CN113194811A

CN113194811A - Method, device and system for evaluating recovery state of hospital patient and storage medium

Info

Publication number: CN113194811A
Application number: CN201880100229.9A
Authority: CN
Inventors: 刘三超; 金星亮; 何先梁; 孙泽辉; 罗汉源; 谈琳
Original assignee: Shenzhen Mindray Bio Medical Electronics Co Ltd
Current assignee: Shenzhen Mindray Bio Medical Electronics Co Ltd
Priority date: 2018-12-29
Filing date: 2018-12-29
Publication date: 2021-07-30
Also published as: WO2020133497A1

Abstract

A hospital patient recovery state assessment method, device (1), system (100) and storage medium. The method comprises the following steps: acquiring at least one type of related parameters of human body state time parameters, motion quantity parameters and physiological parameters (S101); extracting at least two corresponding parameters in a preset time period from the at least one type of related parameters (S102); and performing correlation processing based on the at least two corresponding parameters within the preset time period to obtain a correlation metric, wherein the correlation metric is used for evaluating the recovery state of the patient (S103).

Description

Method, device and system for evaluating recovery state of hospital patient and storage medium

Technical Field

The embodiment of the invention relates to a data transmission technology in the field of wireless communication, in particular to a method, a device and a system for evaluating recovery state of a patient in a hospital and a storage medium.

Background

With the development of medical technology and the improvement of the cognition of people to medicine, the importance and the attention of the postoperative rapid rehabilitation are sharply enhanced and promoted. In the postoperative recovery period, the patient can promote the quick recovery of the body through excessive bed-leaving activities, and a doctor can know the motion condition of the patient through some means so as to estimate the recovery condition of the patient.

At present, the traditional monitoring equipment for monitoring postoperative recovery of a patient is generally products such as a hand ring, a foot ring and a treadmill, and the monitoring equipment shows the motion condition of the patient by detecting real-time parameters (such as step frequency, step number, running number, motion time and the like) of a human body so that a doctor can judge the recovery condition according to the motion condition.

However, although the motion condition of the patient can be obtained by the monitoring device, the motion condition is only represented by the motion parameters monitored in real time in a single mode, and the representing of the rehabilitation condition by the presented motion parameters or motion condition is not very accurate.

Disclosure of Invention

The embodiment of the invention provides a hospital patient recovery state assessment method, device and system and a storage medium, which can monitor a human body from multiple dimensions, realize monitoring diversity and improve the accuracy of assessing the recovery condition of the human body.

The technical scheme of the embodiment of the invention can be realized as follows:

the embodiment of the invention provides a hospital patient recovery state assessment method, which comprises the following steps:

acquiring 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 time parameters of at least one time dimension in human body state time parameters;

performing correlation processing on the first time parameter and the second time parameter to obtain correlation measurement; the correlation metric is used to assess the recovery status of the patient.

acquiring at least one type of relevant parameters of human body state time parameters, motion quantity parameters and physiological parameters;

extracting at least two corresponding parameters in a preset time period from the at least one type of related parameters;

and carrying out correlation processing on the basis of the at least two corresponding parameters in the preset time period to obtain a correlation metric, wherein the correlation metric is used for evaluating the recovery state of the patient.

The embodiment of the invention provides an assessment system for recovery state of a patient in a hospital, which comprises: at least one wearable device worn on a patient;

the wearable device is used for acquiring at least one type of relevant parameters of human body state time parameters, motion quantity parameters and physiological parameters; extracting at least two corresponding parameters within a preset time period from the at least one type of related parameters; and performing correlation processing based on the at least two corresponding parameters in the preset time period to obtain a correlation metric, wherein the correlation metric is used for evaluating the recovery state of the patient.

The embodiment of the invention provides a device for evaluating recovery state of a patient in a hospital, which comprises:

the acquisition part is configured to acquire at least one type of related parameters of human body state time parameters, motion quantity parameters and physiological parameters;

the extraction part is configured to extract at least two corresponding parameters in a preset time period from the at least one type of related parameters;

and the correlation part is configured to perform correlation processing based on the at least two corresponding parameters in the preset time period to obtain a correlation metric, and the correlation metric is used for evaluating the recovery state of the patient.

the acquisition part is configured to acquire a first time parameter and a second time parameter of a human body state time parameter corresponding to a preset time period; the first time parameter and the second time parameter respectively represent time parameters of at least one time dimension in human body state time parameters;

a correlation part 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 assess the recovery status of the patient.

The embodiment of the invention also provides a device for evaluating the recovery state of a patient in a hospital, which comprises:

the memory is used for storing an evaluation instruction capable of executing the recovery state of the patient in the hospital;

a processor for implementing the method for assessing the recovery status of a hospital patient as claimed herein when executing the instructions stored in the memory for performing the assessment of the recovery status of a hospital patient.

An embodiment of the present invention provides a computer-readable storage medium, storing instructions for performing an assessment of a recovery status of a hospital patient, and when the instructions cause a processor to execute the assessment method of a recovery status of a hospital patient according to the claims.

The embodiment of the invention provides a hospital patient recovery state evaluation method, a hospital patient recovery state evaluation device, a hospital patient recovery state evaluation system and a storage medium, wherein at least one type of relevant parameters of human body state time parameters, motion quantity parameters and physiological parameters are obtained; extracting at least two corresponding parameters in a preset time period from at least one type of related parameters; and performing correlation processing based on at least two corresponding parameters in a preset time period to obtain a correlation metric, wherein the correlation metric is used for evaluating the recovery state of the patient. By adopting the technical implementation scheme, the evaluation device for the recovery state of the patient in the hospital can acquire at least two parameters from at least one type of related parameters of human body state time parameters, motion quantity parameters and physiological parameters, and obtains the correlation measurement for evaluating the recovery state of the patient through correlation processing of the at least two parameters.

