Traditional Chinese medicine outpatient service information management system

Abstract

The invention discloses a traditional Chinese medicine outpatient service information management system, and relates to the technical field of information management, and the system comprises an information collection module which is used for collecting patient information and current chief complaint symptoms; the disease module comprises an inspection unit, an auscultation unit, an inquiry unit and a cut diagnosis unit, and the symptom file comprises a current chief complaint symptom input by a patient and a diagnosis symptom input by a doctor; and after the disease module receives a current chief complaint symptom input by a patient, the disease module adopts a multi-mode processing model to identify input characters, voices or pictures, obtains corresponding symptom information and distributes the symptom information to the corresponding inspection unit, the listening unit, the inquiry unit or the cut-off unit. According to the method, the diagnosis and treatment methods of looking, smelling, asking and cutting of traditional Chinese medicine are fully fused, the characteristics of traditional Chinese medicine diagnosis and treatment are combined with the modern technology through the multi-mode technology, the time sequence analysis and the intelligent reminding mechanism, and a new thought and a new solution are provided for informatization of traditional Chinese medicine diagnosis and treatment.

Description

Technical Field

[0001] The present invention relates to the technical field of information management, in particular to a traditional Chinese medicine outpatient information management system. Background Art

[0002] At present, medical information management systems have been widely used in modern hospitals. Their main function is to manage patients' medical records, examination results, diagnostic information and treatment records in a digital way. These systems are centered on data management and provide doctors with convenient information support through standardized storage and query functions.

[0003] In traditional Chinese medicine diagnosis, its unique diagnostic and treatment methods, such as inspection, auscultation, questioning, and palpation, lack effective information support, especially in the ability to dynamically record and analyze changes in symptoms.

[0004] After searching, a Chinese patent (CN104200294A) discloses an outpatient information management system, which includes: an outpatient clinical information database for storing patients' personal health information; a pre-hospital health information questionnaire analysis module for providing patients with a health information questionnaire before medical treatment; an in-hospital diagnosis and treatment management module for managing the pre-medical treatment recommendations generated by the pre-hospital health information questionnaire analysis module, and all diagnosis and treatment information and treatment plans generated during the hospital visit; a post-hospital health management module for providing patients with follow-up health management recommendations and monitoring based on the patient diagnosis and treatment information and treatment plans managed in the in-hospital diagnosis and treatment management module; and a system external interface integration module for enabling data interaction between the outpatient management system and other external systems.

[0005] In the prior art, there is a lack of structured processing capabilities for the four diagnostic data of TCM when processing TCM outpatient information, and the ability to effectively record and analyze the multi-dimensional information generated in the process of TCM diagnosis and treatment is poor. Secondly, these systems are unable to quantify and analyze the accuracy of the patient's main symptoms, nor can they provide a graded processing function, resulting in the subjective deviation of the patient's description may affect the doctor's diagnosis and treatment plan. Therefore, the present invention proposes a TCM outpatient information management system. Summary of the invention

[0006] The purpose of the present invention is to provide a traditional Chinese medicine outpatient information management system to solve the problems mentioned in the above background technology.

[0007] The present invention can be implemented through the following technical solutions: a Chinese medicine outpatient information management system, including an information collection module, a symptom module, and a medical database;

[0008] The information collection module is used to collect patient information and current symptoms. The patient information includes the patient's name, gender, age / date of birth, ID number / medical record number and contact information, and self-reported physical condition (such as fear of cold, easy fatigue, etc.);

[0009] The current main complaint is the main symptom reported by the patient, and the current main complaint can be input in the form of text, voice or picture;

[0010] The symptom module is used to establish a symptom file of the patient, including an inspection unit, an auscultation unit, an inquiry unit and a palpation unit, and the symptom file includes the current main complaint symptoms input by the patient and the diagnosis symptoms input by the doctor;

[0011] After receiving the patient's current main complaint input, the symptom module uses a multimodal processing model to recognize the text, voice or picture input, obtains the corresponding symptom information, and distributes it to the corresponding inspection unit, auscultation unit, questioning unit or palpation unit;

