Intelligent accompanying robot based on elderly nursing

Abstract

The invention relates to the technical field of artificial intelligence, and discloses an intelligent accompanying robot based on elderly nursing, and the robot is controlled by an accompanying control system. The accompanying control system is composed of a health monitoring module, a communication interaction module, a schedule management module, a risk identification and feedback module, a movement and navigation module, a memory storage module, an automatic intervention module and a risk response module. The robot supports the natural language processing technology, simple daily dialogues are carried out, basic communication requirements of the elderly are met, the elderly can feel accompanying and caring through voice dialogues, the loneliness is reduced, abnormal conditions in health data are automatically recognized and reported to family members, the family members can quickly deal with potential health problems, and the service life of the elderly is prolonged. Feedback and intervention can improve the sense of security of the elderly, avoid long-time isolation, and achieve the beneficial effect that the family member end control system is added to solve the problem of emotional communication of the elderly.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to an intelligent companion robot based on elderly care. Background Art

[0002] As the aging population continues to grow, the probability of accidental injuries to the elderly increases with age. Sudden illness, unexplained falls, falling out of bed, accidental ingestion, and burns have become the most common safety issues for the elderly. Therefore, in order to prevent and avoid the risks of elderly people living alone, smart companionship is very important.

[0003] A search revealed an elderly companion intelligent robot control system with publication number CN 118034152 A. By combining artificial intelligence and Internet of Things technologies, it can realize healthy sleep care for family members, healthy room care, assist the elderly in taking and putting items, monitor door and window security, long-range and short-range switching of electrical appliances, memo reminders, cooking and seasoning assistance, toilet flushing, etc. The implementation of this application will accelerate the advent of smart life, help the elderly live a convenient life, and help solve many problems in the lives of the elderly.

[0004] However, although the above-mentioned technical solutions can solve many problems in the lives of the elderly, there is still much room for improvement in the above-mentioned technologies. Family members cannot communicate with the elderly effectively, cannot identify the elderly’s accidents in time, and their mobile control ability is weak. Summary of the invention

[0005] Technical issues solved:

[0006] In view of the deficiencies in the prior art, the present invention provides an intelligent companion robot based on elderly care, which has the advantages of adding a family-side control system to solve the emotional communication problems of the elderly; risk identification and calling for help in addition to keywords; and seeking help nearby while setting a time and route to help the elderly escape from danger, thereby solving the problems of the above-mentioned technologies.

[0007] Technical solution:

[0008] To achieve the above object, the present invention provides the following technical solutions: an intelligent companion robot based on elderly care, the robot is controlled by a companion control system, and the companion control system is composed of a health monitoring module, a communication interaction module, a schedule management module, a risk identification and feedback module, a movement and navigation module, a memory storage module, an automatic intervention module and a risk response module;

[0009] The health monitoring module is used to collect the elderly's vital signs data in real time, including heart rate, blood pressure, blood sugar and body temperature. The data is automatically collected through a wristband, blood glucose meter or finger clip oximeter, and the collected data is compared with the normal range, abnormal conditions are analyzed, regular reports are set, and health status summaries are pushed to family members every 1, 3 or 5 days;

[0010] The communication interaction module is used to support natural language processing technology, conduct simple daily conversations, and provide voice reminder functions to remind the elderly to take medicine, drink water or participate in activities;

[0011] The schedule management module is used for family members to set the schedule of the elderly's life through remote management, including diet, medication and exercise;

[0012] The risk identification and feedback module is used to monitor the behavior of the elderly in real time, detect abnormal situations such as falling, vomiting and loss of consciousness through sensors, and automatically send alarms to family members after identifying risks, and can also notify medical institutions to intervene;

[0013] The mobile and navigation module combines GPS and indoor positioning technology to enable the robot to locate the elderly in real time and follow their activities;

[0014] The memory storage module is used to record the daily interactions between family members and the elderly, health data and system behavior, and provide family members with information about the elderly’s living habits and health changes through big data analysis;

[0015] The automatic intervention module is used to automatically start a preset intervention program when the system does not detect family member interaction for a long time;

[0016] The risk response module is used to automatically initiate emergency response when the system identifies any risk.

