Data Processing System

Abstract

We provide a necklace-type terminal and data processing system for collecting users' biometric data. [Solution] The necklace-type terminal includes a camera that photographs the wearer's surroundings, a sensor that detects the wearer's biometric data, a microphone, and a collection unit that collects the outputs of the camera, the sensor, and the microphone. In addition to a reactive function (normal identification processing), in order to more effectively protect the health of the user 20, it is equipped with a proactive intervention function that predicts risks before abnormalities occur and intervenes early, and a learning function that learns the user 20's past data and behavioral patterns (predictive mode identification processing), enabling responses tailored to each individual user 20.

Description

Technical Field

[0001] The technology of the present disclosure relates to a data processing system.

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the prior art, there is room for improvement in collecting users' biological data.

Means for Solving the Problems

[0005] A first aspect of the technology of the present disclosure is a data processing system comprising: a wearable device equipped with a sensor for detecting the wearer's biometric data and surrounding environmental data; and a data processing device that receives output data from the sensor and prompts requesting a response regarding the wearer's health status based on the output data, wherein the data processing device includes a proactive intervention processing unit that analyzes the output data from the sensor to predict a risk score regarding the wearer's health status and sets warning data according to the degree of risk; and a providing unit that provides the warning data set by the proactive intervention processing unit to the wearer via the wearable device as a response to the prompt.

[0006] A second aspect of the technology of the present disclosure is characterized in that, in the data processing system of the first aspect, the sensor for detecting the biological data includes at least one of a heart rate sensor, a blood pressure sensor, a blood oxygen sensor, a body temperature sensor, and a respiratory pattern sensor, and the sensor for detecting the environmental data includes at least one of a position sensor, a temperature sensor, and a humidity sensor.

[0007] A third aspect of the technology of this disclosure is characterized in that, in the data processing system of the first or second aspect, the data processing device further has a database that stores historical data including the wearer's biometric data and behavioral pattern data, and the proactive intervention processing unit uses the output data from the sensor and the historical data stored in the database in combination to obtain a response regarding the wearer's health status.

[0008] A fourth aspect of the technology of this disclosure is characterized in that, in any one of the data processing systems of the first to third aspects, the prompt is generated as a result of the execution of a predictive mode identification process based on numerical determination of the wearer's voice data input from a microphone provided on the wearable device, or the output data of the sensor.

[0009] A fifth aspect of the technology of this disclosure is characterized in that, in any one of the first to fourth aspects of the data processing system, the wearable device further includes a speaker that outputs a response provided by the providing unit.

[0010] A sixth aspect of the technology of this disclosure is characterized in that, in any one of the data processing systems of the first to fifth aspects, when the response indicates an abnormality in health status, all relevant data is automatically stored and further analyzed or provided to a medical institution. [Brief explanation of the drawing]

[0011] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the main functions of a data processing device and a necklace-type terminal according to the first embodiment. [Figure 3] This is a side view showing the configuration of a necklace-type terminal according to the first embodiment. [Figure 4] This is a top view showing the configuration of a necklace-type terminal according to the first embodiment. [Figure 5] The functional configuration of the control unit of the necklace-type terminal according to the first embodiment is schematically shown. [Figure 6] The functional configuration of the specific processing unit of the data processing device according to the first embodiment is schematically shown. [Figure 7] An example of the operation flow of a specific process by the data processing device according to the first embodiment is schematically shown. [Figure 8] The functional configuration of the specific processing unit of the data processing device according to the second embodiment is schematically shown. [Figure 9] An example of the operation flow of a specific process by the data processing device according to the second embodiment is schematically shown. [Figure 10] Figure 9 is a subroutine flowchart showing the details of step S303. [Modes for carrying out the invention]

[0012] Hereinafter, an example of an embodiment of a data processing apparatus, a data processing method, and a program according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0013] First, the terms used in the following description will be explained.

[0014] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), or an APU (Accelerated Processing Unit), etc.

