Data processing system

Abstract

To provide a data processing system capable of detecting the possibility of an initial symptom of dementia in a user.SOLUTION: The data processing system includes a necklace-type terminal including a microphone that picks up a user's speech of a wearer, a collection unit that collects an output of the microphone, and a communication unit that transmits the output of the microphone collected by the collection unit to an external device, and a data processing device, and the data processing device includes an input unit that receives the user's speech picked up by the microphone, and a processing unit that notifies a preset notification destination that the wearer is likely to have dementia when an utterance indicating a sign of dementia is included in the user's speech.SELECTED DRAWING: Figure 8

Description

[Technical Field]

[0001] The techniques of this disclosure relate to data processing systems. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, 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] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In recent years, society has been aging. In an aging society, the number of patients developing dementia, such as Alzheimer's disease, is increasing, creating a need for early detection of dementia and appropriate treatment. However, the early symptoms of dementia are subtle, and cognitive impairment is often not recognized even after the disease has progressed, making early intervention difficult. While the above-mentioned conventional technologies can generate chatbot utterances corresponding to user utterances, they cannot detect whether the user may be experiencing early symptoms of dementia. [Means for solving the problem]

[0005] A first aspect of the technology of the present disclosure is a necklace-type terminal including a microphone that picks up user utterances of a wearer, a collection unit that collects an output of the microphone, and a communication unit that transmits the output of the microphone collected by the collection unit to an external device; a data processing system comprising: The data processing device includes: an input unit that receives a user utterance picked up by the microphone; A data processing system including a processing unit that, if it is determined that there are signs of dementia based on the user's speech, notifies a pre-set notification destination that the wearer may have dementia.

[0006] A second aspect of the technology disclosed herein is a data processing system according to the first aspect, wherein the processing unit determines that there are signs of dementia when there is a lack of consistency between multiple statements made by the wearer during the user's speech, and notifies a pre-set notification destination that the wearer may have dementia.

[0007] A third aspect of the technology disclosed herein is a data processing system according to the first aspect, wherein the processing unit determines whether or not there are signs of dementia based on the frequency of occurrence of specific words in the user's speech.

[0008] A fourth aspect of the technology of the present disclosure is the data processing system of the third aspect, wherein the specific word is a pronoun.

[0009] A fifth aspect of the technology disclosed herein is a data processing system according to the first aspect, wherein the processing unit counts the number of times that the user's utterances are judged to be signs of dementia, and when the count value within a predetermined period of time reaches or exceeds a threshold value, notifies a predetermined notification destination that the wearer may have dementia.

[0010] A sixth aspect of the technology of the present disclosure is the data processing system of the first aspect, wherein the necklace-type terminal further includes a speaker; The processing unit outputs a pre-prepared question as audio from the speaker, determines whether the wearer is likely to have signs of dementia based on the answer to the question picked up by the microphone, and if the determined possibility is equal to or greater than a predetermined value, notifies a predetermined notification destination that the wearer may have dementia.

[0011] A seventh aspect of the technology disclosed herein is a data processing system according to the first aspect, wherein the processing unit determines whether or not there are signs of dementia based on a pattern of changes in the wearer's emotions estimated from the user's speech, and if it is determined that there are signs of dementia, notifies a pre-set notification destination that the wearer may have dementia.

[0012] An eighth aspect of the technology of the present disclosure is the data processing system of any one of the first to seventh aspects, wherein the necklace-type terminal further includes a heartbeat sensor that detects a heartbeat of the wearer, The processing unit determines the type of dementia by performing frequency analysis of heart rate fluctuations in the wearer's heart rate data detected by the heart rate sensor, and when notifying the wearer that there is a possibility that they have dementia, it also notifies information about the determined type of dementia. [Brief explanation of the drawings]

