Intelligent anti-tumble reminding bracelet based on behavior evaluation reminding and application of intelligent anti-tumble reminding bracelet

Abstract

The invention relates to an intelligent anti-falling reminding bracelet based on behavior evaluation reminding and application thereof, and based on implementation of the intelligent anti-falling reminding bracelet, anti-falling monitoring and propaganda and education can be performed through the bracelet. The falling-down propaganda and education module is integrated on the bracelet, the functions of falling-down monitoring, behavior analysis, propaganda and education measure calling, voice broadcasting, alarming and the like are integrated, falling-down prevention propaganda and education can be carried out on a patient, and timing triggering can be carried out. Meanwhile, whether the patient falls down or not can be supervised, and if so, an alarm is triggered and corresponding rescue measure voice is played to guide the patient to self-rescue. At ordinary times, propaganda and education can be carried out regularly, so that the patient can learn anti-falling propaganda and education knowledge of various behaviors, and the anti-falling awareness of the patient is enhanced.

Description

Technical Field

[0001] The present disclosure relates to the field of intelligent medical technology, and in particular to an intelligent anti-fall reminder bracelet based on behavior assessment reminders, an application method thereof, and an electronic device. Background Art

[0002] Falls have many risks in clinical practice, especially injuries. It is difficult for many patients to change their living habits. Therefore, it is necessary to educate elderly patients about falls, such as the "three and a half minutes" for falling, the trouser legs should not be too long, and the need for crutches.

[0003] For many elderly people or patients who faint, the development of behavioral habits requires encouragement and supervision. Appropriate anti-fall reminders can help patients move correctly and reduce the risk of injury caused by falls.

[0004] In existing hospitals or home life, most of the measures to remind patients of falls are traditional means, such as nurse reminders, educational reminder signs, etc. However, these measures cannot be used with patients to carry out fall prevention reminders or education, and are of little use. Summary of the invention

[0005] In order to solve the above problems, the present application proposes a smart anti-fall reminder bracelet based on behavior assessment reminders, an application method and an electronic device thereof.

[0006] On the one hand, the present application proposes an intelligent anti-fall reminder bracelet based on behavior assessment reminder, including a bracelet body and a fall education module arranged on the bracelet body, wherein the fall education module includes:

[0007] Acceleration sensor, used to collect the acceleration value of the corresponding patient in real time and forward it to the processing system through MCU;

[0008] The processing system is used to monitor whether the acceleration value has a preset change value: if it does, it is determined that the patient has a fall behavior, and corresponding fall guidance voice data is generated, and the fall guidance data is forwarded to the voice module through the MCU;

[0009] A voice module, used for playing the fall guidance voice data;

[0010] Timer, used to send timing signals to MCU at regular intervals;

[0011] MCU, used for logic control and calculation, including: processing various signals / data and forwarding them; and, according to the timing signal, regularly sending a propaganda and learning signal to the processing system; after the processing system responds to the propaganda and learning signal and feeds back the propaganda voice data of the corresponding behavior, forwarding the propaganda voice data to the voice module for broadcasting;

[0012] Power supply, used for power supply;

[0013] The acceleration sensor, voice module, timer and power supply are electrically connected to the MCU respectively;

[0014] The processing system is communicatively connected with the MCU.

[0015] As an optional implementation scheme of the present application, optionally, the fall education module further includes:

[0016] The missionary memory is used for data storage, including: missionary voice data of different behaviors;

[0017] The teaching memory is communicatively connected to the processing system.

[0018] As an optional embodiment of the present application, optionally, the processing system is also used for:

[0019] When it is determined that the patient has fallen, an alarm signal is generated and sent to the MCU;

[0020] The MCU is further used to: forward the alarm signal to the alarm device for broadcasting;

[0021] The alarm is electrically connected to the MCU.