[0012] After the doctor diagnoses the patient, he obtains the patient's diagnostic symptoms, and inputs the diagnostic symptoms into the inspection unit, the auscultation unit, the questioning unit, and the palpation unit of the symptom module respectively, and the inspection unit, the auscultation unit, the questioning unit, and the palpation unit update the current main complaint symptoms in the inspection unit, the auscultation unit, the questioning unit, and the palpation unit based on the diagnostic symptoms, so as to update the symptom file of the corresponding patient;

[0013] The medical database includes a personal data unit and a large data unit;

[0014] The personal data unit is used to store the patient's basic information and symptom profile, and to record the type of disease determined by the doctor, the treatment method prescribed, and the composition of the medicine;

[0015] The big data unit establishes a database based on historical case data, medical literature and expert opinions;

[0016] After the doctor prescribes the treatment method and the prescription components, the big data unit matches the precautions of the corresponding treatment method and the usage of the prescription from the database to form a medication guide, and after confirmation by the doctor, the medication guide is transmitted to the corresponding patient's personal data unit.

[0017] A further technical improvement of the present invention is that the method for using the large data unit comprises the following steps:

[0018] S1. Establish data structure, including treatment method table, medication table, medication usage rules table and precautions table;

[0019] The treatment method table includes fields: treatment method name, treatment method description, applicable constitution, and relevant precautions;

[0020] S2. Collect data;

[0021] By collecting medical literature, historical case data and expert opinions, we classify them according to treatment methods and organize the corresponding herbal combinations, decoction methods, frequency of use and precautions;

[0022] S3. Establish database:

[0023] Select relational data or non-relational data as the database type, and create the database structure, define the structure of the treatment method table, medication table, medication usage rules table, and precautions table, and establish the relationship between the tables;

[0024] Use the data import tool to import the data collected in step S2 into the database;

[0025] S4. Implement matching algorithm:

[0026] After the doctor inputs the treatment method and the prescription components, the big data unit extracts the precautions of the corresponding treatment method from the treatment method table, extracts the dosage range and special treatment requirements of the prescription from the prescription table, and extracts the decoction method and frequency of use from the prescription usage rules table;

[0027] Finally, the big data unit organizes the matching information into medication instructions for doctors to confirm or modify;

[0028] S5. Complete data matching:

[0029] The medication instructions confirmed or modified by the doctor are transmitted to the personal data unit of the corresponding patient.

[0030] A further technical improvement of the present invention is that the personal data unit calculates the consistency between the current main complaint symptoms input by the patient and the diagnosis symptoms input by the doctor, using the formula:

[0031] In the formula, Q i is the weight of the ith symptom, indicating the importance of the symptom; Z i is the number of symptoms that the patient's current complaints match the doctor's diagnosed symptoms, 1 indicates a match, and 0 indicates a mismatch; n represents the number of intersections between the patient's current complaints and the doctor's diagnosed symptoms, that is, the number of matching symptoms; Q j is the weight of all symptoms diagnosed by the doctor; m is the total number of symptoms diagnosed by the doctor;

[0032] M is the matching degree, and its value range is 0%-100%, which indicates the coverage of the former chief complaint symptoms in the doctor's diagnosis symptoms. The closer it is to 100%, the more accurate the patient's description of his or her own symptoms is.

[0033] A further technical improvement of the present invention is that: the big data unit introduces a "symptom combination-symptom type mapping" rule for each symptom type, and each symptom is assigned a corresponding weight in the corresponding "symptom combination-symptom type mapping" rule;

[0034] That is, the symptom type D = matching symptom set, which searches for the corresponding symptom type in the database based on the matched symptom combination;

[0035] And the personal data unit is based on the matching degree, combined with the symptom weight matching degree and the importance of the disease type, to define the patient level, the level classification formula is:

[0036]

[0037] A further technical improvement of the present invention is that the medical database performs the following processing based on the patient level:

[0038] When L = 1, the big data unit provides standard medication information to the personal data unit, including prescriptions and basic medication methods;

[0039] When L=2, the big data unit provides detailed medication instructions and scheduled medication reminders to the personal data unit;

[0040] Detailed medication instructions include step-by-step instructions and post-medication observation details;

[0041] Scheduled medication reminders are pushed through the device after obtaining the patient's device permissions;

[0042] When L=3, the big data unit provides detailed medication instructions and scheduled medication reminders to the personal data unit, and after each reminder, the patient is required to actively close the medication reminder.

