WO2020133497A1

WO2020133497A1 - Method for evaluating recovery status of hospital patient, device, system, and storage medium

Info

Publication number: WO2020133497A1
Application number: PCT/CN2018/125817
Authority: WO
Inventors: 刘三超; 金星亮; 何先梁; 孙泽辉; 罗汉源; 谈琳
Original assignee: 深圳迈瑞生物医疗电子股份有限公司
Priority date: 2018-12-29
Filing date: 2018-12-29
Publication date: 2020-07-02
Also published as: CN113194811A

Abstract

A method for evaluating a recovery status of a hospital patient, a device (1), a system (100), and a storage medium. The method comprises: obtaining at least one type of related parameters from body status time parameters, exercise amount parameters, and physiological parameters (S101); extracting, from the at least one type of related parameters, at least two corresponding arguments in a preset time period (S102); and performing, on the basis of the at least two corresponding arguments in the preset time period, a correlation treatment to obtain a correlation metric for evaluating a recovery status of a patient (S103).

Description

Evaluation method, device, system and storage medium for recovery state of patients in hospital

Technical field

Embodiments of the present invention relate to data transmission technology in the field of wireless communication, and in particular, to a method, device, system, and storage medium for evaluating the recovery state of patients in a hospital.

Background technique

With the development of medical technology and the improvement of people's awareness of medicine, the importance and attention of rapid rehabilitation after surgery have been sharply enhanced and enhanced. During the postoperative recovery period, the patient gets more out of bed to promote the rapid recovery of the body. The doctor can learn the patient's movement through some means, and then estimate the patient's recovery.

At present, the traditional monitoring equipment for monitoring the postoperative recovery of patients is generally household electronic consumer products such as bracelets, ankle rings, treadmills and other products. These monitoring devices are based on the detection of real-time parameters of the human body (for example, cadence, step count, running count , Exercise time, etc.), showing the patient's movement, so that the doctor can judge the rehabilitation according to the movement.

However, although the patient's movement status can be obtained through the above-mentioned monitoring device, the movement status is only reflected by the real-time monitored movement parameters, and it is not very accurate to reflect the rehabilitation status through the presented movement parameters or movement conditions.

Summary of the invention

Embodiments of the present invention provide a method, device, system, and storage medium for evaluating a patient's recovery state in a hospital, which can monitor the human body from multiple dimensions, realize the diversity of monitoring, and improve the accuracy of evaluating the rehabilitation of the human body.

The technical solutions of the embodiments of the present invention may be implemented as follows:

An embodiment of the present invention provides a method for evaluating the recovery state of a patient in a hospital. The method includes:

Obtain the first time parameter and the second time parameter of the corresponding human body state time parameter within the preset time period; the first time parameter and the second time parameter respectively represent at least one time dimension time parameter of the human body state time parameter ;

Correlation processing is performed on the first time parameter and the second time parameter to obtain a correlation metric; the correlation metric is used to evaluate the recovery state of the patient.

Obtain at least one type of related parameters from the human body state time parameter, exercise parameter and physiological parameter;

Extract at least two parameters corresponding to the preset time period from the at least one type of related parameters;

Correlation processing is performed based on at least two parameters corresponding to the preset time period to obtain a correlation metric, and the correlation metric is used to evaluate the recovery state of the patient.

An embodiment of the present invention provides an evaluation system for the recovery state of a patient in a hospital. The system includes: at least one wearable device, and the at least one wearable device is worn on the patient;

The at least one wearable device is used to obtain at least one type of related parameters among the human body state time parameter, the exercise amount parameter and the physiological parameter; and extract at least two corresponding parameters within a preset time period from the at least one type of related parameter Parameters; and performing correlation processing based on at least two parameters corresponding to the preset time period to obtain a correlation metric, where the correlation metric is used to evaluate the recovery state of the patient.

An embodiment of the present invention provides a device for evaluating the recovery state of a patient in a hospital. The device includes:

The obtaining part is configured to obtain at least one type of related parameters among the human body state time parameter, the exercise quantity parameter and the physiological parameter;

An extracting part, configured to extract at least two parameters corresponding to a preset time period from the at least one type of related parameters;

The correlation part is configured to perform correlation processing based on at least two parameters corresponding to the preset time period to obtain a correlation metric, and the correlation metric is used to evaluate a patient's recovery state.

An obtaining part, configured to obtain a first time parameter and a second time parameter of a corresponding human body state time parameter within a preset time period; the first time parameter and the second time parameter respectively represent at least one of the human body state time parameters Time parameters of the time dimension;

The correlation part is configured to perform correlation processing on the first time parameter and the second time parameter to obtain a correlation metric; the correlation metric is used to evaluate the recovery state of the patient.

An embodiment of the present invention also provides a device for evaluating the recovery state of a patient in a hospital. The device includes:

The memory is used to store instructions for evaluating the recovery state of the patients in the hospital;

The processor is configured to implement the method for evaluating the recovery state of the in-hospital patient according to the claims when executing the instruction for evaluating the recovery state of the in-hospital patient stored in the memory.

Embodiments of the present invention provide a computer-readable storage medium that stores executable instruction for evaluating the recovery state of a hospital patient, and is used to cause the processor to execute the method for evaluating the recovery state of the hospital patient according to the claims.

Embodiments of the present invention provide a method, device, system, and storage medium for evaluating the recovery state of patients in hospitals by acquiring at least one type of related parameters among the time parameters, exercise parameters, and physiological parameters of the human body state; from at least one type of related parameters , Extracting at least two parameters corresponding to the preset time period; performing correlation processing based on the at least two parameters corresponding to the preset time period to obtain a correlation metric, and the correlation metric is used to evaluate the recovery state of the patient. With the above technical implementation solution, since the evaluation device for the recovery state of the hospital patient can obtain at least two parameters from at least one type of related parameters among the time parameters, exercise parameters and physiological parameters of the human body state, through the correlation processing of the at least two parameters , To obtain a correlation metric for evaluating the recovery state of the patient, because the correlation metric takes into account at least one type of parameter, and the parameter is obtained by correlation, reflecting the diversity of the correlation metric, based on at least two parameters The correlation measure obtained by correlation is used to evaluate the recovery state of the patient in a more accurate manner, that is, to monitor the human body from multiple dimensions, to achieve diversity in monitoring, and to improve the accuracy of evaluating the rehabilitation of the human body.

BRIEF DESCRIPTION

FIG. 1 is a schematic diagram of an optional architecture of a system for evaluating a patient’s recovery state provided by an embodiment of the present invention;

2 is a schematic diagram of another optional architecture of an evaluation system for the recovery state of a hospital patient provided by an embodiment of the present invention;

3 is a schematic diagram of another optional architecture of an evaluation system for the recovery state of a hospital patient provided by an embodiment of the present invention;

4 is a schematic diagram of yet another optional architecture of an in-hospital patient recovery state assessment system provided by an embodiment of the present invention;

FIG. 5 is a schematic structural diagram 1 of an optional device for evaluating the recovery state of hospital patients according to an embodiment of the present invention; FIG.

FIG. 6 is a second schematic structural diagram 2 of an evaluation device of a hospital patient recovery state provided by an embodiment of the present invention;

7 is a schematic flowchart 1 of an optional method for evaluating a recovery state of a hospital patient according to an embodiment of the present invention;

FIG. 8 is a second schematic flowchart of an optional method for evaluating a patient’s recovery state provided by an embodiment of the present invention;

9 is an exemplary schematic diagram of filtering at least one original signal provided by an embodiment of the present invention;

FIG. 10 is a schematic flowchart 3 of an optional method for evaluating a hospital patient’s recovery state according to an embodiment of the present invention; FIG.

11 is a fourth schematic flowchart of an alternative method for evaluating the recovery state of a hospital patient according to an embodiment of the present invention;

FIG. 12 is a schematic flowchart 5 of an alternative method for evaluating a hospital patient’s recovery state according to an embodiment of the present invention; FIG.

13 is a sixth schematic flowchart of an optional method for evaluating a hospital patient’s recovery state according to an embodiment of the present invention;

FIG. 14 is a schematic flowchart 7 of an optional method for evaluating a hospital patient’s recovery state according to an embodiment of the present invention.

detailed description

In order to understand the features and technical contents of the embodiments of the present invention in more detail, the following describes the implementation of the embodiments of the present invention in detail with reference to the accompanying drawings. The accompanying drawings are for reference only and are not intended to limit the embodiments of the present invention.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field of the present invention. The terminology used herein is for the purpose of describing embodiments of the present invention and is not intended to limit the present invention.

It should be pointed out that the term “first\second\third” involved in the embodiment of the present invention is only to distinguish similar objects, and does not represent a specific order for the objects. Understandably, “first\second\third” "The specific order or the sequential order may be interchanged if allowed, so that the embodiments of the present invention described herein can be implemented in an order other than that illustrated or described herein.

The following describes an exemplary application of an apparatus for evaluating the recovery state of a hospital patient according to an embodiment of the present invention. The apparatus for evaluating the recovery state of a hospital patient provided by the embodiment of the present invention can be implemented as various types of user terminals such as wearable devices and sensor devices. Hereinafter, an exemplary application when the evaluation device for the recovery state of the hospital patient is implemented as a wearable device will be described.

Referring to FIG. 1, FIG. 1 is a schematic diagram of an optional architecture of an in-hospital patient recovery state evaluation system 100 provided by an embodiment of the present invention. To support an exemplary application, it is composed of at least one wearable device 200, wherein, The at least one wearable device is worn on the patient.

At least one wearable device 200, configured to acquire at least one type of related parameters among the human body state time parameters, exercise parameters, and physiological parameters; and extract at least two parameters corresponding to the preset time period from the at least one type of related parameters; And performing correlation processing based on at least two parameters corresponding to the preset time period to obtain a correlation metric, and the correlation metric is used to evaluate the recovery state of the patient.

The human body state parameters mentioned herein may include time parameters statistically related to human motion-related events and/or human sleep-related events in the time dimension. The amount of exercise parameter represents a movement parameter other than time that characterizes the degree of movement of the human body during exercise. Human motion includes active state, static state, etc.

At least one physiological parameter signal is obtained within a first time period through a sensor accessory connected to the patient, and the at least one physiological parameter signal may be temperature (Temp), diastolic blood pressure, systolic blood pressure (BP-S), heart rate collected through the sensor accessory (HR), respiration rate (Respiration, Rate, RR), consciousness level, blood oxygen (SpO2), and oxygen concentration (Supp.O2), EEG and other physiological parameter signals. Then, according to the aforementioned at least one physiological parameter signal, body temperature (Temp), diastolic blood pressure, systolic blood pressure (BP-S), heart rate (HR), respiratory rate (RR, Respiration), awareness level, blood oxygen (SpO2) can be obtained ), and waveforms and/or values corresponding to various physiological parameters such as oxygen concentration (Supp. O2), EEG, etc.

In some embodiments of the present invention, the aforementioned at least one wearable device 200 is further used to perform correlation processing based on at least two parameters corresponding to the aforementioned preset time period, and after obtaining the correlation metric, the correlation metric may be presented.

In this embodiment, at least two parameters may be derived from one type of related parameters; at least two parameters may also be derived from multiple types of related parameters, where each type of related parameter corresponds to at least one parameter. The details can be explained in detail in subsequent examples.

The correlation measure mentioned in this article is used to measure the correlation between at least two parameters, which can be divided into the following categories to evaluate this correlation.

The first one is to obtain the quantitative index of the correlation measure based on the corresponding correlation processing.

Construct a quantization function Y=f(x ₁ , x ₂ ,...) based on the corresponding correlation processing, based on at least one type of correlation parameters among the human state time parameters, exercise parameters and physiological parameters, from the aforementioned at least one type of correlation parameters At least two parameters (x ₁ , x ₂ , ...) corresponding to the preset time period are extracted, and the aforementioned at least two parameters are brought into the aforementioned quantization function f(x ₁ , x ₂ ,...) The quantitative index Y of the correlation measure. With the continuation or change of time, the quantitative indicators Y at different moments (t1, t2, t3, ...) can be obtained corresponding to different preset time periods, such as Y _t1 , Y _t2 , Y _t3 , .... The manner of presenting the correlation measure may be to refresh and display the quantitative indicators (Y _t1 , Y _t2 , Y _t3 ,...) Obtained at different moments in sequence with time, so as to display the quantitative indicator Y in real time. Of course, it is also possible to construct a coordinate system that changes along time, in which a quantitative index (Y _t1 , Y _t2 , Y _t3 ,...) Corresponding to different moments is marked in the coordinate system that changes along time, thereby forming a change trend graph of the quantitative index.

The foregoing quantization function Y=f(x ₁ , x ₂ ,...) Can be a function constructed by at least one operation method such as multiplication, division, sum, difference, etc. For example, it can be based on ratio operation, difference operation, integral ratio operation, The aforementioned quantization function is constructed by one or more of area ratio calculation, integral difference calculation, area difference calculation, and so on.

The second is to obtain a graphical index of the correlation measure based on the corresponding correlation processing.

Construct an icon model containing at least two parameter display elements in the same coordinate system to generate graphical indicators. Extracting at least two parameters (x ₁ , x ₂ ,...) Corresponding to the preset time period from the at least one type of related parameters based on at least one type of related parameters of the human body state time parameter, exercise amount parameter and physiological parameter, Displaying the aforementioned at least two parameters in the same icon model to obtain a graphical indicator on the correlation measure. With the continuation or change of time, the graphical indicators at different moments (t1, t2, t3, ...) can be obtained corresponding to different preset time periods in turn. The graphical indicators at different moments are different due to the change of at least two parameters mentioned above . The way of presenting the correlation measure may be to refresh and display the graphical indicators obtained at different moments in sequence with time, so as to display the graphical indicators in real time. Of course, it is also possible to construct a coordinate system that changes along time, and mark a graphical indicator corresponding to different moments in the coordinate system that changes along time, thereby forming a change trend graph of the graphical indicator.