[0022] As an optional embodiment of the present application, optionally, the processing system comprises:

[0023] CPU, used for data processing and transmission;

[0024] A fall behavior monitoring module is used to monitor whether the acceleration value reaches a preset fall value: if it reaches, it is determined that the patient has a fall behavior, and a feedback is sent to the education measure calling module through the CPU; otherwise, it does not occur;

[0025] The education measure retrieval module is used to retrieve the education voice data of the corresponding behavior from the education memory after receiving the feedback from the fall behavior monitoring module, and feed it back to the voice chip through the CPU;

[0026] A voice chip is used to analyze the teaching voice data, generate a number of teaching voice segments in an orderly manner, and feed them back to the behavior guidance module through the CPU;

[0027] A behavior guidance module, used for sending the preaching voice clips to the MCU in an orderly manner;

[0028] The falling behavior monitoring module, the education measure calling module, the voice chip and the behavior guiding module are respectively connected to the CPU for communication.

[0029] As an optional implementation scheme of the present application, optionally, the processing system responds to the teaching and learning signal and feeds back teaching voice data corresponding to the behavior, including:

[0030] The CPU receives the teaching and learning signal and responds, notifying the teaching measure calling module to randomly call the teaching voice data of the corresponding behavior from the teaching memory, and the CPU feeds back the teaching voice data of the corresponding behavior to the CPU.

[0031] As an optional implementation scheme of the present application, optionally, the fall education module further includes:

[0032] The 5G module is used for base station communication, including: when the MCU receives the alarm signal, the alarm signal is reported to a nearby base station; the base station scans nearby patients, and if the fall education module on the wristband worn by the nearby patient receives the alarm signal, the base station forwards the alarm signal to the nearby patient, and the 5G module in the fall education module receives the alarm signal, and then forwards it to the MCU; the MCU processes the alarm signal and sends it to the alarm in its wristband to alarm, reminding the nearby patient that someone has fallen nearby and please go to rescue;

[0033] The 5G module is electrically connected to the CPU.

[0034] On the other hand, the present application proposes an application method of the smart anti-fall reminder bracelet based on behavior assessment reminder, comprising the following steps:

[0035] The patient wears the bracelet and activates the bracelet's falls education module;

[0036] The acceleration sensor collects the acceleration value of the corresponding patient in real time and forwards it to the processing system through the MCU;

[0037] The processing system monitors whether the acceleration value has a preset change value: if it does, it is determined that the patient has a fall behavior, generates corresponding fall guidance voice data, and forwards the fall guidance data to the voice module through the MCU;

[0038] The voice module plays the fall guidance voice data;

[0039] The timer sends a timing signal to the MCU regularly;

[0040] The MCU sends a propaganda and learning signal to the processing system at a fixed time according to the timing signal; after the processing system responds to the propaganda and learning signal and feeds back the propaganda voice data of the corresponding behavior, the propaganda voice data is forwarded to the voice module for broadcasting.

[0041] In another aspect, the present application further provides an electronic device, comprising:

[0042] processor;

[0043] a memory for storing processor-executable instructions;

[0044] Wherein, the processor is configured to implement the application method when executing the executable instructions.

[0045] Technical effects of the present invention:

[0046] Based on the implementation of the present invention, the present invention can perform anti-fall monitoring and education through a bracelet. The bracelet is integrated with a fall education module, which combines fall monitoring, behavior analysis, education measures retrieval, voice broadcast, alarm and other functions, and can carry out anti-fall education for patients, which can be triggered regularly. At the same time, it can monitor whether the patient falls. If the patient falls, the alarm is triggered and the corresponding rescue measures voice is played to guide the patient to save himself. Education can also be carried out regularly at ordinary times, so that patients can learn the anti-fall education knowledge of various behaviors to enhance the patient's anti-fall awareness.

[0047] In addition, after a patient falls, the module of the present invention can communicate with the base station to seek help from other nearby patients, and can send an alarm signal to other nearby patients to seek help, thereby reducing the risk of the current patient not receiving help for a long time due to the fall.

[0048] Further features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.

[0050] Figure 1 It is a schematic diagram of the application structure of the wristband of the present invention;

[0051] Figure 2 It is a schematic diagram showing the composition of the control system of the fall education module of the present invention;

[0052] Figure 3 It is a schematic diagram showing the composition of the processing system of the present invention;

[0053] Figure 4 A schematic diagram showing the application composition of the fall education module of the present invention for base station communication;

[0054] Figure 5 Shown is a schematic diagram of the application of the electronic device of the present invention. DETAILED DESCRIPTION

[0055] Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0056] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0057] In addition, in order to better illustrate the present disclosure, numerous specific details are given in the following specific embodiments. It should be understood by those skilled in the art that the present disclosure can also be implemented without certain specific details. In some examples, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the main purpose of the present disclosure.