[0013] [Figure 1] FIG. 1 is a conceptual diagram illustrating an example of a configuration of a data processing system. [Figure 2] FIG. 2 is a conceptual diagram showing an example of main functions of a data processing device and a necklace-type terminal. [Figure 3] FIG. 2 is a side view showing the configuration of the necklace-type terminal. [Figure 4] FIG. 2 is a top view showing the configuration of the necklace-type terminal. [Figure 5] 10 is a schematic diagram showing the functional configuration of a control unit of the necklace-type terminal. [Figure 6] 2 shows a schematic functional configuration of a specific processing unit of the data processing device. [Figure 7] 10 is a diagram illustrating an example of an operational flow of specific processing by a data processing device. [Figure 8] 10 is a flowchart showing the operation of the processing unit 294 when detecting early symptoms of dementia from the user utterance of the user 20 using the data generation model 58. [Figure 9] 10 is a flowchart for explaining an operation when updating a data generation model 58. DETAILED DESCRIPTION OF THE INVENTION

[0014] Hereinafter, an example of an embodiment of a data processing device, a data processing method, and a program according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices 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).

[0017] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0018] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0019] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple 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), Bluetooth (registered trademark), etc.

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0021] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to a first embodiment of the present disclosure.

[0022] 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 this embodiment, the data processing device 12 is an example of a "data processing device" according to the technology of the present disclosure, and the necklace-type terminal 14 is an example of a "necklace-type terminal" according to the technology of the present disclosure.

[0023] 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 a "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. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The necklace type terminal 14 includes a computer 36, a microphone 38, a sensor 39, a speaker 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 38, the speaker 40, and the camera 42 are also connected to the bus 52.

[0025] The user 20 who wears the necklace-type terminal 14 may be, for example, a patient whose health condition is to be diagnosed, or may be a normal user.

[0026] The microphone 38 picks up the voice uttered 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 and the like from the user 20 by receiving the voice uttered by the user 20. The microphone 38 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 40 outputs audio in accordance with instructions from the processor 46. The speaker 40 is, for example, a directional speaker, and outputs audio toward the ears of the user 20.

[0027] The sensor 39 is a sensor that detects biological data of the user 20 who is wearing the necklace-type terminal. For example, the sensor 39 is a heart rate sensor or an SPO2 (arterial blood oxygen saturation) sensor.

[0028] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the necklace-type terminal 14.

[0031] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. 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 process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores a data generation model 58. The data generation model 58 is used by the specific processing unit 290. The storage 32 also includes a data accumulation unit 57.

[0033] In the necklace-type terminal 14, the data collection process is performed by the processor 46. A data collection program 60 is stored in the storage 50. The processor 46 reads the data collection program 60 from the storage 50 and executes the read data collection program 60 on the RAM 48. The data collection process is realized by the processor 46 operating as the control unit 46A in accordance with the data collection program 60 executed on the RAM 48.

[0034] As shown in FIGS. 3 and 4, the necklace type terminal 14 includes multiple microphones 38, multiple sensors 39, multiple speakers 40, and multiple cameras 42. FIGS. 3 and 4 show an example in which two microphones 38 are arranged so as to be located in front of the user 20 when the user 20 wears the necklace type terminal 14. FIGS. 3 and 4 also show an example in which two sensors 39 are arranged so as to be located on the right and left sides of the user 20 when the user 20 wears the necklace type terminal 14. FIGS. 3 and 4 also show an example in which two speakers 40 are arranged so as to be located on the right and left rear sides of the user 20 when the user 20 wears the necklace type terminal 14. FIGS. 3 and 4 also show an example in which two cameras 42 are arranged so as to be located on the right and left front sides of the user 20 when the user 20 wears the necklace type terminal 14. FIGS. 3 and 4 also show an example in which two sensors 39 are arranged inside the necklace type terminal 14 so as to come into contact with the neck of the user 20 when the user 20 wears the necklace type terminal 14.

[0035] Next, the processing of the control unit 46A when the necklace-type terminal 14 performs a data collection process for collecting data will be described.

[0036] In the data collection process of this embodiment, biometric data of the user is collected in real time. Furthermore, not only biometric data but also all situational data surrounding the user is collected. This makes it possible to detect early signs of, for example, Alzheimer's disease and dementia. It also makes it possible to monitor the user's health condition (for example, heart disease).

[0037] As shown in FIG. 5, the control unit 46A includes a data collection unit 100 and a communication unit 102.