The aforementioned icon model may be composed of columnar bars, sectors, line segments, and dots to form display elements, and attribute variables such as shape size, rendering attributes, and the like in the display elements are associated with the aforementioned two parameters. For example, at least two columnar bars placed in parallel can be used to display the aforementioned at least two parameters to obtain the aforementioned graphical indicator, and at least two sectors within the same pie can be used to display the aforementioned at least two parameters to obtain the aforementioned graphical indicator, etc. .

Therefore, in one of the embodiments, performing correlation processing based on at least two parameters corresponding to the foregoing preset time period to obtain a correlation metric includes at least one of the following ways: based on at least two corresponding parameters within the foregoing predetermined time period Parameters to obtain a quantitative index on the correlation measure; and, based on at least two parameters corresponding to the aforementioned preset time period, obtain a graphical index on the correlation measure.

In some embodiments of the present invention, the at least one wearable device 200 is specifically configured to obtain the aforementioned quantitative index regarding the correlation measure based on at least two parameters corresponding to the aforementioned preset time period; and, based on the aforementioned Assume at least two parameters corresponding to the time period to obtain the aforementioned graphical index on the correlation measure.

In some embodiments of the present invention, the aforementioned at least one wearable device 200 is specifically used to obtain the aforementioned human body state time parameter as the aforementioned at least one type of related parameter; and,

Extracting at least two time parameters corresponding to the preset time period from the human body state time parameters as the at least two parameters; and performing correlation processing on the at least two time parameters extracted within the preset time period, Obtain quantitative or graphical indicators about the aforementioned correlation measure.

In some embodiments of the present invention, the aforementioned at least one wearable device 200 is specifically used to extract at least two exercise quantity parameters corresponding to a preset time period from the aforementioned exercise quantity parameters as the aforementioned at least two parameters, and Assume that the at least two motion quantity parameters extracted within a time period are subjected to correlation processing to obtain the aforementioned correlation metric, for example, output a quantitative index or a graphical index regarding the aforementioned correlation metric.

In some embodiments of the present invention, the aforementioned human body state time parameters include exercise time parameters. The at least one wearable device 200 is further specifically used to obtain at least one motion signal of the patient; perform time domain feature or frequency domain feature extraction on the at least one motion signal to obtain a motion feature; based on the motion feature, obtain the preset The at least two time parameters that are counted in at least two dimensions of the motion time parameter within the time period are used as the at least two parameters.

In some embodiments of the present invention, the aforementioned human state time parameters include exercise time parameters and sleep time parameters. The at least one wearable device 200 is further specifically used to obtain at least one motion signal of the patient; perform time domain feature or frequency domain feature extraction on the at least one motion signal to obtain a motion feature; based on the motion feature, obtain the preset At least one exercise time parameter in at least one dimension characterizing the aforementioned exercise time parameter within the time period; acquiring the sleep time parameter of the patient, using the aforementioned sleep time parameter and the aforementioned at least one exercise time parameter as the aforementioned at least two time parameters, As the aforementioned at least two parameters.

Here is an example to illustrate the acquisition of sleep time parameters.

In one of the embodiments, first, the movement characteristics are obtained according to the aforementioned at least one movement signal, the corresponding physiological signal is obtained through a sensor attachment attached to the patient's body, heart rate characteristic information is obtained from the physiological signal, and then, based on the movement characteristic And heart rate characteristic information determines the sleep state of the patient. It can be understood that the body motion signal can be obtained through a motion sensor. For example, the motion sensor may be an acceleration sensor, a gyroscope, or the like. When the motion sensor is an acceleration sensor, the real-time quantification value is the real-time acceleration value or the sum of the real-time acceleration values measured by the acceleration sensor; when the motion sensor is a gyroscope, since the gyroscope can monitor the user's motion track, therefore, at this time, The motion feature can also be the distance the user moves over a period of time.

Further, the foregoing obtaining motion characteristics according to the foregoing at least one motion signal includes:

Use the motion sensor on the at least one wearable device 200 to obtain the acceleration signal of the patient's motion for preprocessing to obtain the real-time acceleration value;

The motion sensor on the at least one wearable device 200 is used to obtain the acceleration signal and the angular velocity signal of the patient's motion for preprocessing, and at least the real-time acceleration value and the moving distance of the user are obtained. Based on the obtained real-time acceleration value, the exercise quantity parameter about the patient's movement can be obtained, and the current movement state of the patient can also be judged. At the same time, sleep time parameters are determined by combining heart rate characteristic information.

Among them, the process of obtaining heart rate characteristic information from physiological signals includes:

Processing physiological signals to obtain ECG data;

Analyze the ECG data to extract real-time and effective R wave intervals;

Resampling the R wave interval;

The heart rate characteristic information is calculated according to the R wave intervals at different scales to obtain heart rate characteristic information; wherein, the heart rate characteristic information includes time domain characteristic information and frequency domain characteristic information.

The heart rate characteristic information refers to the difference in physiological signals collected at two different times; the different times are two or more physiological signals with the same length in the sequence; the sequence can be continuous or intermittent collection; The physiological signal difference may be a physiological signal waveform or a waveform characteristic difference; the difference is a degree of difference or variability.

For example, the heart rate characteristic information may refer to a small change in the interval between two heartbeats. Heart rate feature information includes frequency domain feature information and time domain feature information.

In one embodiment, the processing of the physiological signal to obtain frequency domain characteristic information includes: processing the physiological signal to obtain ECG data; and analyzing the ECG data to extract real-time and effective R wave interval; resampling the R wave interval; calculating the heart rate characteristic information according to the R wave interval at different scales to obtain heart rate characteristic information.

Among them, for example, the process of processing physiological signals to obtain ECG data includes: after the sleep state determination device receives the user's ECG ECG signal, the ECG ECG signal is filtered to remove noise, and then the signal is used The amplifier expands the amplitude of the processed signal, and finally performs A/D conversion (It is understandable that A/D conversion is analog-to-digital conversion. The role of A/D conversion is to convert continuous time and amplitude analog values into continuous Digital signal with discrete time and discrete amplitude), convert analog signal to data signal. It can be understood that the data signal includes the electrocardiographic data. Understandably, when the physiological signal is a signal other than the ECG ECG signal, such as a pulse wave signal, the pulse wave signal can also be processed to obtain ECG data, as long as it performs physiological data data to obtain ECG The data is sufficient.

In addition, it should be noted that the electrocardiogram is composed of a series of wave groups, and each wave group represents each cardiac cycle. A wave group includes P wave, QRS wave group, T wave and U wave. Among them, QRS wave group includes three closely connected waves, the first downward wave is called Q wave, a high-pointed upright wave following Q wave is called R wave, and the downward wave after R wave is called S wave. Because they are closely connected and reflect the process of ventricular electrical excitation, they are collectively called QRS complexes. This wave group reflects the depolarization process of the left and right ventricles.

Secondly, the sleep state of the user is determined according to the aforementioned exercise characteristics and the aforementioned heart rate characteristic information. For example, for example, the heart rate characteristic information is frequency domain characteristic information, and the judgment of the user's sleep state according to the aforementioned exercise characteristics and the heart rate characteristic information includes: comparing the aforementioned exercise characteristics with the first threshold, and comparing The heart rate characteristic information and the second threshold; when the aforementioned motion characteristic is lower than the first threshold and the heart rate characteristic information is less than the second threshold, it is determined that the user is in a sleep state. It can be understood that the second threshold is an adaptive threshold or a fixed value. When the heart rate feature information is time domain feature information, the time domain feature information includes a standard deviation of intervals within a preset time segment, and the user's sleep state is determined according to the aforementioned motion feature and the standard deviation.

Among them, when the second threshold is an adaptive threshold, it should be pointed out that the adaptive threshold dynamically changes with the heart rate. Therefore, before comparing the heart rate characteristic information and the adaptive threshold, the method further includes: acquiring the user's current heart rate value; inputting the user's current heart rate value into a threshold determination model to determine the adaptive threshold .

Further, it should be noted that before inputting the current heart rate of the user into a threshold determination model to determine the adaptive threshold, the method further includes: acquiring the user's included acceleration within a preset time period Signals and awakening sleep data of electrocardiogram signals; annotate the user's awakening sleep cycle according to time series; wherein, the content of the labeling includes the awakening state and sleep state; extract the user's heart rate value and An adaptive threshold corresponding to the heart rate value (ie, an ECG value); obtaining a threshold determination model according to the extracted heart rate value and the adaptive threshold corresponding to the heart rate value.

The sleep stage of the user is determined according to the ratio and corresponding relationship between multi-scale heart rate feature information, the sleep stage includes but not limited to deep sleep, light sleep and fast phase sleep REM (or called fast wave sleep or out of phase Sleep). Therefore, sleep time parameters can be determined based on the above method.

In some embodiments of the present invention, the at least two types of parameters include at least one of the following: the human body state time parameter and the aforementioned exercise quantity parameter, the aforementioned human body state time parameter and the aforementioned physiological parameter, the aforementioned exercise quantity parameter and the aforementioned physiological parameter, and the aforementioned The human body state time parameter, the aforementioned exercise quantity parameter and the aforementioned physiological parameter.

In some embodiments of the present invention, the at least one wearable device 200 is further specifically configured to acquire at least one motion signal of the patient; and based on the at least one motion signal, count the human body state time within the preset time period Parameters and the aforementioned motion parameters.

In some embodiments of the present invention, when the aforementioned at least two types of parameters include the aforementioned human state time parameter and the aforementioned physiological parameter, the aforementioned at least one wearable device 200 is further specifically used to obtain at least one motion signal of the aforementioned patient; The body characteristic sensor acquires the aforementioned physiological parameter; based on the aforementioned at least one motion signal, statistics the aforementioned human body state time parameter within the aforementioned preset time period.

In some embodiments of the present invention, the at least one wearable device 200 is further specifically configured to acquire the at least one original motion signal of the patient through a preset motion sensor; filtering the at least one original motion signal to obtain the at least one A motion signal.

In some embodiments of the present invention, the aforementioned at least one wearable device 200 is further specifically used to obtain an exercise time based on the aforementioned exercise characteristics; based on the aforementioned at least one exercise signal, statistics of the aforementioned exercise amount parameter within the preset time period; The aforementioned exercise amount parameter, the preset rest threshold and the aforementioned exercise time determine the bed-off time; according to the aforementioned preset time period and the aforementioned bed-out time, determine the bed rest time; the aforementioned departure time, the aforementioned exercise time, the aforementioned preset time period and Any combination of at least two of the aforementioned bed rest times is used as the aforementioned at least two time parameters among the aforementioned human body state time parameters as the aforementioned at least two parameters.

In some embodiments of the present invention, the aforementioned at least one wearable device 200 is further specifically used to obtain a preset time feature threshold in real time; when the aforementioned motion feature is greater than the preset time feature threshold, it is determined to be in a sports state, and the aforementioned motion is recorded The duration of the state gives the aforementioned movement time.

In some embodiments of the present invention, the aforementioned at least one wearable device 200 is specifically used to obtain a preset correlation algorithm; the foregoing preset correlation algorithm is used to calculate the correlation of at least two parameters corresponding to the preset time period To obtain the aforementioned correlation measure.

In some embodiments of the present invention, the aforementioned preset correlation algorithm includes at least one of the following: ratio calculation, difference calculation, integral ratio calculation, area ratio calculation, integral difference calculation, and area difference calculation.

Based on FIG. 1, refer to FIG. 2. FIG. 2 is another schematic diagram of an alternative architecture of an in-hospital patient recovery state evaluation system 100 provided by an embodiment of the present invention. In order to support an exemplary application, at least one wearable device 200. A bedside monitor 300 is configured, wherein the at least one wearable device is worn 200 on a patient, and the bedside monitor 300 communicates with at least one wearable device 200.

The aforementioned at least one wearable device 200 is configured to acquire at least one type of related parameters among human body state time parameters, exercise parameters and physiological parameters; and extract at least two corresponding preset time periods from the aforementioned at least one type of related parameters Parameters; and performing correlation processing based on the at least two parameters corresponding to the aforementioned preset time period to obtain a correlation metric, the correlation metric is used to evaluate the recovery state of the patient; transmitting the correlation metric to the bedside monitor 300; the aforementioned bedside monitor 300 is used to present the aforementioned correlation measure.

Based on FIG. 1, refer to FIG. 2. FIG. 2 is another schematic diagram of an alternative architecture of an in-hospital patient recovery state evaluation system 100 provided by an embodiment of the present invention. In order to support an exemplary application, at least one wearable device 200. The bedside monitor 300 is configured, wherein the at least one wearable device is worn on the patient, and the bedside monitor communicates with the at least one wearable device.

The aforementioned at least one wearable device 200 is configured to acquire at least one type of related parameters among human body state time parameters, exercise parameters and physiological parameters; and extract at least two corresponding preset time periods from the aforementioned at least one type of related parameters Parameters; transmitting the at least two parameters to the bedside monitor 300; the bedside monitor 300 is used to perform correlation processing on the at least two parameters to obtain the correlation measure and present the correlation measure.