[0015] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0016] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0017] In the following embodiments, the communication I / F (Interface) with a reference sign is an interface including a communication processor, an antenna, and the like. The communication I / F manages communications between a plurality of computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0018] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

[0019] (First Embodiment) FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0020] As shown in FIG. 1, the data processing system 10 includes a data processing device 12 and a necklace-type terminal 14. An example of the data processing device 12 is a server. In the first embodiment,

[0021] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of the "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32; the processor 28, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are connected to the bus 34. The communication I / F is connected to a network 53. Examples of the network 53 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0022] The necklace-type terminal 14 includes a computer 36, a microphone 38, a sensor 39, a speaker 40, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 38, speaker 40, and camera 42 are also connected to the bus 52.

[0023] The user 20 wearing the necklace-type terminal 14 may be, for example, a patient whose health condition is being diagnosed, or a regular user 20.

[0024] The microphone 38 collects the voice emitted by the user 20, who is wearing the necklace-type terminal 14, as well as sounds around the user 20. The microphone 38 also receives instructions from the user 20 by receiving the voice emitted by the user 20. The microphone 38 captures the voice emitted by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 40 outputs audio according to the instructions from the processor 46. The speaker 40 is, for example, a directional speaker and outputs audio towards the user 20's ears.

[0025] Sensor 39 is a sensor that detects biometric data of user 20, who is wearing the necklace-type terminal. For example, sensor 39 includes at least one of a heart rate sensor, a blood pressure sensor, a blood oxygen sensor, a body temperature sensor, and a respiratory pattern sensor.

[0026] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0027] Communication interface 44 is connected to network 53. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 53.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the necklace-type terminal 14.

[0029] As shown in Figure 2, in the data processing device 12, specific processing is performed by the processor 28. The storage 32 stores a specific processing program 56. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores the data generation model 58. The data generation model 58 is used by the specific processing unit 290. The storage 32 also includes a data storage unit 54.

[0031] In the necklace-type terminal 14, data acquisition processing is performed by the processor 46. The storage 50 stores the data acquisition program 60. The processor 46 reads the data acquisition program 60 from the storage 50 and executes the read data acquisition program 60 on the RAM 48. The data acquisition processing is realized by the processor 46 operating as a control unit 46A according to the data acquisition program 60 executed on the RAM 48.

[0032] As shown in Figures 3 and 4, the necklace-type terminal 14 includes multiple microphones 38, multiple sensors 39, multiple speakers 40, and multiple cameras 42. Figures 3 and 4 show an example where two microphones 38 are positioned in front of the user 20 (see Figure 1) when the user 20 wears the necklace-type terminal 14. They also show an example where two sensors 39 are positioned to the right and left of the user 20 when the user 20 wears the necklace-type terminal 14. They also show an example where two speakers 40 are positioned to the right rear and left rear of the user 20 when the user 20 wears the necklace-type terminal 14. They also show an example where two cameras 42 are positioned to the right front and left front of the user 20 when the user 20 wears the necklace-type terminal 14. Finally, they show an example where two sensors 39 are positioned inside the necklace-type terminal 14 so as to contact the user 20's neck when the user 20 wears the necklace-type terminal 14.

[0033] Next, the processing performed by the control unit 46A shown in Figure 2 when the necklace-type terminal 14 performs data collection processing will be explained in detail with reference to Figure 5.

[0034] In the data collection process of the first embodiment, the user 20's biometric data is collected in real time. In addition to biometric data, all surrounding environment data of the user 20 is also collected. This makes it possible to detect early signs of conditions such as Alzheimer's disease and dementia. It also allows for monitoring of the user 20's health status (e.g., heart disease).

[0035] As shown in Figure 5, the control unit 46A includes a data acquisition unit 100 and a communication unit 102.

[0036] The data acquisition unit 100 collects the outputs of the microphone 38, sensor 39, and camera 42, respectively.

