Old people health condition monitoring system based on wristband oximeter

Abstract

The invention particularly relates to an old people health condition monitoring system based on a wristband oximeter. The system comprises a state determination module; a motion index module; a fatigue index module; and an analysis processing module. According to the system, the wrist strap type oximeter obtains the exercise step number, monitors key physiological parameters such as the blood oxygen saturation degree, the pulse rate and the perfusion index, and deeply analyzes the parameters in different exercise states to obtain the exercise index, the fatigue index and the cooperation index, so that the multi-dimensional comprehensive monitoring of the health condition of the old people is realized; the physical state of the old people can be reflected more accurately, and potential health problems can be found in time.

Description

Technical Field

[0001] The present invention relates to the field of medical health technology, and in particular to a health status monitoring system for the elderly based on a wristband oximeter. Background Art

[0002] At present, wristband oximeters, as a convenient wearable device, have been widely used in the field of elderly health monitoring because they can monitor the body's basic physiological parameters such as blood oxygen saturation and pulse rate in real time and non-invasively.

[0003] However, existing wristband oximeter-based monitoring systems generally have functional limitations. Most can only achieve simple recording of a single or a few physiological parameters, and cannot deeply explore the rich information about the overall health status of the elderly contained in these data. For example, it is impossible to effectively combine the physiological parameters with the exercise status for comprehensive analysis, it is difficult to accurately assess the changes in the physical functions of the elderly in different activity states, and it is impossible to timely detect potential health risks such as fatigue and abnormal movement, and it is even more impossible to provide comprehensive and targeted health warnings and guidance for the elderly and their guardians.

[0004] Therefore, a health status monitoring system for the elderly based on a wristband oximeter is needed to solve the above-mentioned problems. Summary of the invention

[0005] The purpose of the present invention is to solve the above problems and to propose a health status monitoring system for the elderly based on a wristband oximeter.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions: The elderly health status monitoring system based on wristband oximeter includes the following parts: State determination module: obtains the wearer's exercise steps through a wrist-worn oximeter and analyzes the exercise steps to obtain the exercise state; Motion index module: based on the obtained motion state, obtain the parameter information respectively monitored by the wrist oximeter in each motion state; and analyze the parameter information respectively monitored in each motion state to obtain the motion index corresponding to each motion state; wherein the parameter information includes blood oxygen saturation, pulse rate, and perfusion index; Fatigue index module: analyzes the process of each parameter information returning from each motion state to the relaxation state in turn, so as to obtain the fatigue index; Analysis and processing module: Comprehensively analyze the motion index and fatigue index to obtain the evaluation index, and analyze the obtained evaluation index to perform corresponding early warning processing.

[0007] Preferably, the method of obtaining the number of steps of the wearer through a wristband oximeter and analyzing the number of steps to obtain the exercise state specifically includes the following parts: At preset time intervals, the number of exercise steps of the wearer is obtained through a wristband oximeter, the difference between two adjacent exercise steps obtained in the time series is calculated, the difference calculation result is divided by the time interval, and the absolute value is taken to obtain the step frequency; different step frequencies are preset to correspond to different exercise states, so as to determine the exercise state corresponding to the step frequency; the exercise state is divided into a relaxation state, a walking state, and a running state.

[0008] Preferably, the analysis of the parameter information respectively monitored in each motion state specifically includes the following parts: Obtaining parameter information corresponding to a number of wristband oximeter wearers when their exercise state is a relaxed state, and calculating the mean of the blood oxygen saturation, pulse rate, and perfusion index in the parameter information in turn to obtain the mean value of the blood oxygen saturation, the mean value of the pulse rate, and the mean value of the perfusion index; The mean values ​​of the parameter information measured when the exercise state is in a relaxed state are used as the standard values ​​corresponding to the blood oxygen saturation, pulse rate, and perfusion index respectively; Obtain the parameter information corresponding to each motion state, and perform difference calculations on the parameter information and the corresponding standard value in turn to obtain the standard difference value of the parameter information corresponding to each motion state; The allowable fluctuation range of the parameter information standard deviation value corresponding to each motion state is preset, and the parameter information data standard deviation value that is not within the allowable fluctuation range is recorded as the parameter information standard deviation value, and the duration corresponding to each parameter information standard deviation value is obtained in turn, recorded as the abnormal duration, and marked as ,in is the motion state number, ; is the number of each parameter, ; The number of parameter information standard difference values ​​corresponding to each motion state is counted, and it is divided by the duration of each motion state to obtain the frequency of occurrence of parameter information standard difference values ​​corresponding to each motion state, which is recorded as abnormal frequency and marked as ; Extract the parameter information standard difference value corresponding to each motion state, and the corresponding maximum parameter information standard difference value is recorded as the difference extreme value and marked as ; The abnormal duration , abnormal frequency , Difference extreme value Substituting into the formula: , get the motion index in each motion state ,in , , They are the allowable abnormal duration, maximum allowable abnormal frequency, and maximum allowable difference extreme value of the corresponding parameters under each motion state. , , They are the weight factors corresponding to the abnormal duration, abnormal frequency and extreme value of difference of the corresponding parameters in each motion state.

