claim 1, characterized in that: The spatial information perception module includes an array radar unit, an intelligent camera unit, a concealed monitoring unit deployed in the furniture, and a floor tile pressure sensor; The spatial information perception module outputs information on falling, wandering, and entering dangerous areas.

4. The health early warning monitoring system based on spatial information perception according to claim 2, characterized in that: The millimeter-wave radar array is a 60 GHz frequency band dual-channel radar.

5. The health early warning monitoring system based on spatial information perception according to claim 1, characterized in that: The data fusion module includes establishing a spatiotemporal feature mapping model, and performing spatiotemporal alignment based on the waveform data of the wearable sampling unit and the millimeter wave radar spatial coordinates; The attention mechanism is used to weightedly fuse multi-source data to generate a comprehensive health index.

6. The health early warning monitoring system based on spatial information perception according to claim 1, characterized in that: The management center includes three levels of early warning decision-making units: first-level early warning, second-level early warning and third-level early warning; The management center is also connected to the nursing-side PDA, the family-side APP, and the community warning terminal.

7. A health warning monitoring method based on spatial information perception, applied to the health warning monitoring system according to any one of claims 1 to 6, characterized in that: The steps include: Step 1: Multi-source data collection; Step 2: Spatiotemporal feature alignment; Step 3: Abnormal behavior pattern recognition; Step 4: Multimodal data fusion decision.

8. The health early warning monitoring system based on spatial information perception according to claim 7, characterized in that: Step 1 includes acquiring ECG / PPG physiological signals through a wearable sampling unit, collecting three-dimensional spatial coordinates through a 60GHz millimeter wave radar array, and acquiring temperature, humidity, and air quality parameters through environmental sensors.

9. The health early warning monitoring system based on spatial information perception according to claim 7, characterized in that: The step 2 includes establishing a spatiotemporal mapping model between physiological signals and spatial trajectories, and the step 3 obtains spatial information perception data by analyzing the continuous spatial trajectory features through the LSTM neural network to identify falls, wandering and staying in dangerous areas.

10. The health early warning monitoring system based on spatial information perception according to claim 7, characterized in that: In step 4, the attention mechanism is used to calculate the weight of each data source, generate a user health profile, and output decision information through the three-level warning decision unit.

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