[0017] Preferably, the vital sign data collection parameters in the health monitoring module are expressed as:

[0018] H is heart rate data, BP is blood pressure data, BG is blood sugar data, and T is body temperature data;

[0019] The data collection method in the health monitoring module is: heart rate H: wristband, blood pressure BP: cuff, blood sugar BG: finger clip oximeter, body temperature T: thermometer;

[0020] The abnormality detection expression in the health monitoring module is:

[0021] Set normal range:

[0022] Normal heart rate range norm =[60,100];

[0023] Normal blood pressure range BP norm =[90,140]"Systolic blood pressure";

[0024] Normal blood sugar range BG norm =[5,7.5]"Unit:

[0025] Normal body temperature range Tnorm =[36.1,37.2] "Unit: ℃";

[0026] Determine abnormal conditions: If H<60 or H>100, BP<90 or BP>140, BG<5 or BG>7.5 or T<36.1 or T>37.2, report it as abnormal.

[0027] Preferably, the regular report push expression in the health detection module is:

[0028] Set push frequency F:

[0029] F∈1,3,5

[0030] Define the push report function:

[0031]

[0032] Where: n is the number of days, starting from the last push.

[0033] Preferably, the daily conversation function expression of the communication interaction module is:

[0034] Set the user input to U and the response output to R;

[0035] The dialogue process is expressed as: R = NLU (U);

[0036] Among them, NLU is the Natural Language Understanding function.

[0037] Preferably, the schedule arrangement function expression in the schedule management module is to set a schedule event set E:

[0038] E = diet, medication, exercise;

[0039] The expression of family remote management is: the schedule set by the family is D, which includes the specific time of each event:

[0040] D=D[diet],D[medication],D[exercise]

[0041] Where D[diet] = {time 饮食1 ,time 饮食2 ,…}; D[medication] = {time 用药1 ,time 用药2 ,…};ξ[exercise]={time 锻炼1 ,time 锻炼2 ,…}.

[0042] Preferably, the risk detection expression in the risk identification and feedback module is:

[0043] Set the abnormal event set E detected by the sensor, including:

[0044] E = fall, vomit, lose consciousness;

[0045] Set the sensor output to S, where:

[0046] S[fall] = 1 means a fall is detected, 0 means no fall is detected;

[0047] S[vomiting] = 1 means vomiting was detected, 0 means vomiting was not detected;

[0048] S[loss of consciousness] = 1 if loss of consciousness was detected, 0 if loss of consciousness was not detected;

[0049] The test conditions are:

[0050] If S[fall]=1 or S[vomit]=1 or S[lose consciousness]=1, it indicates that there is a risk.

[0051] Preferably, the real-time positioning expression of the mobile and navigation module is: the output of GPS and indoor positioning system is set as follows: GPS positioning output is (X GPS ,Y GPS ), represents the position coordinates on a two-dimensional plane;

[0052] The indoor positioning output is (X IND ,Y IND ), represents the position coordinates in the indoor environment;

[0053] The comprehensive positioning expression is:

[0054] The comprehensive positioning function is C, which determines the actual location based on GPS and indoor positioning data:

[0055]

[0056] Preferably, the data record expression in the memory storage module is:

[0057] Set the recorded data set: interaction record between family members and the elderly I; health data H; system behavior record B; set the recording function R:

[0058] Family member interaction record I = {I[interaction time], I[interaction content]};

[0059] Health data H = {H[date], H[body temperature], H[blood pressure], H[heart rate]};

[0060] System behavior record B = {B[time], B[event type], B[event details]}.