[0009] Preferably, the process of sequentially analyzing each parameter information when returning from each motion state to a relaxation state, so as to obtain a fatigue index, specifically includes the following parts: The moment when the number of steps of the wearer detected by the wristband oximeter changes from the step frequency corresponding to each exercise state to the step frequency corresponding to the relaxation state is recorded as the starting moment; and each parameter information of the wearer of the wristband oximeter is obtained at a set time interval from the starting moment, and each parameter information obtained is analyzed; The time taken by the wearer to transition from each exercise state to a relaxed state is recorded as the actual recovery time and marked as ; The acceleration values ​​recorded by the acceleration sensor of the wrist-worn oximeter in the X, Y, and Z axis directions are obtained at set time intervals and marked as , , The subsequent entry formula is: , get the acceleration amplitude obtained at each time interval; According to the time series, the next acceleration amplitude in the adjacent time interval is subtracted from the previous acceleration amplitude to obtain the adjacent acceleration amplitude difference; the relaxation amplitude threshold is preset, and the time when the adjacent acceleration amplitude difference is less than the relaxation amplitude threshold is marked as the relaxation recovery time, and the relaxation recovery time used to transition from each motion state to the relaxation state is obtained and marked as ; Obtain the age and gender of the current elderly person, extract the age value ranges corresponding to different genders from the pre-built database, and set each age value range corresponding to different genders to correspond to a standard time used in a relaxation state and a standard relaxation recovery time; Based on the specific gender of the elderly, the elderly's age is matched with the corresponding age range, so as to determine the standard time used for the relaxation state and the standard relaxation recovery time; The actual recovery time and relaxation recovery time Substituting into the formula: , get the fatigue index ,in The standard time for transitioning from each exercise state to a relaxed state, It is the standard relaxation recovery time used to transition from each exercise state to the relaxation state. is the weight factor corresponding to the actual recovery time of each motion state, is the weight factor corresponding to the actual relaxation recovery time of each motion state, is the preset matching index.

[0010] Preferably, after normalizing the motion index of each motion state and the matching index corresponding to each motion state, a bottom circle model is established with the motion index of each motion state as the radius, and a cone model is established with the matching index corresponding to each motion state as the height, and the volume of the cone model corresponding to each motion state is calculated, and the obtained volume of the cone model is recorded as the evaluation index of each motion state in turn.

[0011] Preferably, the method for obtaining the matching index specifically includes the following parts: The acceleration amplitude obtained by the wristband oximeter at each time interval is obtained at a preset time interval, and a sleep acceleration amplitude threshold is preset. The acceleration amplitude obtained at each time interval is compared with the sleep acceleration amplitude threshold, and the time intervals corresponding to the acceleration amplitudes that are continuously smaller than the sleep acceleration amplitude threshold in the time series are accumulated to obtain a single quiet time. A sleep duration threshold is preset, and a single quiet duration greater than the sleep duration threshold is marked as a single sleep duration, and all single sleep durations are accumulated to obtain the total sleep duration; Obtain the pulse rate monitored in the time interval corresponding to each single sleep duration, preset a resting pulse rate range, and compare the pulse rate monitored in the time interval corresponding to each single sleep duration with the resting pulse rate range in turn, and mark the time interval corresponding to the single sleep duration that is not within the resting pulse rate range as an abnormal time interval; The duration corresponding to all abnormal time intervals is accumulated and marked as the awake time; the actual sleep time is obtained by subtracting the awake time from the total sleep time; the sleep time standard value is preset, and the actual sleep time is divided by the sleep time standard value to obtain the sleep ratio; Obtain the time interval corresponding to the actual sleep time, and obtain the acceleration values ​​monitored in the X, Y, and Z axis directions within the time interval, and respectively preset the turning over acceleration thresholds in the X, Y, and Z axis directions; record the moment when the acceleration values ​​on the X, Y, and Z axis directions within the preset time length are greater than or equal to the corresponding turning over acceleration thresholds as the turning over moment; accumulate the number of all turning over moments and mark them as the number of turning over; preset the normal number of turning over, and divide the number of turning over by the normal number of turning over to obtain the turning over ratio; The sleep ratio value is used as the two right-angled sides of a right triangle, and the ends of the two right-angled sides are connected with a straight line to obtain a complete right triangle, and the right triangle is used as the base of the triangular pyramid; the turning over ratio is used as the height of the triangular pyramid, a triangular pyramid model is established, and the volume of the triangular pyramid is calculated and recorded as the fitting index.