Based on FIG. 1 and referring to FIG. 3, FIG. 3 is a schematic diagram of another optional architecture of an in-hospital patient recovery state evaluation system 100 provided by an embodiment of the present invention. In order to support an exemplary application, at least one wearable device 200. The central station 400 is configured, wherein the at least one wearable device 200 is worn on the patient, and the central station 400 communicates with the at least one wearable device 200.

The aforementioned at least one wearable device 200 is configured to acquire at least one type of related parameters among human body state time parameters, exercise parameters and physiological parameters; and extract at least two corresponding preset time periods from the aforementioned at least one type of related parameters Parameters; and performing correlation processing based on the at least two parameters corresponding to the aforementioned preset time period to obtain a correlation metric, which is used to evaluate the recovery state of the patient; transmitting the correlation metric to the central station 400; The aforementioned central station 400 is used to present the aforementioned correlation metric.

The aforementioned at least one wearable device 200 is configured to acquire at least one type of related parameters among human body state time parameters, exercise parameters and physiological parameters; and extract at least two corresponding preset time periods from the aforementioned at least one type of related parameters Parameters; transmitting the at least two parameters to the central station 400; the central station 400 is used to perform correlation processing on the at least two parameters to obtain the correlation metrics, and present the correlation metrics.

Based on FIG. 1 and referring to FIG. 4, FIG. 4 is a schematic diagram of yet another optional architecture of an in-hospital patient recovery state evaluation system 100 provided by an embodiment of the present invention. In order to support an exemplary application, at least one wearable device 200. A bedside monitor 300 and a central station 400 are configured, wherein the at least one wearable device 200 is worn on a patient, and the bedside monitor 300 and the central station 400 communicate with at least one wearable device 200, respectively.

The aforementioned at least one wearable device 200 is configured to acquire at least one type of related parameters among human body state time parameters, exercise parameters and physiological parameters; and extract at least two corresponding preset time periods from the aforementioned at least one type of related parameters Parameters; transmitting the at least two parameters to the central station 400 and the bedside monitor 300; the central station 400 is used to perform correlation processing on the at least two parameters to obtain the correlation measure and present the correlation Correlation measure; and, the aforementioned bedside monitor 300 is used to perform correlation processing on the aforementioned at least two parameters to obtain the aforementioned correlation measure, and present the aforementioned correlation measure.

In some embodiments of the present invention, the aforementioned at least one wearable device 200 is used to acquire at least one type of related parameters among the human body state time parameter, exercise amount parameter and physiological parameter; and extract the Set at least two parameters corresponding to the time period; and perform correlation processing based on the at least two parameters corresponding to the preset time period to obtain a correlation metric, and the correlation metric is used to evaluate the recovery state of the patient; The sex metric is transmitted to the aforementioned central station 400 and the aforementioned bedside monitor 300; the aforementioned bedside monitor 300 is used to present the aforementioned correlation metric; and the aforementioned central station 400 is used to present the aforementioned correlation metric.

It should be noted that in the embodiment of the present invention, the communication method between the at least one wearable device 200 and the bedside monitor 300 and the central station 400 may be wireless communication through a wireless node, and the embodiment of the present invention does not limit wireless communication. Specific implementation.

Moreover, in the embodiment of the present invention, the central station 400 and the bedside monitor 300 are both exemplary devices that can communicate with at least one wearable device, and other embodiments and at least one wearable device can also be used in the embodiment of the present invention. Communication is used to calculate or present correlation metrics for use in evaluating the recovery state of the patient. The embodiments of the present invention are not limited.

It should be noted that in the evaluation system of the recovery state of patients in different hospitals, the implementation of specific correlation measures, the acquisition of at least two parameters, and other processes are all the same principle and technical implementation means, and will not be repeated here.

The device for evaluating the recovery state of a hospital patient provided by an embodiment of the present invention may be implemented in a hardware or a combination of software and hardware. The following describes various exemplary implementations of the device for evaluating the recovery state of a hospital patient provided by an embodiment of the present invention.

Referring to FIG. 5, FIG. 5 is an optional structural schematic diagram of an evaluation device for a hospital patient recovery state provided by an embodiment of the present invention. The evaluation device for the hospital patient recovery state may be a wearable device. Sensor devices and other electronic devices that can acquire at least one type of related parameters from patients. The structure described here should not be considered as a limitation. For example, some components described below can be omitted, or components not described below can be added to suit Special needs for certain applications.

An evaluation device 1 for the recovery state of a hospital patient shown in FIG. 5 includes:

The memory 10 is used to store an evaluation instruction that can execute the recovery state of the patient in the hospital;

The processor 11 is configured to execute the following evaluation method of the in-hospital patient recovery state when executing the instruction for evaluating the in-hospital patient recovery state stored in the foregoing memory 10.

It should be noted that, in the embodiment of the present invention, each component in the evaluation device 1 for the recovery state of the patient in the hospital is coupled together through the bus system 12. It can be understood that the bus system 12 is used to implement connection and communication between these components. In addition to the data bus, the bus system 12 also includes a power bus, a control bus, a status signal bus, and a communication interface that communicates with other devices (for example, a wireless communication interface that communicates with a central station or bedside monitor). However, for clarity, various buses and interfaces are marked as the bus system 12 in FIG. 5.

It should be noted that the memory 10 may be a volatile memory or a non-volatile memory, and may also include both volatile and non-volatile memory. Among them, the non-volatile memory can be read-only memory (ROM, Read Only Memory), programmable read-only memory (PROM, Programmable Read-Only Memory), erasable programmable read-only memory (EPROM, Erasable Programmable Read- Only Memory), Flash memory, etc. The volatile memory may be a random access memory (RAM, Random Access Memory), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM, Static Random Access Memory), synchronous static random access memory (SSRAM, Synchronous Static Random Access Memory). The memory 10 described in the embodiments of the present invention is intended to include these and any other suitable types of memories.

As an example, the processor 11 may be an integrated circuit chip with signal processing capabilities, such as a general-purpose processor, a digital signal processor (DSP, Digital Processor), or other programmable logic devices, discrete gates, or transistor logic devices , Discrete hardware components, etc., wherein the general-purpose processor may be a microprocessor or any conventional processor, etc.

The following describes an exemplary structure of a software module of an in-hospital patient recovery state assessment device. In some embodiments, as shown in FIG. 6, a software module in an in-hospital patient recovery state assessment device 1 may include:

The obtaining part 13 is configured to obtain at least one type of relevant parameters among the human body state time parameter, the exercise quantity parameter and the physiological parameter;

The extracting portion 14 is configured to extract at least two parameters corresponding to the preset time period from the aforementioned at least one type of related parameters;

The correlation section 15 is configured to perform correlation processing based on at least two parameters corresponding to the foregoing preset time period to obtain a correlation metric, and the foregoing correlation metric is used to evaluate the recovery state of the patient.

In some embodiments of the present invention, the aforementioned acquiring section 13 is specifically configured to acquire the sum of at least two types of parameters among the aforementioned human body state time parameter, the aforementioned exercise amount parameter and the aforementioned physiological parameter,

At least two parameters respectively corresponding to the preset time period are extracted from the aforementioned at least two types of parameters, wherein each type of related parameter corresponds to at least one parameter.

In some embodiments of the present invention, the aforementioned correlation section 15 is specifically configured to obtain a quantitative index regarding the correlation measure based on at least two parameters corresponding to the aforementioned preset time period; and,

Based on the at least two parameters corresponding to the aforementioned preset time period, a graphical indicator regarding the correlation measure is obtained.

In some embodiments of the present invention, the aforementioned acquiring section 13 is specifically configured to acquire the aforementioned human body state time parameter as the aforementioned at least one type of related parameter; and,

At least two time parameters corresponding to the preset time period are extracted from the aforementioned human body state time parameters as the aforementioned at least two parameters.

In some embodiments of the present invention, the correlation section 15 is specifically configured to perform correlation processing on the at least two time parameters extracted in the preset time period to obtain the correlation measure.

In some embodiments of the present invention, the aforementioned acquiring section 13 is specifically configured to acquire the aforementioned exercise quantity parameter as the aforementioned at least one type of related parameter; extract at least two corresponding exercise quantity parameters within a preset time period from the aforementioned exercise quantity parameter as The aforementioned at least two parameters.

In some embodiments of the present invention, the correlation section 15 is specifically configured to perform correlation processing on the at least two motion amount parameters extracted in the preset time period to obtain the correlation measure.

In some embodiments of the present invention, the aforementioned human body state time parameters include exercise time parameters;

The aforementioned acquiring section 13 is further specifically configured to acquire at least one motion signal of the aforementioned patient; and perform time domain feature or frequency domain feature extraction on the aforementioned at least one motion signal to obtain a motion feature; and based on the foregoing motion feature, obtain the preset time The at least two time parameters that are statistical in at least two dimensions of the motion time parameter within the segment are used as the at least two parameters.

In some embodiments of the present invention, the aforementioned human body state time parameters include exercise time parameters and sleep time parameters;

The foregoing acquiring section 13 is further specifically configured to acquire at least one motion signal of the patient, and perform time domain feature or frequency domain feature extraction on the at least one motion signal to obtain a motion feature; based on the motion feature, obtain the Set at least one exercise time parameter that counts at least one dimension of the exercise time parameter within a time period; obtain a sleep time parameter of the patient; use the sleep time parameter and the at least one exercise time parameter as the at least one Two time parameters are used as the at least two parameters.

In some embodiments of the present invention, when the aforementioned at least two types of parameters include the aforementioned human body state time parameter and the aforementioned exercise amount parameter;

The aforementioned acquiring section 13 is further specifically configured to acquire at least one movement signal of the aforementioned patient; and, based on the aforementioned at least one movement signal, count the aforementioned human body state time parameter and the aforementioned exercise amount parameter within the preset time period.

In some embodiments of the present invention, when the aforementioned at least two types of parameters include the aforementioned human state time parameter and the aforementioned physiological parameter;

The acquiring section 13 is further specifically configured to acquire at least one movement signal of the patient; and based on the at least one movement signal, count the human body state time parameter in the preset time period; and acquire the physiological parameter through a biological characteristic sensor .

In some embodiments of the present invention, the aforementioned acquiring section 13 is further specifically configured to acquire the aforementioned at least one original motion signal of the patient through a preset motion sensor; and filter the aforementioned at least one original motion signal to obtain the aforementioned at least one motion signal.

In some embodiments of the present invention, the acquiring section 13 is further specifically configured to obtain a movement time based on the movement characteristics; and based on the at least one movement signal, calculate the movement amount parameter in the preset time period; and Exercise amount parameter, preset rest threshold and the aforementioned exercise time, determine the bed-off time; and determine the bed time based on the aforementioned preset time period and the aforementioned bed-out time; and the aforementioned departure time, the exercise time, the aforementioned preset time period A combination with any at least two of the aforementioned bed time is used as the aforementioned at least two time parameters among the aforementioned human body state time parameters as the aforementioned at least two parameters.

In some embodiments of the present invention, the aforementioned acquiring section 13 is further specifically configured to acquire a preset time characteristic threshold in real time; and when the aforementioned motion characteristic is greater than the aforementioned preset time characteristic threshold, it is determined to be a motion state, and a record of the motion state is recorded The duration obtains the aforementioned exercise time.

In some embodiments of the present invention, the foregoing device 1 further includes: a receiving section 16.

The receiving portion 16 is configured to obtain the exercise time based on the movement characteristics, and combine any at least two of the bed leaving time, the exercise time, the preset time period, and the bed time as the human body state. Before the at least two time-related parameters in the time parameter, receive the bed leaving time and the bed rest time monitored by the bedside sensor transmission.

In some embodiments of the present invention, the aforementioned correlation section 15 is specifically configured to obtain a preset correlation algorithm; and use the aforementioned preset correlation algorithm to calculate the correlation of at least two parameters corresponding to the aforementioned preset time period To get the aforementioned correlation measure.

In some embodiments of the present invention, the aforementioned device 1 further includes: a presentation portion 17.

The foregoing presentation section 17 is configured to perform the correlation processing based on the at least two parameters corresponding to the preset time period, and obtain the correlation metric after obtaining the correlation metric. Presenting the aforementioned correlation metric may be: outputting and displaying the correlation metric on the monitoring device, where the correlation metric includes a quantitative index and/or a graphical index. The monitoring devices mentioned in this article include monitors, portable monitoring devices, mobile terminals with vital sign monitoring functions, central stations, nurse stations, etc.

Wherein, the correlation metric is presented, and the manner of presenting the correlation metric is at least one of the following ways: sequentially refreshing and displaying quantitative indicators about the correlation metric obtained at different moments over time; refreshing and displaying different moments sequentially over time The obtained graphical index on the correlation measure; construct a coordinate system that changes along the time, mark the quantitative index on the correlation measure at different times in the coordinate system that changes along the time, and form a change trend graph of the quantitative index; and , Build a coordinate system that changes along time, mark the graphical indicators of the correlation measure at different times in the coordinate system that changes along time, and form a change trend graph of the graphical indicators

In some embodiments of the present invention, the foregoing device 1 further includes: a sending section 18.

The foregoing sending part 18 is configured to perform correlation processing based on the at least two parameters corresponding to the preset time period and obtain the correlation metric, and then transmit the correlation metric to the bedside monitor and/or the central station; The aforementioned correlation measure is presented on the aforementioned bedside monitor and/or the aforementioned central station.

Exemplarily, the following describes an evaluation device for the recovery state of a hospital patient when at least one type of related parameter is a human state time parameter.

An embodiment of the present invention provides an evaluation device 1 for the recovery state of a patient in a hospital.