Drawings

Fig. 1 is a schematic diagram of an alternative architecture of a system for evaluating recovery status of a patient in a hospital according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of an alternative architecture of a system for evaluating recovery status of a patient in a hospital according to an embodiment of the present invention;

fig. 3 is a schematic diagram illustrating an alternative architecture of a system for evaluating recovery status of a patient in a hospital according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of an alternative architecture of a system for evaluating recovery status of a patient in a hospital according to an embodiment of the present invention;

FIG. 5 is a first schematic structural diagram of an alternative apparatus for evaluating a recovery status of a patient in a hospital according to an embodiment of the present invention;

FIG. 6 is a schematic structural diagram of an alternative apparatus for evaluating recovery status of a patient in a hospital according to an embodiment of the present invention;

FIG. 7 is a first flowchart illustrating an alternative method for assessing a recovery status of a patient in a hospital according to an embodiment of the present invention;

FIG. 8 is a schematic diagram of an alternative flow chart of a method for evaluating recovery status of a patient in a hospital according to an embodiment of the present invention;

FIG. 9 is a schematic diagram illustrating an exemplary filtering of at least one raw signal provided by an embodiment of the present invention;

FIG. 10 is a schematic flow chart of an alternative method for assessing the recovery status of a patient in a hospital according to an embodiment of the present invention;

FIG. 11 is a fourth flowchart illustrating an alternative method for assessing a recovery status of a patient in a hospital according to an embodiment of the present invention;

FIG. 12 is a schematic flow chart illustrating an alternative method for assessing the recovery status of a patient in a hospital according to an embodiment of the present invention;

FIG. 13 is a sixth alternative flowchart of a method for assessing a recovery status of a patient in a hospital according to an embodiment of the present invention;

fig. 14 is a seventh alternative flowchart of a method for evaluating a recovery status of a patient in a hospital according to an embodiment of the present invention.

Detailed Description

So that the manner in which the features and aspects of the embodiments of the present invention can be understood in detail, a more particular description of the embodiments of the invention, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein is for the purpose of describing embodiments of the invention only and is not intended to be limiting of the invention.

It should be noted that the terms "first \ second \ third" related to the embodiments of the present invention merely distinguish similar objects and do not represent specific ordering for the objects, and it should be understood that "first \ second \ third" may exchange specific orders or sequences where allowed, so that the embodiments of the present invention described herein can be implemented in an order other than that shown or described herein.

An exemplary application of the device for evaluating the recovery state of the hospital patient according to the embodiment of the present invention is described below, and the device for evaluating the recovery state of the hospital patient according to the embodiment of the present invention may be implemented as various types of user terminals such as a wearable device and a sensing device. Next, an exemplary application when the evaluation apparatus of the state of recovery of the patient in the hospital is implemented as a wearable device will be explained.

Referring to fig. 1, fig. 1 is an alternative architectural diagram of a hospital patient recovery status evaluation system 100 according to an embodiment of the present invention, which is configured to support an exemplary application and is composed of at least one wearable device 200, wherein the at least one wearable device is worn on a patient.

The wearable device 200 is used for acquiring at least one type of relevant parameters of human body state time parameters, motion quantity parameters and physiological parameters; extracting at least two corresponding parameters in a preset time period from at least one type of related parameters; and performing correlation processing based on the at least two corresponding parameters within the preset time period to obtain a correlation metric, wherein the correlation metric is used for evaluating the recovery state of the patient.

The human state parameters referred to herein may comprise temporal parameters statistically related to human motion related events and/or human sleep related events in a temporal dimension. The motion quantity parameter represents the motion parameter of the human body when moving, which represents the degree of motion, except for time. The human body movement includes an active state, a static state, and the like.

The method includes obtaining at least one physiological parameter signal in a first time period through a sensor accessory connected with a patient, wherein the at least one physiological parameter signal can be at least one of body temperature (Temp), blood pressure diastolic pressure (diastolic blood pressure), systolic blood pressure (BP-S), Heart Rate (HR), Respiratory Rate (RR), consciousness level, blood oxygen (SpO2), oxygen concentration (sup. o2), electroencephalogram and other physiological parameter signals collected through the sensor accessory. Then, according to the at least one physiological parameter signal, waveforms and/or values corresponding to various physiological parameters such as body temperature (Temp), blood pressure diastolic pressure, systolic pressure (BP-S), Heart Rate (HR), Respiratory Rate (RR), consciousness level, blood oxygen (SpO2), oxygen concentration (supp. o2), brain electricity, and the like can be obtained.

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

In this embodiment, the at least two parameters may be derived from a class of related parameters; the at least two parameters may also be derived from a plurality of classes of related parameters, wherein each class of related parameters has at least one parameter. The details can be illustrated in the following examples.

The relevance metric mentioned herein is used to measure the relevance between at least two parameters, and can be classified into the following categories to evaluate the relevance.

First, a quantitative indicator of a correlation metric is obtained based on a corresponding correlation process.

Constructing a quantization function Y ═ f (x) based on corresponding correlation processing₁,x ₂… …), extracting at least two parameters (x) corresponding to the preset time period from at least one kind of relevant parameters based on the human body state time parameter, the motion amount parameter and the physiological parameter₁,x ₂… …) to bring the aforementioned at least two parameters into the aforementioned quantization function f (x)₁,x ₂… …) to obtain a quantitative index Y on the correlation measure. The quantization indexes Y, such as Y, at different times (t1, t2, t3 and … …) can be obtained correspondingly and sequentially based on different preset time periods along with the time continuation or change_t1,Y _t2，Y _t3… …. The relevance metric may be presented by sequentially refreshing the quantization index (Y) obtained at different times of display as a function of time_t1,Y _t2,Y _t3… …) to display the quantization index Y in real time. It is of course also possible to construct a time-varying coordinate system in which quantization indices (Y) corresponding to different times are marked_t1,Y _t2，Y _t3… …) to form a trend graph of the quantitative indicators.

The quantization function Y ═ f (x)₁,x ₂… …) may be a function constructed using at least one of multiplication, division, sum, difference, etc., for example, the aforementioned quantization function may be constructed based on one or more of a ratio operation, a difference operation, an integral ratio operation, an area ratio operation, an integral difference operation, an area difference operation, etc.

Second, a graphical indicator of the correlation metric is obtained based on the respective correlation process.