[0043] A further technical improvement of the present invention is that: after obtaining the corresponding diagnostic symptoms, the inspection unit, the auscultation unit, the questioning unit and the palpation unit add a timestamp to each diagnostic symptom;

[0044] The inspection unit, the auscultation unit, the questioning unit and the palpation unit store the collected diagnostic symptoms and timestamps in the personal data unit of the corresponding patient;

[0045] The personal data unit is based on timestamps and organizes the diagnostic symptoms in chronological order to form a time series to facilitate doctors to dynamically monitor the condition.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] The present invention integrates the TCM diagnosis and treatment methods of observation, auscultation, inquiry and palpation, and combines the TCM diagnosis and treatment characteristics with modern technology through multimodal technology, time series analysis and intelligent reminder mechanism, providing new ideas and solutions for the informatization of TCM diagnosis and treatment. Moreover, through the combination of big data units and personal data units, the system can realize the linkage analysis of historical data and real-time diagnostic data, make full use of resources such as TCM literature and case data, and provide patients with more accurate diagnosis and treatment services.

[0048] The present invention adds timestamps to the information collected by the inspection, auscultation, questioning and palpation units and generates a time series of symptoms, thereby achieving dynamic monitoring and trend analysis of disease changes, helping doctors to timely understand the development of the disease, adjust treatment plans, and improve diagnosis and treatment efficiency. In addition, by calculating the matching degree between the patient's main symptoms and the doctor's diagnosed symptoms and dividing them into levels based on weights, the present invention can quantify the accuracy of the patient's description of the symptoms, and provide corresponding personalized medication guidance and reminders according to different levels, thereby greatly improving patient compliance and treatment effects.

[0049] On the other hand, for patients of different levels, the present invention designs a graded medication guidance and reminder mechanism, provides detailed medication operation instructions, precautions and real-time reminder functions, and realizes scheduled push and medication records through device authority management, which can effectively reduce medication risks and improve treatment effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0051] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0052] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0053] See also Figure 1 As shown, the present invention provides a traditional Chinese medicine outpatient information management system, including an information collection module, a symptom module, and a medical database;

[0054] The information collection module is used to collect patient information and current symptoms. The patient information includes the patient's name, gender, age / date of birth, ID number / medical record number and contact information, and self-reported physical condition (such as fear of cold, easy fatigue, etc.);

[0055] The current main complaint is the main symptom reported by the patient, and the current main complaint can be input in the form of text, voice or picture;

[0056] The symptom module is used to establish the patient's symptom file, including the inspection unit, the auscultation unit, the questioning unit and the palpation unit, and the symptom file includes the current main complaint symptoms input by the patient and the diagnosis symptoms input by the doctor;

[0057] After receiving the patient's current main complaint, the symptom module uses a multimodal processing model to recognize the text, voice or picture input, obtain the corresponding symptom information, and assign it to the corresponding inspection unit, auscultation unit, questioning unit or palpation unit;

[0058] In this embodiment, the patient enters the text "headache, sore throat, cough with phlegm" through the system interface and uploads a picture of the tongue coating;

[0059] The symptom module uses NLP algorithms to segment and extract features from text, extracting key symptom information from the text, such as "headache", "cough", and "sore throat". The symptom module then maps the extracted keywords to the following categories based on the TCM symptom classification rules:

[0060] "Headache"--consultation unit;

[0061] “Cough” – auscultation unit;

[0062] “Sore Throat” – Olfaction Unit;

[0063] And the disease module uses CNN computer vision technology to assign tongue coating photos to the visual diagnosis unit;

[0064] After the doctor diagnoses the patient, he obtains the patient's diagnostic symptoms, and inputs the diagnostic symptoms into the inspection unit, the auscultation unit, the questioning unit, and the palpation unit of the symptom module respectively, and the inspection unit, the auscultation unit, the questioning unit, and the palpation unit update the current main complaint symptoms in the inspection unit, the auscultation unit, the questioning unit, and the palpation unit based on the diagnostic symptoms, so as to update the symptom file of the corresponding patient;