[0012] Preferably, the obtained evaluation index is analyzed to perform corresponding early warning processing, which specifically includes the following parts: The evaluation index threshold is preset. If the evaluation index is greater than the evaluation index threshold, the motion index, fatigue index, and coordination index are compared with their corresponding thresholds respectively: If the motion index is greater than the threshold, the abnormal duration, abnormal frequency, and extreme difference value corresponding to the motion index are marked as abnormal motion information, and the abnormal motion information is sent to the smart terminal to which the guardian of the wristband oximeter is bound; If the fatigue index is greater than the threshold, the actual recovery time and relaxation recovery time corresponding to the fatigue index are marked as fatigue abnormality information, and the fatigue abnormality information is sent to the smart terminal to which the guardian of the wristband oximeter is bound; If the coordination index is greater than its threshold, the sleep ratio and turning ratio corresponding to the coordination index are marked as coordination abnormality information, and the coordination abnormality information is sent to the smart terminal to which the guardian of the wristband oximeter is bound.

[0013] Preferably, the analysis of the obtained evaluation index to perform corresponding early warning processing also includes the following parts: The evaluation index is obtained at set time intervals, and the obtained evaluation indexes are arranged in chronological order from left to right. If the adjacent evaluation indexes in the time series are greater than the preset evaluation index threshold, then on the basis of the original warning, a vibration reminder is sent to the wrist-band oximeter worn by the elderly, and a communication connection is established with a medical institution that cooperates with the manufacturer of the wrist-band oximeter. The elderly's evaluation index and the corresponding exercise index, fatigue index, and cooperation index are sent to the medical institution, requesting the medical institution to arrange medical staff to conduct a health check on the elderly at home, or assist the elderly to go to the hospital for examination.

[0014] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. The present invention obtains the number of exercise steps through a wristband oximeter, and also monitors key physiological parameters such as blood oxygen saturation, pulse rate, perfusion index, etc., and conducts in-depth analysis of these parameters under different exercise states to obtain exercise index, fatigue index and cooperation index, etc., thereby realizing multi-dimensional and comprehensive monitoring of the health status of the elderly, which can more accurately reflect the physical condition of the elderly and discover potential health problems in a timely manner.

[0015] 2. The present invention presets the threshold of the evaluation index and the thresholds of the exercise index, fatigue index and coordination index. When the evaluation index exceeds the threshold, it will further compare and analyze the sub-indexes, and send the abnormal information to the smart terminal bound to the guardian's account in time, so that the guardian can understand the abnormal health conditions of the elderly at the first time, realize layered early warning, and improve the accuracy and effectiveness of the early warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Further details, features and advantages of the present application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which: Figure 1 is a flow chart of the present invention; DETAILED DESCRIPTION

[0017] Several embodiments of the present application will be described in more detail below with reference to the accompanying drawings so that those skilled in the art can implement the present application. The present application can be embodied in many different forms and purposes and should not be limited to the embodiments described herein. These embodiments are provided to make the present application comprehensive and complete, and to fully convey the scope of the present application to those skilled in the art. The embodiments do not limit the present application.

[0018] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those of ordinary skill in the art to which this application belongs. It will be further understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the relevant art and / or the context of this specification, and will not be interpreted in an idealized or overly formal sense unless explicitly defined as such herein.