And constructing an icon model containing at least two parameter display elements in the same coordinate system to generate a graphical index. Extracting at least two parameters (x) corresponding to a preset time period from at least one type of relevant parameters based on at least one type of relevant parameters of human body state time parameters, motion quantity parameters and physiological parameters₁,x ₂… …), displaying the aforementioned at least two quantities in the same icon model results in a graphical indicator of the measure of relevance. The graphical indicators at different times (t1, t2, t3, … …) can be obtained correspondingly and sequentially based on different preset time periods along with the time continuation or change, and the graphical indicators at different times are different due to the change of the at least two parameters. The method for presenting the correlation measurement can be that the graphical indexes obtained at different moments are sequentially refreshed and displayed along with the change of time, so that the graphical indexes are displayed in real time. Of course, a time-varying coordinate system may also be constructed, and graphical indicators corresponding to different times are marked in the time-varying coordinate system, so as to form a variation trend graph of the graphical indicators.

The icon model may be a display element formed of a bar, a sector, a line segment, and a dot, and the two parameters are associated with attribute variables such as a shape size and a rendering attribute in the display element. For example, the graphical indicators may be obtained by displaying the at least two parameters by using at least two bars placed in parallel, by displaying the at least two parameters by using at least two sectors in the same pie, and so on.

Therefore, in one embodiment, the correlation processing is performed based on the at least two parameters corresponding to the preset time period, so as to obtain the correlation metric, which includes at least one of the following manners: obtaining a quantitative index related to the correlation measurement based on at least two corresponding parameters in the preset time period; and obtaining a graphical index related to the correlation metric based on the corresponding at least two parameters in the preset time period.

In some embodiments of the present invention, the at least one wearable device 200 is specifically configured to obtain the quantitative indicator related to the correlation metric based on the corresponding at least two parameters within the preset time period; and obtaining the graphical index related to the correlation metric based on at least two corresponding parameters in the preset time period.

In some embodiments of the present invention, the at least one wearable device 200 is specifically configured to obtain the human body state time parameter as the at least one type of relevant parameter; and the combination of (a) and (b),

extracting at least two corresponding time parameters within a preset time period from the human body state time parameters to serve as the at least two parameters; and performing correlation processing on the at least two time parameters extracted in the preset time period to obtain a quantitative index or a graphical index related to the correlation measurement.

In some embodiments of the present invention, the at least one wearable device 200 is specifically configured to extract at least two motion parameters corresponding to a preset time period from the motion parameters to serve as the at least two parameters, and perform correlation processing on the at least two motion parameters extracted within the preset time period to obtain the correlation metric, for example, output a quantitative index or a graphical index related to the correlation metric.

In some embodiments of the invention, the aforementioned human body state time parameter comprises a movement time parameter. The at least one wearable device 200 is further specifically configured to acquire at least one motion signal of the patient; extracting time domain characteristics or frequency domain characteristics of the at least one motion signal to obtain motion characteristics; and acquiring the at least two time parameters representing at least two dimension statistics of the motion time parameters in the preset time period based on the motion characteristics as the at least two parameters.

In some embodiments of the present invention, the aforementioned human body state time parameters include an exercise time parameter and a sleep time parameter. The at least one wearable device 200 is further specifically configured to acquire at least one motion signal of the patient; extracting time domain characteristics or frequency domain characteristics of the at least one motion signal to obtain motion characteristics; acquiring at least one motion time parameter which represents at least one dimension statistic of the motion time parameter in the preset time period based on the motion characteristics; acquiring a sleep time parameter of the patient, and taking 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.

Here, the acquisition of the sleep time parameter is exemplified.

In one embodiment, the motion characteristics are obtained according to the at least one motion signal, corresponding physiological signals are obtained through a sensor accessory attached to the body of the patient, heart rate characteristic information is obtained from the physiological signals, and then the sleep state of the patient is determined based on the motion characteristics and the heart rate characteristic information. It is understood that the body motion signal may be obtained by a motion sensor, for example, an acceleration sensor, a gyroscope, or the like. When the motion sensor is an acceleration sensor, the real-time quantized value is a 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, the gyroscope can monitor the motion track of the user, so that the motion characteristic can also be the moving distance of the user in a period of time.

Still further, the aforementioned obtaining the motion characteristics according to the at least one motion signal comprises:

acquiring an acceleration signal of the movement of the patient by using the motion sensor on the at least one wearable device 200, and preprocessing the acceleration signal to obtain a real-time acceleration value;

the acceleration signal and the angular velocity signal of the movement of the patient are obtained by the motion sensor on the wearable device 200 for preprocessing, and at least a real-time acceleration value and a moving distance of the user are obtained. The motion quantity parameter related to the motion of the patient can be obtained based on the obtained real-time acceleration value, and the current motion state of the patient can also be judged. And meanwhile, the sleep time parameter is determined by combining the heart rate characteristic information.

Wherein, the process of obtaining heart rate characteristic information from physiological signals comprises:

processing the physiological signals to obtain electrocardiographic data;

analyzing the electrocardiographic data to extract real-time valid R-wave intervals;

resampling the R-wave intervals;

calculating the heart rate characteristic information according to the R wave intervals under different scales to obtain heart rate characteristic information; the heart rate characteristic information comprises time domain characteristic information and frequency domain characteristic information.

The heart rate characteristic information refers to the difference between two physiological signals acquired at different times; the different time is two or more sections of physiological signals with the same length in sequence; the front and back sequence can be continuous or discontinuous acquisition; the physiological signal difference can be a physiological signal waveform or waveform characteristic difference; the difference is the difference degree and the variability.

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

In an embodiment, the processing the physiological signal to obtain frequency domain feature information includes: processing the physiological signals to obtain electrocardiographic data; analyzing the electrocardiographic data to extract real-time valid R-wave intervals; resampling the R-wave intervals; and calculating the heart rate characteristic information according to the R wave intervals under different scales to obtain the heart rate characteristic information.

For example, the process of processing the physiological signal to obtain the electrocardiographic data includes: after receiving the ECG electrocardiographic signals of the user, the sleep state determination device filters the ECG electrocardiographic signals to remove noise, expands the amplitude of the processed signals by using a signal amplifier, and finally performs a/D conversion (it is understood that the a/D conversion is analog-to-digital conversion, and the a/D conversion functions to convert analog quantities which are continuous in time and continuous in amplitude into digital signals which are discrete in time and discrete in amplitude) to convert the analog signals into data signals. It will be appreciated that the electrocardiographic data is included in the data signal. It is understood that when the physiological signal is a signal other than an ECG electrocardiographic signal, for example, a pulse wave signal, the pulse wave signal may be processed to obtain electrocardiographic data as long as it performs data processing on the physiological data to obtain electrocardiographic data.