[0065] Medical databases include personal data units and big data units;

[0066] The personal data unit is used to store the patient's basic information and symptom profile, and to record the type of disease diagnosed by the doctor, the treatment method prescribed, and the composition of the medicine dispensed;

[0067] After obtaining the corresponding diagnostic symptoms, the inspection unit, the auscultation unit, the questioning unit and the palpation unit add a timestamp to each diagnostic symptom;

[0068] The inspection unit, the auscultation unit, the questioning unit and the palpation unit store the collected diagnostic symptoms and timestamps in the personal data unit of the corresponding patient;

[0069] Personal data units are based on timestamps, and diagnostic symptoms are organized in chronological order to form a time series to facilitate doctors to dynamically monitor the condition;

[0070] The Big Data Unit builds a database based on historical case data, medical literature, and expert opinions;

[0071] After the doctor prescribes the treatment method and the prescription components, the big data unit matches the precautions of the corresponding treatment method and the usage method of the prescription from the database to form a medication guide, and after confirmation by the doctor, transmits the medication guide to the personal data unit of the corresponding patient;

[0072] The method of using the large data unit includes the following steps:

[0073] S1. Establish data structure, including treatment method table, medication table, medication usage rules table and precautions table;

[0074] The treatment method table includes fields: treatment method name, treatment method description, applicable constitution, and relevant precautions;

[0075] For example:

[0076] Treatment method name: Relieving the exterior and dispersing cold;

[0077] Description of treatment method: dispel external cold, harmonize Ying and Wei;

[0078] Applicable constitution: Yang deficiency constitution;

[0079] Related precautions: Avoid cold and wind, and avoid eating raw, cold and spicy food;

[0080] The prescription table includes fields: name of medicinal material, dosage range, special treatment method, and incompatibility;

[0081] For example:

[0082] Medicinal material name: cinnamon twig, white peony root;

[0083] Dosage range: 3-10g of cinnamon twig, 6-15g of white peony root;

[0084] Special treatment methods: cinnamon twig (none), white peony root (none);

[0085] Contraindications: cinnamon twig (not suitable for use with gypsum), white peony root (not available);

[0086] The prescription usage rules table includes fields such as treatment method name, medicinal material combination, decoction method, administration method, and usage frequency;

[0087] For example:

[0088] Field treatment method name: Relieving exterior symptoms and dispersing cold;

[0089] Medicinal material combination: 10g cinnamon twig + 10g white peony root + 10g jujube;

[0090] Decoction method: decoct with 400ml water until 200ml;

[0091] Dosage: Take warm, twice a day;

[0092] Frequency of use: 1 dose per day;

[0093] The fields of the precautions table include: treatment method name, precautions content;

[0094] For example:

[0095] Treatment method name: Relieving the exterior and dispersing cold;

[0096] Precautions: Avoid wind and cold, and avoid spicy food;

[0097] S2. Collect data;

[0098] By collecting medical literature, historical case data and expert opinions, we classify them according to treatment methods and organize the corresponding herbal combinations, decoction methods, frequency of use and precautions;

[0099] S3. Establish database:

[0100] Use relational data as the database type and create a database structure to define the structure of the treatment method table, medication table, medication usage rules table and precautions table, and establish the relationship between the tables, for example, the treatment method table is associated with the medication table through the treatment method name;

[0101] Use the data import tool to import the data collected by S2 into the database;

[0102] S4. Implement matching algorithm:

[0103] After the doctor inputs the treatment method and the prescription components, the big data unit extracts the precautions of the corresponding treatment method from the treatment method table, extracts the dosage range and special treatment requirements of the prescription from the prescription table, and extracts the decoction method and frequency of use from the prescription usage rules table;

[0104] Finally, the big data unit organizes the matching information into medication instructions for doctors to confirm or modify;

[0105] S5. Complete data matching:

[0106] The medication instructions confirmed or modified by the doctor are transmitted to the personal data unit of the corresponding patient;

[0107] The personal data unit calculates the consistency between the current symptoms entered by the patient and the diagnostic symptoms entered by the doctor using the following formula:

[0108] In the formula, Q i is the weight of the ith symptom, indicating the importance of the symptom; Z i is the number of symptoms that the patient's current complaints match the doctor's diagnosed symptoms, 1 indicates a match, and 0 indicates a mismatch; n represents the number of intersections between the patient's current complaints and the doctor's diagnosed symptoms, that is, the number of matching symptoms; Q j is the weight of all symptoms diagnosed by the doctor; m is the total number of symptoms diagnosed by the doctor;

[0109] M is the matching degree, which ranges from 0% to 100%, indicating the coverage of the former chief complaint symptoms in the doctor's diagnosis symptoms. The closer to 100%, the more accurate the patient's description of his own symptoms;

[0110] The big data unit introduces the “symptom combination-symptom type mapping” rule for each symptom type;

[0111] That is, the symptom type D = matching symptom set, which searches for the corresponding symptom type in the database according to the matched symptom combination, and each symptom is given a weight in the corresponding "symptom combination-symptom type mapping" rule;

[0112] For example:

[0113] Combination: {fever, cough, sore throat} → Symptom type: cold and wind-heat;

[0114] Combination: {headache, aversion to cold, floating and tight pulse} → Symptom type: exogenous wind-cold;

[0115] And the personal data unit is based on the matching degree, combined with the symptom weight matching degree and the importance of the disease type, to define the patient level, the level classification formula is:

[0116]

[0117] In this embodiment, the weights of the various symptoms include: fever: 0.3; cough: 0.2; sore throat: 0.2; aversion to cold: 0.3; floating pulse: 0.4;

[0118] Symptom combination and disease type mapping and weights:

[0119] Symptom combination: {fever, cough, sore throat}, disease type: cold and wind-heat, weight: 0.7;

[0120] Symptom combination: {headache, aversion to cold, floating and tight pulse}, disease type: exogenous wind-cold, weight: 0.8;

[0121] Symptom combination: {fatigue, poor appetite, abdominal distension}, Symptom type: weak spleen and stomach, Weight: 0.6;

[0122] The patient's previous complaints were fever and cough, and the doctor's diagnosis was fever, cough, and sore throat;

[0123] When calculating the match, we first determine the intersection symptoms: fever, cough;

[0124]

[0125] When judging the type of symptoms, the matching symptom combination: {fever, cough, sore throat}, corresponding to the type of symptoms: cold wind-heat (weight 0.7);

[0126] Then M = 83.33%, D = 0.7, according to the classification formula, the level L = 2;

[0127] The medical database performs the following processing based on the patient level:

[0128] When L = 1, the big data unit provides standard medication information to the personal data unit, including prescriptions and basic medication methods;

[0129] When L=2, the big data unit provides detailed medication instructions and scheduled medication reminders to the personal data unit;

[0130] Detailed medication instructions include step-by-step instructions and post-medication observation details;

[0131] Scheduled medication reminders are pushed through the device after obtaining the patient's device permissions;

[0132] When L=3, the big data unit provides detailed medication instructions and scheduled medication reminders to the personal data unit, and after each reminder, the patient is required to actively close the medication reminder.

[0133] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A Chinese medicine outpatient information management system, characterized in that: include: Information collection module, used to collect patient information and current symptoms; Symptom module, used to establish the patient's symptom file, including inspection unit, auscultation unit, questioning unit and palpation unit; and the symptom profile includes the current presenting symptoms entered by the patient and the diagnosed symptoms entered by the physician; After receiving the patient's current main complaint input, the symptom module uses a multimodal processing model to recognize the text, voice or picture input, obtains the corresponding symptom information, and distributes it to the corresponding inspection unit, auscultation unit, questioning unit or palpation unit; After the doctor diagnoses the patient, he obtains the patient's diagnostic symptoms and inputs the diagnostic symptoms into the inspection unit, auscultation unit, questioning unit and palpation unit of the symptom module respectively, and updates the current main complaint symptoms in the inspection unit, auscultation unit, questioning unit and palpation unit; Medical databases, including personal data units and big data units; The personal data unit is used to store the patient's basic information and symptom profile, and to record the type of disease determined by the doctor, the treatment method prescribed, and the composition of the medicine; The big data unit establishes a database based on historical case data, medical literature and expert opinions; After the doctor prescribes the treatment method and the prescription components, the big data unit matches the precautions of the corresponding treatment method and the usage of the prescription from the database to form a medication guide, and after confirmation by the doctor, the medication guide is transmitted to the corresponding patient's personal data unit.

