Smart old-age care data remote transmission method and humanoid old-age care robot

Abstract

The invention relates to the technical field of data processing, in particular to an intelligent old-age care data remote transmission method and a human-shaped old-age care robot, and the method comprises the steps: obtaining a to-be-transmitted heart rate data sequence, a current blood oxygen data sequence, a historical heart rate data sequence and a historical blood oxygen data sequence of an old-age person, obtaining suspected heart rate abnormal data, obtaining comparison heart rate data of each piece of suspected heart rate abnormal data and the initial health reflection degree, obtaining related blood oxygen data of each piece of suspected heart rate abnormal data, obtaining the initial health reflection degree of the related blood oxygen data of each piece of suspected heart rate abnormal data, obtaining the final health reflection degree of each piece of suspected heart rate abnormal data, and obtaining the final health reflection degree of each piece of suspected heart rate abnormal data. And the data transmitted preferentially are obtained. The invention aims to solve the problem that normal heart rate data in a part of movement process can be preferentially transmitted when heart rate data when the body health of a pension has a problem is preferentially transmitted.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method for remotely transmitting smart elderly care data and a humanoid elderly care robot. Background Art

[0002] With the increasing aging of society, smart elderly care has become the focus of global attention. It aims to improve the quality of life of the elderly through high-tech means and provide more convenient and safe elderly care services. In this context, the combination of data remote transmission technology and humanoid elderly care robots has brought a new solution to the field of smart elderly care.

[0003] The core of the remote transmission method of smart elderly care data is to transmit the collected physical data of the elderly, so as to facilitate medical staff to monitor the health status of the elderly in real time, respond to emergencies in time, and provide a basis for the elderly to formulate personalized care plans. However, in real life, due to the influence of network bandwidth, the strength of network signals, the comprehensive consideration of energy consumption of humanoid elderly care robots, and the collection of multiple dimensions of physical data each time, the amount of data is too large when the data is transmitted remotely over the network, which is demanding for the network. Therefore, in order to provide more timely medical assistance and health status to the elderly, it is necessary to give priority to transmitting data that shows abnormal health status of the elderly during data transmission. When obtaining heart rate data reflecting the onset of heart diseases such as coronary heart disease in the elderly, the existing method is to regard heart rate data beyond a certain range as abnormal data. However, when the elderly exercise, the heart rate data will also rise, so the heart rate data of the elderly during exercise is regarded as the heart rate data of heart diseases such as coronary heart disease. Summary of the invention

[0004] The present invention provides a smart elderly care data remote transmission method and a humanoid elderly care robot to solve the existing problems.

[0005] The invention discloses a method for remotely transmitting smart elderly care data and a humanoid elderly care robot using the following technical solutions: The present invention proposes a method for remote transmission of smart elderly care data, which comprises the following steps: Acquire the elderly person's heart rate data sequence to be transmitted, current blood oxygen data sequence, historical heart rate data sequence and historical blood oxygen data sequence to obtain suspected abnormal heart rate data; the data in the elderly person's heart rate data sequence to be transmitted, current blood oxygen data sequence, historical heart rate data sequence and historical blood oxygen data sequence all correspond to a collection day and a specific collection time; According to the specific collection time of each suspected abnormal heart rate data and the historical heart rate data, the comparative heart rate data of each suspected abnormal heart rate data is obtained; according to the distribution of the heart rate data to be transmitted around each suspected abnormal heart rate data and the distribution of the historical heart rate data around the comparative heart rate data of each suspected abnormal heart rate data, the initial health reflection degree of each suspected abnormal heart rate data is obtained; According to the distribution of the heart rate data to be transmitted around each suspected abnormal heart rate data and the distribution of the current blood oxygen data around each current blood oxygen data, the relevant blood oxygen data of each suspected abnormal heart rate data is obtained, and then the initial health reflectivity of the relevant blood oxygen data of each suspected abnormal heart rate data is obtained; according to the initial health reflectivity of each suspected abnormal heart rate data, the difference and distribution of the initial health reflectivity of each suspected abnormal heart rate data and the initial health reflectivity of its relevant blood oxygen data, the final health reflectivity of each suspected abnormal heart rate data is obtained, and then the data for priority transmission is obtained.

[0006] The specific method of obtaining the suspected abnormal heart rate data includes: Preset abnormal threshold , the heart rate data sequence to be transmitted is greater than the abnormal threshold The heart rate data to be transmitted is recorded as suspected abnormal heart rate data.