In addition, it should be noted that an electrocardiogram is made up of a series of wave groups, each representing each cardiac cycle. One wave group includes P-waves, QRS complexes, T-waves, and U-waves. The QRS complex includes three closely-connected waves, the first downward wave is called a Q wave, a high-tip vertical wave following the Q wave is called an R wave, and the backward downward wave of the R wave is called an S wave. Because they are closely linked and reflect the ventricular electrical activation process, they are collectively referred to as QRS complexes. This burst reflects the depolarization process of the left and right ventricles.

Secondly, determining the sleep state of the user according to the motion characteristics and the heart rate characteristic information. For example, the determining the sleep state of the user according to the motion characteristic and the heart rate characteristic information includes: comparing the aforementioned motion characteristic with a first threshold value, and comparing the heart rate characteristic information with a second threshold value; and when the motion characteristics are lower than the first threshold and the heart rate characteristic information is smaller than the second threshold, determining that the user is in a sleep state. Wherein it is understood that the second threshold is an adaptive threshold or a fixed value. And when the heart rate characteristic information is time domain characteristic information, the time domain characteristic information comprises a standard deviation of an interval in a preset time segment, and the sleep state of the user is determined according to the exercise characteristic and the standard deviation.

Where the second threshold is an adaptive threshold, it is noted that the adaptive threshold is dynamically variable with heart rate. Thus, before comparing the heart rate characteristic information to the adaptive threshold, the method further comprises: acquiring the current heart rate value of the user; inputting the user's current heart rate value into a threshold determination model to determine the adaptive threshold.

Further, it is noted that before inputting the current heart rate of the user into the threshold determination model to determine the adaptive threshold, the method further comprises: acquiring data of the user, including an acceleration signal and an electrocardiosignal, of waking sleep within a preset time period; labeling the arousal sleep cycles of the user in a time sequence; wherein the marked content comprises an awakening state and a sleeping state; extracting a heart rate value of the user and an adaptive threshold (i.e. a value of an ECG) corresponding to the heart rate value for all sleep cycles; and obtaining a threshold value determination model according to the extracted heart rate value and the self-adaptive threshold value corresponding to the heart rate value.

Determining sleep stages of the user according to the ratio and correspondence between the multi-scale heart rate characteristic information, wherein the sleep stages include, but are not limited to, deep sleep, light sleep and rapid phase sleep REM (or fast wave sleep or out-of-phase sleep). Thus, the sleep time parameter may be determined based on the above method.

In some embodiments of the invention, the aforementioned at least two types of parameters comprise at least one of: the human body state time parameter and the exercise amount parameter, the human body state time parameter and the physiological parameter, the exercise amount parameter and the physiological parameter, and the human body state time parameter, the exercise amount parameter and the 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 counting the human body state time parameter and the motion quantity parameter in the preset time period based on the at least one motion signal.

In some embodiments of the present invention, 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 200 is further specifically configured to acquire at least one motion signal of the patient; acquiring the physiological parameters through a biological characteristic sensor; and counting the human body state time parameters in the preset time period based on the at least one motion signal.

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

In some embodiments of the present invention, the at least one wearable device 200 is further specifically configured to obtain the exercise time based on the exercise characteristics; counting the motion quantity parameter in the preset time period based on the at least one motion signal; determining the time of leaving the bed according to the exercise quantity parameter, a preset rest threshold value and the exercise time; determining the time for lying in bed according to the preset time period and the time for leaving the bed; and any at least two combinations of the bed leaving time, the exercise time, the preset time period and the bed lying time are used as the at least two time parameters of the human body state time parameters and used as the at least two parameters.

In some embodiments of the present invention, the at least one wearable device 200 is further specifically configured to obtain a preset time characteristic threshold in real time; and when the motion characteristic is larger than the preset time characteristic threshold value, determining the motion state, and recording the duration of the motion state to obtain the motion time.

In some embodiments of the present invention, the at least one wearable device 200 is specifically configured to obtain a preset correlation algorithm; and calculating the correlation of at least two corresponding parameters in the preset time period by adopting the preset correlation algorithm to obtain the correlation measurement.

In some embodiments of the present invention, the predetermined correlation algorithm comprises at least one of: ratio operation, difference operation, integral ratio operation, area ratio operation, integral difference operation and area difference operation.

Based on fig. 1, referring to fig. 2, fig. 2 is another alternative architecture diagram of an evaluation system 100 for the recovery status of a patient in a hospital, which is provided by an embodiment of the present invention and is configured to support an exemplary application, and the evaluation system is composed of at least one wearable device 200 and a bedside monitor 300, wherein the at least one wearable device 200 is worn on the patient, and the bedside monitor 300 is in communication with the at least one wearable device 200.

The wearable device 200 is used for acquiring at least one type of relevant parameters of human body state time parameters, motion quantity parameters and physiological parameters; extracting at least two corresponding parameters within a preset time period from the at least one type of related parameters; performing correlation processing on the basis of at least two corresponding parameters in the preset time period to obtain correlation measurement, wherein the correlation measurement is used for evaluating the recovery state of the patient; transmitting the correlation metric to the bedside monitor 300; the bedside monitor 300 is configured to present the correlation metric.

Referring to fig. 2 based on fig. 1, fig. 2 is a schematic diagram of another alternative architecture of an evaluation system 100 for the recovery status of a patient in a hospital, which is provided by an embodiment of the present invention and is configured to support an exemplary application, and the evaluation system is composed of at least one wearable device 200 and a bedside monitor 300, wherein the at least one wearable device is worn on the patient, and the bedside monitor is in communication with the at least one wearable device.