2. A Chinese medicine outpatient information management system according to claim 1, characterized in that: The method for using the large data unit comprises the following steps: S1. Establish data structure, including treatment method table, medication table, medication usage rules table and precautions table; S2. Collect data; By collecting medical literature, historical case data and expert opinions, we classify them according to treatment methods and organize the corresponding herbal combinations, decoction methods, frequency of use and precautions; S3. Establish database: Select the database type and create the database structure, define the structure of the treatment method table, medication table, medication usage rules table and precautions table, and establish the relationship between the tables; Use the data import tool to import the data collected by S2 into the database; S4. Implement matching algorithm: After the doctor inputs the treatment method and the prescription components, the big data unit extracts the precautions of the corresponding treatment method from the treatment method table, extracts the dosage range and special treatment requirements of the prescription from the prescription table, and extracts the decoction method and frequency of use from the prescription usage rules table; Finally, the big data unit organizes the matching information into medication instructions for doctors to confirm or modify; S5. Complete data matching: The medication instructions confirmed or modified by the doctor are transmitted to the personal data unit of the corresponding patient.

3. A Chinese medicine outpatient information management system according to claim 2, characterized in that: The treatment method table includes fields: treatment method name, treatment method description, applicable constitution, and relevant precautions; The prescription table includes fields: name of medicinal material, dosage range, special treatment method, and incompatibility; The prescription usage rules table includes fields such as treatment method name, medicinal material combination, decoction method, administration method, and usage frequency; The fields of the precautions table include: treatment method name and precautions content.

4. A Chinese medicine outpatient information management system according to claim 1, characterized in that: The personal data unit calculates the consistency between the current main complaint symptoms input by the patient and the diagnosis symptoms input by the doctor, using the following formula: In the formula, Q i is the weight of the ith symptom, indicating the importance of the symptom; Z i is the symptom that matches the patient's current complaint and the doctor's diagnosis; n is the number of intersections between the patient's current complaint and the doctor's diagnosis; Q j The weight of all symptoms diagnosed by the doctor; m is the total number of symptoms diagnosed by the physician; M is the matching degree, and its value range is 0%-100%.

5. A TCM outpatient information management system according to claim 4, characterized in that: The big data unit introduces a "symptom combination-symptom type mapping" rule for each symptom type: symptom type D = matching symptom set, and each symptom is assigned a corresponding weight in the corresponding "symptom combination-symptom type mapping" rule; And the big data unit searches for the corresponding disease type in the database according to the matched symptom combination.

6. A TCM outpatient information management system according to claim 5, characterized in that: The personal data unit defines the patient level based on the matching degree, combined with the symptom weight matching degree and the importance of the disease type. The level classification formula is:

7. A TCM outpatient information management system according to claim 6, characterized in that: The medical database performs the following processing based on the patient level: When L = 1, the big data unit provides standard medication information to the personal data unit, including prescriptions and basic medication methods; When L=2, the big data unit provides detailed medication instructions and scheduled medication reminders to the personal data unit; Detailed medication instructions include step-by-step instructions and post-medication observation details; Scheduled medication reminders are pushed through the device after obtaining the patient's device permissions; When L=3, the big data unit provides detailed medication instructions and scheduled medication reminders to the personal data unit, and after each reminder, the patient is required to actively close the medication reminder.

8. A TCM outpatient information management system according to claim 1, characterized in that: The inspection unit, the auscultation unit, the questioning unit and the palpation unit add a timestamp to each diagnostic symptom after obtaining the corresponding diagnostic symptom.

9. A TCM outpatient information management system according to claim 8, characterized in that: The inspection unit, the auscultation unit, the questioning unit and the palpation unit store each collected diagnostic symptom and time stamp in the personal data unit of the corresponding patient; The personal data unit is based on timestamps and organizes the diagnostic symptoms in chronological order to form a corresponding time series.

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