[0058] Example 1

[0059] like Figure 1 As shown, on the one hand, the present application proposes a smart anti-fall reminder bracelet based on behavior assessment reminders, including a bracelet body and a fall education module arranged on the bracelet body.

[0060] The bracelet body can directly adopt and refer to the surgical main body structure of the existing smart bracelet, and this embodiment does not limit it.

[0061] The fall education module integrates various electronic facilities, control chips, processing chips, etc. required for the control circuit. The present embodiment does not limit the selection of various electronic devices and chips. For example, the MCU can be an STM32 single-chip control chip, and the CPU chip can be various microprocessor chips. The corresponding hardware facilities can be configured by the user. As for the software program, please embed it in combination with the control and processing logic of the present invention.

[0062] The following will describe in detail the service functions of the fall education module of the present invention.

[0063] As attached Figure 2 As shown, the fall education module includes:

[0064] The acceleration sensor is used to collect the acceleration value of the corresponding patient in real time and forward it to the processing system through the MCU; it can sense and detect the acceleration value. When the patient falls, the acceleration value increases. Therefore, the system can determine whether the patient falls according to the change of the patient's acceleration value, such as the acceleration changes from 0 to 3.0m / s 2 ;

[0065] The processing system is used to monitor whether the acceleration value has a preset change value: if it does, it is determined that the patient has a fall behavior, and the corresponding fall guidance voice data is generated, and the fall guidance data is forwarded to the voice module through the MCU; the processing system has its own data processing capabilities, can perform data calculation and judgment based on the CPU, can communicate with the MCU, perform relevant data processing and behavior judgment, and can retrieve the fall guidance voice data of the corresponding behavior from the database (the present embodiment is the education memory) when a fall is found, and after processing the fall guidance voice data, it is forwarded to the MCU To the voice module for voice broadcast, so as to guide the patient how to save himself after falling by voice broadcast; here, the fall guidance voice data is configured and saved in advance by the administrator, and the fall guidance voice data includes several teaching voice segments of the guidance steps, and the teaching voice segments are specific guidance voice data for each step, such as the teaching voice segment 1 represents the voice data of "checking for injuries after falling"; these teaching voice segments can be saved in order in advance, and the processor can retrieve, process and issue the teaching data of the behavior according to the detection results; the specific guidance voice is configured by the administrator, and this embodiment is not limited;

[0066] The voice module is used to play the fall guidance voice data; the hardware of the voice module mainly includes microphone, audio processor (or voice processor), digital signal processor (DSP), memory and interface circuit, etc.: the microphone is used to capture sound signals and convert them into electrical signals; the audio processor is responsible for pre-processing such as amplification and filtering to improve the quality of voice signals; DSP is the core of the voice module and is responsible for executing complex voice processing algorithms such as voice recognition and voice synthesis; the memory is used to store voice data and processing results; the interface circuit is responsible for connecting the voice module with other hardware or systems to realize data input and output. These hardware components work together to form the basic architecture of the voice module; the specific options are configured by yourself;

[0067] The timer is used to send a timing signal to the MCU at regular intervals; if the processing system detects a patient fall and retrieves voice data for passive guidance, the purpose of the timer is to actively guide learning; the timer sends a timing signal to the MCU at a preset frequency, and after reaching the learning time point, notifies the MCU to start the education learning mode (sends a signal to notify the MCU, and after receiving the signal, the MCU requests the corresponding education voice data from the processing system and forwards it to the voice module for broadcasting, and regularly plays the fall education voice for patients to learn); it is sent every 1-3 hours, for example, to conduct education learning at regular intervals;