[0061] Preferably, the data recorded in the automatic intervention module is: setting the interaction time recording function I(t) between the family members and the elderly:

[0062] I(t)={I[time 1],I[time 2],…,I[time N]}

[0063] Where: t is the time variable, N is the number of recorded interactions;

[0064] The calculation expression of the interaction time interval is:

[0065] Set the total observation time T and the update time interval ΔP.

[0066] Latest interaction time T last =max(I(t));

[0067] Last interaction time T now = current time;

[0068] Interaction time interval ΔT interaction :

[0069] ΔT interacrion =T now -T last .

[0070] Preferably, the risk detection expression of the risk response module is: setting the risk index R(t):

[0071] R(t)={R[index1](t),R[index2](t),…,R[indexN](t)}

[0072] Where: t is the time variable, and N is the number of risk indicators detected.

[0073] Compared with the prior art, the present invention provides an intelligent companion robot based on elderly care, which has the following beneficial effects:

[0074] 1. The present invention supports natural language processing technology through robots to conduct simple daily conversations and meet the basic communication needs of the elderly. Through voice conversations, the elderly feel accompanied and cared for, reducing loneliness. At the same time, it provides medication reminders, water drinking reminders and activity arrangements to help the elderly maintain a regular life and make them feel the care and attention of their family members. Even if their family members are not around, they can maintain communication. The system regularly collects and analyzes the elderly's health data: heart rate, blood pressure, blood sugar and body temperature, and pushes the health status summary to the family members, which not only allows the family members to understand the health status of the elderly in a timely manner, but also shows the family members' concern and care for the elderly, thereby strengthening emotional connections, automatically identifying abnormal situations in health data and reporting them to family members, so that family members can quickly respond to potential health problems. Feedback and intervention can improve the elderly's sense of security and avoid long-term isolation, achieving the beneficial effect of adding a family-side control system to solve the emotional communication problem of the elderly.

[0075] 2. The present invention monitors the behavior of the elderly in real time through the sensors of the risk identification and feedback module, and can detect abnormal situations such as falls, vomiting and loss of consciousness. Active monitoring can detect emergency situations in real time and automatically compared with simple keyword calls for help, reducing dependence on the elderly and response time. Utilizing sensor data: S[fall], S[vomiting], S[loss of consciousness], the system can accurately identify and record abnormal events, ensuring the accuracy and timeliness of risk identification. After identifying a risk event, the system will automatically send an alarm to family members and medical institutions. The automated alarm mechanism avoids the need for the elderly to actively seek help when facing an emergency, and can quickly initiate an emergency response and provide timely assistance. The system can also start a preset intervention program when no interaction with family members is detected for a long time. When family members are unable to pay attention in real time, measures are automatically taken to deal with risks, thereby improving the safety of the elderly and achieving the beneficial effect of risk identification in addition to keyword calls for help.

[0076] 3. The present invention combines GPS and indoor positioning technology to locate the elderly in real time by obtaining the coordinates of the elderly on a two-dimensional plane: X GPS ,Y GPS and indoor coordinates: X IND ,Y IND The system can accurately track the real-time location of the elderly, monitor the elderly's behavior in real time, such as abnormal situations such as falling, vomiting and losing consciousness, and automatically send alarms. It triggers emergency response measures through identified abnormal situations, such as notifying family members or medical institutions to intervene. When the system detects that family members have not interacted for a long time, it automatically starts the preset intervention program, including automatic alarms, emergency requests to family members or medical institutions, etc., to ensure that help can be obtained in time in an emergency, achieving the beneficial effect of seeking help nearby at the set time and route to help the elderly out of danger. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 It is a schematic diagram of the system of the present invention; DETAILED DESCRIPTION

[0078] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0079] See also Figure 1 , an intelligent companion robot based on elderly care, the robot is controlled by a companion control system, and the companion control system consists of a health monitoring module, a communication interaction module, a schedule management module, a risk identification and feedback module, a movement and navigation module, a memory storage module, an automatic intervention module and a risk response module;