[0007] The specific method of obtaining the comparative heart rate data of each suspected abnormal heart rate data according to the specific collection time of each suspected abnormal heart rate data and the historical heart rate data includes: The historical heart rate data sequence of the elderly is combined with the The historical heart rate data with the same specific collection time as the suspected abnormal heart rate data is recorded as Compare the heart rate data of suspected abnormal heart rate data.

[0008] The initial health reflection degree of each suspected abnormal heart rate data is obtained according to the distribution of the heart rate data to be transmitted around each suspected abnormal heart rate data and the distribution of the historical heart rate data around the comparison heart rate data of each suspected abnormal heart rate data, including the specific method of: The heart rate data sequence to be transmitted will be The specific collection time of the suspected abnormal heart rate data is closest to data, recorded as Control heart rate data of suspected abnormal heart rate data; among them, Indicates the number of preset control heart rate data; Get the The specific calculation formula for the heart rate change rate of suspected abnormal heart rate data is as follows: In the formula, Indicates The heart rate change rate of suspected abnormal heart rate data, Indicates the number of control heart rate data, Indicates The value of suspected abnormal heart rate data, Indicates The first suspected abnormal heart rate data The value of the control heart rate data, represents the absolute value function; Get the The comparison heart rate data of suspected abnormal heart rate data is obtained by The heart rate change rate of the compared heart rate data of suspected abnormal heart rate data; According to The heart rate change rate of the suspected abnormal heart rate data and the heart rate change rate of the comparison heart rate data are obtained. The initial health reflection of suspected abnormal heart rate data.

[0009] According to the The heart rate change rate of the suspected abnormal heart rate data and the heart rate change rate of the comparison heart rate data are obtained. The initial health reflection of suspected abnormal heart rate data includes the following specific methods: In the formula, Indicates The initial health reflection of suspected abnormal heart rate data, Indicates The number of heart rate data to be compared with suspected abnormal heart rate data, Indicates The heart rate change rate of suspected abnormal heart rate data, Indicates The first suspected abnormal heart rate data The heart rate change rate of the compared heart rate data, represents the absolute value function, is an exponential function with a natural constant as its base.

[0010] The method of obtaining the blood oxygen data related to each suspected abnormal heart rate data according to the distribution of the heart rate data to be transmitted around each suspected abnormal heart rate data and the distribution of the current blood oxygen data around each current blood oxygen data comprises the following specific methods: In the heart rate data sequence to be transmitted, the data before any suspected abnormal heart rate data and closest to the specific collection time of the suspected abnormal heart rate data is transmitted. The heart rate data is recorded as the heart rate comparison data of the suspected abnormal heart rate data; In the blood oxygen data sequence to be transmitted, the data before any blood oxygen data and closest to the specific collection time of the blood oxygen data The heart rate data is recorded as the blood oxygen comparison data of the blood oxygen data; Combine the current blood oxygen data sequence with the The current blood oxygen data with the same specific collection time as the suspected abnormal heart rate data is recorded as Reference data of suspected abnormal heart rate data; Get the The specific calculation formula for the blood oxygen data related to suspected abnormal heart rate data is as follows: In the formula, Indicates The hysteresis of suspected abnormal heart rate data is The responsiveness, Indicates The value of suspected abnormal heart rate data, Indicates The first suspected abnormal heart rate data The value of the heart rate comparison data, Indicates the number of The first reference data after the suspected abnormal heart rate data Current blood oxygen data, Indicates the number of The first reference data after the suspected abnormal heart rate data The current blood oxygen data The value of the blood oxygen comparison data, Indicates the number of comparison data. represents the absolute value function, Indicates the preset maximum number of lags, is an exponential function with a natural constant as base; Will The maximum value corresponds to The value of Hysteresis value of suspected abnormal heart rate data ; In the current blood oxygen data sequence, The first The current blood oxygen data is recorded as The blood oxygen data related to suspected abnormal heart rate data.

[0011] The specific method of obtaining the initial health reflection degree of the blood oxygen data related to each suspected abnormal heart rate data includes: According to the specific collection time of the blood oxygen data related to each suspected abnormal heart rate data and the distribution of the surrounding current blood oxygen data, as well as the specific collection time and distribution of the historical blood oxygen data, the initial health reflection degree of the blood oxygen data related to each suspected abnormal heart rate data is obtained.