The obtaining section 13 is configured to obtain the first time parameter and the second time parameter of the corresponding human body state time parameter within the preset time period; the foregoing first time parameter and the foregoing second time parameter respectively represent at least one time in the human body state time parameter Time parameter of dimension;

The correlation section 15 is configured to perform correlation processing on the first time parameter and the second time parameter to obtain a correlation metric; the correlation metric is used to evaluate the recovery state of the patient.

The foregoing acquiring section 13 is specifically configured to acquire at least one motion signal of the patient within the preset time period; and perform time-frequency domain feature time domain feature or frequency domain feature extraction on the at least one motion signal to obtain a motion feature; And based on the aforementioned motion characteristics, acquiring the aforementioned first time parameter and the aforementioned second time parameter characterizing the aforementioned exercise time parameter statistics within the aforementioned preset time period.

The foregoing acquiring section 13 is specifically configured to acquire a motion signal of the patient within the preset time period; and perform time-frequency domain feature time-domain feature or frequency domain feature extraction on the foregoing motion signal to obtain a first motion feature; And based on the first motion feature, acquiring a motion time parameter that characterizes the motion time parameter within the preset time period; within the preset time period, acquiring the sleep time parameter of the patient; and combining the sleep time The parameter and the aforementioned one movement time parameter serve as the aforementioned first time parameter and second time parameter.

In some embodiments of the present invention, the acquiring section 13 is further specifically configured to determine the exercise time according to the aforementioned movement characteristics; and based on the at least one movement signal, to calculate the exercise amount parameter within the preset time period; and according to the aforementioned exercise amount Parameters, a preset rest threshold and the aforementioned exercise time to determine the bed-off time; and based on the aforementioned preset time period and the aforementioned bed-off time to determine the bed-rest time; and from the aforementioned exercise time, the aforementioned bed-out time, which characterize the aforementioned exercise-time parameters The first time parameter and the second time parameter are selected from the preset time period and the bed rest time.

In some embodiments of the present invention, the aforementioned device further includes: a receiving section 16.

The receiving section 16 is configured to perform time-frequency domain feature time-domain feature or frequency domain feature extraction on the at least one motion signal to obtain a motion feature, and the foregoing from the motion time, the bed leaving time, the preset time period Before selecting the aforementioned first time parameter and the aforementioned second time parameter from the aforementioned bed time, receiving the bed leaving time and the bed time monitored by the bedside sensor transmission monitoring.

In some embodiments of the present invention, the combination of the foregoing first time parameter and the foregoing second time parameter is any one of the following:

The aforementioned exercise time and the aforementioned bed leaving time;

The aforementioned exercise time and the aforementioned preset time period;

The aforementioned bed leaving time and the aforementioned preset time period;

The aforementioned exercise time and the aforementioned bed time;

The aforementioned bed leaving time and the aforementioned bed time;

The aforementioned bed time and the aforementioned preset time period.

In some embodiments of the present invention, the aforementioned correlation section 15 is specifically configured to acquire a preset correlation algorithm; and use the aforementioned preset correlation algorithm to calculate the correlation between the first time parameter and the second time parameter, The aforementioned correlation measure is obtained.

In some embodiments of the present invention, the aforementioned preset correlation algorithm includes at least one of the following: ratio calculation, difference calculation, integral ratio calculation, area ratio calculation, integral difference calculation, and area difference calculation. In one of the embodiments, the correlation measure mentioned herein refers to the ratio between two parameters.

In some embodiments of the present invention, the device further includes: a presentation portion 17;

The foregoing presentation part is configured to output and display the correlation metric on the monitoring device, the correlation metric includes a quantitative indicator and/or a graphical indicator

As an example of evaluating the recovery state of the hospital patient provided by the embodiment of the present invention using hardware, the evaluation method of the recovery state of the hospital patient provided by the embodiment of the present invention can be directly completed by using a processor 11 in the form of a hardware decoding processor For example, one or more application specific integrated circuits (ASIC, Application Integrated Circuit), DSP, programmable logic device (PLD, Programmable Logic Device), complex programmable logic device (CPLD, Complex Programmable Logic Device), field A programmable gate array (FPGA, Field-Programmable Gate Array) or other electronic component executes the method for evaluating the recovery state of the hospital patient provided by the embodiment of the present invention.

In the following, the method for evaluating the recovery state of the in-hospital patient according to the embodiment of the present invention will be described with reference to the exemplary application and implementation of the evaluation device for the recovery state of the in-hospital patient according to the embodiment of the invention.

Referring to FIG. 7, FIG. 7 is a schematic flowchart of an optional method for evaluating the recovery state of a hospital patient provided by an embodiment of the present invention, which will be described in conjunction with the steps shown in FIG. 7.

S101. Acquire at least one type of related parameter among the human body state time parameter, the exercise quantity parameter and the physiological parameter;

S102. Extract at least two parameters corresponding to a preset time period from at least one type of related parameters;

S103. Perform correlation processing based on at least two parameters corresponding to the preset time period to obtain a correlation metric, and the correlation metric is used to evaluate the recovery state of the patient.

In the embodiment of the present invention, the device for evaluating the patient's recovery state in the hospital may use the correlation of the parameters to evaluate the patient's recovery state. The parameters herein refer to some parameters associated with the recovery of the patient, such as the human state time parameter, Exercise parameters and physiological parameters.

In the embodiment of the present invention, the evaluation device for the recovery state of the hospital patient may be a wearable device, which is worn on the patient and used to obtain at least one type of related parameters. The embodiment of the invention does not limit the device type of the evaluation device for the recovery state of the hospital patient .

In S101, the device for evaluating the recovery state of the patient in the hospital can acquire at least one type of related parameters among the time parameters, the amount of exercise parameters, and the physiological parameters of the human body state; the at least one type of related parameters here are some of the above-mentioned parameters associated with the patient's recovery .

In the embodiment of the present invention, the combination of at least one type of related parameters may include at least one of the following combinations: a combination of a human state time parameter and an exercise amount parameter, a combination of a human state time parameter and a physiological parameter, a combination of an exercise amount parameter and a physiological parameter, The combination of the human body state time parameter, the exercise quantity parameter and the physiological parameter, the combination of at least two exercise quantity parameters of the exercise quantity parameter, the combination of at least two time parameters of the human body state time parameter, and the combination of at least two exercise quantity parameters of the physiological parameter.

In some embodiments of the present invention, the device for evaluating the recovery state of the in-hospital patient may obtain at least two types of parameters of the human body state time parameter, exercise amount parameter, and physiological parameter; wherein at least two types of parameters are at least one type of related parameters.

Among them, at least two types of parameters include at least one of the following: human body state time parameters and exercise quantity parameters, human body state time parameters and physiological parameters, exercise quantity parameters and physiological parameters, and human body state time parameters, exercise quantity parameters and physiological parameters.

In some embodiments of the present invention, the evaluation device for the recovery state of the in-hospital patient may acquire at least two time parameters of the time parameters of the human body state; wherein at least two time parameters serve as at least two parameters.

In some embodiments of the present invention, the evaluation device of the hospital patient's recovery state may acquire at least two exercise quantity parameters of the exercise quantity parameter; wherein, at least two exercise quantity parameters serve as at least two parameters.

In the embodiment of the present invention, the time parameter of the human body state represents a time-related parameter related to the human body state based on different time dimensions such as events related to human motion and sleep related events.

It should be noted that the method for evaluating the recovery state of a patient in a hospital provided by an embodiment of the present invention is used to assess the physical recovery of a patient, especially for the scenario of a patient undergoing rehabilitation training. The time, the time to leave the bed, and the time to do exercise, etc., can fully reflect the recovery of the patient's body. The better the recovery, the corresponding exercise time and bed time will be longer, and the bed time will be Short, etc. Therefore, for example, the human body state time parameter used here may be the bed leaving time, exercise time, bed rest time, exercise time, and sleep time within a preset time period, which is not limited in this embodiment of the present invention.

In the embodiment of the present invention, the exercise quantity parameter represents a motion parameter other than time that characterizes the degree of exercise of the human body during exercise.

Exemplarily, the exercise quantity parameter may be cadence, step number, exercise distance, exercise intensity, exercise calorie consumption, etc., which is not limited in the embodiment of the present invention.

In the embodiments of the present invention, the physiological parameters are parameters that characterize the biological characteristics of the human body.

Exemplarily, the physiological parameters may include: heart rate, pulse rate, blood flow speed, and respiratory rate, etc., which is not limited in the embodiment of the present invention.

In S102, after obtaining the at least one type of relevant parameters in the human body state time parameter, exercise quantity parameter and physiological parameter, the device for evaluating the patient's recovery state in the hospital, because the evaluation of the patient's recovery state needs to be compared to better reflect whether The physical state has improved. Therefore, in the embodiment of the present invention, a correlation process is performed using parameters within a preset time period to obtain a correlation metric, which is obtained through the difference in the correlation metric within different preset time periods. Assess the patient's recovery status.

In the embodiment of the present invention, the evaluation device for the recovery state of the hospital patient may extract at least two parameters corresponding to the preset time period from at least one type of related parameters.

The preset time period here may be calculated in units of minutes, in units of hours, in units of days, etc., which is not limited in this embodiment of the present invention.

It should be noted that when the device for evaluating the recovery state of the hospital patient extracts at least two parameters from at least one type of related parameters, the parameters within the preset time period are extracted every time a preset time period passes.

Based on the aforementioned combination of at least one type of related parameters, the at least two parameters in the preset time period in the embodiment of the present invention include at least one of the following combinations:

The combination of the human body state time parameter and the exercise quantity parameter within the preset time period, the combination of the human body state time parameter and the physiological parameter within the preset time period, the combination of the exercise quantity parameter and the physiological parameter, the human body within the preset time period A combination of state time parameters, exercise quantity parameters and physiological parameters, a combination of at least two exercise quantity parameters of exercise quantity parameters within a preset time period, and a combination of at least two time parameters of human body state time parameters within a preset time period, And a combination of at least two exercise quantity parameters of physiological parameters within a preset time period.

In S103, after the at least two parameters corresponding to the preset period of time are extracted by the evaluation device for the recovery state of the hospital patient, the evaluation device for the recovery state of the hospital patient can be based on the at least two parameters corresponding to the preset time period Correlation processing is performed to obtain correlation metrics, and the correlation metrics used to evaluate the recovery status of the patient are used to evaluate the recovery status of the patient.

In the embodiment of the present invention, the evaluation device for the recovery state of the hospital patient performs correlation processing based on at least two parameters corresponding to the preset time period, and the process of obtaining the correlation measure may be: the evaluation device for the recovery state of the hospital patient obtains the preset Correlation algorithm; a preset correlation algorithm is used to calculate the correlation of at least two parameters corresponding to a preset time period to obtain a correlation metric.

In the embodiment of the present invention, the preset correlation algorithm includes at least one of the following: ratio calculation, difference calculation, integral ratio calculation, area ratio calculation, integral difference calculation, and area difference calculation.

In the embodiment of the present invention, the evaluation device for the recovery state of the hospital patient adopts at least one of ratio calculation, difference calculation, integral ratio calculation, area ratio calculation, integral difference calculation and area difference calculation to perform at least two parameters Correlation processing, thus obtaining correlation metrics that can characterize the patient's recovery status.

For example, the preset correlation algorithm may include: the ratio of exercise time to bed-off time, the difference between exercise time and bed-out time, the projected area at different time periods on the time window, the movement time to the preset time period The ratio, the ratio of exercise time to bed time, the ratio of time to bed to the preset time period, the correlation calculation of different time periods such as infrared heat map; and, the ratio of human body state time parameter and heart rate, human body state time parameter and heart rate Difference, the projection area of the human state time parameter and heart rate on the time window, the integration of the human state time parameter and heart rate, the ratio of the human state time parameter and heart rate integration, the difference between the human state time parameter and heart rate integration , Human body state time parameters and heart rate infrared heat map and other different calculation methods; and the ratio of cadence and movement distance, cadence and movement distance difference, the projected area of cadence and movement distance on the time window, cadence and movement Different calculation methods such as distance integration, ratio of cadence and movement distance integration, difference between cadence and movement distance integration, infrared heat map of cadence and movement distance, etc.

It should be noted that in the embodiment of the present invention, the movement distance is constant, the greater the cadence, and the shorter the exercise time, the better the recovery of the patient. The greater the ratio of cadence to movement distance, the better the patient recovers.

It can be understood that, since the evaluation device for the recovery state of the patient in the hospital can obtain at least two parameters from at least one type of related parameters among the human body time parameters, exercise parameters, and physiological parameters, through the correlation processing of the at least two parameters, Obtain a correlation metric for evaluating the recovery state of the patient. Since the correlation metric takes into account at least one type of parameter and is obtained by correlating the parameters, it reflects the diversity of the correlation metric and is based on the correlation of at least two parameters The correlation measure obtained by sex is used to evaluate the recovery state of the patient in a more accurate manner, that is, the human body is monitored from multiple dimensions, the diversity of monitoring is realized, and the accuracy of evaluating the rehabilitation of the human body is improved.

In the embodiment of the present invention, the device for evaluating the recovery state of the hospital patient from at least one type of related parameters, the process of extracting at least two parameters corresponding to the preset time period is: acquiring the human body state time parameter, exercise parameter and physiological parameter At least two types of parameters; and, extracting at least two parameters corresponding to the preset time period from the at least two types of parameters, wherein each type of related parameter corresponds to at least one parameter.

Based on this, the evaluation device of the hospital patient's recovery state performs correlation processing based on at least two parameters corresponding to the preset time period, and the process of obtaining the correlation metric is at least one of the following ways: based on at least two corresponding parameters within the preset time period Parameters to obtain a quantitative index on the correlation measure; and, based on at least two parameters corresponding to the preset time period, obtain a graphical index on the correlation measure.