[0080] The health monitoring module is used to collect the elderly's vital signs data in real time, including heart rate, blood pressure, blood sugar and body temperature. The data is automatically collected through a wristband or finger clip oximeter, and the collected data is compared with the normal range, abnormal conditions are analyzed, regular reports are set, and health status summaries are pushed to family members every 1, 3 or 5 days;

[0081] The communication interaction module is used to support natural language processing technology, conduct simple daily conversations, and provide voice reminder functions to remind the elderly to take medicine, drink water or participate in activities;

[0082] The schedule management module is used for family members to set the schedule of the elderly's life through remote management, including diet, medication and exercise;

[0083] The risk identification and feedback module is used to monitor the behavior of the elderly in real time, detect abnormal situations such as falling, vomiting and loss of consciousness through sensors, and automatically send alarms to family members after identifying risks, and can also notify medical institutions to intervene;

[0084] The mobile and navigation module combines GPS and indoor positioning technology to enable the robot to locate the elderly in real time and follow their activities;

[0085] The memory storage module is used to record the daily interactions between family members and the elderly, health data and system behavior, and provide family members with information about the elderly’s living habits and health changes through big data analysis;

[0086] The automatic intervention module is used to automatically start a preset intervention program when the system does not detect family member interaction for a long time;

[0087] The risk response module is used to automatically initiate emergency response when the system identifies any risk.

[0088] Preferably, the vital sign data collection parameters in the health monitoring module are expressed as:

[0089] H is heart rate data, BP is blood pressure data, BG is blood sugar data, and T is body temperature data;

[0090] The data collection method in the health monitoring module is: heart rate H: wristband, blood pressure BP: cuff, blood sugar BG: finger clip oximeter, body temperature T: thermometer;

[0091] The abnormality detection expression in the health monitoring module is:

[0092] Set normal range:

[0093] Normal heart rate range norm =[60,100];

[0094] Normal blood pressure range BP norm =[90,140]"Systolic blood pressure";

[0095] Normal blood sugar range BG norm =[5,7.5]"Unit:

[0096] Normal range of body temperature Tn notm =[36.1,37.2] "Unit: ℃";

[0097] Determine abnormal conditions: If H<60 or H>100, BP<90 or BP>140, BG<5 or BG>7.5 or T<36.1 or T>37.2, report it as abnormal.

[0098] Preferably, the regular report push expression in the health detection module is:

[0099] Set push frequency F:

[0100] F∈1,3,5

[0101] Define the push report function:

[0102]

[0103] Where: n is the number of days, starting from the last push.

[0104] Preferably, the daily conversation function expression of the communication interaction module is:

[0105] Set the user input to U and the response output to R;

[0106] The dialogue process is expressed as: R = NLU (U);

[0107] Among them, NLU is the Natural Language Understanding function.

[0108] Preferably, the schedule arrangement function expression in the schedule management module is to set a schedule event set E:

[0109] E = diet, medication, exercise;

[0110] The expression of family remote management is: the schedule set by the family is D, which includes the specific time of each event:

[0111] D=D[diet],D[medication],D[exercise]

[0112] Where D[diet] = {time 饮食1 ,time 饮食2 ,…}; D[medication] = {time 用药1 ,time 用药2 ,…}; D[exercise] = {time 锻炼1 ,time 锻炼2 ,…}.

[0113] Preferably, the risk detection expression in the risk identification and feedback module is:

[0114] Set the abnormal event set E detected by the sensor, including:

[0115] E = fall, vomit, lose consciousness;

[0116] Set the sensor output to S, where:

[0117] S[fall] = 1 means a fall is detected, 0 means no fall is detected;

[0118] S[vomiting] = 1 means vomiting was detected, 0 means vomiting was not detected;

[0119] S[loss of consciousness] = 1 if loss of consciousness was detected, 0 if loss of consciousness was not detected;

[0120] The test conditions are:

[0121] If S[fall]=1 or S[vomit]=1 or S[lose consciousness]=1, it indicates that there is a risk.