[0037] The communication unit 102 transmits the outputs of the microphone 38, sensor 39, and camera 42, which are collected by the data acquisition unit 100, to the data processing unit 12.

[0038] Next, the processing of the specific processing unit 290 shown in Figure 2, when the data processing device 12 performs specific processing to acquire a response corresponding to user utterance, will be explained in detail with reference to Figure 6.

[0039] In the specific processing of the first embodiment, a response corresponding to the user utterance picked up by the microphone 38 of the necklace-type terminal 14 is obtained using the data generation model 58.

[0040] As shown in Figure 6, the specific processing unit 290 includes an input unit 292, a processing unit 294, and an output unit 296.

[0041] The input unit 292 stores the outputs of the microphone 38, sensor 39, and camera 42, received from the necklace-type terminal 14, in the data storage unit 54 (see Figure 2).

[0042] The input unit 292 acquires user utterances received by the necklace-type terminal 14. Specifically, it acquires user utterances picked up by the microphone 38 of the necklace-type terminal 14.

[0043] The processing unit 294 performs specific processing using the data generation model 58 (see Figure 2). Specifically, it inputs a prompt including user utterance to the data generation model 58 and obtains a generation result. At this time, the outputs of the sensor 39 and camera 42 collected by the data acquisition unit 100 may also be included in the prompt.

[0044] The output unit 296 transmits the result of the specific processing to the necklace-type terminal 14. In the necklace-type terminal 14, the control unit 46A causes the speaker 40 to output the result of the specific processing. In this way, a response corresponding to the user utterance picked up by the microphone 38 is output to the user 20 by the speaker 40. The microphone 38 further acquires the user utterance in response to the result of the specific processing. The control unit 46A transmits the audio data indicating the user utterance acquired by the microphone 38 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the user utterance.

[0045] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0046] The outputs of the microphone 38, sensor 39, and camera 42 stored in the data storage unit 54 are used, for example, to diagnose the health status of user 20. In this case, the outputs of the microphone 38, sensor 39, and camera 42 stored in the data storage unit 54 may be transmitted to a terminal on the medical institution's side. Alternatively, the data processing device 12 may analyze the outputs of the microphone 38, sensor 39, and camera 42 stored in the data storage unit 54 to diagnose the health status of user 20.

[0047] Next, we will explain the operation of the data processing system 10. First, we will describe an example of the data collection process flow.

[0048] When user 20 is wearing the necklace-type terminal 14, the data acquisition unit 100 sequentially collects the outputs of the microphone 38, sensor 39, and camera 42. The communication unit 102 sequentially transmits the outputs of the microphone 38, sensor 39, and camera 42 collected by the data acquisition unit 100 to the data processing unit 12.

[0049] Next, an example of the flow of a specific process will be explained with reference to Figure 7. Here, the input unit 292 of the data processing device 12 sequentially acquires the outputs of the microphone 38, sensor 39, and camera 42 received from the necklace-type terminal 14 and stores them in the data storage unit 54.

[0050] In step S300, the processing unit 294 determines whether a predetermined trigger condition is met. Specifically, the trigger condition may be that the user utterance picked up by the microphone 38 contains a specific word (for example, the name of the agent installed in the necklace-type terminal 14) or a phrase (for example, "Hi! XX" (where XX is the name of the agent)).

[0051] If the trigger condition is met in step S300 (step S300; Yes), the data processing system 10 proceeds to step S301. On the other hand, if the trigger condition is not met in step S300 (step S300; No), the data processing system 10 terminates the specific processing.

[0052] In step S301, the processing unit 294 generates a prompt by adding an instruction to obtain the result of a specific process to the text representing the user utterance picked up by the microphone 38.