[0068] MCU, used for logic control and calculation, including: processing various signals / data and forwarding them; and, according to the timing signal, regularly sending a propaganda and learning signal to the processing system; after the processing system responds to the propaganda and learning signal and feeds back the propaganda voice data of the corresponding behavior, the propaganda voice data is forwarded to the voice module for broadcasting; during the interactive process of data transmission, the microcontroller unit (MCU) will send a clear request to the processing system, which is intended to obtain the required data; this request is usually sent through a predefined communication protocol or interface, such as SPI, I2C, UART, etc., to ensure the accuracy and efficiency of data transmission; the request contains an identification or request for specific data The request type is set so that the processing system can identify and respond to the specific needs of the MCU; after receiving this request, the processing system will parse its content, retrieve or calculate the corresponding data, and return the result to the MCU through the same communication channel. The whole process realizes effective data exchange between the MCU and the processing system; please configure the specific communication port between the MCU and the processing system in combination with the selected chip type, such as the communication port of the single-chip microcomputer; the processing system responds to the request of the MCU and can retrieve the corresponding behavior education data from the education memory (it can be retrieved according to the range of the detected acceleration change value, divided into different stages / gears of fall education, such as acceleration changes from 0 to 1.5m / s 2 , retrieve the education data of the gear, etc., so as to achieve different degrees of anti-fall education and rescue); if it is in the active learning process, the processing system can randomly retrieve the education voice data and forward it to the MCU for random learning, so as to improve the patient's random learning ability for anti-fall and improve the patient's flexible adaptability;

[0069] Power source, used for power supply; it can be powered by lithium batteries or the like;

[0070] The acceleration sensor, voice module, timer and power supply are electrically connected to the MCU respectively;

[0071] The processing system is communicatively connected with the MCU.

[0072] As an optional implementation scheme of the present application, optionally, the fall education module further includes:

[0073] The missionary memory is used for data storage, including: missionary voice data of different behaviors;

[0074] The teaching memory is communicatively connected to the processing system.

[0075] The memory can be connected to the CPU through USB or the like.

[0076] As an optional embodiment of the present application, optionally, the processing system is also used for:

[0077] When it is determined that the patient has fallen, an alarm signal is generated and sent to the MCU;

[0078] The MCU is further used to: forward the alarm signal to the alarm device for broadcasting;

[0079] The alarm is electrically connected to the MCU.

[0080] The present invention can also alarm. The MCU can control the alarm to sound an alarm according to the alarm signal generated by the processing system, so as to remind family members or medical staff in the hospital or other patients to provide rescue. The alarm can be a buzzer with positioning. After receiving the alarm control command from the MCU, it automatically sends an alarm positioning to the background and buzzes at the same time (it can also be a separate buzzer alarm); or it can be an indicator alarm. For example, if someone falls at night, the indicator light can flash to prompt other personnel to locate and rescue.

[0081] As attached Figure 3 As shown, as an optional embodiment of the present application, optionally, the processing system includes:

[0082] CPU, used for data processing and transmission;

[0083] A fall behavior monitoring module is used to monitor whether the acceleration value reaches a preset fall value: if it reaches, it is determined that the patient has a fall behavior, and a feedback is sent to the education measure calling module through the CPU; otherwise, it does not occur;

[0084] The education measure retrieval module is used to retrieve the education voice data of the corresponding behavior from the education memory after receiving the feedback from the fall behavior monitoring module, and feed it back to the voice chip through the CPU;

[0085] A voice chip is used to analyze the teaching voice data, generate a number of teaching voice segments in an orderly manner, and feed them back to the behavior guidance module through the CPU;

[0086] A behavior guidance module, used for sending the preaching voice clips to the MCU in an orderly manner;

[0087] The falling behavior monitoring module, the education measure calling module, the voice chip and the behavior guiding module are respectively connected to the CPU for communication.

[0088] As mentioned above, when it is found that the change value of the patient's acceleration reaches the preset range value, the fall behavior monitoring module determines that the patient has fallen, and confirms the "education gear" according to the current patient's acceleration change value, and notifies the education measure retrieval module to retrieve the "education voice data" of the corresponding gear. The education measure retrieval module retrieves the education voice data of the corresponding gear from the education storage device (database) according to the gear, and feeds it back to the voice chip.

[0089] The propaganda voice data of each gear stored in the propaganda memory (database) can save the corresponding relationship for easy retrieval.

[0090] After receiving the voice data, the voice chip will perform a series of complex processing steps to parse and divide the data into several voice segments. First, the chip will use the internal digital signal processor (DSP) or similar computing unit to pre-process the input voice signal, including noise removal, gain control, etc., to improve the purity and recognizability of the voice data.