[0122] Preferably, the real-time positioning expression of the mobile and navigation module is set as follows:

[0123] The GPS positioning output is (X GPS ,Y GPS), represents the position coordinates on a two-dimensional plane;

[0124] The indoor positioning output is (X IND ,Y IND ), represents the position coordinates in the indoor environment;

[0125] The comprehensive positioning expression is:

[0126] The comprehensive positioning function is C, which determines the actual location based on GPS and indoor positioning data:

[0127]

[0128] Preferably, the data record expression in the memory storage module is:

[0129] Set the data set to be recorded: interaction records between family members and the elderly I; health data H; system behavior records B;

[0130] Set the recording function R:

[0131] Family member interaction record I = {I[interaction time], I[interaction content]};

[0132] Health data H = {H[date], H[body temperature], H[blood pressure], H[heart rate]};

[0133] System behavior record B = {B[time], B[event type], B[event details]}.

[0134] Preferably, the data recorded in the automatic intervention module is: setting the interaction time recording function I(t) between the family members and the elderly:

[0135] I(t)={I[time 1],I[time 2],…,I[time N]}

[0136] Where: t is the time variable, N is the number of recorded interactions;

[0137] The calculation expression of the interaction time interval is:

[0138] Set the total observation time T and the update time interval ΔT.

[0139] Latest interaction time T last =max(I(t));

[0140] Last interaction time T now = current time;

[0141] Interaction time interval ΔT interaction :

[0142] ΔT interaction =T now -Tlast .

[0143] Preferably, the risk detection expression of the risk response module is: setting the risk index R(t):

[0144] R(t)={R[index1](t),R[index2](t),…,R[indexN](t)}

[0145] Where: t is the time variable, and N is the number of risk indicators detected.

[0146] Natural language processing: The robot supports natural language processing technology, conducts simple daily conversations, and meets the basic communication needs of the elderly. Through voice conversations, the elderly feel accompanied and cared for, reducing loneliness.

[0147] Voice reminder function: provides medication reminders, water drinking reminders and activity arrangements to help the elderly maintain a regular life, while making them feel the care and attention of their family members, and maintaining communication even if their family members are not around.

[0148] Remote management: Family members can set the elderly’s schedule, including diet, medication and exercise, through the remote management system. Regular intervention and adjustments by family members ensure that the elderly have a regular life, increase their sense of security, and make them feel the family’s continuous attention.

[0149] Health data feedback: The system regularly collects and analyzes the health data of the elderly (such as heart rate, blood pressure, blood sugar and body temperature), and pushes the health status summary to family members. This mechanism not only allows family members to understand the health status of the elderly in a timely manner, but also shows that the family members care and care for the elderly, thereby strengthening emotional connections.

[0150] Anomaly detection: Automatically identify anomalies in health data and report them to family members, allowing them to quickly respond to potential health problems. This timely feedback and intervention can improve the elderly’s sense of security and avoid long-term isolation.

[0151] Interaction records: Record the daily interactions, health data and system behaviors between family members and the elderly. Family members can understand the elderly’s living habits and health changes through these records. The records help family members adjust their companionship strategies, enhance the pertinence and effectiveness of interactions, and make emotional exchanges more in line with the actual needs of the elderly.

[0152] Automatic intervention: When no family interaction is detected for a long time, the system can automatically start the preset intervention program, so that when family members are unable to participate in real time, care for the elderly can be maintained, reducing the possibility of the elderly feeling isolated and helpless.

[0153] Risk Response: The system can identify risks and automatically initiate emergency responses, which not only improves the safety of the elderly, but also allows family members to be notified in time in times of crisis, so that they can better care for and look after the elderly.