[0012] The method of obtaining the final health reflectivity of each suspected abnormal heart rate data according to the initial health reflectivity of each suspected abnormal heart rate data and the difference and distribution between the initial health reflectivity of each suspected abnormal heart rate data and the initial health reflectivity of its related blood oxygen data includes: In the formula, Indicates The final health reflection of suspected abnormal heart rate data, Indicates the number of suspected abnormal heart rate data. Indicates The initial health reflection of suspected abnormal heart rate data, Indicates The initial health reflection of the blood oxygen data related to the suspected abnormal heart rate data, Indicates The initial health reflection of suspected abnormal heart rate data, Indicates The initial health reflection of the blood oxygen data related to the suspected abnormal heart rate data, represents the absolute value function, is an exponential function with a natural constant as its base.

[0013] The data to be transmitted with priority includes the following specific methods: Preset responsiveness threshold , the final health reflection degree is less than the reflection degree threshold The suspected abnormal heart rate data is recorded as the data for priority transmission.

[0014] The present invention also proposes a humanoid elderly care robot, the robot comprising: Data acquisition module, data detection module, data transmission module; the data acquisition module is used to obtain the heart rate data and blood oxygen data of the elderly through the smart bracelet, the data detection module obtains abnormal heart rate data by calling a computer program to implement a method for remote transmission of smart elderly care data, and the data transmission module is used to transmit the heart rate data.

[0015] The beneficial effects of the technical solution of the present invention are as follows: in the process of obtaining the heart rate data for priority transmission, the present invention obtains the initial health reflection degree of each suspected abnormal heart rate data according to the distribution of data around the historical heart rate data with the same collection time of each suspected abnormal heart rate data based on the fact that the life of the elderly is relatively regular, so that the heart rate data at the same time of each day are relatively close, so that the initial health reflection degree of each suspected abnormal heart rate data reflects the degree of conformity with the relatively regular characteristics of the life of the elderly; based on the fact that blood oxygen data is affected by heart rate data during human exercise, a heart rate data is relatively close to some characteristics of the blood oxygen data affected by it, and the relevant blood oxygen value of each suspected abnormal heart rate data is obtained according to the data distribution around each suspected abnormal heart rate data and the data distribution around each blood oxygen data. According to the method, the data changes around each suspected abnormal heart rate data and its related blood oxygen data are relatively similar; according to the characteristic that the influence of heart rate on blood oxygen does not change significantly when a person is exercising, the final reflectivity of each suspected abnormal heart rate data is obtained by the difference in the initial reflectivity of each suspected abnormal heart rate data and its related blood oxygen data and the difference in the initial reflectivity of other suspected abnormal heart rate data and their related blood oxygen data, so that there is a more obvious difference in the final health reflectivity of the heart rate data collected during exercise and the heart rate data of the elderly when heart diseases such as coronary heart disease occur. This solves the problem of identifying the heart rate data during exercise as the heart rate data of the elderly when heart diseases such as coronary heart disease occur when the heart rate data of the elderly when heart diseases such as coronary heart disease are obtained directly based on the numerical value of the heart rate data. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 This is a flow chart of the steps of a method for remote transmission of smart elderly care data according to the present invention. DETAILED DESCRIPTION

[0018] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a smart elderly care data remote transmission method and a humanoid elderly care robot proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0019] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0020] The following is a detailed description of a method for remotely transmitting smart elderly care data and a specific solution of a humanoid elderly care robot provided by the present invention in conjunction with the accompanying drawings.

[0021] See also Figure 1 , which shows a flowchart of a method for remote transmission of smart elderly care data provided by an embodiment of the present invention, the method comprising the following steps: Step S001: Obtain the heart rate data sequence to be transmitted, the current blood oxygen data sequence, the historical heart rate data sequence and the historical blood oxygen data sequence of the elderly person to obtain suspected abnormal heart rate data.

[0022] This embodiment is mainly to solve the problem of which heart rate data to transmit first when transmitting the heart rate data of the elderly, thereby obtaining multiple data sequences of the elderly.

[0023] Specifically, the blood oxygen data and heart rate data of the elderly are obtained through the smart bracelet to obtain the heart rate data sequence to be transmitted and the current blood oxygen data sequence of the elderly. The collection time of the heart rate data to be transmitted and the current blood oxygen data is day, the collection frequency is times / second. The collection time preset in this embodiment is , , this is used as an example for description, and other values ​​may be set in other implementation modes.