On the one hand, based on different combinations of at least two parameters, they will be described separately below.

In some embodiments of the present invention, the evaluation device for the recovery state of the patient in the hospital may extract at least two types of parameters of the human body state time parameter, exercise amount parameter and physiological parameter within the preset time period, for the human body extracted within the preset time period At least two types of state time parameters, exercise parameters and physiological parameters are subjected to correlation processing to obtain correlation metrics.

In some embodiments of the present invention, when at least two types of parameters include a human body state time parameter and an exercise amount parameter, as shown in FIG. 8, FIG. 8 is one of an evaluation method of a hospital patient’s recovery state provided by an embodiment of the present invention An optional flowchart, the method may include:

S201. Acquire at least one motion signal of a patient.

In the embodiment of the present invention, the evaluation device for the recovery state of the hospital patient is equipped with a preset motion sensor, so the evaluation device for the recovery state of the hospital patient can acquire at least one original motion signal of the patient through the preset motion sensor; The original motion signal is filtered to obtain at least one motion signal.

It should be noted that, in the embodiment of the present invention, the evaluation device for the recovery state of the hospital patient can acquire at least one motion signal within a preset time period, or extract the preset time after acquiring at least one motion signal. At least one motion signal within the segment.

In the embodiment of the present invention, the evaluation device for the recovery state of the hospital patient acquires at least one original motion signal of the patient through a preset motion sensor, the at least one original motion signal is an electrical signal, and the evaluation device for the recovery state of the hospital patient has at least one original motion signal After hardware filtering and signal amplification of the signal, the analog-to-digital conversion is performed to complete the filtering of at least one original motion signal and remove the redundancy. After the mode conversion, at least one motion signal is obtained, so that at least one motion signal obtained in this way removes impurities, Can better reflect the essence of motion signals.

In the embodiment of the present invention, the preset motion sensor may be an accelerometer, and the at least one motion signal obtained in this manner may be at least one acceleration data. In this embodiment of the present invention, another motion sensor may be used to collect at least one motion signal. The embodiment of the present invention is not limited.

Exemplarily, as shown in FIG. 9, the evaluation device for the recovery state of the hospital patient adopts at least one original motion signal through an accelerometer preset by itself, and then filters the at least one original motion signal to remove clutter through hardware, and performs the signal After the method and analog-to-digital conversion, acceleration data (ie at least one motion signal) is obtained.

S202. Based on at least one motion signal, count human body state time parameters and exercise quantity parameters within a preset time period.

After the at least one motion signal is collected by the evaluation device for the recovery state of the hospital patient, the at least one motion signal is a signal within a preset period of time. Therefore, the evaluation device for the recovery state of the hospital patient can obtain Set the time parameters and exercise parameters of the human body state within the time period.

Specifically, the device for evaluating the recovery state of the patient in the hospital performs time domain feature or frequency domain feature extraction on at least one motion signal to obtain a motion feature, and based on the motion feature, obtains a motion time; and also calculates a preset time period based on at least one motion signal Within the amount of exercise parameters; according to the amount of exercise parameters and preset rest threshold, determine the time to get out of bed; according to the preset time period and time to get out of bed, determine the time to stay in bed; and you can also get the sleep time, the time to get out of bed, exercise time, preset Any one or more of the time period, bed time, and sleep time are used as human body state time parameters.

In the embodiment of the present invention, the device for evaluating the recovery state of the hospital patient performs time domain feature or frequency domain feature extraction on the at least one motion signal to obtain the motion feature, and based on the motion feature, the process of obtaining the motion time may include: The evaluation device extracts time-domain features and frequency-domain features (motion features) from at least one motion signal, and determines whether the patient is in motion according to the time-domain features or frequency-domain features. When it is determined that the patient is in motion, the patient is in motion State time, get exercise time.

In the embodiment of the present invention, the time domain information may include: search information and amplitude information, and the time domain characteristics may include: the average SMV (Signal Magnitude Vector acceleration intensity vector), SMA (Signal Magnitude Area), area Acceleration intensity), etc., frequency domain characteristics can include: ultra low frequency (VLF, Very Low Frequency), low frequency (LF, Low Frequency), high frequency (HF, High Frequency), TP (Total Power), LF/HF Features such as ratio are not limited in the embodiments of the present invention.

In the embodiment of the present invention, the evaluation device of the in-hospital patient recovery state based on the movement characteristics, the process of obtaining the exercise time is specifically as follows: the evaluation device of the in-hospital patient recovery state obtains the preset time characteristic threshold in real time; when the motion characteristic is greater than the preset time characteristic threshold When it is determined as the exercise state, record the duration of the exercise state to get the exercise time.

Here, the evaluation device for the recovery state of the patient in the hospital compares the time domain feature with the preset time domain threshold. When the time domain feature is greater than the preset time domain threshold, it is determined that the patient is in motion and is in motion. At this time, the patient is in motion. Time, you can get the patient's exercise time. Or, the evaluation device for the recovery state of the patient in the hospital compares the frequency domain feature with the preset frequency domain threshold, and when the frequency domain feature is greater than the preset frequency domain threshold, it is determined that the patient is in motion and is in motion. At this time, the patient is in motion The time of the state can get the patient's exercise time.

In the embodiment of the present invention, the preset time characteristic threshold includes a preset time domain threshold and a preset frequency domain threshold.

Exemplarily, for the time domain characteristics, the evaluation device of the hospital patient's recovery state compares the SMV with a preset time domain threshold (for example, 30 mg), or compares the SMA with a preset time domain threshold (for example, 9.8 per second), when the SMV or When the SMA and the preset time domain threshold are used, it can be judged that the patient is in motion and is in motion. At this time, the evaluation device for the recovery state of the patient in the hospital counts the time during which the patient is in motion, and the motion time can be obtained.

For the frequency domain features, the evaluation device of the hospital’s recovery state counts the time-frequency features (such as HF or LF/HF, etc.) within the preset time window, and when the frequency domain features are greater than the preset frequency domain threshold (such as 50%), it is determined When the patient is in motion and is in motion, and count the time when the patient is in motion, you can get the exercise time.

In the embodiment of the present invention, the preset motion sensor may include multiple types, and at least one motion signal obtained by the preset motion sensor may also count the amount of exercise parameters, such as cadence, step number, exercise distance, exercise intensity, and exercise consumption Calories, etc. These motion quantity parameters may be determined by at least one motion signal obtained by different preset motion sensors, or may be determined by at least one motion signal obtained by a preset motion sensor, which is not limited in this embodiment of the present invention.

In the embodiment of the present invention, according to clinical experience, the basic mode of the patient's activities after leaving the bed is: walk outside, sit and rest outside, walk again, rest, and after a few cycles, walk back to the ward after feeling tired, Rest in bed. Exemplarily, based on the mode used by the patient, the judgment of the time of leaving the bed can be determined

The time between two walks is less than the rest time of the preset rest threshold (for example, 5-15 minutes) + all the walking time (ie, exercise time), that is, the rest time is determined according to the amount of exercise parameters and the preset rest threshold, and the rest time And exercise time, determine the time to get out of bed. Statistics of bed time: In the preset time period, get the bed time, and use the total time-bed time to get the bed time, that is, determine the bed time according to the preset time period and the aforementioned bed time.

In some embodiments of the present invention, the evaluation device for the recovery state of the patient in the hospital may receive the bed leaving sensor or the bed-borne sensor to transmit the monitored bed leaving time and bed rest time. In other words, a sensor can be installed beside the bed, such as a video camera, for real-time observation of whether the patient is out of bed or the lying time on the bed through video images. For example, a bed-mounted sensor can be installed on the bed, such as bed-mounted Electrode detection sensor or pressure sensor, because the patient leaves the bed or lies on the bed will cause changes in the sampling signal of the bed-mounted electrode detection sensor or pressure sensor, based on this difference to determine whether the patient is out of bed or lying on the bed Time etc.

S203. Perform correlation processing on the human body state time parameter and the exercise amount parameter extracted within the preset time period to obtain a correlation metric.

After obtaining the human body state time parameter and exercise amount parameter in the hospital patient recovery state assessment device, the hospital patient recovery state assessment device can perform correlation processing according to the human body state time parameter and exercise amount parameter extracted within a preset time period To get the correlation measure.

In some embodiments of the present invention, when at least two types of parameters include human state time parameters and physiological parameters, as shown in FIG. 10, FIG. 10 is one of the methods for evaluating the recovery state of hospital patients provided by embodiments of the present invention. An optional flowchart, the method may include:

S301. Acquire at least one motion signal of a patient.

Here, the process of acquiring the at least one motion signal of the patient by the evaluation device for the recovery state of the patient in the hospital is consistent with the description of S201, and will not be repeated here.

S302. Based on at least one motion signal, count human body state time parameters within a preset time period.

Here, the evaluation device for the recovery state of the patient in the hospital counts the process of calculating the human body state time parameter within the preset time period based on at least one motion signal and the process of calculating the human body state time parameter within the preset time period based on at least one motion signal in S202 "Is consistent with the description and will not be repeated here.

S303. Acquire physiological parameters through a biological characteristic sensor.

Here, the sensor in the evaluation device for the recovery state of the hospital patient may further include a biometric sensor, so that the evaluation device for the recovery state of the hospital patient can also obtain the physiological parameters of the patient.

In the embodiment of the present invention, the biometrics sensor may include a sleep detection sensor, a heart rate sensor, a pulse sensor, etc. that can detect physiological parameters of the human body, for example, heart rate and respiration rate can be detected through an attachment of an electrocardiographic sensor, and detected through a pulse wave The sensor can obtain the pulse rate, and the electrode provided on the hospital bed can detect whether the human body has left the bed to determine the sleep state, etc. The embodiment of the present invention is not limited.

S304. Perform correlation processing on the human body state time parameters and physiological parameters extracted within a preset time period to obtain correlation metrics.

After the patient’s recovery state assessment device in the hospital has acquired the human body state time parameters and physiological parameters, the hospital patient recovery state assessment device can perform correlation processing based on the extracted human body state time parameters and physiological parameters within a preset time period To get the correlation measure.

Exemplarily, the combination of human body state time parameters and physiological parameters (taking heart rate and pulse rate as examples) includes: exercise time and heart rate; bed time and heart rate; bed time and heart rate; preset time period and heart rate; sleep time and Heart rate.

Further, in the embodiment of the present invention, at least two types of parameters may also include: physiological parameters and exercise quantity parameters, physiological parameters, human body state time parameters and exercise quantity parameters. Based on the foregoing embodiment, the preset time has been clarified. Under the premise of how to obtain the human body state time parameters, physiological parameters and exercise quantity parameters in the segment, the evaluation device of the hospital patient's recovery state only needs to perform correlation processing on the parameters of different combinations to obtain the correlation measurement to perform the patient The evaluation of the recovery state is not repeated here.

On the other hand, the device for evaluating the recovery state of patients in the hospital can extract the parameters of different dimensions of at least two parameters of the human body state time parameter, exercise quantity parameter and physiological parameter within the preset time period, for the human body extracted within the preset time period The parameters of different dimensions of at least two parameters of the state time parameter, the exercise quantity parameter and the physiological parameter are subjected to correlation processing to obtain a correlation metric.

In some embodiments of the present invention, when at least one type of related parameter is a human state time parameter, as shown in FIG. 11, FIG. 11 is an optional method for evaluating the recovery state of a patient in a hospital according to an embodiment of the present invention. Schematic diagram of the process, the method may include:

S401. Acquire human body state time parameters as at least one type of related parameters.

S402. Extract at least two time parameters corresponding to a preset time period from the human body state time parameters as at least two parameters.

S403. Perform correlation processing on at least two time parameters extracted within a preset time period to obtain a correlation metric.

In the embodiment of the present invention, at least two time parameters within a preset time period are extracted as the at least two time parameters from the human body state parameters obtained by the evaluation device for the recovery state of the hospital patient, and finally, based on the at least two time parameters Relevance processing.

It should be noted that the process of acquiring the time parameters of the human body state by the evaluation device for the recovery state of the patient in the hospital has been described in the foregoing embodiments, and will not be repeated here. The time parameter of the human body state obtained by the evaluation device for the recovery state of the patient in the hospital is one or more of the time to get out of bed, the time to exercise, the preset time period, the time to stay in bed, and the time to sleep.

In the embodiment of the present invention, the human body state time parameters include: exercise time parameters and sleep time parameters. Among them, the exercise time parameters include: out of bed time, exercise time, bed time and preset time period.

When the time parameter of the human body state is only the motion time parameter, the acquisition process of the at least two parameters is as follows: the evaluation device for the recovery state of the hospital patient acquires at least one motion signal of the patient, and extracts the time domain feature or the frequency domain feature from the at least one motion signal , To obtain movement characteristics; based on the movement characteristics, to obtain at least one movement time parameter of at least one dimension characterizing the movement time parameter within a preset time period; to obtain the sleep time parameter of the patient; to use the sleep time parameter and at least one movement time parameter as At least two time parameters as at least two parameters. That is, the evaluation device for the recovery state of the patient in the hospital acquires at least two of the bed-off time, exercise time, bed rest time, and preset time period as at least two time parameters.

At this time, the combination of at least two time parameters includes any of the following:

Exercise time and bed leaving time;

Exercise time and preset time period;

Bed leaving time and preset time period;

Exercise time and bed time;

Bed time and bed time;

Bed time and preset time period;

Exercise time, bed leaving time and preset time period;

Exercise time, bed rest time and preset time period;

Exercise time, bed time and bed time;

Bed time, bed time and preset time period;

Exercise time, bed time, bed time and preset time period.