[0053] For example, a prompt such as "The user is speaking as follows: XXX. Please respond as the agent." (XXX is the user's utterance.) can be generated. Alternatively, the outputs of sensor 39 and camera 42 can be added to the prompt to generate a prompt such as "This is biometric data representing the user's heart rate and video data representing the user's surroundings. The user is also speaking as follows: XXX. Please respond as the agent." (XXX is the user 20's utterance.)

[0054] In step S303, the processing unit 294 inputs the generated prompt to the data generation model 58 and obtains the result of a specific process based on the output of the data generation model 58.

[0055] In step S304, the output unit 296 outputs the result of the specific processing to the necklace-type terminal 14 and terminates the specific processing.

[0056] (Second Embodiment) A second embodiment of the present disclosure will be described below. Since the second embodiment has the same system configuration as the data processing system 10 described in Figures 1 and 2 as the first embodiment, Figures 1 and 2 will be used as the data processing system 10 of the second embodiment, and the same components will be described using the same reference numerals.

[0057] In the first embodiment, the system is configured to collect biometric and status data of user 20 in real time to detect early signs of Alzheimer's disease, dementia, etc., and to monitor user 20's health status (e.g., heart disease). In other words, the necklace-type terminal 14 of the first embodiment has a so-called "reactive" function that responds after an abnormality occurs, for example, and monitors user 20's health status, etc.

[0058] In contrast, in the second embodiment, the data processing system 10 is configured to have a so-called "proactive intervention" function that predicts risks before abnormalities occur and intervenes early, in order to more effectively protect the health of the user 20. Furthermore, the data processing system 10 in the second embodiment is equipped with a learning function that learns the user 20's past data and behavioral patterns.

[0059] In the following, the specific processing performed by the specific processing unit 290 will be distinguished as normal specific processing when a reactive function is executed, and predictive mode specific processing when a proactive intervention function is executed.

[0060] In the second embodiment, the sensor 39 attached to the necklace-type terminal 14 consists of a sensor that detects biometric data and a sensor that detects environmental data around the user.

[0061] The sensors for detecting biometric data include at least one of the following: a heart rate sensor, a blood oxygen sensor, a blood pressure sensor, a body temperature sensor, and a respiratory pattern detection sensor. Additionally, the sensors for detecting environmental data include at least one of the following: a position sensor, a temperature sensor, and a humidity sensor.

[0062] Furthermore, the sensors do not need to be concentrated in one location; they may be placed on other parts of the necklace-type terminal 14, or via wireless devices, on the user's body such as the wrists, ankles, and chest, in positions that make it easiest to collect the desired data, as needed.

[0063] Figure 8 provides a detailed explanation of the functional configuration of the specific processing unit 290A according to the second embodiment.

[0064] In the second embodiment, the specific processing unit 290A comprises an input unit 292A, a processing unit 294A, and an output unit 296A. The processing unit 294 includes a proactive intervention function.

[0065] The input unit 292A receives real-time biometric data of the user 20, such as the user's heart rate, blood pressure, body temperature, and breathing pattern, based on the outputs of the microphone 38, sensor 39, and camera 42, which are collected by the data acquisition process of the control unit 46A of the necklace-type terminal 14. In addition to biometric data, all situational data of the user 20's surroundings is also input.

[0066] Furthermore, the input unit 292A receives past sensor data and behavioral pattern data of the user 20 that have been stored in the data storage unit 54.

[0067] The processing unit 294A performs specific processing (normal specific processing) using the data generation model 58 (see Figure 2). Specifically, it inputs a prompt including user utterance to the data generation model 58 and obtains the generation result. At this time, the outputs of the sensor 39 and camera 42 collected by the data acquisition unit 100 may also be included in the prompt.