[0091] Next, the chip uses one of the key technologies in speech recognition technology, endpoint detection, to determine the starting and ending points of the voice signal (in this embodiment, the endpoints corresponding to each step are set by the administrator and can be directly detected by the voice chip). This step is very critical because it helps the chip separate the segments that actually contain voice information from the continuous audio stream and remove the silence or background noise.

[0092] After determining the boundaries of the speech segments, the chip will further extract features from these segments. This usually involves converting the speech signal into a series of parameters or vectors that can represent its characteristics, such as Mel-frequency cepstral coefficients (MFCC), linear prediction coefficients (LPC), etc. These feature vectors are the basis for subsequent speech recognition or processing steps. The chip will classify, identify or further process the speech segments based on these feature vectors and pre-trained models or algorithms. This may involve a variety of application scenarios such as matching with predefined keywords, parsing voice commands, and recognizing emotions.

[0093] Throughout the process, voice chips need to efficiently process large amounts of data and find a balance between real-time performance, accuracy, and resource consumption. Therefore, voice chips often use advanced algorithm optimization, hardware acceleration, and power management technologies to improve performance and reduce power consumption.

[0094] Therefore, after processing the voice data, the CPU communicates with the MCU, and the behavior guidance module sends the teaching voice segments (forwarded by the CPU) to the MCU in order. After forwarding by the MCU, the voice module will play each teaching voice segment in order.

[0095] After processing data, signals or instructions, the CPU interacts with the microcontroller unit (MCU). This interaction is usually achieved through specific interfaces and protocols, allowing the CPU to pass processing results or new instructions to the MCU so that the MCU can further perform related control or data processing tasks. After receiving information from the CPU, the MCU will perform corresponding operations according to its internal logic and program, and may pass the results back to the CPU or other related devices. This interaction is a common operating mode in many modern electronic devices and systems, ensuring the coordination and efficient operation of different components. In the interaction between the CPU and the MCU, the transmission of data, signals or instructions often depends on precise timing control and reliable data transmission protocols. As the central processor, the CPU is responsible for overall data processing, logical judgment and instruction control, while the MCU focuses on performing specific control tasks, such as motor driving, sensor data reading or peripheral management. The CPU is also able to forward data.

[0096] In order to ensure seamless collaboration between the CPU and the MCU, a complete communication mechanism is usually designed. This includes defining the interface type (such as SPI, I2C, UART, etc.), communication rate, data format, and error detection and correction strategy used when the two parties communicate. Through these mechanisms, the CPU can efficiently send data, instructions, or control signals to the MCU, and the MCU can accurately receive and parse this information and then perform corresponding operations.

[0097] In addition, in order to improve the flexibility and scalability of the system, the interaction between the CPU and the MCU may also support dynamic configuration and parameter adjustment. This means that the CPU can dynamically change the communication parameters or control logic with the MCU according to the actual operation and needs of the system to adapt to different application scenarios and environmental changes.

[0098] With the rapid development of technologies such as the Internet of Things and artificial intelligence, the interaction between CPUs and MCUs is becoming more complex and diverse. For example, in a smart home system, the CPU may need to interact with multiple MCUs to achieve coordinated control of different devices; in the field of industrial automation, the interaction between CPUs and MCUs may need to meet higher real-time and reliability requirements.

[0099] In this embodiment, the chip models of the CPU and the MCU are not limited in this embodiment. The communication connection configuration can be connected according to the communication link mode supported by the selected chip, which can be completed by the technician.

[0100] As an optional implementation scheme of the present application, optionally, the processing system responds to the teaching and learning signal and feeds back teaching voice data corresponding to the behavior, including:

[0101] The CPU receives the teaching and learning signal and responds, notifying the teaching measure calling module to randomly call the teaching voice data of the corresponding behavior from the teaching memory, and the CPU feeds back the teaching voice data of the corresponding behavior to the CPU.