The wearable device 200 is used for acquiring at least one type of relevant parameters of human body state time parameters, motion quantity parameters and physiological parameters; extracting at least two corresponding parameters within a preset time period from the at least one type of related parameters; transmitting the at least two parameters to the bedside monitor 300; the bedside monitor 300 is configured to perform correlation processing on the at least two parameters to obtain the correlation metric, and to present the correlation metric.

Based on fig. 1, referring to fig. 3, fig. 3 is a schematic diagram of a further alternative architecture of an evaluation system 100 for the recovery status of a patient in a hospital, which is provided by an embodiment of the present invention, and is configured by at least one wearable device 200 and a central station 400, for supporting an exemplary application, wherein the at least one wearable device 200 is worn on the patient, and the central station 400 is in communication with the at least one wearable device 200.

The wearable device 200 is used for acquiring at least one type of relevant parameters of human body state time parameters, motion quantity parameters and physiological parameters; extracting at least two corresponding parameters within a preset time period from the at least one type of related parameters; performing correlation processing on the basis of at least two corresponding parameters in the preset time period to obtain correlation measurement, wherein the correlation measurement is used for evaluating the recovery state of the patient; transmitting the correlation metric to the central station 400; the aforementioned central station 400 for presenting the aforementioned correlation metric.

The wearable device 200 is used for acquiring at least one type of relevant parameters of human body state time parameters, motion quantity parameters and physiological parameters; extracting at least two corresponding parameters within a preset time period from the at least one type of related parameters; transmitting said at least two parameters to said central station 400; the central station 400 is configured to perform correlation processing on the at least two parameters to obtain the correlation metric, and present the correlation metric.

Based on fig. 1, referring to fig. 4, fig. 4 is a schematic diagram of a further alternative architecture of an evaluation system 100 for the recovery status of a patient in a hospital, which is provided by an embodiment of the present invention, and is configured to support an exemplary application, and includes at least one wearable device 200, a bedside monitor 300, and a central station 400, wherein the at least one wearable device 200 is worn on the patient, and the bedside monitor 300 and the central station 400 are respectively in communication with the at least one wearable device 200.

The wearable device 200 is used for acquiring at least one type of relevant parameters of human body state time parameters, motion quantity parameters and physiological parameters; extracting at least two corresponding parameters within a preset time period from the at least one type of related parameters; transmitting said at least two parameters to said central station 400 and to said bedside monitor 300; the central station 400 is configured to perform correlation processing on the at least two parameters to obtain the correlation metric, and present the correlation metric; and the bedside monitor 300 is configured to perform correlation processing on the at least two parameters to obtain the correlation metric, and to present the correlation metric.

In some embodiments of the present invention, the at least one wearable device 200 is configured to obtain at least one kind of relevant parameters of a human body state time parameter, an exercise amount parameter and a physiological parameter; extracting at least two corresponding parameters within a preset time period from the at least one type of related parameters; performing correlation processing on the basis of at least two corresponding parameters in the preset time period to obtain correlation measurement, wherein the correlation measurement is used for evaluating the recovery state of the patient; transmitting the correlation metric to the central station 400 and the bedside monitor 300; the aforementioned bedside monitor 300 for presenting the aforementioned correlation metric; the aforementioned central station 400 for presenting the aforementioned correlation metric.

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

Furthermore, in the embodiment of the present invention, the central station 400 and the bedside monitor 300 are exemplary devices that can communicate with at least one wearable device, and in the embodiment of the present invention, other devices can also communicate with at least one wearable device to calculate or present a correlation metric for use in evaluating the recovery status of the patient, which is not limited by the embodiment of the present invention.

It should be noted that, in different systems for evaluating the recovery state of the patient in the hospital, the implementation of the specific correlation metric, the acquisition of at least two parameters, and other processes is the same principle and technical implementation means, and is not described herein again.

The device for evaluating the recovery state of the hospital patient according to the embodiment of the present invention may be implemented in hardware or a combination of hardware and software, and various exemplary implementations of the device for evaluating the recovery state of the hospital patient according to the embodiment of the present invention are described below.

Referring to fig. 5, fig. 5 is an alternative structural schematic diagram of an apparatus for evaluating a recovery state of a hospital patient according to an embodiment of the present invention, where the apparatus for evaluating a recovery state of a hospital patient may be a wearable device. Sensor devices and the like may be used to acquire at least one type of relevant parameter from a patient, and the configurations described herein should not be considered limiting, e.g., some of the components described below may be omitted, or components not described below may be added to accommodate the particular needs of some applications.

An apparatus 1 for evaluating a recovery state of a patient in a hospital shown in fig. 5 includes:

a memory 10 for storing an evaluation instruction for performing a hospital-in-patient recovery state;

and a processor 11, configured to implement the following method for evaluating the recovery status of the hospital patient when executing the executable instruction stored in the memory 10 for evaluating the recovery status of the hospital patient.

It should be noted that, in the embodiment of the present invention, the respective components in the apparatus for evaluating the recovery state of the patient in the hospital 1 are coupled together by the bus system 12. It will be appreciated that the bus system 12 is used to enable communications among the components of the connection. The bus system 12 includes, in addition to a data bus, a power bus, a control bus, a status signal bus, and a communication interface for communicating with other devices (e.g., a wireless communication interface for communicating with a central station or bedside monitor, etc.). For clarity of illustration, however, the various buses and interfaces are labeled as bus system 12 in fig. 5.

The memory 10 may be a volatile memory or a nonvolatile memory, or may include both volatile and nonvolatile memories. Among them, the nonvolatile Memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read Only Memory (EPROM), a Flash Memory (Flash Memory), and the like. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM). The memory 10 described in the embodiments of the present invention is intended to comprise these and any other suitable types of memory.

By way of example, the Processor 11 may be an integrated circuit chip having Signal processing capabilities, such as a general purpose Processor, a Digital Signal Processor (DSP), or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or the like, wherein the general purpose Processor may be a microprocessor or any conventional Processor or the like.

An exemplary structure of software modules of the apparatus for evaluating a recovery status of a hospital patient is described below, and in some embodiments, as shown in fig. 6, the software modules of the apparatus 1 for evaluating a recovery status of a hospital patient may include:

an acquisition part 13 configured to acquire at least one type of relevant parameters among a human body state time parameter, an exercise amount parameter, and a physiological parameter;

an extracting part 14 configured to extract at least two parameters corresponding to a preset time period from the at least one kind of relevant parameters;

and the correlation part 15 is configured to perform correlation processing based on the at least two corresponding parameters in the preset time period to obtain a correlation metric, and the correlation metric is used for evaluating the recovery state of the patient.