[0024] Furthermore, the historical heart rate data and historical blood oxygen data collected within 180 days before the heart rate data to be transmitted by the elderly are obtained to obtain the historical heart rate data and historical blood oxygen data of the elderly. The collection frequency of the historical heart rate data and historical blood oxygen data is also times / second. Among them, the blood oxygen data, current heart rate data, historical blood oxygen data and historical heart rate data to be transmitted all correspond to a collection day and a specific collection time. Among them, the data collection day refers to the day on which the data is collected, and the specific data collection time refers to the hour, minute and second at which the data is collected in a day.

[0025] Furthermore, the abnormal threshold is preset , the heart rate data sequence to be transmitted is greater than the abnormal threshold The heart rate data to be transmitted is recorded as suspected abnormal heart rate data. The abnormal threshold value preset in this embodiment , this is used as an example for description, and other values ​​may be set in other implementation modes.

[0026] Step S002: Obtain comparative heart rate data for each suspected abnormal heart rate data based on the specific collection time of each suspected abnormal heart rate data and the historical heart rate data; obtain the initial health reflection degree of each suspected abnormal heart rate data based on the distribution of the heart rate data to be transmitted around each suspected abnormal heart rate data and the distribution of the historical heart rate data around the comparative heart rate data of each suspected abnormal heart rate data.

[0027] It should be noted that since the elderly live a relatively regular life, they do the same things at a fixed time period every day. For example, they get up at a fixed time period every day and exercise at a fixed time period every day. As a result, the heart rate data of the elderly at the same specific collection time on different days are relatively similar. Therefore, by comparing the suspected abnormal heart rate data with the historical heart rate data with the same specific collection time of the suspected abnormal heart rate data, the initial health reflectivity of each suspected abnormal heart rate data is obtained.

[0028] Specifically, the heart rate data sequence to be transmitted will be The specific collection time of the suspected abnormal heart rate data is closest to data, recorded as Compare the historical heart rate data of the elderly with the suspected abnormal heart rate data. The historical heart rate data with the same specific collection time as the suspected abnormal heart rate data is recorded as The number of comparison heart rate data preset in this embodiment is , this is used as an example for description, and other values ​​may be set in other implementation modes.

[0029] Further, get the The specific calculation formula for the heart rate change rate of suspected abnormal heart rate data is as follows: In the formula, Indicates The heart rate change rate of suspected abnormal heart rate data, Indicates the number of control heart rate data, Indicates The value of suspected abnormal heart rate data, Indicates The first suspected abnormal heart rate data The value of the control heart rate data, represents the absolute value function.

[0030] It should be noted that The larger the value, the The difference between the suspected abnormal heart rate data and the surrounding heart rate data is large, which further explains the The faster the change of heart rate data at the collection time corresponding to the suspected abnormal heart rate data.

[0031] Further, get the The comparison heart rate data of suspected abnormal heart rate data is obtained by The heart rate change rate of the compared heart rate data of the suspected abnormal heart rate data.

[0032] Further, get the The specific calculation formula for the initial health reflection degree of suspected abnormal heart rate data is as follows: In the formula, Indicates The initial health reflection of suspected abnormal heart rate data, Indicates The number of heart rate data to be compared with suspected abnormal heart rate data, Indicates The heart rate change rate of suspected abnormal heart rate data, Indicates The first suspected abnormal heart rate data The heart rate change rate of the compared heart rate data, represents the absolute value function, is an exponential function with a natural constant as the base. Model to present inverse proportional relationship and normalization, As the input of the model, the implementer can set the inverse proportional function and normalization function according to the actual situation.

[0033] It should be noted that The smaller the value, the The difference between the heart rate change rate of the suspected abnormal heart rate data and the heart rate change rate of the historical heart rate data with the same specific collection time is small, which further shows that the The stronger the similarity between the suspected abnormal heart rate data and the historical heart rate data with the same specific collection time, the The more likely the suspected abnormal heart rate data is the heart rate data collected when the elderly person was in relatively good health.

[0034] At this point, the initial health reflection degree of each suspected abnormal heart rate data is obtained.