When the human body state time parameter includes exercise time parameter and sleep time parameter, the acquisition process of at least two parameters is: the in-hospital patient recovery state assessment device acquires at least one movement signal and sleep time parameter of the patient; Extract the domain feature or frequency domain feature to obtain the motion feature; based on the motion feature, obtain at least one motion time parameter of at least one dimension characterizing the motion time parameter within a preset time period; use the sleep time parameter and at least one motion time parameter as At least two time parameters as at least two parameters.

Among them, the combination of at least one exercise time parameter includes any one of the following:

time for excercise;

Bed time

Preset time period;

Exercise time and bed leaving time;

Exercise time and preset time period;

Bed leaving time and preset time period;

Exercise time and bed time;

Bed time and bed time;

Bed time and preset time period;

Exercise time, bed leaving time and preset time period;

Exercise time, bed rest time and preset time period;

Exercise time, bed time and bed time;

Bed time, bed time and preset time period;

Exercise time, bed time, bed time and preset time period.

In the embodiment of the present invention, the specific process of obtaining the exercise time parameter is described in detail in the foregoing embodiment, and will not be repeated here.

In some embodiments of the present invention, when at least one type of parameter is an exercise quantity parameter, as shown in FIG. 12, FIG. 12 is an optional flowchart of a method for evaluating the recovery state of a hospital patient provided by an embodiment of the present invention. , The method may include:

S501. Acquire a motion amount parameter as at least one type of related parameter.

S502. Extract at least two exercise quantity parameters corresponding to a preset time period from the exercise quantity parameters as at least two parameters.

S503. Perform correlation processing on at least two motion quantity parameters extracted within a preset time period to obtain a correlation metric.

In the embodiment of the present invention, at least two exercise quantity parameters within a preset time period are extracted from the exercise quantity parameters obtained by the evaluation device of the hospital patient's recovery state, and finally, correlation processing is performed based on the at least two exercise quantity parameters.

It should be noted that the process of obtaining the exercise quantity parameter by the evaluation device for the recovery state of the patient in the hospital has been described in the foregoing embodiments, and will not be repeated here. The exercise quantity parameters acquired by the evaluation device for the recovery state of the patients in the hospital are one or more of cadence, step number, exercise distance, exercise intensity and exercise calorie consumption.

Further, in the embodiment of the present invention, at least one type of related parameters may further include: physiological parameters. When at least two parameters are physiological parameters, the evaluation device of the hospital patient's recovery state acquires at least two physiological relevant parameters of the physiological parameters; at least two physiological relevant parameters are at least one type of relevant parameters, from the at least two physiological relevant parameters, Extracting at least two physiological parameters corresponding to the preset time period, performing correlation processing on the at least two physiological parameters extracted from the preset time period to obtain a correlation measure.

In some embodiments of the present invention, referring to FIG. 13, FIG. 13 is a schematic flowchart of an optional method for evaluating the recovery state of a hospital patient according to an embodiment of the present invention. Based on FIG. 7, the device for evaluating the recovery state of a patient in the hospital obtains After the correlation measurement, S104 or S105 can also be performed. as follows:

S104. Present the correlation measure.

After obtaining the correlation measure, the evaluation device for the recovery state of the patient in the hospital can directly present the correlation measure, so that the doctor can intuitively observe the recovery state of the patient through the correlation measure and reflect the intuitive visualization performance.

In the embodiment of the present invention, it can be displayed directly or played by voice. Of course, the correlation measure can also be presented in at least one of the following ways:

The quantitative indicators related to the correlation measure obtained at different times are refreshed and displayed in sequence with time;

Over time, refresh and display the graphical indicators related to the correlation measurement obtained at different times;

Construct a coordinate system that changes along time, and mark the quantitative indicators about the correlation measure corresponding to different moments in the coordinate system that changes along time to form a change trend graph of the quantitative indicators; and,

Construct a coordinate system that changes along time, and mark a graphical index on the correlation measure corresponding to different moments in the coordinate system that changes along time to form a change trend graph of the graphical index.

S105. Transmit the correlation measure to the bedside monitor and/or central station; so that the correlation measure is presented on the bedside monitor and/or central station.

After obtaining the correlation measure, the evaluation device for the recovery state of the hospital patient can also transmit the correlation measure to the bedside monitor and/or the central station; so that the bedside monitor and/or The correlation measure is presented on the central station, showing the intelligent effect of performing the correlation measure on the third-party device.

Further, in the embodiment of the present invention, after the in-hospital patient recovery state evaluation device obtains at least two parameters, the process of performing correlation processing on the at least two parameters and presenting the correlation metric may be restored by the hospital patient to the state The third-party device communicates with the evaluation device of the evaluation device; or, after the evaluation device of the in-hospital patient’s recovery state acquires at least two parameters and performs correlation processing on the at least two parameters, the process of presenting the correlation measure may be performed by The third-party device communicates with the evaluation device of the patient's recovery status in the hospital. The specific implementation principle is the same as the processing principle of the evaluation device of the patient's recovery state in the hospital, and will not be repeated here.

In the embodiment of the present invention, the third-party device may include a bedside monitor and/or a central station, and the embodiment of the present invention is not limited.

In the following, the human body state time parameters including the first time parameter and the second time are used to describe the process of the correlation measurement of the in-hospital patient's recovery state assessment device based on the two time parameters.

Referring to FIG. 14, FIG. 14 is a schematic flowchart of an optional method for evaluating the recovery state of a hospital patient provided by an embodiment of the present invention. The foregoing method includes:

S601. Acquire a first time parameter and a second time parameter of a corresponding human body state time parameter within a preset time period; the first time parameter and the second time parameter respectively represent at least one time dimension time parameter of the human body state time parameter.

In the embodiment of the present invention, the evaluation device for the recovery state of the hospital patient collects at least one motion signal, obtains the human body state time parameter based on the at least one motion signal, and extracts the corresponding first time within a preset time period from the human body state time parameter The time parameter and the second time parameter have at least two dimensions of time.

In the embodiment of the present invention, the human body state time parameters include exercise time parameters and sleep time parameters, where the exercise time parameters may also include: multi-dimensional time parameters, for example, exercise time, bed time, bed time, and Set the time period, etc. That is to say, the evaluation device for the recovery state of the patient in the hospital obtains the first time parameter and the second time parameter according to the exercise time parameter and the sleep time parameter.

S602: Perform correlation processing on the first time parameter and the second time parameter to obtain a correlation metric; the correlation metric is used to evaluate the recovery state of the patient.

After the first time parameter and the second time parameter are acquired by the evaluation device for the recovery state of the hospital patient, the evaluation device for the recovery state of the hospital patient can perform relevant processing on the first time parameter and the second time parameter, so as to be used for evaluation Correlation measure of the patient's recovery status.

In the embodiment of the present invention, the device for evaluating the recovery state of the patient in the hospital can obtain a preset correlation algorithm; the preset correlation algorithm is used to calculate the correlation between the first time parameter and the second time parameter to obtain a correlation metric. A correlation measure is output and displayed on the monitoring device, and the correlation measure includes a quantitative indicator and/or a graphical indicator.

In the embodiment of the present invention, the preset correlation algorithm includes at least one of the following: ratio calculation, difference calculation, integral ratio calculation, area ratio calculation, integral difference calculation, and area difference calculation, and the embodiment of the present invention does not limit it.

In some embodiments of the present invention, when the human body state time parameter includes the exercise time parameter, the process of S601 may include: S6011-6013. as follows:

S6011: Acquire at least one motion signal of the patient within a preset time period;

S6012: Perform time domain feature or frequency domain feature extraction on at least one motion signal to obtain a motion feature;

S6013: Based on the motion characteristics, obtain a first time parameter and a second time parameter that characterize the motion time parameter statistics within a preset time period.

In some embodiments of the present invention, the process of acquiring the first time parameter and the second time parameter that characterize the movement time parameter statistics within the preset time period based on the movement characteristics includes: determining the movement time according to the aforementioned movement characteristics; based on at least A motion signal that counts the amount of exercise parameters within a preset period of time; determines the time to get out of bed based on the amount of exercise parameters, preset rest threshold, and exercise time; determines the time to bed based on the preset period of time and the aforementioned time to get out of bed; The first time parameter and the second time parameter are selected from among the motion time of the parameter, the aforementioned bed leaving time, the preset time period and the bed rest time.

In some embodiments of the present invention, the combination of the first time parameter and the second time parameter is any one of the following:

Exercise time and bed leaving time;

Exercise time and preset time period;

Bed leaving time and preset time period;

Exercise time and bed time;

Bed time and bed time;

Bed time and preset time period.

In some embodiments of the present invention, the evaluation device for the recovery state of the in-hospital patient performs time domain feature or frequency domain feature extraction on at least one motion signal to obtain the motion feature, and from the foregoing motion time, bed leaving time, and preset time period Before selecting the first time parameter and the aforementioned second time parameter from the bed time, the bed leaving time and the bed time monitored by the receiving bedside sensor transmission are received.

In the embodiment of the present invention, a bedside sensor is provided in front of the patient's bed. The bedside sensor and bed time can be obtained through the bedside sensor, and then the bed time and bed time are sent to the evaluation device of the patient's recovery state in the hospital for use.

In the embodiment of the present invention, the bedside sensor may be provided on the hospital bed or on the bedside monitor. The embodiment of the present invention is not limited. Among them, the equipment where the bedside sensor is located can communicate with the evaluation device of the patient's recovery state in the hospital.

Optionally, the communication method may include wireless communication technology, which is not limited in the embodiment of the present invention.

In some embodiments of the present invention, when the human body state time parameters include exercise time parameters and sleep time parameters, the process of S601 may include: S6014-S6018. as follows:

S6014. Acquire a motion signal of the patient within a preset time period;

S6015: Perform time domain feature or frequency domain feature extraction on a motion signal to obtain a first motion feature;

S6016: Based on the first motion feature, obtain a motion time parameter that characterizes the motion time parameter within a preset time period.

S6017: Acquire the sleep time parameter of the patient within a preset time period.

S6018. Use the sleep time parameter and a motion time parameter as the first time parameter and the second time parameter.

In the embodiment of the present invention, the combination of the first time parameter and the second time parameter is any one of the following:

Exercise time and sleep time parameters;

Preset time period and sleep time parameters;

Parameters of bed time and sleep time;

Bed time and sleep time parameters.

It should be noted that the process of acquiring human body time parameters and the process of correlation measurement in the embodiments of the present invention have been discussed in detail in the foregoing embodiments, and will not be repeated here.

It can be understood that, because the evaluation device for the recovery state of the patient in the hospital can obtain the correlation metric for evaluating the recovery state of the patient from the correlation between the first time parameter and the second time parameter of the time parameter of the human body state, due to the correlation The correlation measure takes into account the two-dimensional time parameters, and the correlation of the parameters is obtained, thus reflecting the diversity of the correlation measure. Therefore, based on the correlation of the multiple dimensions of the first time parameter and the second time parameter The correlation measure is used to evaluate the recovery state of the patient in a more accurate manner, that is, to monitor the human body from multiple dimensions, to achieve diversity in monitoring, and to improve the accuracy of evaluating the recovery of the human body.

An embodiment of the present invention provides a computer-readable storage medium that stores executable instruction for evaluating the recovery state of a hospital patient, and when used to cause the processor to execute, it will cause the processor to perform the evaluation of the recovery state of the hospital patient provided by the embodiment of the present invention. method.

In some embodiments of the present invention, the computer-readable storage medium may be FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM and other memories; it may also include one of the above memories or Various devices in any combination.

In some embodiments of the present invention, the evaluation instructions that can execute the recovery state of the hospital patient can be in the form of programs, software, software modules, scripts, or codes, in any form of programming language (including compiled or interpreted languages, or declarative or Written in a procedural language), and it can be deployed in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

As an example, an executable instruction for evaluating the patient's recovery status in the hospital may but does not necessarily correspond to a file in the file system, and may be stored in a part of a file that stores other programs or data, for example, stored in a hypertext markup language (HTML, HyperText (MarkupLanguage) in one or more scripts in the document, stored in a single file dedicated to the program in question, or in multiple collaborative files (for example, storing one or more modules, subprograms, or code Part of the document).

As an example, an instruction for evaluating the recovery state of an in-hospital patient may be deployed to be executed on one computing device, or executed on multiple computing devices located in one location, or may be distributed in multiple locations and communicate with each other through a communication network. On multiple computing devices.

The above are only the embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modification, equivalent replacement and improvement made within the spirit and scope of the present invention are included in the protection scope of the present invention.

Industrial applicability

Embodiments of the present invention provide a method, device, system, and storage medium for evaluating the recovery state of a hospital patient. The evaluation device for the recovery state of a hospital patient can be performed from at least one type of related parameters of the human body state time parameter, exercise amount parameter, and physiological parameter. The acquisition of at least two parameters, through the correlation processing of the at least two parameters, obtains a correlation metric for evaluating the recovery state of the patient, because the correlation metric takes into account at least one type of parameter, and the parameter is obtained by correlation Therefore, the diversity of correlation measures is reflected, and the correlation measure obtained based on the correlation of at least two parameters is used to assess the recovery state of the patient in a more accurate manner, that is, monitoring the human body from multiple dimensions and monitoring The diversity of the system has improved the accuracy of evaluating the rehabilitation of the human body.