[0038] The data collection unit 100 collects the output of each of the microphone 38, the sensor 39, and the camera 42.

[0039] The communication unit 102 transmits the outputs of the microphone 38 , the sensor 39 , and the camera 42 collected by the data collection unit 100 to the data processing device 12 .

[0040] Next, a description will be given of the processing of the specific processing unit 290 when the data processing device 12 performs the specific processing to acquire a response corresponding to a user utterance.

[0041] In the identification process of this embodiment, a response corresponding to a user utterance picked up by the microphone 38 of the necklace-type terminal 14 is acquired using the data generation model 58.

[0042] As shown in FIG. 6, the specific processing unit 290 includes an input unit 292, a processing unit 294, and an output unit 296.

[0043] The input unit 292 stores the outputs of the microphone 38 , the sensor 39 , and the camera 42 received from the necklace-type terminal 14 in the data storage unit 57 .

[0044] The input unit 292 acquires the user's utterance received by the necklace type terminal 14. Specifically, the input unit 292 acquires the user's utterance picked up by the microphone 38 of the necklace type terminal 14.

[0045] The processing unit 294 performs a specific process using the data generation model 58. Specifically, a prompt including a user utterance is input to the data generation model 58 to obtain a generation result. At this time, the prompt may further include outputs from the sensor 39 and the camera 42 collected by the data collection unit 100.

[0046] The output unit 296 transmits the result of the identification process 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 identification process. 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 identification process. The control unit 46A transmits voice data indicating the user utterance acquired by the microphone 38 to the data processing device 12. In the data processing device 12, the identification processing unit 290 acquires the user utterance.

[0047] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generative AI models. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0048] The outputs of the microphone 38, the sensor 39, and the camera 42 stored in the data storage unit 57 are used, for example, to diagnose the health condition of the user 20. In this case, the outputs of the microphone 38, the sensor 39, and the camera 42 stored in the data storage unit 57 may be transmitted to a terminal on the medical institution side. Alternatively, the data processing device 12 may analyze the outputs of the microphone 38, the sensor 39, and the camera 42 stored in the data storage unit 57 to diagnose the health condition of the user 20.

[0049] Next, the operation of the data processing system 10 will be described.

[0050] First, an example of the flow of the data collection process will be described.

[0051] When the user 20 is wearing the necklace-type terminal 14, the data collection unit 100 sequentially collects the outputs of the microphone 38, the sensor 39, and the camera 42. The communication unit 102 sequentially transmits the outputs of the microphone 38, the sensor 39, and the camera 42 collected by the data collection unit 100 to the data processing device 12.

[0052] Next, an example of the flow of the identification process will be described with reference to Fig. 7. Here, it is assumed that the input unit 292 of the data processing device 12 sequentially acquires the outputs of the microphone 38, the sensor 39, and the camera 42 received from the necklace-type terminal 14 and stores them in the data accumulation unit 57.

[0053] In step S300, the processing unit 294 determines whether a predetermined trigger condition is satisfied. Specifically, the trigger condition may be that a specific word (for example, the name of an agent installed in the necklace type terminal 14) or phrase (for example, "Hi! XXX" (XXX is the name of the agent)) is included in the user utterance picked up by the microphone 38.

[0054] 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 ends the identification process.

[0055] In step S301, the processing unit 294 generates a prompt by adding an instruction sentence for obtaining a result of a specific process to text representing a user utterance picked up by the microphone 38.

[0056] For example, a prompt such as "The user is saying the following: XXX. Please respond as an agent." (XXX is the user's utterance) may be generated. Alternatively, the outputs of the sensor 39 and the camera 42 may 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 saying the following: XXX. Please respond as an agent." (XXX is the user's utterance).

[0057] In step S303, the processing unit 294 inputs the generated prompt to the data generation model 58, and obtains the result of the specific process based on the output of the data generation model 58.

[0058] In step S304, the output unit 296 outputs the result of the identification process to the necklace-type terminal 14, and the identification process ends.