[0019] See also Figure 1 As shown, the present invention provides a technical solution: The elderly health status monitoring system based on wristband oximeter includes the following parts: State determination module: obtains the wearer's exercise steps through a wrist-worn oximeter and analyzes the exercise steps to obtain the exercise state, which specifically includes the following parts: Among them, obtaining the number of steps of the wearer through a wrist-band oximeter is an existing technology. Specifically, when the wearer of the wrist-band oximeter walks, his arm swings to produce regular acceleration changes. After the sensor captures these change signals, it is processed by an algorithm and converted into corresponding step data; At preset time intervals, the number of steps of the wearer is obtained through a wrist oximeter, the difference between two consecutive steps in the time series is calculated, the difference calculation result is divided by the time interval, and the absolute value is taken to obtain the step frequency; different step frequencies are preset to correspond to different exercise states, so as to determine the exercise state corresponding to the step frequency; the exercise state is divided into a relaxed state, a walking state, and a running state; Motion index module: based on the obtained motion state, obtain the parameter information respectively monitored by the wrist oximeter in each motion state; and analyze the parameter information respectively monitored in each motion state to obtain the motion index corresponding to each motion state; wherein the parameter information includes blood oxygen saturation, pulse rate, and perfusion index; Wrist-type oximeters usually use photoelectric transmission measurement, based on the principle that the amount of light absorbed by arterial blood changes with arterial pulsation, to detect blood oxygen saturation, pulse rate, and perfusion index. The specific process is as follows: Blood oxygen saturation: The wrist-worn oximeter has two built-in light-emitting diodes of different wavelengths, one emitting red light and the other emitting near-infrared light. When the oximeter is turned on and worn correctly on the wrist, the two LEDs will emit light alternately, and the light will pass through the skin, tissues, blood vessels, etc. The built-in microprocessor of the oximeter will calculate the blood oxygen saturation through a specific algorithm based on the intensity ratio of the red light and near-infrared light received by the detector. Pulse rate detection: The microprocessor in the oximeter analyzes and processes the intensity fluctuations of the light signal reflecting the arterial pulsation received by the detector, and calculates the number of arterial pulsations per unit time (usually per minute), that is, the pulse rate; Perfusion index detection: The microprocessor analyzes and calculates the pulsation component and DC component in the optical signal received by the detector to obtain the perfusion index; The parameter information monitored for each motion state is analyzed to obtain the motion index corresponding to each motion state, which specifically includes the following parts: Obtaining parameter information corresponding to a number of wristband oximeter wearers when their exercise state is a relaxed state, and calculating the mean of the blood oxygen saturation, pulse rate, and perfusion index in the parameter information in turn to obtain the mean value of the blood oxygen saturation, the mean value of the pulse rate, and the mean value of the perfusion index; The mean values ​​of the parameter information measured when the exercise state is in a relaxed state are used as the standard values ​​corresponding to the blood oxygen saturation, pulse rate, and perfusion index respectively; Obtain the parameter information corresponding to each motion state, and perform difference calculations on the parameter information and the corresponding standard value in turn to obtain the standard difference value of the parameter information corresponding to each motion state; The allowable fluctuation range of the parameter information standard deviation value corresponding to each motion state is preset, and the parameter information data standard deviation value that is not within the allowable fluctuation range is recorded as the parameter information standard deviation value, and the duration corresponding to each parameter information standard deviation value is obtained in turn, recorded as the abnormal duration, and marked as ,in is the motion state number, ; is the number of each parameter, ; The number of parameter information standard difference values ​​corresponding to each motion state is counted, and it is divided by the duration of each motion state to obtain the frequency of occurrence of parameter information standard difference values ​​corresponding to each motion state, which is recorded as abnormal frequency and marked as ; Extract the parameter information standard difference value corresponding to each motion state, and the corresponding maximum parameter information standard difference value is recorded as the difference extreme value and marked as ; The abnormal duration , abnormal frequency , Difference extreme value Substituting into the formula: , get the motion index in each motion state ,in , , They are the allowable abnormal duration, maximum allowable abnormal frequency, and maximum allowable difference extreme value of the corresponding parameters under each motion state. , , They are the weight factors corresponding to the abnormal duration, abnormal frequency and extreme difference value of the corresponding parameters under each motion state; Fatigue index module: analyzes the process of each parameter information returning from each motion state to the relaxation state in turn, so as to obtain the fatigue index; It includes the following parts: The moment when the number of steps of the wearer detected by the wristband oximeter changes from the step frequency corresponding to each exercise state to the step frequency corresponding to the relaxation state is recorded as the starting moment; and each parameter information of the wearer of the wristband oximeter is obtained at a set time interval from the starting moment, and each parameter information obtained is analyzed; The time taken by the wearer to transition from each exercise state to a relaxed state is recorded as the actual recovery time and marked as ; The acceleration values ​​recorded by the acceleration sensor of the wrist-worn oximeter in the X, Y, and Z axis directions are obtained at set time intervals and marked as , , The subsequent entry formula is: , get the acceleration amplitude obtained at each time interval; According to the time series, the next acceleration amplitude in the adjacent time interval is subtracted from the previous acceleration amplitude to obtain the adjacent acceleration amplitude difference; the relaxation amplitude threshold is preset, and the time when the adjacent acceleration amplitude difference is less than the relaxation amplitude threshold is marked as the relaxation recovery time, and the relaxation recovery time used to transition from each motion state to the relaxation state is obtained and marked as ; Obtain the age and gender of the current elderly person, extract the age value ranges corresponding to different genders from the pre-built database, and set each age value range corresponding to different genders to correspond to a standard time used in a relaxation state and a standard relaxation recovery time; Based on the specific gender of the elderly, the elderly's age is matched with the corresponding age range, so as to determine the standard time used for the relaxation state and the standard relaxation recovery time; The actual recovery time and relaxation recovery time Substituting into the formula: , get the fatigue index ,in The standard time for transitioning from each exercise state to a relaxed