Claims

A method for evaluating the recovery state of a patient in a hospital, the method comprising:

Obtain the first time parameter and the second time parameter of the corresponding human body state time parameter within the preset time period; the first time parameter and the second time parameter respectively represent at least one time dimension time parameter of the human body state time parameter ;

Correlation processing is performed on the first time parameter and the second time parameter to obtain a correlation metric, and the correlation metric is used to evaluate the recovery state of the patient.
The method according to claim 1, wherein the human body state time parameter includes an exercise time parameter, and the first time parameter and second time parameter for acquiring the corresponding human body state time parameter within a preset time period include:

Acquiring at least one motion signal of the patient within the preset time period;

Performing time domain feature or frequency domain feature extraction on the at least one motion signal to obtain motion features;

Based on the movement characteristics, the first time parameter and the second time parameter that characterize the movement time parameter statistics in the preset time period are acquired.
The method according to claim 1, wherein the human body state time parameter includes an exercise time parameter and a sleep time parameter, and the first time parameter and the second time parameter of acquiring the corresponding human body state time parameter within a preset time period ,include:

Acquiring a motion signal of the patient within the preset time period;

Performing time domain feature or frequency domain feature extraction on the one motion signal to obtain a first motion feature;

Based on the first motion feature, acquiring a motion time parameter characterizing the motion time parameter within the preset time period;

Acquiring the sleep time parameter of the patient within the preset time period;

The sleep time parameter and the one exercise time parameter are used as the first time parameter and the second time parameter.
The method according to claim 2, wherein, based on the motion characteristics, acquiring the first time parameter and the second time parameter characterizing the motion time parameter statistics in the preset time period, include:

Determine the exercise time according to the movement characteristics;

Based on the at least one motion signal, statistics of the amount of motion parameters in the preset time period;

Determine the time to get out of bed according to the exercise amount parameter, preset rest threshold and the exercise time;

Determine the bed time according to the preset time period and the bed leaving time;

The first time parameter and the second time parameter are selected from the exercise time, the bed leaving time, the preset time period, and the bed time characterizing the exercise time parameter.
The method according to claim 4, wherein after performing time-domain feature or frequency-domain feature extraction on the at least one motion signal to obtain a motion feature, and from the motion time, the bed-off time, Before the first time parameter and the second time parameter are selected from the preset time period and the bed rest time, the method further includes:

The bedside sensor transmits the monitored bed leaving time and bed rest time.
The method according to claim 4, wherein the combination of the first time parameter and the second time parameter is any one of the following:

The exercise time and the bed leaving time;

The exercise time and the preset time period;

The bed leaving time and the preset time period;

The exercise time and the bed time;

The bed leaving time and the bed rest time;

The bed rest time and the preset time period.
The method according to claim 1, wherein the performing correlation processing on the first time parameter and the second time parameter to obtain a correlation metric includes:

Get preset correlation algorithm;

The preset correlation algorithm is used to calculate the correlation between the first time parameter and the second time parameter to obtain the correlation metric.
The method according to claim 1, wherein

The correlation measure is output and displayed on the monitoring device, and the correlation measure includes a quantitative indicator and/or a graphical indicator.
A method for evaluating the recovery state of a patient in a hospital, the method comprising:

Obtain at least one type of related parameters from the human body state time parameter, exercise parameter and physiological parameter;

Extract at least two parameters corresponding to the preset time period from the at least one type of related parameters; and,

Correlation processing is performed based on at least two parameters corresponding to the preset time period to obtain a correlation metric, and the correlation metric is used to evaluate the recovery state of the patient.
The method according to claim 9, wherein the acquiring at least one type of related parameters among the human body state time parameter, the exercise amount parameter and the physiological parameter, and extracting from the at least one type of related parameter a corresponding parameter within a preset time period At least two parameters, including:

Acquiring at least two types of parameters of the human body state time parameter, the exercise quantity parameter and the physiological parameter; and,

At least two parameters corresponding to the preset time period are extracted from the at least two types of parameters, wherein each type of related parameter corresponds to at least one parameter.
The method according to claim 9, wherein the performing correlation processing based on at least two parameters corresponding to the preset time period to obtain a correlation metric includes at least one of the following ways:

Based on at least two parameters corresponding to the preset time period, obtain a quantitative index regarding the correlation measure; and,

Based on the at least two parameters corresponding to the preset time period, a graphical indicator regarding the correlation measure is obtained.
The method according to claim 9, wherein the extracting the at least two parameters corresponding to the preset time period from the at least one type of related parameters includes:

Acquiring the human body state time parameter as the at least one type of related parameter; and,

Extracting at least two time parameters corresponding to a preset time period from the human body state time parameters as the at least two parameters.
The method according to claim 12, wherein the performing correlation processing based on at least two parameters corresponding to the preset time period to obtain a correlation metric includes:

Performing correlation processing on the at least two time parameters extracted within the preset time period to obtain a quantified index about the correlation metric.
The method according to claim 9, wherein the extracting the at least two parameters corresponding to the preset time period from the at least one type of related parameters includes:

Acquiring the exercise quantity parameter as the at least one type of related parameter;

Extracting, from the exercise quantity parameters, at least two exercise quantity parameters corresponding to a preset time period as the at least two parameters.
The method according to claim 14, wherein the performing correlation processing based on at least two parameters corresponding to the preset time period to obtain a correlation metric includes:

Performing correlation processing on the at least two motion quantity parameters extracted in the preset time period to obtain the correlation metric.
The method according to claim 12, wherein the human body state time parameter includes an exercise time parameter, and the at least two time parameters corresponding to a preset time period are extracted from the human body state time parameter as the at least Two parameters, including:

Acquiring at least one motion signal of the patient;

Performing time domain feature or frequency domain feature extraction on the at least one motion signal to obtain motion features;

Based on the motion characteristics, the at least two time parameters statistically obtained in at least two dimensions characterizing the motion time parameters in the preset time period are acquired as the at least two parameters.
The method according to claim 12, wherein the human body state time parameter includes an exercise time parameter and a sleep time parameter, and the at least two time parameters corresponding to a preset time period are extracted from the human body state time parameter, The at least two parameters include:

Acquiring at least one motion signal of the patient, and performing time domain feature or frequency domain feature extraction on the at least one motion signal to obtain a motion feature;

Based on the movement characteristics, acquiring at least one movement time parameter in at least one dimension characterizing the movement time parameter within the preset time period;

Obtaining the sleep time parameter of the patient;

The sleep time parameter and the at least one exercise time parameter are used as the at least two time parameters as the at least two parameters.
The method according to claim 10, wherein the at least two types of parameters include at least one of the following:

The human body state time parameter and the exercise quantity parameter, the human body state time parameter and the physiological parameter, the exercise quantity parameter and the physiological parameter, and the human body state time parameter, the exercise quantity parameter and the physiological state parameter.
The method according to claim 18, wherein when the at least two types of parameters include the human body state time parameter and the exercise amount parameter, the acquiring the human body state time parameter, the exercise amount parameter, and the physiology At least two types of parameters, including:

Acquiring at least one motion signal of the patient;

Based on the at least one motion signal, the human body state time parameter and the motion amount parameter within the preset time period are counted.
The method according to claim 18, wherein when the at least two types of parameters include the human body state time parameter and the physiological parameter, the acquiring the human body state time parameter, the exercise quantity parameter and the physiological state At least two types of parameters, including:

Acquiring at least one motion signal of the patient;

Based on the at least one motion signal, counting the human body state time parameter within the preset time period;

The physiological parameter is acquired through a biological characteristic sensor.
The method according to any one of claims 16, 17, 19, or 20, wherein the acquiring at least one motion signal of the patient includes:

Acquiring the at least one original motion signal of the patient through a preset motion sensor;

Filtering the at least one original motion signal to obtain the at least one motion signal.
The method according to claim 16, wherein, based on the motion feature, acquiring the at least two time parameters that are counted in at least two dimensions of the human body state time parameter within the preset time period, The at least two parameters include:

Based on the movement characteristics, the exercise time is obtained;

Based on the at least one motion signal, counting the motion amount parameter in the preset time period;

Determine the time to get out of bed according to the exercise amount parameter, preset rest threshold and the exercise time;

Determine the bed time according to the preset time period and the bed leaving time;

Any at least two combinations of the bed leaving time, the exercise time, the preset time period and the bed rest time are used as the at least two time parameters in the human body state time parameter as the at least Two parameters.
The method according to claim 22, wherein the obtaining exercise time based on the exercise characteristics comprises:

Obtain the preset time characteristic threshold in real time;

When the movement characteristic is greater than the preset time characteristic threshold, it is determined as a movement state, and the duration of the movement state is recorded to obtain the movement time.
The method according to claim 23, wherein after the exercise time is obtained based on the movement characteristics, and the bed leaving time, the exercise time, the preset time period and the bed time are obtained Before any combination of at least two of the at least two time parameters in the human body state time parameter, the method further includes:

The bedside sensor or bedside sensor transmits the monitored bed leaving time and bed rest time.
The method according to claim 9, wherein the performing correlation processing based on at least two parameters corresponding to the preset time period to obtain a correlation metric includes:

Get preset correlation algorithm;

The preset correlation algorithm is used to calculate the correlation of at least two parameters corresponding to the preset time period to obtain the correlation metric.
The method according to claim 25, wherein the preset correlation algorithm includes at least one of the following: ratio calculation, difference calculation, integral ratio calculation, area ratio calculation, integral difference calculation, and area difference calculation.
The method according to claim 9, wherein the correlation processing is performed based on at least two parameters corresponding to a preset time period, and after obtaining a correlation metric, the method further comprises:

Presenting the correlation measure, the manner of presenting the correlation measure adopts at least one of the following ways:

The quantitative indicators related to the correlation measure obtained at different times are refreshed and displayed in sequence with time;

Over time, refresh and display the graphical indicators related to the correlation measurement obtained at different times;

Construct a coordinate system that changes along time, and mark the quantitative indicators about the correlation measure corresponding to different moments in the coordinate system that changes along time to form a change trend graph of the quantitative indicators; and,

Construct a coordinate system that changes along time, and mark a graphical index on the correlation measure corresponding to different moments in the coordinate system that changes along time to form a change trend graph of the graphical index.
The method according to claim 9, wherein the correlation processing is performed based on at least two parameters corresponding to a preset time period, and after obtaining a correlation metric, the method further comprises:

Transmitting the correlation measure to the bedside monitor and/or the central station; causing the correlation measure to be presented on the bedside monitor and/or the central station.
An evaluation system for the recovery state of a patient in a hospital, the system comprising: at least one wearable device, the at least one wearable device is worn on the patient;

The at least one wearable device is used to obtain at least one type of related parameters among the human body state time parameter, the exercise amount parameter and the physiological parameter; Parameters; and performing correlation processing based on at least two parameters corresponding to the preset time period to obtain a correlation metric, where the correlation metric is used to evaluate the recovery state of the patient.
The system of claim 29, wherein

The at least one wearable device is also used for performing correlation processing based on at least two parameters corresponding to the preset time period, and after obtaining a correlation metric, presenting the correlation metric.
The system of claim 29, wherein the system further comprises: a bedside monitor that communicates with the at least one wearable device;

The at least one wearable device is configured to extract at least two parameters corresponding to a preset time period from the at least one type of related parameters, and then transmit the at least two parameters to the bedside monitor;

The bedside monitor is used to perform correlation processing on the at least two parameters, obtain the correlation metric, and present the correlation metric.
The system according to claim 29 or 31, wherein the system further comprises: a central station, the central station communicating with the at least one wearable device;

The at least one wearable device is configured to extract at least two parameters corresponding to a preset time period from the at least one type of related parameters, and then transmit the at least two parameters to the central station;

The central station is configured to perform correlation processing on the at least two parameters, obtain the correlation metric, and present the correlation metric.
The system of claim 29, wherein the system further comprises: a bedside monitor that communicates with the at least one wearable device;

The at least one wearable device is also used to perform correlation processing based on at least two parameters corresponding to the preset time period to obtain a correlation metric, and then transmit the correlation metric to the bedside monitor ;

The bedside monitor is used to present the correlation measure.
The system according to claim 29 or 33, wherein the system further comprises: a central station, the central station communicating with the at least one wearable device;

The at least one wearable device is further configured to perform correlation processing based on at least two parameters corresponding to the preset time period, and after obtaining a correlation metric, transmit the correlation metric to the central station;

The central station is used to present the correlation metric.
The system of claim 29, wherein

The at least one wearable device is specifically configured to obtain a quantified index regarding the correlation measure based on at least two parameters corresponding to the preset time period; and, based on at least two corresponding parameters within the preset time period Parameters to obtain graphical indicators about correlation metrics.
The system of claim 29, wherein

The at least one wearable device is specifically used to obtain the human body state time parameter as the at least one type of related parameter; and,

Extracting at least two time parameters corresponding to a preset time period from the human body state time parameters as the at least two parameters; and for the at least two time parameters extracted within the preset time period, Correlation processing to obtain a quantitative index on the correlation measure.
The system of claim 29, wherein

The at least one wearable device is specifically configured to extract at least two exercise quantity parameters corresponding to a preset time period from the exercise quantity parameters as the at least two parameters and the extracted data within the preset time period The at least two motion quantity parameters are subjected to correlation processing to obtain the correlation metric.
The system according to claim 36, wherein the human body state time parameters include exercise time parameters;

The at least one wearable device is further specifically used to obtain at least one motion signal of the patient; perform time domain feature or frequency domain feature extraction on the at least one motion signal to obtain a motion feature; based on the motion feature, obtain The at least two time parameters counted in at least two dimensions of the motion time parameter within the preset time period are used as the at least two parameters.
The system according to claim 36, wherein the human body state time parameters include exercise time parameters and sleep time parameters;