[0059] [Second embodiment] Next, a second embodiment will be described in which a process for detecting early symptoms of dementia in a user is executed as the identification process described in the first embodiment. Note that the second embodiment will also be described using the configuration and symbols of the data processing system 10 in the first embodiment described above.

[0060] In this embodiment, a user 20 who may have dementia is asked to wear a necklace-type device 14. As described above, this necklace-type device 14 includes a microphone 38 that picks up user utterances from the wearer, the user 20, a data collection unit 100 that collects the output of the microphone 38, and a communication unit 102 that transmits the output of the microphone 38 collected by the data collection unit 100 to the data processing device 12, which is an external device.

[0061] The data processing device 12 in this embodiment includes an input unit 292 that accepts user utterances picked up by the microphone 38, and a processing unit 294 that, if it is determined that there are signs of dementia based on the user utterances, notifies a pre-set notification destination that the user 20 who is wearing the device may have dementia.

[0062] Here, the preset notification destination may be, for example, a medical professional such as a doctor or nurse, or may be a caregiver for user 20, a care worker at a facility where user 20 is staying, etc. The medical professional, caregiver, care worker, etc. who receives this notification can understand that user 20 has early symptoms of dementia, and can take appropriate measures or responses.

[0063] Here, if there is no consistency between multiple statements made by the wearer, user 20, while the user is speaking, processing unit 294 determines that there are signs of dementia and notifies a pre-set notification destination that user 20 may have dementia.

[0064] For example, if a user utterance includes a statement such as "I have never been to XX" and a statement such as "I have been to XX many times," the processing unit 294 determines that there is no consistency between the multiple utterances. Also, for example, if a user utterance includes a statement such as "I don't have any siblings" and a statement such as "I have a younger brother and sister," the processing unit 294 determines that there is no consistency between the multiple utterances.

[0065] Furthermore, when the same utterance content is repeatedly included in the user's utterance, the processing unit 294 may notify a preset notification destination that the user 20 may have dementia. For example, when the user's utterance repeatedly includes the utterance "Did I have breakfast?", the processing unit 294 may determine that the user 20 may have dementia.

[0066] Furthermore, the processing unit 294 may be configured to determine whether or not there are signs of dementia based on the frequency of appearance of specific words in the user's utterances. Pronouns such as "that," "it," and "this" may be frequently included in the utterances of a patient with dementia. Specifically, the utterances of a patient with dementia may contain an extremely high frequency of pronouns, such as "I'm going there with that, with that." Therefore, the processing unit 294 may be configured to determine whether or not the user 20 has dementia based on the frequency of appearance of pronouns in the user's utterances, using specific words as pronouns.

[0067] Note that the processing unit 294 may not determine that the user 20 may have dementia if the user's speech contains even one statement indicating a sign of dementia, but may count the number of times that the user's speech is determined to contain a sign of dementia, and may determine that the user 20 may have dementia if the count value within a predetermined period, for example, within one day, is equal to or greater than a threshold value.

[0068] Furthermore, the processing unit 294 may not only detect early symptoms of dementia from user utterances in the daily life of the user 20, but also actively check whether or not the user 20 has early symptoms of dementia. When performing such a check, the processing unit 294 outputs a question sentence with a prepared content as sound from the speaker 40, determines whether the user 20 has a sign of dementia based on the answer to the question sentence picked up by the microphone 38, and if the determined possibility is equal to or greater than a preset value, notifies a preset notification destination that the user 20 may have dementia.

[0069] For example, the processing unit 294 outputs questions such as "What year, month and day is it today?", "What day of the week is it today?", and "Where are you currently?" as audio from the speaker 40, and determines the possibility of dementia of the user 20 based on the accuracy rate of the answers to these questions.

[0070] There are various types of dementia depending on the cause. The most common type of dementia is Alzheimer's disease, followed by dementia with Lewy bodies. Since treatment methods vary depending on the type of dementia, it is possible to take appropriate measures if it is possible to not only determine whether a person has dementia, but also what type of dementia they may have early on.

[0071] As described above, the necklace type terminal 14 includes, as one of the sensors 39, a heartbeat sensor that detects the heartbeat of the user 20.