[0154] Risk identification and feedback module: This module monitors the elderly's behavior in real time through sensors and can detect abnormal situations such as falls, vomiting and loss of consciousness. Compared with simple keyword calls for help, this active monitoring can detect emergencies in real time and automatically, reducing dependence on the elderly and response time.

[0155] Sensor data: Using sensor data: S[fall], S[vomiting], S[loss of consciousness], the system can accurately identify and record abnormal events, ensuring the accuracy and timeliness of risk identification.

[0156] Automatic alarm function: After identifying a risk event, the system will automatically send an alarm to family members and medical institutions. This automated alarm mechanism avoids the need for the elderly to actively seek help when facing an emergency, and can quickly initiate an emergency response and provide timely assistance.

[0157] Automatic intervention module: The system can also start the preset intervention program when no interaction from family members is detected for a long time. This mechanism automatically takes measures to deal with risks when family members are unable to pay attention in real time, thereby improving the safety of the elderly.

[0158] The risk response module sets up a detailed emergency response mechanism, which can automatically start the emergency procedure when any risk is detected. Compared with the traditional way of calling for help, this automated response mechanism can respond to various risk situations more quickly and ensure the safety of the elderly.

[0159] The risk index R(t) is set to comprehensively assess the risk, and the emergency response strategy is automatically adjusted according to the actual detection situation, ensuring the timeliness and pertinence of emergency measures.

[0160] The health monitoring module collects and analyzes the vital signs of the elderly in real time, and automatically detects abnormalities by setting the normal range. If abnormal data is found: heart rate, blood pressure, blood sugar, body temperature exceeds the normal range, the system will automatically trigger an alarm and perform further processing to ensure timely response to health risks.

[0161] The memory storage module records the interactions between family members and the elderly, health data, and system behavior. Through big data analysis, these records help family members understand the health changes and living habits of the elderly, so as to better predict and prevent possible risks.

[0162] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and alterations may be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An intelligent companion robot based on elderly care, characterized in that: The robot is controlled by a companion control system, which consists of a health monitoring module, a communication interaction module, a schedule management module, a risk identification and feedback module, a movement and navigation module, a memory storage module, an automatic intervention module and a risk response module; The health monitoring module is used to collect the elderly's vital signs data in real time, including heart rate, blood pressure, blood sugar and body temperature. The data is automatically collected through a wristband or finger clip oximeter, and the collected data is compared with the normal range, abnormal conditions are analyzed, regular reports are set, and health status summaries are pushed to family members every 1, 3 or 5 days; The communication interaction module is used to support natural language processing technology, conduct simple daily conversations, and provide voice reminder functions to remind the elderly to take medicine, drink water or participate in activities; The schedule management module is used for family members to set the schedule of the elderly's life through remote management, including diet, medication and exercise; The risk identification and feedback module is used to monitor the behavior of the elderly in real time, detect abnormal situations such as falling, vomiting and loss of consciousness through sensors, and automatically send alarms to family members after identifying risks, and can also notify medical institutions to intervene; The mobile and navigation module combines GPS and indoor positioning technology to enable the robot to locate the elderly in real time and follow their activities; The memory storage module is used to record the daily interactions between family members and the elderly, health data and system behavior, and provide family members with information about the elderly’s living habits and health changes through big data analysis; The automatic intervention module is used to automatically start a preset intervention program when the system does not detect family member interaction for a long time; The risk response module is used to automatically initiate emergency response when the system identifies any risk.