[0035] Step S003: According to the distribution of the heart rate data to be transmitted around each suspected abnormal heart rate data and the distribution of the current blood oxygen data around each current blood oxygen data, the relevant blood oxygen data of each suspected abnormal heart rate data is obtained, and then the initial health reflectivity of the relevant blood oxygen data of each suspected abnormal heart rate data is obtained; according to the initial health reflectivity of each suspected abnormal heart rate data, the difference and distribution between the initial health reflectivity of each suspected abnormal heart rate data and the initial health reflectivity of its relevant blood oxygen data, the final health reflectivity of each suspected abnormal heart rate data is obtained, and then the data for priority transmission is obtained.

[0036] It should be noted that although the elderly live a very regular life, in reality, it is unlikely that the elderly do the same thing in exactly the same time period. For example, under normal circumstances, the elderly exercise from 9 to 10 o'clock a day, but in some cases, the elderly start exercising at around 9 o'clock, such as 8:59, and end exercising at around 10 o'clock, such as 9:58, so that some of the heart rate data collected by the elderly during exercise will have a certain difference from the historical heart rate data with the same specific collection time, resulting in some of the heart rate data collected by the elderly during exercise being closer to the initial health reflection of some of the heart rate data collected by the elderly when a heart disease such as coronary heart disease attacks, so that when the heart rate data of the elderly when a heart disease such as coronary heart disease attacks is directly obtained through threshold segmentation, the heart rate data collected by some of the elderly during exercise will be mistakenly identified as the heart rate data when a heart disease attacks. Therefore, the initial health reflection of each suspected abnormal heart rate data is corrected.

[0037] It should be further explained that the various physiological indicators of the human body affect each other. For example, when people exercise, due to intense activities, the body needs to consume a lot of energy, which speeds up metabolism. At this time, in order to meet the body's energy consumption needs, the breathing rate increases and the heart beats faster. Due to the increase in heart rate, the heart's oxygen intake and delivery per unit time increase, thereby increasing the body's blood oxygen content; that is, the human heart rate will affect blood oxygen. Therefore, based on the correlation between heart rate and blood oxygen, the initial health reflection of each suspected abnormal heart rate data is corrected.

[0038] It should be further explained that when the initial health reflection degree of each suspected abnormal heart rate data is corrected, when a person's exercise state of the day is advanced, for example, under normal circumstances, the elderly person starts to exercise at 9 o'clock, but the elderly person exercises at 8:59 in one day, so that the heart rate data collected by the elderly person around 8:59 is significantly different from the heart rate data collected at the same specific collection time in other days, resulting in the heart rate data collected around 8:59 having a smaller initial health reflection degree. Because; the heart rate data collected by the elderly person at 8:59 is significantly different from the heart rate data collected at the same specific collection time in other days, the blood oxygen content affected by the heart rate data collected around 8:59 is significantly different from the blood oxygen content collected at the same specific collection time in other days, resulting in the blood oxygen data affected by the heart rate data at 8:59 having a smaller initial health reflection degree. That is, the initial health reflection degree of the heart rate data collected by the elderly person during exercise is the same or smaller than the initial health reflection degree of the blood oxygen data affected by the heart rate data. Since the degree of influence of the heart rate on blood oxygen during exercise does not change significantly, the difference between the initial health reflection degree of a heart rate data collected during exercise and the blood oxygen data affected by the heart rate data is close to the difference between the initial health reflection degree of another heart rate data collected during exercise and the blood oxygen data affected by the heart rate data. Therefore, the initial health reflection degree of each suspected abnormal heart rate data is adjusted according to the initial health reflection degree affected by each suspected abnormal heart rate data.

[0039] It should be further explained that when obtaining the blood oxygen data affected by each suspected abnormal heart rate data, since the blood oxygen data is affected by the heart rate data, the change rate of the abnormal heart rate data is closer to the change rate of the blood oxygen data affected by it. Therefore, according to the difference between each abnormal heart rate and the surrounding heart rate data, and the difference between each blood oxygen data and the surrounding heart rate data, the blood oxygen data affected by each suspected abnormal heart rate data is obtained, and the final health reflection degree of each suspected abnormal heart rate data is obtained.