In some embodiments of the present invention, the aforementioned acquisition part 13 is specifically configured to acquire a sum of at least two kinds of parameters selected from the aforementioned human body state time parameter, the aforementioned motion amount parameter and the aforementioned physiological parameter,

and extracting at least two parameters respectively corresponding to the preset time period from the at least two types of parameters, wherein each type of related parameter correspondingly has at least one parameter.

In some embodiments of the present invention, the correlation portion 15 is specifically configured to obtain a quantitative index related to the correlation metric based on at least two corresponding parameters within the preset time period; and the combination of (a) and (b),

and obtaining a graphical index related to the correlation metric based on the corresponding at least two parameters in the preset time period.

In some embodiments of the present invention, the acquiring part 13 is specifically configured to acquire the human body state time parameter as the at least one type of relevant parameter; and the combination of (a) and (b),

and extracting at least two corresponding time parameters within a preset time period from the human body state time parameters to serve as the 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 within the preset time period to obtain the correlation metric.

In some embodiments of the present invention, the acquiring portion 13 is specifically configured to acquire the motion amount parameter as the at least one type of related parameter; and extracting at least two corresponding motion parameters within a preset time period from the motion parameters to serve as the 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 parameters extracted within the preset time period to obtain the correlation metric.

In some embodiments of the invention, the aforementioned human body state time parameter comprises a movement time parameter;

the aforementioned acquisition portion 13, further specifically configured to acquire at least one motion signal of the aforementioned patient; extracting time domain characteristics or frequency domain characteristics of the at least one motion signal to obtain motion characteristics; and acquiring the at least two time parameters representing at least two dimension statistics of the motion time parameters in the preset time period based on the motion characteristics as the at least two parameters.

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

the acquiring part 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; acquiring at least one motion time parameter representing at least one dimension statistic of the motion time parameter in the preset time period based on the motion characteristics; acquiring sleep time parameters of the patient; and taking the sleep time parameter and the at least one motion time parameter as the at least two time parameters.

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

the aforementioned acquisition portion 13, further specifically configured to acquire at least one motion signal of the aforementioned patient; and counting the human body state time parameter and the motion quantity parameter in the preset time period based on the at least one motion signal.

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

the aforementioned acquisition portion 13, further specifically configured to acquire at least one motion signal of the aforementioned patient; counting the human body state time parameters in the preset time period based on the at least one motion signal; and acquiring the physiological parameters through a biological characteristic sensor.

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

In some embodiments of the present invention, the obtaining part 13 is further specifically configured to obtain a movement time based on the movement characteristics; counting the motion quantity parameter in the preset time period based on the at least one motion signal; determining the time of leaving the bed according to the exercise quantity parameter, a preset rest threshold value and the exercise time; determining the time for lying in bed according to the preset time period and the time for leaving the bed; and any at least two combinations of the bed leaving time, the exercise time, the preset time period and the bed lying time are used as the at least two time parameters of the human body state time parameters and used as the at least two parameters.

In some embodiments of the present invention, the obtaining part 13 is further specifically configured to obtain a preset time characteristic threshold in real time; and when the motion characteristic is larger than the preset time characteristic threshold value, determining the motion state, and recording the duration time of the motion state to obtain the motion time.

In some embodiments of the invention, the aforementioned device 1 further comprises: a receiving portion 16.

The receiving part 16 is configured to receive the bed leaving time and the bed lying time which are monitored by the bedside sensor after the exercise time is obtained based on the exercise characteristics and before any at least two combinations of the bed leaving time, the exercise time, the preset time period and the bed lying time are taken as the at least two time-related parameters in the human body state time parameters.

In some embodiments of the present invention, the correlation section 15 is specifically configured to obtain a preset correlation algorithm; and calculating the correlation of at least two corresponding parameters in the preset time period by adopting the preset correlation algorithm to obtain the correlation measurement.

In some embodiments of the invention, the aforementioned device 1 further comprises: the portion 17 is presented.

The presenting part 17 is configured to present the correlation metric after performing correlation processing based on at least two parameters corresponding to each other in a preset time period to obtain the correlation metric. Presenting the aforementioned correlation metric may be: the correlation metric is output and displayed on a monitoring device, and comprises a quantitative index and/or a graphical index. The monitoring device referred to herein comprises one of a monitor, a portable monitoring device, a mobile terminal with vital signs monitoring function, a central station, a nurse station, etc.

Wherein the relevance metric is presented in at least one of: sequentially refreshing and displaying the quantitative indexes about the correlation measurement obtained at different moments along with the time change; the graphical indexes related to the correlation measurement obtained at different moments are sequentially refreshed and displayed along with the time change; constructing a coordinate system which changes along time, marking quantitative indexes which correspond to different moments and are related to correlation measurement in the coordinate system which changes along time, and forming a change trend graph of the quantitative indexes; and constructing a time-varying coordinate system, marking graphical indexes related to the correlation measurement corresponding to different moments in the time-varying coordinate system, and forming a variation trend graph of the graphical indexes

In some embodiments of the invention, the aforementioned device 1 further comprises: a transmission section 18.

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

Illustratively, the following describes an evaluation apparatus for the recovery status of a patient in a hospital when at least one type of relevant parameter is a body status time parameter.

The embodiment of the invention provides an assessment device 1 for recovery state of a patient in a hospital, which comprises:

an acquisition part 13 configured to acquire a first time parameter and a second time parameter of a human body state time parameter corresponding to a preset time period; the first time parameter and the second time parameter respectively represent time parameters of at least one time dimension in the human body state time parameters;

a correlation section 15 configured to perform correlation processing on the first time parameter and the second time parameter to obtain a correlation metric; the foregoing correlation metrics are used to assess the recovery status of the patient.

the aforementioned acquisition portion 13, in particular configured to acquire at least one motion signal of the aforementioned patient during the aforementioned preset time period; extracting time-frequency domain characteristics or frequency domain characteristics of the at least one motion signal to obtain motion characteristics; and acquiring the first time parameter and the second time parameter which represent the statistics of the motion time parameters in the preset time period based on the motion characteristics.

the acquiring part 13 is specifically configured to acquire a motion signal of the patient during the preset time period; extracting time-frequency domain characteristics or frequency domain characteristics of the motion signal to obtain first motion characteristics; acquiring a motion time parameter representing the motion time parameter in the preset time period based on the first motion characteristic; acquiring a sleep time parameter of the patient within the preset time period; and using the sleep time parameter and the one exercise time parameter as the first time parameter and the second time parameter.