[0072] Therefore, the processing unit 294 may determine the type of dementia by performing frequency analysis of heart rate fluctuations in the heart rate data of the user 20 detected by the heart rate sensor, and when notifying the user 20 that there is a possibility that the user 20 has dementia, the processing unit 294 may also notify information about the determined type of dementia.

[0073] For example, the processing unit 294 performs frequency analysis of the heart rate fluctuations in the detected heart rate data to obtain a power spectrum, calculates the high frequency component HF and the low frequency component LF of this power spectrum, and calculates LF / HF. This LF / HF value indicates the ratio of the activity levels of the sympathetic and parasympathetic nerves, which are the autonomic nerves, and it is possible to determine that if this LF / HF value is equal to or greater than a reference value, there is a high possibility of Alzheimer's disease, and if this LF / HF value is less than the reference value, there is a high possibility of Lewy body dementia.

[0074] Note that the data generation model 58 is generated in advance as a learning model for dementia assessment by inputting user utterances of a user with dementia and information that the user has dementia into the data generation model 58 as training data and performing machine learning. The processing unit 294 then inputs the user utterances into the data generation model 58 and receives from the data generation model 58 a determination result as to whether or not the user 20 is likely to have dementia, thereby executing the above-described processing.

[0075] Next, the operation of the data processing system 10 in this embodiment will be described in detail with reference to the drawings.

[0076] First, the operation of the processing unit 294 when detecting early symptoms of dementia from the user utterance of the user 20 using the data generation model 58 is shown in the flowchart of Fig. 8. Note that in the flowchart of Fig. 8, as an example, a case will be described in which if the user utters 10 or more times in a day that indicate signs of dementia, the user is determined to have the possibility of dementia.

[0077] First, the processing unit 294 clears the count value A used when determining that the user 20 has dementia (step S401). Next, the processing unit 294 determines whether or not one day, which is a preset period, has passed since the start of the determination (step S402). Here, if one day has not passed since the start of the determination (no in step S402), the processing unit 294 monitors the conversation of the user 20 who is the wearer (step S403).

[0078] Then, the processing unit 294 inputs the monitored user utterances of the user 20 into the data generation model 58 to check whether or not there are any utterances indicating signs of dementia in the conversation of the user utterances (step S404). Then, the processing unit 294 determines whether or not there are any utterances indicating signs of dementia based on the determination result output from the data generation model 58 (step S405).

[0079] If it is determined in step S405 that the user's speech contains a utterance indicating a symptom of dementia (yes in step S405), the processing unit 294 adds 1 to the count value A (step S406). If it is determined in step S405 that the user's speech contains no utterance indicating a symptom of dementia (no in step S405), the processing unit 294 returns to the processing of step S402.

[0080] Then, when count value A is incremented by 1 in step S406, processing unit 294 determines whether count value A is equal to or greater than a threshold value of 10 (step S407). If it is determined in step S407 that count value A is equal to or greater than 10, processing unit 294 notifies a preset notification destination that user 20 may have dementia (step S408). If it is determined in step S407 that count value A is not equal to or greater than 10, processing unit 294 returns to the processing of step S402.

[0081] By performing the above-described processing, if the processing unit 294 determines that the user's speech in one day contains 10 or more statements indicating signs of dementia, it will notify the pre-set notification destination that the user 20 may have dementia.

[0082] When the previously set notification destination is notified by the process described above that the user 20 may have dementia, a medical professional or the like will diagnose the user 20 to confirm whether or not the user 20 actually has dementia. However, if the determination accuracy of the data generation model 58 is not high, even if it is determined that the user 20 may have dementia, the user may not actually have dementia. Therefore, by feeding back the actual diagnosis result of the user 20 to the data generation model 58, it is expected that the data generation model 58 will be updated and the determination accuracy will be improved.

[0083] The operation when updating the data generation model 58 will be described with reference to the flowchart of FIG.