state, It is the standard relaxation recovery time used to transition from each exercise state to the relaxation state. is the weight factor corresponding to the actual recovery time of each motion state, is the weight factor corresponding to the actual relaxation recovery time of each motion state, is the preset matching index; The actual recovery time Greater than 0. Its value range usually depends on the intensity of the elderly's exercise state and the ability of their body functions to recover. Generally speaking, the actual recovery time under more intense exercise will be relatively long, ranging from several minutes to several hours. The specific value will vary with the accumulation of monitoring data and the differences between different individuals. Relaxation recovery time It is also greater than 0. Its length is related to the degree of muscle relaxation and the overall coordination recovery of the elderly after exercise. The value range is usually between several minutes and tens of minutes. Different sports and exercise duration will have an impact on it. The preset coordination index is a comprehensive indicator that reflects the correlation between the elderly's sleep quality and their body recovery status. When the coordination index is high, it means that the elderly have good sleep quality and their body recovers better during sleep. When calculating the fatigue index, the matching index can appropriately reduce the influence weight of the actual recovery time and relaxation recovery time on the fatigue index, that is, it plays a certain regulatory role, so that the fatigue index can more truly reflect the physical fatigue state; For example, if the coordination index is 1.2 (assuming that it is measured with a certain baseline value of 1), it means that the sleep quality is good. When calculating the fatigue index, the fatigue index can be appropriately reduced. and The actual effect of the coordination index is to ensure that the calculated fatigue index will not be exaggerated due to a slightly longer recovery time; on the contrary, if the coordination index is low, such as 0.8, it means that the sleep quality is poor and the body recovery may be affected. At this time, it can be appropriately strengthened. and The fatigue index can better reflect the fatigue state of the body; The specific method of obtaining the coordination index includes the following parts: The acceleration amplitude obtained by the wristband oximeter at each time interval is obtained at a preset time interval, and a sleep acceleration amplitude threshold is preset. The acceleration amplitude obtained at each time interval is compared with the sleep acceleration amplitude threshold, and the time intervals corresponding to the acceleration amplitudes that are continuously smaller than the sleep acceleration amplitude threshold in the time series are accumulated to obtain a single quiet time. A sleep duration threshold is preset, and a single quiet duration greater than the sleep duration threshold is marked as a single sleep duration, and all single sleep durations are accumulated to obtain the total sleep duration; Obtain the pulse rate monitored in the time interval corresponding to each single sleep duration, preset a resting pulse rate range, and compare the pulse rate monitored in the time interval corresponding to each single sleep duration with the resting pulse rate range in turn, and mark the time interval corresponding to the single sleep duration that is not within the resting pulse rate range as an abnormal time interval; The duration corresponding to all abnormal time intervals is accumulated and marked as the awake time; the actual sleep time is obtained by subtracting the awake time from the total sleep time; the sleep time standard value is preset, and the actual sleep time is divided by the sleep time standard value to obtain the sleep ratio; Obtain the time interval corresponding to the actual sleep time, and obtain the acceleration values ​​monitored in the X, Y, and Z axis directions within the time interval, and respectively preset the turning over acceleration thresholds in the X, Y, and Z axis directions; record the moment when the acceleration values ​​on the X, Y, and Z axis directions within the preset time length are greater than or equal to the corresponding turning over acceleration thresholds as the turning over moment; accumulate the number of all turning over moments and mark them as the number of turning over; preset the normal number of turning over, and divide the number of turning over by the normal number of turning over to obtain the turning over ratio; The sleeping ratio is used as the two right-angled sides of a right triangle, and the ends of the two right-angled sides are connected with a straight line to obtain a complete right triangle, and the right triangle is used as the base of the triangular pyramid; the turning over ratio is used as the height of the triangular pyramid, a triangular pyramid model is established, and the volume of the triangular pyramid is calculated and recorded as the matching index; Analysis and processing module: Comprehensively analyze the motion index and fatigue index to obtain the evaluation index, and analyze the obtained evaluation index to perform corresponding early warning processing, including: After normalizing the motion index of each motion state and the matching index corresponding to each motion state, a bottom circle model is established with the motion index of each motion state as the radius, and a cone model is established with the matching index corresponding to each motion state as the height, and the volume of the cone model corresponding to each motion state is calculated respectively, and the volume of the cone model obtained is recorded as the evaluation index of each motion state in turn; The obtained evaluation index is analyzed to carry out corresponding early warning processing, which specifically includes the following parts: The evaluation index threshold is preset. If the evaluation index is greater than the evaluation index threshold, the motion index, fatigue index, and coordination index are compared with their corresponding thresholds respectively: If the motion index is greater than the threshold, the abnormal duration, abnormal frequency, and extreme difference value corresponding to the motion index are marked as abnormal motion information, and the abnormal motion information is sent to the smart terminal to which the guardian of the wristband oximeter is bound; If the fatigue index is greater than the threshold, the actual recovery time and relaxation recovery time corresponding to the fatigue index are marked as fatigue abnormality information, and the fatigue abnormality information is sent to the smart terminal to which the guardian of the wristband oximeter is bound; If the coordination index is greater than the threshold, the sleep ratio and turning ratio corresponding to the coordination index are marked as coordination abnormality information, and the coordination abnormality information is sent to the smart terminal to which the guardian of the wristband oximeter is bound; Also includes the following sections: The evaluation index is obtained at set time intervals, and the obtained evaluation indexes are arranged in chronological order from left to right. If the adjacent evaluation indexes in the time series are greater than the preset evaluation index threshold, then on the basis of the original warning, a vibration reminder is sent to the wrist-band oximeter worn by the elderly, and a communication connection is established with a medical institution that cooperates with the manufacturer of the wrist-band oximeter. The elderly's evaluation index and the corresponding exercise index, fatigue index, and cooperation index are sent to the medical institution, requesting the medical institution to arrange medical staff to conduct a health check on the elderly at home, or assist the elderly to go to the hospital for examination.