[0102] As attached Figure 4 As shown, as an optional implementation scheme of the present application, optionally, the fall education module further includes:

[0103] The 5G module is used for base station communication, including: when the MCU receives the alarm signal, the alarm signal is reported to a nearby base station; the base station scans nearby patients, and if the fall education module on the wristband worn by the nearby patient receives the alarm signal, the base station forwards the alarm signal to the nearby patient, and the 5G module in the fall education module receives the alarm signal, and then forwards it to the MCU; the MCU processes the alarm signal and sends it to the alarm in its wristband to alarm, reminding the nearby patient that someone has fallen nearby and please go to rescue;

[0104] The 5G module is electrically connected to the CPU.

[0105] Using 5G base station communication technology to find nearby users and communicate first relies on the high speed, low latency and large capacity characteristics of the 5G network. When devices are connected to the 5G network, the base station will identify and manage the connection status of these devices.

[0106] In this embodiment, the 5G module is only one type of wireless communication, and may also be a wireless communication module such as WiFi, Bluetooth, etc.

[0107] To find nearby users, base stations collect signal information from devices within their coverage area, including device identification, location estimates (possibly through GPS, base station positioning technology, or network signal strength, etc.), and their current communication status. This information is processed at the base station level and may be further transmitted to a higher-level network management system for more extensive resource allocation and scheduling.

[0108] When it is necessary to communicate with nearby users, the device initiating the communication will send a request to the base station, and the base station will select the appropriate communication path and parameters based on the current network conditions, resource allocation, and the location and status information of the target user. This includes determining which frequency, modulation method, coding scheme, etc. to use to ensure the reliability and efficiency of communication.

[0109] In 5G networks, due to support for higher spectrum efficiency and more flexible network architecture, direct communication between devices (such as D2D, Device-to-Device) can be more easily achieved, which further enhances the ability to find and communicate with nearby users. However, this direct communication usually requires devices to be able to discover each other and establish connections, which may require additional protocols and mechanisms to support.

[0110] Using 5G base station communication technology to find nearby users and communicate is a complex process involving multiple levels of technology and protocols. As 5G technology continues to develop and improve, we have reason to believe that this capability will become more efficient and reliable.

[0111] In the present invention, the base station (home base station) can be deployed in a hospital or in a community, etc., for patient communication "within the hospital (within a certain range)".

[0112] Take Patient 1 and Patient 2 who are active in the community / hospital as an example:

[0113] Several low-power base stations are deployed in the hospital, and the communication background records, manages and forwards the communication signals reported by the base stations. For details, please refer to the existing working mode of mobile 5G communication.

[0114] The bracelets worn by each patient perform 5G data communication through the 5G module on it, and can communicate with other patients based on the base station network.

[0115] When the alarm signal is received by the MCU of patient 1, the alarm signal is reported to a nearby base station; the base station scans nearby patients, and if the fall education module on the wristband worn by the nearby patient 2 receives the alarm signal, the base station forwards the alarm signal to the nearby patient 2, and the 5G module in the fall education module receives it, and then forwards it to the MCU; the MCU processes the alarm signal and sends it to the alarm in its wristband to alert the nearby patient 2, reminding the nearby patient 2 that someone nearby (patient 1) has fallen, please go to rescue. In this way, it is possible to try to find the nearby patient 2, give him an alarm and rescue reminder, and remind him that the nearby patient 1 has fallen. When the patient 1 sends out an alarm signal, the alarm signal can also carry the basic information of the patient 1, such as the name, etc., to facilitate the patient 2 to locate and rescue (generally speaking, the patient 2 knows the name of the patient 1 and can probably know his activity area, so he can go to rescue).

[0116] The present invention mainly performs small-scale communication, and a home base station can be used for small-scale communication interaction. The communication positioning of the home base station mainly relies on the technical principle of the mobile communication network, and determines the user's location through the signal interaction between the base station and the user equipment. Deploying base stations for positioning in a home environment is usually to provide more accurate and personalized location services, especially in indoor environments.

[0117] Home base stations, also known as small base stations or micro base stations, are small devices used to provide wireless coverage in mobile communication networks. They can be deployed in indoor environments such as homes, offices or small commercial places to improve signal coverage and enhance communication quality. When home base stations communicate with user devices (such as mobile phones, tablets, etc.), positioning can be achieved through a variety of technical means.