[0068] Furthermore, the processing unit 294A performs a specific processing (predictive specific processing) using the proactive intervention function. In the predictive specific processing, based on the user 20's biometric data and situational data collected via the input unit 292A, and the user 20's past sensor data and behavioral pattern data stored in the data storage unit 54 (see Figure 2), the processing unit predicts potential health risks to the user 20 (execution of prediction mode), and prompts the data generation model 58 to analyze behavioral patterns for early intervention regarding those risks (e.g., advice on risk avoidance behavior, warnings, etc.), and obtains the results of the behavioral pattern analysis. For example, the biometric data and situational data of the user 20 collected via the input unit 292A, and the user 20's past behavioral pattern data stored in the database storage unit 54 (see Figure 2) are input to the data generation model 58, and the prompt "This is the user's biometric data, situational data, and past behavioral pattern data. Predict potential health risks to the user and generate warnings for early intervention regarding those risks." is input to the data generation model 58. As a result, the data generation model 58 generates a warning message stating, "You are at risk of dementia, so please be mindful of adopting behavioral habits to prevent dementia."

[0069] This makes it possible to detect signs of Alzheimer's disease and dementia tailored to each user's individual living environment, even before the disease develops (before the initial symptoms appear). The behavioral pattern analyzed by the processing unit 294A is sent to the output unit 296A.

[0070] Next, the operation of the second embodiment will be described. First, an example of the data collection process flow will be explained.

[0071] When user 20 is wearing the necklace-type terminal 14, the data acquisition unit 100 sequentially collects the outputs of the microphone 38, sensor 39, and camera 42. At this time, a feature of the second embodiment is that it collects various data (heart rate, blood oxygen, body temperature, breathing pattern, etc.) detected from sensor 39, which is a collection of biosensors including a heart rate sensor, blood oxygen sensor, blood pressure sensor, body temperature sensor, and breathing pattern detection sensor. The communication unit 102 sequentially transmits the outputs of the microphone 38, sensor 39, and camera 42 collected by the data acquisition unit 100 to the data processing device 12.

[0072] Next, an example of the flow of a specific process will be explained with reference to Figure 9. Here, the input unit 292 of the data processing device 12 sequentially acquires the outputs of the microphone 38, sensor 39, and camera 42 received from the necklace-type terminal 14 and stores them in the data storage unit 54.

[0073] In step S300A, the processing unit 294 determines whether a predetermined trigger condition is met. Specifically, the trigger condition may be that the user utterance picked up by the microphone 38 contains a specific word (for example, the name of the agent installed in the necklace-type terminal 14) or a phrase (for example, "Hi! XX" (where XX is the name of the agent)).

[0074] If the trigger condition is met in step S300A (step S300A; Yes), the data processing system 10 proceeds to step S301. On the other hand, if the trigger condition is not met in step S300A (step S300A; No), the data processing system 10 terminates the specific processing.

[0075] In step S301A, the processing unit 294 generates a prompt by adding an instruction to obtain the result of a specific process to the text representing the user utterance picked up by the microphone 38.

[0076] For example, a prompt such as "The user is speaking as follows: XXX. Please respond as the agent." (XXX is the user's utterance) can be generated. Alternatively, the outputs of sensor 39 and camera 42 can be added to the prompt to generate a prompt such as "This is the user's biometric data and video data representing the user's surroundings. The user is also speaking as follows: XXX. Please respond as the agent." (XXX is the user's utterance) can be generated. In this case, if user 20's utterance is "Are there any signs that I might experience health problems in the future?", the emergency trigger condition will be met, the proactive intervention function will be executed, and the system can switch from normal identification processing (normal mode) to predictive identification processing (predictive mode).

[0077] In prediction mode, the proactive intervention function is used to predict potential health risks for user 20 based on the collected biometric and situational data of user 20, as well as past sensor data and behavioral pattern data of user 20 stored in the data storage unit 54.

[0078] Furthermore, as described above, the emergency trigger condition is activated when the collected biometric and situational data of user 20 meets predetermined conditions, and the system may enter prediction mode regardless of user utterance.

[0079] In step S303A, the processing unit 294 inputs the generated prompt to the data generation model 58 and obtains the result of a normal identification process (execution of a normal identification mode similar to the first embodiment) or a predictive identification process (execution of a predictive mode) based on the output of the data generation model 58.