[0040] Specifically, in the heart rate data sequence to be transmitted, the data before any suspected abnormal heart rate data and closest to the specific collection time of the suspected abnormal heart rate data is transmitted. The heart rate data is recorded as the heart rate comparison data of the suspected abnormal heart rate data. In the blood oxygen data sequence to be transmitted, the data before any blood oxygen data and closest to the specific collection time of the blood oxygen data is recorded as the heart rate comparison data of the suspected abnormal heart rate data. heart rate data, recorded as the blood oxygen comparison data of the blood oxygen data. Among them, the number of comparison data preset in this example is , which is described as an example, and other implementations may be set to other values. Among them, if the heart rate data before a suspected abnormal heart rate data is insufficient Then, from the historical heart rate data with the closest collection day to the abnormal heart rate data, select several historical heart rate data with the largest difference from the specific collection time of the abnormal heart rate data, so that each suspected abnormal heart rate data has If the blood oxygen data sequence to be transmitted is insufficient, Through the above method, blood oxygen comparison data of blood oxygen data is obtained.

[0041] Further, the current blood oxygen data sequence is compared with the first The current blood oxygen data with the same specific collection time as the suspected abnormal heart rate data is recorded as Reference data for suspected abnormal heart rate data.

[0042] Furthermore, the specific calculation formula for obtaining the relevant blood oxygen data of each suspected abnormal heart rate data is as follows: In the formula, Indicates The hysteresis of suspected abnormal heart rate data is The responsiveness, Indicates The value of suspected abnormal heart rate data, Indicates The first suspected abnormal heart rate data The value of the heart rate comparison data, Indicates the number of The first reference data after the suspected abnormal heart rate data Current blood oxygen data, Indicates the number of The first reference data after the suspected abnormal heart rate data The current blood oxygen data The value of the blood oxygen comparison data, Indicates the number of comparison data. represents the absolute value function, represents the longest lag number, is an exponential function with a natural constant as the base. Model to present inverse proportional relationship and normalization, The input of the model is the inverse proportional function and the normalization function. The maximum number of lags preset in this embodiment is , this is used as an example for description, and other values ​​may be set in other implementation modes.

[0043] It should be noted that Indicates The ratio of a suspected abnormal heart rate data to its previous multiple heart rate data reflects the The degree of change of suspected abnormal heart rate data; It indicates the ratio of a blood oxygen data to its previous blood oxygen data, reflecting the degree of change of a blood oxygen data; The smaller the value, the more it indicates the degree of change between the suspected abnormal heart rate data and the blood oxygen data, that is, The blood oxygen data affected by the suspected abnormal heart rate data is likely to be collected after the specific collection time. Blood oxygen data.

[0044] Further, The maximum value corresponds to The value of Hysteresis value of suspected abnormal heart rate data . In the current blood oxygen data sequence, The first The current blood oxygen data is recorded as The relevant blood oxygen data of each suspected abnormal heart rate data. According to the specific collection time of the relevant blood oxygen data of each suspected abnormal heart rate data and the distribution of the surrounding current blood oxygen data, as well as the specific collection time and distribution of the historical blood oxygen data, the initial health reflection degree of the relevant blood oxygen data of each suspected abnormal heart rate data is obtained.

[0045] Furthermore, the specific calculation formula for obtaining the final health reflection degree of each suspected abnormal heart rate data is as follows: In the formula, Indicates The final health reflection of suspected abnormal heart rate data, Indicates the number of suspected abnormal heart rate data. Indicates The initial health reflection of suspected abnormal heart rate data, Indicates The initial health reflection of the blood oxygen data related to the suspected abnormal heart rate data, Indicates The initial health reflection of suspected abnormal heart rate data, Indicates The initial health reflection of the blood oxygen data related to the suspected abnormal heart rate data, represents the absolute value function, is an exponential function with a natural constant as the base. Model to present inverse proportional relationship and normalization, As the input of the model, the implementer can set the inverse proportional function and normalization function according to the actual situation.

[0046] It should be noted that The smaller the value, the The more the initial health reflection of the suspected abnormal heart rate data and the blood oxygen data affected by it conforms to the characteristic that the initial health reflection of the heart rate data collected during the elderly's exercise and the blood oxygen data affected by the heart rate data are the same or the same. The more likely the suspected abnormal heart rate data is the heart rate data collected during the elderly person's exercise; The smaller the value of The closer the difference between the initial health reflection degree of the suspected abnormal heart rate data and the blood oxygen data affected by it is to the difference between the initial health reflection degree of other suspected abnormal heart rate data and the blood oxygen data affected by it, the more it conforms to the characteristic that the degree of influence of the heart rate on the blood oxygen of the elderly during exercise will not change significantly, that is, The greater the possibility that the suspected abnormal heart rate data is the heart rate data collected during the elderly person's exercise.