[0118] A common positioning method is to use the signal transmission characteristics between the base station and the user equipment. Specifically, the base station can measure the arrival time (TOA) or arrival time difference (TDOA) of the signal sent by the user equipment, and calculate the approximate location of the user equipment through algorithms such as triangulation positioning in combination with the geographical location information of the base station. This method does not require the user equipment to have independent positioning capabilities such as GPS, but the positioning accuracy is affected by many factors such as the distribution of base stations and the signal transmission environment.

[0119] In addition, home base stations can also be combined with other positioning technologies to improve positioning accuracy and reliability. For example, multiple Wi-Fi access points can be deployed in a home environment in combination with Wi-Fi positioning technology, and the location of user devices can be estimated by measuring the signal strength of different Wi-Fi access points. In addition, indoor positioning technologies such as Bluetooth and RFID can be used to provide users with more accurate location services.

[0120] Obviously, those skilled in the art should understand that the implementation of all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above-mentioned embodiments. Those skilled in the art can understand that the implementation of all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above-mentioned embodiments. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory (Flash Memory), a hard disk (Hard Disk Drive, abbreviated: HDD) or a solid-state drive (SSD), etc.; the storage medium can also include a combination of the above-mentioned types of memory.

[0121] Example 2

[0122] Based on the implementation principle of Example 1, on the other hand, the present application proposes an application method of the smart anti-fall reminder bracelet based on behavior assessment reminder, comprising the following steps:

[0123] The patient wears the bracelet and activates the bracelet's falls education module;

[0124] The acceleration sensor collects the acceleration value of the corresponding patient in real time and forwards it to the processing system through the MCU;

[0125] The processing system monitors whether the acceleration value has a preset change value: if it does, it is determined that the patient has a fall behavior, generates corresponding fall guidance voice data, and forwards the fall guidance data to the voice module through the MCU;

[0126] The voice module plays the fall guidance voice data;

[0127] The timer sends a timing signal to the MCU regularly;

[0128] The MCU sends a propaganda and learning signal to the processing system at a fixed time according to the timing signal; after the processing system responds to the propaganda and learning signal and feeds back the propaganda voice data of the corresponding behavior, the propaganda voice data is forwarded to the voice module for broadcasting.

[0129] The specific implementation principles of the above steps can be understood and implemented in conjunction with Example 1, and will not be repeated in this example.

[0130] As for the application steps and procedures recorded in other Embodiment 1, this embodiment does not elaborate on them, and please refer to the description of Embodiment 1.

[0131] The modules or steps of the present invention described above can be implemented by a general-purpose computing system, they can be concentrated on a single computing system, or distributed on a network composed of multiple computing systems, and optionally, they can be implemented by a program code executable by a computing system, so that they can be stored in a storage system and executed by the computing system, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0132] Example 3

[0133] As attached Figure 5 As shown, further, in another aspect, the present application also proposes an electronic device, including:

[0134] processor;

[0135] a memory for storing processor-executable instructions;

[0136] Wherein, the processor is configured to implement the application method described in Example 2 when executing the executable instructions.

[0137] The electronic device of the embodiment of the present disclosure includes a processor and a memory for storing instructions executable by the processor, wherein the processor is configured to implement the application method described in the above embodiment 2 when executing the executable instructions.

[0138] Here, it should be noted that the number of processors can be one or more. At the same time, the electronic device of the embodiment of the present disclosure may also include an input system and an output system. Among them, the processor, memory, input system and output system may be connected through a bus or in other ways, which are not specifically limited here.

[0139] The memory is a computer-readable storage medium that can be used to store software programs, computer executable programs, and various modules, such as the program or module corresponding to the application method of the embodiment of the present disclosure. The processor executes various functional applications and data processing of the electronic device by running the software programs or modules stored in the memory.

[0140] The input system can be used to receive input numbers or signals. The signal can be a key signal related to user settings and function control of the device / terminal / server. The output system can include display devices such as display screens.