In some embodiments of the present invention, the acquiring part 13 is further specifically configured to determine the movement time according to the movement characteristics; counting the motion quantity parameter in the preset time period based on the at least one motion signal; determining the time of leaving the bed according to the exercise quantity parameter, a preset rest threshold value and the exercise time; determining the time for lying in bed according to the preset time period and the time for leaving the bed; and selecting the first time parameter and the second time parameter from the exercise time, the bed leaving time, the preset time period and the bed lying time which represent the exercise time parameters.

In some embodiments of the invention, the aforementioned apparatus further comprises: a receiving portion 16.

The receiving part 16 is configured to receive the bed leaving time and the bed lying time which are transmitted and monitored by the bed side sensor after the motion feature is obtained by extracting the time domain feature or the frequency domain feature of the time domain feature of the at least one motion signal and before the first time parameter and the second time parameter are selected from the motion time, the bed leaving time, the preset time period and the bed lying time.

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

the aforementioned movement time and the aforementioned bed exit time;

the movement time and the preset time period;

the bed leaving time and the preset time period;

the exercise time and the bed rest time;

the time of leaving the bed and the time of lying in the bed;

the bedridden time and the preset time period.

In some embodiments of the present invention, the correlation section 15 is specifically configured to obtain a preset correlation algorithm; and calculating the correlation between the first time parameter and the second time parameter by adopting the preset correlation algorithm to obtain the correlation metric.

In some embodiments of the present invention, the predetermined correlation algorithm comprises at least one of: ratio operation, difference operation, integral ratio operation, area ratio operation, integral difference operation and area difference operation. In one embodiment, the correlation metric referred to herein is the ratio between two parameters.

In some embodiments of the invention, the apparatus further comprises: a presentation section 17;

the aforementioned presenting part is configured to output and display the correlation metric on the monitoring device, wherein the correlation metric comprises a quantitative index and/or a graphical index

As an example of the method for evaluating the recovery state of the hospital patient provided by the embodiment of the present invention implemented by hardware, the method for evaluating the recovery state of the hospital patient provided by the embodiment of the present invention can be directly implemented by the processor 11 in the form of a hardware decoding processor, and for example, the method for evaluating the recovery state of the hospital patient provided by the embodiment of the present invention is implemented by one or more Application Specific Integrated Circuits (ASICs), DSPs, Programmable Logic Devices (PLDs), Complex Programmable Logic Devices (CPLDs), Field Programmable Gate Arrays (FPGAs), or other electronic components.

The method for evaluating the recovery status of a patient in a hospital according to an embodiment of the present invention will be described below with reference to the foregoing exemplary application and implementation of the apparatus for evaluating the recovery status of a patient in a hospital according to an embodiment of the present invention.

Referring to fig. 7, fig. 7 is an alternative flow chart of a method for evaluating a recovery status of a patient in a hospital according to an embodiment of the present invention, which will be described with reference to the steps shown in fig. 7.

S101, acquiring at least one type of relevant parameters of human body state time parameters, motion quantity parameters and physiological parameters;

s102, extracting at least two corresponding parameters in a preset time period from at least one type of related parameters;

s103, performing correlation processing based on at least two corresponding parameters in a preset time period to obtain correlation measurement, wherein the correlation measurement is used for evaluating the recovery state of the patient.

In the embodiment of the present invention, the means for evaluating the recovery state of the patient in the hospital may evaluate the recovery state of the patient by using the correlation of parameters, such as a human body state time parameter, an exercise amount parameter and a physiological parameter, associated with the recovery time of the patient.

In the embodiment of the present invention, the device for evaluating the recovery state of the hospital patient may be a wearable device, which is worn on the patient to obtain at least one type of relevant parameters.

In S101, the in-hospital patient recovery state evaluation device may obtain at least one type of relevant parameters among a human body state time parameter, a motion amount parameter, and a physiological parameter; at least one type of relevant parameters here are the parameters mentioned above in connection with the recovery of the patient.

In an 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 amount of exercise parameter, a combination of a human state time parameter and a physiological parameter, a combination of an amount of exercise parameter and a physiological parameter, a combination of a human state time parameter, an amount of exercise parameter and a physiological parameter, a combination of at least two amounts of exercise parameter of an amount of exercise parameter, a combination of at least two time parameters of a human state time parameter, and a combination of at least two amounts of exercise parameter of a physiological parameter.

In some embodiments of the present invention, the in-hospital patient recovery status assessment apparatus may acquire at least two of a human body status time parameter, an exercise amount parameter, and a physiological parameter; wherein the at least two types of parameters are at least one type of related parameters.

Wherein the at least two types of parameters include at least one of: the human body state time parameter and the exercise amount parameter, the human body state time parameter and the physiological parameter, the exercise amount parameter and the physiological parameter, and the human body state time parameter, the exercise amount parameter and the physiological parameter.

In some embodiments of the present invention, the in-hospital patient recovery status assessment apparatus may obtain at least two time parameters of the human body status time parameters; wherein at least two time parameters are used as at least two parameters.

In some embodiments of the present invention, the means for evaluating the recovery state of the in-hospital patient may acquire at least two motion amount parameters of the motion amount parameters; wherein at least two motion quantity parameters are used as at least two parameters.

In the embodiment of the invention, the human body state time parameter represents human body motion related events, sleep related events and other human body state related and time related parameters based on different time dimensions.