[0047] Furthermore, a preset reflection threshold , the final health reflection degree is less than the reflection degree threshold The suspected abnormal heart rate data is recorded as the data to be transmitted first. , this is used as an example for description, and other values ​​may be set in other implementation modes.

[0048] At this point, this embodiment is completed.

[0049] The present invention also provides a humanoid elderly care robot, which includes: a data acquisition module, a data detection module, and a data transmission module; wherein the data acquisition module is used to obtain the heart rate data and blood oxygen data of the elderly through a smart bracelet, the data detection module obtains abnormal heart rate data by calling a computer program to implement a method for remote transmission of smart elderly care data, and the data transmission module is used to transmit the heart rate data.

[0050] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for remote transmission of smart elderly care data, characterized in that: The method comprises the following steps: Acquire the elderly person's heart rate data sequence to be transmitted, current blood oxygen data sequence, historical heart rate data sequence and historical blood oxygen data sequence to obtain suspected abnormal heart rate data; the data in the elderly person's heart rate data sequence to be transmitted, current blood oxygen data sequence, historical heart rate data sequence and historical blood oxygen data sequence all correspond to a collection day and a specific collection time; According to the specific collection time of each suspected abnormal heart rate data and the historical heart rate data, the comparative heart rate data of each suspected abnormal heart rate data is obtained; according to the distribution of the heart rate data to be transmitted around each suspected abnormal heart rate data and the distribution of the historical heart rate data around the comparative heart rate data of each suspected abnormal heart rate data, the initial health reflection degree of each suspected abnormal heart rate data is obtained; According to the distribution of the heart rate data to be transmitted around each suspected abnormal heart rate data and the distribution of the current blood oxygen data around each current blood oxygen data, the relevant blood oxygen data of each suspected abnormal heart rate data is obtained, and then the initial health reflectivity of the relevant blood oxygen data of each suspected abnormal heart rate data is obtained; according to the initial health reflectivity of each suspected abnormal heart rate data, the difference and distribution of the initial health reflectivity of each suspected abnormal heart rate data and the initial health reflectivity of its relevant blood oxygen data, the final health reflectivity of each suspected abnormal heart rate data is obtained, and then the data for priority transmission is obtained.

2. According to claim 1, a method for remote transmission of smart elderly care data is characterized in that: The specific method of obtaining the suspected abnormal heart rate data includes: Preset abnormal threshold , the heart rate data sequence to be transmitted is greater than the abnormal threshold The heart rate data to be transmitted is recorded as suspected abnormal heart rate data.

3. According to claim 1, a method for remote transmission of smart elderly care data is characterized in that: The specific method of obtaining the comparative heart rate data of each suspected abnormal heart rate data according to the specific collection time of each suspected abnormal heart rate data and the historical heart rate data includes: The historical heart rate data sequence of the elderly is combined with the The historical heart rate data with the same specific collection time as the suspected abnormal heart rate data is recorded as Compare the heart rate data of suspected abnormal heart rate data.

4. According to claim 1, a method for remote transmission of smart elderly care data is characterized in that: The initial health reflection degree of each suspected abnormal heart rate data is obtained according to the distribution of the heart rate data to be transmitted around each suspected abnormal heart rate data and the distribution of the historical heart rate data around the comparison heart rate data of each suspected abnormal heart rate data, including the specific method of: The heart rate data sequence to be transmitted will be The specific collection time of the suspected abnormal heart rate data is closest to data, recorded as Control heart rate data of suspected abnormal heart rate data; among them, Indicates the number of preset control heart rate data; Get the The specific calculation formula for the heart rate change rate of suspected abnormal heart rate data is as follows: In the formula, Indicates The heart rate change rate of suspected abnormal heart rate data, Indicates the number of control heart rate data, Indicates The value of suspected abnormal heart rate data, Indicates The first suspected abnormal heart rate data The value of the control heart rate data, represents the absolute value function; Get the Compare the suspected abnormal heart rate data with the heart rate data of several control heart rate data to obtain the first The heart rate change rate of the compared heart rate data of suspected abnormal heart rate data; According to The heart rate change rate of the suspected abnormal heart rate data and the heart rate change rate of the comparison heart rate data are obtained. The initial health reflection of suspected abnormal heart rate data.