The at least one wearable device is further specifically used to obtain at least one motion signal of the patient; perform time domain feature or frequency domain feature extraction on the at least one motion signal to obtain a motion feature; based on the motion feature, obtain At least one exercise time parameter counted in at least one dimension characterizing the exercise time parameter within the preset time period; during the preset time period, acquiring the sleep time parameter of the patient; converting the sleep time parameter And the at least one movement time parameter as the at least two time parameters as the at least two parameters.
The system of claim 35, wherein the at least two types of parameters include at least one of the following:

The human body state time parameter and the exercise quantity parameter, the human body state time parameter and the physiological parameter, the exercise quantity parameter and the physiological parameter, and the human body state time parameter, the exercise quantity parameter and the physiological state parameter.
The system of claim 40, wherein

The at least one wearable device is further specifically used to obtain at least one movement signal of the patient; and based on the at least one movement signal, statistics of the human body state time parameter and the amount of exercise within the preset time period parameter.
The system according to claim 40, wherein when the at least two types of parameters include the human body state time parameter and the physiological parameter, the at least one wearable device is further specifically used to obtain at least A motion signal; acquiring the physiological parameter through a biological characteristic sensor; based on the at least one motion signal, counting the human body state time parameter within the preset time period.
The system according to any one of claims 38, 39, 41 or 42, wherein

The at least one wearable device is further specifically configured to acquire the at least one original motion signal of the patient through a preset motion sensor; filter the at least one original motion signal to obtain the at least one motion signal.
The system of claim 38, wherein

The at least one wearable device is further specifically used to obtain an exercise time based on the exercise characteristics; based on the at least one exercise signal, count the exercise amount parameter in the preset time period; according to the exercise amount parameter, Preset a rest threshold and the exercise time to determine the time to get out of bed; determine the time to stay in bed according to the preset time period and the time to get out of bed; combine the time to get out of bed, the exercise time and the preset time Any at least two combinations of the segment and the bed rest time are used as the at least two time parameters in the human body state time parameter as the at least two parameters.
The system of claim 44, wherein:

The at least one wearable device is also specifically used to obtain a preset time characteristic threshold in real time; when the movement characteristic is greater than the preset time characteristic threshold, it is determined to be a movement state, and the duration of the movement state is recorded to obtain Describe exercise time.
The system of claim 45, wherein

The at least one wearable device is further used for obtaining the exercise time based on the movement characteristics, and the step of leaving the bed, the exercise time, the preset time period and the bed time Before any at least two of the combinations are used as the at least two time-related parameters in the human body state time parameter, receive the bedside sensor or the bedborne sensor to transmit the bed leaving time and the bed time monitored by the bedside sensor or the bedborne sensor.
The system of claim 29, wherein

The at least one wearable device is specifically used to obtain a preset correlation algorithm; the preset correlation algorithm is used to calculate the correlation of at least two parameters corresponding to the preset time period to obtain the correlation measure.
The system of claim 35, wherein

Presenting the correlation measure, the manner of presenting the correlation measure adopts at least one of the following ways:

The quantitative indicators related to the correlation measure obtained at different times are refreshed and displayed in sequence with time;

Over time, refresh and display the graphical indicators related to the correlation measurement obtained at different times;

Construct a coordinate system that changes along time, and mark the quantitative indicators about the correlation measure corresponding to different moments in the coordinate system that changes along time to form a change trend graph of the quantitative indicators; and,

Construct a coordinate system that changes along time, and mark a graphical index on the correlation measure corresponding to different moments in the coordinate system that changes along time to form a change trend graph of the graphical index.
An evaluation device for the recovery state of a patient in a hospital, the device comprising:

The obtaining part is configured to obtain at least one type of related parameters among the human body state time parameter, the exercise quantity parameter and the physiological parameter;

An extracting part, configured to extract at least two parameters corresponding to a preset time period from the at least one type of related parameters;

The correlation part is configured to perform correlation processing based on at least two parameters corresponding to the preset time period to obtain a correlation metric, and the correlation metric is used to evaluate a patient's recovery state.
The apparatus according to claim 49, wherein

The acquiring part is specifically configured to acquire at least two types of parameters of the human body state time parameter, the exercise quantity parameter and the physiological parameter; and,

At least two parameters corresponding to the preset time period are extracted from the at least two types of parameters, wherein each type of related parameter corresponds to at least one parameter.
The apparatus according to claim 50, wherein

The correlation part is specifically configured to obtain a quantitative index about the correlation measure based on at least two parameters corresponding to the preset time period; and,

Based on the at least two parameters corresponding to the preset time period, a graphical indicator regarding the correlation measure is obtained.
The apparatus according to claim 49, wherein

The acquiring part is specifically configured to acquire the human body state time parameter as the at least one type of related parameter; and,

Extracting at least two time parameters corresponding to a preset time period from the human body state time parameters as the at least two parameters.
The apparatus of claim 52, wherein

The correlation part is specifically configured to perform correlation processing on the at least two time parameters extracted within the preset time period to obtain the correlation metric.
The apparatus according to claim 49, wherein

The acquiring section is specifically configured to acquire the exercise quantity parameter as the at least one type of related parameter; extract at least two exercise quantity parameters corresponding to a preset time period from the exercise quantity parameter as the at least two parameters .
The apparatus according to claim 54, wherein

The correlation part is specifically configured to perform correlation processing on the at least two motion amount parameters extracted within the preset time period to obtain the correlation metric.
The apparatus according to claim 52, wherein the human body state time parameter includes an exercise time parameter;

The acquiring part is further specifically configured to acquire at least one motion signal of the patient; and perform time domain feature or frequency domain feature extraction on the at least one motion signal to obtain a motion feature; and based on the motion feature, obtain The at least two time parameters counted in at least two dimensions of the motion time parameter within the preset time period are used as the at least two parameters.
The device according to claim 52, wherein the human body state time parameters include exercise time parameters and sleep time parameters;

The acquiring section is further specifically configured to acquire at least one motion signal of the patient, and perform time domain feature or frequency domain feature extraction on the at least one motion signal to obtain a motion feature; based on the motion feature, obtain the pre Set at least one exercise time parameter that counts at least one dimension of the exercise time parameter within a time period; obtain a sleep time parameter of the patient; use the sleep time parameter and the at least one exercise time parameter as the at least one Two time parameters are used as the at least two parameters.
The apparatus according to claim 50, wherein

The at least two types of parameters include at least one of the following: the body state time parameter and the exercise amount parameter, the body state time parameter and the physiological parameter, the exercise amount parameter and the physiological parameter, and the human body The state time parameter, the exercise quantity parameter and the physiological parameter.
The apparatus according to claim 58, wherein when the at least two types of parameters include the human body state time parameter and the exercise amount parameter;

The acquiring part is further specifically configured to acquire at least one movement signal of the patient; and based on the at least one movement signal, count the human body state time parameter and the exercise amount parameter within the preset time period.
The apparatus according to claim 58, wherein when the at least two types of parameters include the human body state time parameter and the physiological parameter;

The acquiring part is further specifically configured to acquire at least one motion signal of the patient; and based on the at least one motion signal, count the human body state time parameter within the preset time period; and pass a biological characteristic sensor Obtain the physiological parameters.
The device according to any one of claims 56, 57, 59 or 60, wherein

The acquiring part is further specifically configured to acquire the at least one original motion signal of the patient through a preset motion sensor; and filter the at least one original motion signal to obtain the at least one motion signal.
The apparatus according to claim 56, wherein

The acquiring section is further specifically configured to obtain a movement time based on the movement characteristics; and based on the at least one movement signal, count the movement amount parameter in the preset time period; and according to the movement amount parameter, the Set a rest threshold and the exercise time to determine the time to get out of bed; and determine the bed time according to the preset time period and the time to get out of bed; and the time to leave bed, the exercise time, and the preset time Any at least two combinations of the time period and the bed rest time are used as the at least two time parameters in the human body state time parameter as the at least two parameters.
The device of claim 62, wherein

The acquiring part is further specifically configured to acquire a preset time feature threshold in real time; and when the motion feature is greater than the preset time feature threshold, it is determined to be a motion state, and the duration of the motion state is recorded to obtain the motion time.
The apparatus according to claim 63, wherein the apparatus further comprises: a receiving section;

The receiving part is configured to obtain the exercise time based on the movement characteristics, and the at least any one of the bed leaving time, the exercise time, the preset time period and the bed time Before the two combinations serve as the at least two time parameters in the human body state time parameter, the bedside sensor and the bed time monitored by the receiving bedside sensor are transmitted.
The apparatus according to claim 49, wherein

The correlation part is specifically configured to obtain a preset correlation algorithm; and use the preset correlation algorithm to calculate the correlation of at least two parameters corresponding to the preset time period to obtain the correlation metric .
The apparatus of claim 66, wherein

The correlation measure is output and displayed on the monitoring device, and the correlation measure includes a quantitative indicator and/or a graphical indicator.
The apparatus according to claim 49, wherein the apparatus further comprises: a presentation section;

The presenting part is configured to perform correlation processing based on at least two parameters corresponding to a preset time period, and obtain the correlation metric, and then present the correlation metric. The manner of presenting the correlation metric is at least as follows One of the methods: refreshing and displaying the quantitative indicators related to the correlation measure obtained at different times in sequence with time changes; refreshing and displaying the graphical indicators about the correlation measure obtained at different times in sequence with time changes; constructing a coordinate system that changes along time, in The time-varying coordinate system is marked with quantitative indicators of correlation metrics corresponding to different moments to form a change trend graph of the quantitative indicators; and, a coordinate system with time variation is constructed, and different marks are marked in the time-varying coordinate system Corresponding graphical indicators on the correlation measure at all times form a change trend graph of the graphical indicators.
The apparatus according to claim 49, wherein the apparatus further comprises: a transmitting section;

The sending part is configured to perform correlation processing based on at least two parameters corresponding to a preset time period, and after obtaining a correlation metric, transmit the correlation metric to a bedside monitor and/or a central station; Causing the correlation metric to be presented on the bedside monitor and/or the central station.
An evaluation device for the recovery state of a patient in a hospital, the device comprising:

An obtaining part, configured to obtain a first time parameter and a second time parameter of a corresponding human body state time parameter within a preset time period; the first time parameter and the second time parameter respectively represent at least one of the human body state time parameters Time parameters of the time dimension;

The correlation part is configured to perform correlation processing on the first time parameter and the second time parameter to obtain a correlation metric; the correlation metric is used to evaluate a patient's recovery state.
The apparatus according to claim 69, wherein the human body state time parameter includes an exercise time parameter;

The acquiring part is specifically configured to acquire at least one motion signal of the patient within the preset time period; and perform time domain feature or frequency domain feature extraction on the at least one motion signal to obtain a motion feature; and Based on the motion characteristics, the first time parameter and the second time parameter that characterize the motion time parameter statistics within the preset time period are obtained.
The apparatus according to claim 69, wherein the human body state time parameters include exercise time parameters and sleep time parameters;

The acquiring part is specifically configured to acquire a motion signal of the patient within the preset time period; perform time-domain feature or frequency-domain feature extraction on the one motion signal to obtain a first motion feature; Obtaining the first motion feature, acquiring a motion time parameter that characterizes the motion time parameter within the preset time period; within the preset time period, acquiring the sleep time parameter of the patient; converting the sleep time The parameter and the one movement time parameter serve as the first time parameter and the second time parameter.
The apparatus according to claim 70, wherein

The acquiring part is further specifically configured to determine an exercise time according to the exercise characteristics; and based on the at least one exercise signal, count the exercise amount parameters in the preset time period; and according to the exercise amount parameters, the preset rest Threshold and the exercise time to determine the time to get out of bed; and based on the preset time period and the time to get out of bed to determine the time to stay in bed; and from the exercise time and the time to get out of bed that characterize the parameters of the exercise time , The first time parameter and the second time parameter are selected from the preset time period and the bed rest time.
The apparatus according to claim 72, wherein the apparatus further comprises: a receiving section;

The receiving part is configured to perform time domain feature or frequency domain feature extraction on the at least one motion signal to obtain a motion feature, and the slave motion time, the bed leaving time, and the preset Before selecting the first time parameter and the second time parameter from the time period and the bed time, receiving the bed leaving time and the bed time monitored by the bedside sensor.
The device of claim 72, wherein

The combination of the first time parameter and the second time parameter is any one of the following:

The exercise time and the bed leaving time;

The exercise time and the preset time period;

The bed leaving time and the preset time period;

The exercise time and the bed time;

The bed leaving time and the bed rest time;

The bed rest time and the preset time period.
The device of claim 69, wherein

The correlation part is specifically configured to obtain a preset correlation algorithm; and use the preset correlation algorithm to calculate the correlation between the first time parameter and the second time parameter to obtain the correlation metric .
The apparatus according to claim 75, wherein the apparatus further comprises: a presentation section;

The presentation part is configured to output and display the correlation measure on the monitoring device, where the correlation measure includes a quantitative indicator and/or a graphical indicator.
An evaluation device for the recovery state of a patient in a hospital, the device comprising:

The memory is used to store instructions for evaluating the recovery state of the patients in the hospital;

A processor, configured to execute the method according to any one of claims 1 to 8 when executing the evaluation instruction of the recovery state of the in-hospital patient stored in the memory, or implement the method according to any one of claims 9 to 28 method.
A computer-readable storage medium, in which an evaluation instruction for the recovery state of an in-hospital patient is stored, which is used to cause the processor to execute the method according to any one of claims 1 to 8, or the claims 9 to 8. The method according to any one of 28.