[0141] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A smart anti-fall reminder bracelet based on behavioral assessment reminders, It is characterized in that The invention comprises a wristband body and a fall education module arranged on the wristband body, wherein the fall education module comprises: Acceleration sensor, used to collect the acceleration value of the corresponding patient in real time and forward it to the processing system through MCU; The processing system is used to monitor whether the acceleration value has a preset change value: if it does, it is determined that the patient has a fall behavior, and corresponding fall guidance voice data is generated, and the fall guidance data is forwarded to the voice module through the MCU; A voice module, used for playing the fall guidance voice data; Timer, used to send timing signals to MCU at regular intervals; MCU, used for logic control and calculation, including: processing various signals / data and forwarding them; and, according to the timing signal, regularly sending a propaganda and learning signal to the processing system; after the processing system responds to the propaganda and learning signal and feeds back the propaganda voice data of the corresponding behavior, forwarding the propaganda voice data to the voice module for broadcasting; Power supply, used for power supply; The acceleration sensor, voice module, timer and power supply are electrically connected to the MCU respectively; The processing system is communicatively connected with the MCU.

2. According to claim 1, the smart anti-fall reminder bracelet based on behavior assessment reminder, It is characterized in that The fall education module also includes: The missionary memory is used for data storage, including: missionary voice data of different behaviors; The teaching memory is communicatively connected to the processing system.

3. According to claim 1, the smart anti-fall reminder bracelet based on behavior assessment reminder, It is characterized in that The processing system is also used for: When it is determined that the patient has fallen, an alarm signal is generated and sent to the MCU; The MCU is further used to: forward the alarm signal to the alarm device for broadcasting; The alarm is electrically connected to the MCU.

4. According to claim 1, the smart anti-fall reminder bracelet based on behavior assessment reminder, It is characterized in that The processing system comprises: CPU, used for data processing and transmission; A fall behavior monitoring module is used to monitor whether the acceleration value reaches a preset fall value: if so, it is determined that the patient has a fall behavior, and a feedback is sent to the education measure calling module through the CPU; otherwise, it does not occur; The education measure retrieval module is used to retrieve the education voice data of the corresponding behavior from the education memory after receiving the feedback from the fall behavior monitoring module, and feed it back to the voice chip through the CPU; A voice chip is used to analyze the teaching voice data, generate a number of teaching voice segments in an orderly manner, and feed them back to the behavior guidance module through the CPU; A behavior guidance module, used for sending the preaching voice clips to the MCU in an orderly manner; The falling behavior monitoring module, the education measure calling module, the voice chip and the behavior guiding module are respectively connected to the CPU for communication.

5. According to claim 4, the smart anti-fall reminder bracelet based on behavior assessment reminder, It is characterized in that The processing system responds to the teaching and learning signal and feeds back teaching voice data corresponding to the behavior, including: The CPU receives the teaching and learning signal and responds, notifying the teaching measure calling module to randomly call the teaching voice data of the corresponding behavior from the teaching memory, and the CPU feeds back the teaching voice data of the corresponding behavior to the CPU.

6. According to claim 3, the smart anti-fall reminder bracelet based on behavior assessment reminder, It is characterized in that The fall education module also includes: The 5G module is used for base station communication, including: when the MCU receives the alarm signal, the alarm signal is reported to a nearby base station; the base station scans nearby patients, and if the fall education module on the wristband worn by the nearby patient receives the alarm signal, the base station forwards the alarm signal to the nearby patient, and the 5G module in the fall education module receives the alarm signal, and then forwards it to the MCU; the MCU processes the alarm signal and sends it to the alarm in its wristband to alarm, reminding the nearby patient that someone has fallen nearby and please go to rescue; The 5G module is electrically connected to the CPU.

7. An application method of the smart anti-fall reminder bracelet based on behavior assessment reminder as described in any one of claims 1 to 6, It is characterized in that The steps include: The patient wears the bracelet and activates the bracelet's falls education module; The acceleration sensor collects the acceleration value of the corresponding patient in real time and forwards it to the processing system through the MCU; The processing system monitors whether the acceleration value has a preset change value: if it does, it is determined that the patient has a fall behavior, generates corresponding fall guidance voice data, and forwards the fall guidance data to the voice module through the MCU; The voice module plays the fall guidance voice data; The timer periodically sends a timing signal to the MCU; The MCU sends a propaganda and learning signal to the processing system at a fixed time according to the timing signal; after the processing system responds to the propaganda and learning signal and feeds back the propaganda voice data of the corresponding behavior, the propaganda voice data is forwarded to the voice module for broadcasting.

8. Electronic equipment, It is characterized in that include: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to implement the application method described in claim 7 when executing the executable instructions.

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