[0080] In prediction mode, prompts are input to the data generation model 58 instructing it to analyze behavioral patterns for early intervention regarding risk (e.g., advice on risk avoidance behavior, warnings, etc.), and the results of the behavioral pattern analysis are obtained.

[0081] Figure 10 shows the detailed processing of step 303A in Figure 8 as a subroutine flow. In step 303A, it is determined whether the prompt is in predictive mode. If the result in step 303A is negative, the process proceeds to step 303B, where the specific processing described in detail in the first embodiment is executed, and the system returns. If the result in step 303A is positive, the process proceeds to step 303C, where the predictive mode identification processing (proactive intervention function) according to the second embodiment is executed, and the system returns.

[0082] In step S304A, the output unit 296 outputs the result of the specific processing to the necklace-type terminal 14 and terminates the specific processing.

[0083] As explained above, in the second embodiment, in addition to the reactive function (normal specific processing) of the first embodiment, a proactive intervention function is provided to more effectively protect the health of user 20 by predicting risks before abnormalities occur and intervening early, and a learning function (predictive mode) is provided to learn user 20's past data and behavioral patterns, enabling responses tailored to each individual user 20.

[0084] In this embodiment, the prediction mode identification process provided a response to the user 20. However, the data processing device 12 may be equipped with a real-time data log processing function that automatically saves all relevant data when it indicates an abnormality in the health status, and performs detailed analysis or provides the data to a medical institution.

[0085] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer, or as an application that runs on a smartphone, etc. The method related to this disclosure may be provided to the user 20 in SaaS (Software as a Service) format.

[0086] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which may involve multiple computers, including computer 22.

[0087] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0088] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 53, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0089] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 53, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0090] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0091] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0092] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0093] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0094] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0095] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference. [Explanation of symbols]

[0096] 10 Data Processing Systems 12 Data Processing Devices 14. Necklace-type terminal (wearable device) 38 Microphones 39 Sensors 40 speakers 42 cameras 46A Control Unit 54. Data Storage Unit (Database) 100 Data Acquisition Unit 102 Communications Department 290 Specific Processing Unit (Proactive Intervention Processing Unit) 292 Input section 294 Processing Unit 296 Output section (provider section)< / url:>

Claims

1. A data processing system comprising: a wearable device equipped with sensors that detect the wearer's biometric data and surrounding environmental data; and a data processing device that receives output data from the sensors and prompts requesting a response regarding the wearer's health status based on the output data, The aforementioned data processing device is A proactive intervention processing unit analyzes the output data of the sensor to predict a risk score related to the wearer's health status and sets warning data according to the degree of risk. A providing unit that provides the alert data set in the proactive intervention processing unit to the wearer via the wearable device as a response to the prompt, A data processing system having the following features.

2. The sensor for detecting the aforementioned biological data includes at least one of a heart rate sensor, a blood pressure sensor, a blood oxygen sensor, a body temperature sensor, and a respiratory pattern sensor. The data processing system according to claim 1, wherein the sensor for detecting the environmental data includes at least one of a position sensor, a temperature sensor, and a humidity sensor.

3. The data processing device further includes a database that stores past data, including the wearer's biometric data and behavioral pattern data. The data processing system according to claim 1, wherein the proactive intervention processing unit obtains a response regarding the wearer's health status by using output data from the sensor and past data stored in the database in combination.

4. The aforementioned prompt, The data processing system according to claim 1, which is generated as a result of executing a prediction mode identification process based on numerical determination of voice data of the wearer input from a microphone provided on the wearable device, or output data of the sensor.

5. The data processing system according to claim 1, wherein the wearable device further includes a speaker that outputs a response provided by the providing unit.

6. The data processing system according to claim 1, wherein if the response indicates an abnormality in health status, all relevant data is automatically saved and further analyzed or provided to a medical institution.

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