[0020] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The influencing weight factor and specific coefficient value in the formula are set by technical personnel in this field according to actual conditions, and can be adjusted and modified later.

[0021] The above description of the embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A health status monitoring system for the elderly based on a wristband oximeter, characterized in that: Includes the following sections: State determination module: obtains the wearer's exercise steps through a wrist-worn oximeter and analyzes the exercise steps to obtain the exercise state; Motion index module: based on the obtained motion state, obtain the parameter information respectively monitored by the wrist oximeter in each motion state; and analyze the parameter information respectively monitored in each motion state to obtain the motion index corresponding to each motion state; wherein the parameter information includes blood oxygen saturation, pulse rate, and perfusion index; Fatigue index module: analyzes the process of each parameter information returning from each motion state to the relaxation state in turn, so as to obtain the fatigue index; Analysis and processing module: Comprehensively analyze the motion index and fatigue index to obtain the evaluation index, and analyze the obtained evaluation index to perform corresponding early warning processing.

2. The elderly health status monitoring system based on a wristband oximeter according to claim 1 is characterized in that: The method of obtaining the number of steps of the wearer through the wristband oximeter and analyzing the number of steps to obtain the exercise state specifically includes the following parts: At preset time intervals, the number of exercise steps of the wearer is obtained through a wristband oximeter, the difference between two adjacent exercise steps obtained in the time series is calculated, the difference calculation result is divided by the time interval, and the absolute value is taken to obtain the step frequency; different step frequencies are preset to correspond to different exercise states, so as to determine the exercise state corresponding to the step frequency; the exercise state is divided into a relaxation state, a walking state, and a running state.