[0084] When the control unit 294 notifies a preset notification destination that the user 20 may have dementia, the control unit 294 receives a feedback result regarding the validity of this notification (step S501). Then, the control unit 294 evaluates the determination accuracy of the data generation model 58 based on the received feedback result (step S502). Finally, the control unit 294 performs deep learning based on the evaluation result to update the data generation model 58 (step S503).

[0085] By performing the processing as described above, the data generation model 58 performs machine learning again based on the feedback results each time it is determined that the user 20 may have dementia, thereby improving the accuracy of the determination.

[0086] The processing unit 294 may determine whether or not there are signs of dementia based on a pattern of changes in the wearer's emotions estimated from the user's utterances, and if it is determined that there are signs of dementia, may notify a pre-set notification destination that the wearer may have dementia. For example, each time a collected user utterance is obtained, the processing unit 294 estimates the wearer's emotions using an emotion engine that estimates the speaker's emotions based on the collected user utterance. Then, the processing unit 294 may determine whether or not there are signs of dementia based on the time-series changes in the estimated wearer's emotions using the data generation model 58. For example, the processing unit 294 may add the estimated time-series changes in the wearer's emotions to a prompt, generating a prompt such as "This is a time-series change in the user's emotions. Please determine whether or not there are signs of dementia." The generated prompt may be input to the data generation model 58, and a determination result of whether or not there are signs of dementia may be obtained based on the output of the data generation model 58.

[0087] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[0088] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0089] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0090] 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 54, 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.

[0091] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0092] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0093] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[0094] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0095] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0096] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0097] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0098] 10 Data Processing System 12 Data Processing Device 14 Necklace-type device 20 users 22 Computer 24 databases 28 processors 32 Storage 34 Bus 36 Computer 38 Microphone 39 Sensors 40 speakers 42 Camera 46 processors 46A Control Unit 50 Storage 52 Bus 54 Network 56 Specific Processing Program 57 Data Storage Unit 58 Data Generation Model 60 Data Collection Program 100 Data Collection Department 102 Communications Department 290 Special Processing Department 292 Input section 294 Processing Section 296 Output Section< / url:>

Claims

1. a necklace-type terminal including a microphone that picks up user utterances of a wearer, a collection unit that collects an output of the microphone, and a communication unit that transmits the output of the microphone collected by the collection unit to an external device; a data processing system comprising: The data processing device includes: an input unit that receives a user utterance picked up by the microphone; a processing unit that, when it is determined that there is a sign of dementia based on the user utterance, notifies a preset notification destination that the wearer may have dementia, Data processing system.

2. When there is no consistency between a plurality of utterances made by the wearer during the user's speech, the processing unit determines that there is a sign of dementia, and notifies a preset notification destination that the wearer may have dementia.

10. The data processing system of claim 1.

3. the processing unit determines whether or not there is a sign of dementia based on the frequency of appearance of a specific word in the user's utterance; 10. The data processing system of claim 1.

4. 4. The data processing system of claim 3, wherein the particular word is a pronoun.

5. The processing unit counts the number of times that it is determined that there are signs of dementia based on the user utterances, and when the count value within a predetermined period of time becomes equal to or greater than a threshold value, notifies a predetermined notification destination that the wearer may have dementia.

10. The data processing system of claim 1.

6. the necklace-type terminal further includes a speaker; The processing unit outputs a prepared question as sound from the speaker, determines whether the wearer has a sign of dementia based on the answer to the question picked up by the microphone, and notifies a predetermined notification destination that the wearer may have dementia if the determined possibility is equal to or greater than a predetermined value.

10. The data processing system of claim 1.

7. The processing unit determines whether or not there are signs of dementia based on a pattern of changes in the wearer's emotions estimated from the user's utterance, and if it is determined that there are signs of dementia, notifies a preset notification destination that the wearer may have dementia.

10. The data processing system of claim 1.

8. the necklace-type terminal further includes a heart rate sensor for detecting the heart rate of the wearer, the processing unit determines the type of dementia by performing frequency analysis of heart rate variability in the heart rate data of the wearer detected by the heart rate sensor, and when notifying the wearer that the wearer may have dementia, notifies the wearer of information about the determined type of dementia.

8. A data processing system according to any one of claims 1 to 7.

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