5. A method for remote transmission of smart elderly care data according to claim 4, characterized in that: According to the The heart rate change rate of the suspected abnormal heart rate data and the heart rate change rate of the comparison heart rate data are obtained. The initial health reflection of suspected abnormal heart rate data includes the following specific methods: In the formula, Indicates The initial health reflection of suspected abnormal heart rate data, Indicates The number of heart rate data to be compared with suspected abnormal heart rate data, Indicates The heart rate change rate of suspected abnormal heart rate data, Indicates The first suspected abnormal heart rate data The heart rate change rate of the compared heart rate data, represents the absolute value function, is an exponential function with a natural constant as its base.

6. A method for remote transmission of smart elderly care data according to claim 1, characterized in that: The method of obtaining the blood oxygen data related to each suspected abnormal heart rate data according to the distribution of the heart rate data to be transmitted around each suspected abnormal heart rate data and the distribution of the current blood oxygen data around each current blood oxygen data comprises the following specific methods: In the heart rate data sequence to be transmitted, the data before any suspected abnormal heart rate data and closest to the specific collection time of the suspected abnormal heart rate data is transmitted. The heart rate data is recorded as the heart rate comparison data of the suspected abnormal heart rate data; In the blood oxygen data sequence to be transmitted, the data before any blood oxygen data and closest to the specific collection time of the blood oxygen data The heart rate data is recorded as the blood oxygen comparison data of the blood oxygen data; Combine the current blood oxygen data sequence with the The current blood oxygen data with the same specific collection time as the suspected abnormal heart rate data is recorded as Reference data of suspected abnormal heart rate data; Get the The specific calculation formula for the blood oxygen data related to suspected abnormal heart rate data is as follows: In the formula, Indicates The hysteresis of suspected abnormal heart rate data is The responsiveness, Indicates The value of suspected abnormal heart rate data, Indicates The first suspected abnormal heart rate data The value of the heart rate comparison data, Indicates the number of The first reference data after the suspected abnormal heart rate data Current blood oxygen data, Indicates the number of The first reference data after the suspected abnormal heart rate data The current blood oxygen data The value of the blood oxygen comparison data, Indicates the number of comparison data. represents the absolute value function, Indicates the preset maximum number of lags, is an exponential function with a natural constant as base; Will The maximum value corresponds to The value of Hysteresis value of suspected abnormal heart rate data ; In the current blood oxygen data sequence, The first The current blood oxygen data is recorded as The blood oxygen data related to suspected abnormal heart rate data.

7. A method for remote transmission of smart elderly care data according to claim 4, characterized in that: The specific method of obtaining the initial health reflection degree of the blood oxygen data related to each suspected abnormal heart rate data includes: According to the specific collection time of the blood oxygen data related to each suspected abnormal heart rate data and the distribution of the surrounding current blood oxygen data, as well as the specific collection time and distribution of the historical blood oxygen data, the initial health reflection degree of the blood oxygen data related to each suspected abnormal heart rate data is obtained.

8. The method for remote transmission of smart elderly care data according to claim 1 is characterized in that: The method of obtaining the final health reflectivity of each suspected abnormal heart rate data according to the initial health reflectivity of each suspected abnormal heart rate data and the difference and distribution between the initial health reflectivity of each suspected abnormal heart rate data and the initial health reflectivity of its related blood oxygen data includes: In the formula, Indicates The final health reflection of suspected abnormal heart rate data, Indicates the number of suspected abnormal heart rate data. Indicates The initial health reflection of suspected abnormal heart rate data, Indicates The initial health reflection of the blood oxygen data related to the suspected abnormal heart rate data, Indicates The initial health reflection of suspected abnormal heart rate data, Indicates The initial health reflection of the blood oxygen data related to the suspected abnormal heart rate data, represents the absolute value function, is an exponential function with a natural constant as its base.

9. The method for remote transmission of smart elderly care data according to claim 1 is characterized in that: The data to be transmitted with priority includes the following specific methods: Preset responsiveness threshold , the final health reflection degree is less than the reflection degree threshold The suspected abnormal heart rate data is recorded as the data for priority transmission.

10. A humanoid elderly care robot, characterized in that: The robot comprises: Data acquisition module, data detection module, data transmission module; the data acquisition module is used to obtain the heart rate data and blood oxygen data of the elderly through a smart bracelet; the data detection module obtains abnormal heart rate data by calling a computer program to implement the steps of a smart elderly care data remote transmission method as described in any one of claims 1-9; the data transmission module is used to transmit the heart rate data.

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