3. The elderly health status monitoring system based on a wristband oximeter according to claim 2 is characterized in that: The analysis of the parameter information monitored in each motion state specifically includes the following parts: Obtaining parameter information corresponding to a number of wristband oximeter wearers when their exercise state is a relaxed state, and calculating the mean of the blood oxygen saturation, pulse rate, and perfusion index in the parameter information in turn to obtain the mean of the blood oxygen saturation, the mean of the pulse rate, and the mean of the perfusion index; The mean values ​​of the parameter information measured when the exercise state is in a relaxed state are used as the standard values ​​corresponding to the blood oxygen saturation, pulse rate, and perfusion index respectively; Obtain the parameter information corresponding to each motion state, and perform difference calculations on the parameter information and the corresponding standard value in turn to obtain the standard difference value of the parameter information corresponding to each motion state; The allowable fluctuation range of the parameter information standard deviation value corresponding to each motion state is preset, and the parameter information data standard deviation value that is not within the allowable fluctuation range is recorded as the parameter information standard deviation value, and the duration corresponding to each parameter information standard deviation value is obtained in turn, recorded as the abnormal duration, and marked as ,in is the motion state number, ; is the number of each parameter, ; The number of parameter information standard difference values ​​corresponding to each motion state is counted, and it is divided by the duration of each motion state to obtain the frequency of occurrence of parameter information standard difference values ​​corresponding to each motion state, which is recorded as abnormal frequency and marked as ; Extract the parameter information standard difference value corresponding to each motion state, and the corresponding maximum parameter information standard difference value is recorded as the difference extreme value and marked as .

4. The elderly health status monitoring system based on a wristband oximeter according to claim 3 is characterized in that: The step of obtaining the motion index corresponding to each motion state specifically includes the following parts: The abnormal duration , abnormal frequency , Difference extreme value Substituting into the formula: , get the motion index in each motion state ,in , , They are the allowable abnormal duration, maximum allowable abnormal frequency, and maximum allowable difference extreme value of the corresponding parameters under each motion state. , , They are the weight factors corresponding to the abnormal duration, abnormal frequency and extreme value of difference of the corresponding parameters in each motion state.

5. The elderly health status monitoring system based on a wristband oximeter according to claim 1 is characterized in that: The process of successively analyzing each parameter information from each motion state to the relaxation state, thereby obtaining a fatigue index, specifically includes the following parts: The moment when the number of steps of the wearer detected by the wristband oximeter changes from the step frequency corresponding to each exercise state to the step frequency corresponding to the relaxation state is recorded as the starting moment; and each parameter information of the wearer of the wristband oximeter is obtained at a set time interval from the starting moment, and each parameter information obtained is analyzed; The time taken by the wearer to transition from each exercise state to a relaxed state is recorded as the actual recovery time and marked as ; The acceleration values ​​recorded by the acceleration sensor of the wrist-worn oximeter in the X, Y, and Z axis directions are obtained at set time intervals and marked as , , The subsequent entry formula is: , get the acceleration amplitude obtained at each time interval; According to the time series, the next acceleration amplitude in the adjacent time interval is subtracted from the previous acceleration amplitude to obtain the difference between the adjacent acceleration amplitudes; A relaxation amplitude threshold is preset, and the time when the adjacent acceleration amplitude difference is less than the relaxation amplitude threshold is marked as the relaxation recovery time, and the relaxation recovery time used to transition from each motion state to the relaxation state is obtained and marked as ; Obtain the age and gender of the current elderly person, extract the age value ranges corresponding to different genders from the pre-built database, and set each age value range corresponding to different genders to correspond to a standard time used in a relaxation state and a standard relaxation recovery time; Based on the specific gender of the elderly, the age of the elderly is matched with the corresponding age value range, so as to determine the standard time used for the relaxation state and the standard relaxation recovery time; The actual recovery time and relaxation recovery time Substituting into the formula: , get the fatigue index ,in The standard time for transitioning from each exercise state to a relaxed state, It is the standard relaxation recovery time used to transition from each exercise state to the relaxation state. is the weight factor corresponding to the actual recovery time of each motion state, is the weight factor corresponding to the actual relaxation recovery time of each motion state, is the preset matching index.