2. The intelligent companion robot based on elderly care according to claim 1, characterized in that: The vital sign data collection parameters in the health monitoring module are expressed as: H is heart rate data, BP is blood pressure data, BG is blood sugar data, and T is body temperature data; The data collection method in the health monitoring module is: heart rate H: wristband, blood pressure BP: cuff, blood sugar BG: finger clip oximeter, body temperature T: thermometer; The abnormality detection expression in the health monitoring module is: Set normal range: Normal heart rate range norm = [60, 100]; Normal blood pressure range BP norm =[90,140]"Systolic blood pressure"; Normal blood sugar range BG norm =[5,7.5]"Unit: ”; Normal body temperature range T norm =[36.1, 37.2]"Unit: ℃"; Determine abnormal conditions: If H<60 or H>100, BP<90 or BP>140, BG<5 or BG>7.5 or T<36.1 or T>37.2, report it as abnormal.

3. The intelligent companion robot based on elderly care according to claim 1, characterized in that: The expression for periodic report push in the health detection module is: Set push frequency F: F∈1，3，5 Define the push report function: Where: n is the number of days, starting from the last push.

4. The intelligent companion robot based on elderly care according to claim 1, characterized in that: The daily conversation function expression of the communication interaction module is: Set the user input to U and the response output to R; The dialogue process is expressed as: R = NLU (U); Among them, NLU is the Natural Language Understanding function.

5. The intelligent companion robot based on elderly care according to claim 1 is characterized in that: The schedule arrangement function expression in the schedule management module is to set the schedule event set E: E = diet, medication, exercise; The expression of family remote management is: the schedule set by the family is D, which includes the specific time of each event: D = D [diet], D [medication], D [exercise] Where D[diet] = {time 饮食1 ,time 饮食2 , ...}; D[medication] = {time 用药1 ,time 用药2 , ...}; D[exercise={time 锻炼1 ,time 锻炼2 , ...}.

6. The intelligent companion robot based on elderly care according to claim 1, characterized in that: The risk detection expression in the risk identification and feedback module is: Set the abnormal event set E detected by the sensor, including: E = fall, vomit, lose consciousness; Set the sensor output to S, where: S[fall] = 1 means a fall is detected, 0 means no fall is detected; S[vomiting] = 1 means vomiting was detected, 0 means vomiting was not detected; S[loss of consciousness] = 1 if loss of consciousness was detected, 0 if loss of consciousness was not detected; The test conditions are: If S[fall]=1 or S[vomit]=1 or S[lose consciousness]=1, it indicates that there is a risk.

7. The intelligent companion robot based on elderly care according to claim 1 is characterized in that: The real-time positioning expression of the mobile and navigation module is, setting the output of GPS and indoor positioning system: The GPS positioning output is (X GPS , Y GPS ), represents the position coordinates on a two-dimensional plane; The indoor positioning output is (X IND , Y IND ), represents the position coordinates in the indoor environment; The comprehensive positioning expression is: The comprehensive positioning function is C, which determines the actual location based on GPS and indoor positioning data:

8. The intelligent companion robot based on elderly care according to claim 1 is characterized in that: The data record expression in the memory storage module is: Set the data set to be recorded: interaction record between family members and the elderly I; health data H; system behavior record 5; Set the recording function R: Family member interaction record I = {I [interaction time], I [interaction content]}; Key health data H = {H [blood sugar], H [body temperature], H [blood pressure], H [heart rate]}; System behavior record B = {B[time], B[event type], B[event details]}.

9. The intelligent companion robot based on elderly care according to claim 1, characterized in that: The data recorded in the automatic intervention module is: setting the interaction time recording function I(t) between the family members and the elderly: I(t)={I[time 1], I[time 2], ..., I[time N]} Where: t is the time variable, N is the number of recorded interactions; The calculation expression of the interaction time interval is: Set the total observation time T and the update time interval ΔT. Latest interaction time T last =max(I(t)); Last interaction time T now = current time; Interaction time interval ΔT interaction : ΔT interaction =T now -T last 。 10. The intelligent companion robot based on elderly care according to claim 1, characterized in that: The risk detection expression of the risk response module is: Set the risk index R(t): R(t)={R[index1](t), R[index2](t), ..., R[indexN](t)} Where: t is the time variable, and N is the number of risk indicators detected.

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