6. The elderly health status monitoring system based on a wristband oximeter according to claim 5 is characterized in that: The method for obtaining the matching index specifically includes the following parts: The acceleration amplitude obtained by the wristband oximeter at each time interval is obtained at a preset time interval, and a sleep acceleration amplitude threshold is preset. The acceleration amplitude obtained at each time interval is compared with the sleep acceleration amplitude threshold, and the time intervals corresponding to the acceleration amplitudes that are continuously smaller than the sleep acceleration amplitude threshold in the time series are accumulated to obtain a single quiet time. A sleep duration threshold is preset, and a single quiet duration greater than the sleep duration threshold is marked as a single sleep duration, and all single sleep durations are accumulated to obtain the total sleep duration; Obtain the pulse rate monitored in the time interval corresponding to each single sleep duration, preset a resting pulse rate range, and compare the pulse rate monitored in the time interval corresponding to each single sleep duration with the resting pulse rate range in turn, and mark the time interval corresponding to the single sleep duration that is not within the resting pulse rate range as an abnormal time interval; The duration corresponding to all abnormal time intervals is accumulated and marked as the awake time; the actual sleep time is obtained by subtracting the awake time from the total sleep time; The sleep duration standard value is preset, and the actual sleep duration is divided by the sleep duration standard value to obtain the sleep ratio; Obtain the time interval corresponding to the actual sleep time, and obtain the acceleration values ​​monitored in the X, Y, and Z axis directions during the time interval, and respectively preset the turning over acceleration thresholds in the X, Y, and Z axis directions; record the moment when the acceleration values ​​on the X, Y, and Z axis directions are greater than or equal to the corresponding turning over acceleration thresholds within the preset time as the turning over moment; accumulate the number of all turning over moments and mark them as the number of turning over times; The normal number of turning over is preset, and the turning over ratio is obtained by dividing the number of turning over by the normal number of turning over.

7. The elderly health status monitoring system based on a wristband oximeter according to claim 6 is characterized in that: The sleep ratio value is used as the two right-angled sides of a right triangle, and the ends of the two right-angled sides are connected with a straight line to obtain a complete right triangle, and the right triangle is used as the base of the triangular pyramid; the turning over ratio is used as the height of the triangular pyramid, a triangular pyramid model is established, and the volume of the triangular pyramid is calculated and recorded as the fitting index.

8. The elderly health status monitoring system based on a wristband oximeter according to claim 7 is characterized in that: After normalizing the motion index of each motion state and the matching index corresponding to each motion state, a base circle model is established with the motion index of each motion state as the radius, and a cone model is established with the matching index corresponding to each motion state as the height. The volume of the cone model corresponding to each motion state is calculated, and the volume of the cone model obtained is recorded as the evaluation index of each motion state in turn.

9. The elderly health status monitoring system based on a wristband oximeter according to claim 1 is characterized in that: The obtained evaluation index is analyzed to perform corresponding early warning processing, which specifically includes the following parts: The evaluation index threshold is preset. If the evaluation index is greater than the evaluation index threshold, the motion index, fatigue index, and coordination index are compared with their corresponding thresholds respectively: If the motion index is greater than the threshold, the abnormal duration, abnormal frequency, and extreme difference value corresponding to the motion index are marked as abnormal motion information, and the abnormal motion information is sent to the smart terminal to which the guardian of the wristband oximeter is bound; If the fatigue index is greater than the threshold, the actual recovery time and relaxation recovery time corresponding to the fatigue index are marked as fatigue abnormality information, and the fatigue abnormality information is sent to the smart terminal to which the guardian of the wristband oximeter is bound; If the coordination index is greater than its threshold, the sleep ratio and turning ratio corresponding to the coordination index are marked as coordination abnormality information, and the coordination abnormality information is sent to the smart terminal to which the guardian of the wristband oximeter is bound.

10. The elderly health status monitoring system based on a wristband oximeter according to claim 9 is characterized in that: The analysis of the obtained evaluation index to perform corresponding early warning processing also includes the following parts: The evaluation index is obtained at set time intervals, and the obtained evaluation indexes are arranged in chronological order from left to right. If the adjacent evaluation indexes in the time series are greater than the preset evaluation index threshold, then on the basis of the original warning, a vibration reminder is sent to the wrist-band oximeter worn by the elderly, and a communication connection is established with a medical institution that cooperates with the manufacturer of the wrist-band oximeter. The elderly's evaluation index and the corresponding exercise index, fatigue index, and cooperation index are sent to the medical institution, requesting the medical institution to arrange medical staff to conduct a health check on the elderly at home, or assist the elderly to go to the hospital for examination.

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