It should be noted that, the method for evaluating the recovery state of a patient in a hospital provided by the embodiment of the present invention is used for evaluating the physical recovery condition of the patient, and particularly, for a situation of a patient performing rehabilitation training, the time when the patient is in the hospital in a bed, the time when the patient leaves the bed, the time when the patient is doing exercise, and the like, can sufficiently reflect the physical recovery condition of the patient, and the better the recovery is, the corresponding exercise time and the time when the patient leaves the bed will be long, and the time when the patient is in the bed will be short, and the like.

In the embodiment of the invention, the motion quantity parameter represents the motion parameter of the human body, which represents the degree of motion when the human body moves, except time.

For example, the exercise amount parameter may be a step frequency, a step number, an exercise distance, an exercise strength, an exercise calorie consumption, and the like, and the embodiment of the present invention is not limited thereto.

In an embodiment of the invention, the physiological parameter is a parameter characterizing a biological feature of the human body.

Exemplary physiological parameters may include: heart rate, pulse rate, blood flow rate, respiratory rate, etc., and the embodiments of the present invention are not limited thereto.

In S102, after the in-hospital patient recovery state evaluation device obtains at least one type of relevant parameters from the human body state time parameter, the motion amount parameter, and the physiological parameter, since the evaluation of the patient recovery state needs to be compared to better reflect whether the physical state is improved, in the embodiment of the present invention, a parameter in a preset time period is used to perform a correlation process to obtain a correlation metric, and the recovery state of the patient is evaluated through a difference of the correlation metrics in different preset time periods.

In the embodiment of the invention, the device for evaluating the recovery state of the patient in the hospital can extract at least two corresponding parameters in a preset time period from at least one type of related parameters.

The preset time period may be calculated in units of minutes, hours, days, and the like, and the embodiment of the present invention is not limited.

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

Based on the combination of the aforementioned at least one type of relevant 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 amount parameter within a 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 amount parameter and the physiological parameter, the combination of the human body state time parameter, the exercise amount parameter and the physiological parameter within the preset time period, the combination of at least two exercise amount parameters of the exercise amount parameter within the preset time period, the combination of at least two time parameters of the human body state time parameter within the preset time period, and the combination of at least two exercise amount parameters of the physiological parameter within the preset time period.

In S103, after the evaluation device for the recovery state of the patient in the hospital extracts the at least two parameters corresponding to the preset time period, the evaluation device for the recovery state of the patient in the hospital may perform correlation processing based on the at least two parameters corresponding to the preset time period to obtain a correlation metric, and implement the evaluation of the recovery state of the patient by using the correlation metric for evaluating the recovery state of the patient.

In the embodiment of the present invention, the evaluation device for the recovery state of the patient in the hospital performs correlation processing based on at least two corresponding parameters in a preset time period, and the process of obtaining the correlation metric may be: acquiring a preset correlation algorithm by an evaluation device for the recovery state of the patient in the hospital; and calculating the correlation of at least two corresponding parameters in a preset time period by adopting a preset correlation algorithm to obtain correlation measurement.

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

In the embodiment of the invention, the evaluation device for the recovery state of the patient in the hospital performs correlation processing on at least two parameters by adopting at least one of ratio operation, difference operation, integral ratio operation, area ratio operation, integral difference operation and area difference operation, thereby obtaining the correlation measurement capable of representing the recovery state of the patient.

For example, the predetermined correlation algorithm may include: calculating the correlation of the specific value of the movement time and the bed leaving time, the difference value of the movement time and the bed leaving time, the projection areas of different time periods on a time window, the specific value of the movement time and a preset time period, the specific value of the movement time and the bed lying time, the specific value of the bed leaving time and the preset time period, the infrared chart and other different time periods; the human body state time parameter and the heart rate are calculated in different modes, such as a ratio of the human body state time parameter to the heart rate, a difference value of the human body state time parameter to the heart rate, a projection area of the human body state time parameter to the heart rate on a time window, an integral of the human body state time parameter to the heart rate, a ratio of the human body state time parameter to the integral of the heart rate, a difference value of the human body state time parameter to the integral of the heart rate, an infrared chart of the human body state time parameter and the heart rate, and the like; and different calculation modes such as the ratio of the step frequency to the movement distance, the difference value of the step frequency and the movement distance, the projection area of the step frequency and the movement distance on a time window, the integral of the step frequency and the movement distance, the ratio of the step frequency to the integral of the movement distance, the difference value of the step frequency to the integral of the movement distance, the infrared chart of the step frequency and the movement distance and the like.

It should be noted that, in the embodiment of the present invention, the movement distance is constant, and the larger the step frequency is, the shorter the movement time is, and the better the patient recovers. The larger the ratio of the step frequency to the movement distance, the better the patient's recovery.

It can be understood that, because the evaluation device for the recovery state of the patient in the hospital can acquire at least two parameters from at least one type of related parameters of the human body state time parameter, the motion amount parameter and the physiological parameter, and the correlation measurement for evaluating the recovery state of the patient is obtained through the correlation processing of the at least two parameters, the diversity of the correlation measurement is embodied because the correlation measurement considers the at least one type of parameters and is obtained by correlating the parameters, and the mode for evaluating the recovery state of the patient based on the correlation measurement obtained by the correlation of the at least two parameters is more accurate, namely, the monitoring of the human body from multiple dimensions is realized, the monitoring diversity is realized, and the accuracy for evaluating the recovery condition of the human body is improved.

In the embodiment of the present invention, the process of extracting at least two parameters corresponding to a preset time period from at least one type of relevant parameters by the hospital patient recovery state assessment device is as follows: acquiring at least two parameters of human body state time parameters, motion quantity parameters and physiological parameters; and extracting at least two parameters respectively corresponding to the preset time period from the at least two types of parameters, wherein each type of related parameter correspondingly has at least one parameter.

Based on the above, the hospital patient recovery state evaluation device performs correlation processing based on at least two corresponding parameters in a preset time period, and the correlation measurement is obtained in at least one of the following ways: obtaining a quantitative index related to the correlation measurement based on at least two corresponding parameters within a preset time period; and obtaining a graphical index related to the correlation metric based on the corresponding at least two parameters within the preset time period.

On the one hand, different combinations of at least two variables are used, which are explained below in each case.

In some embodiments of the present invention, the device for evaluating the recovery state of the patient in the hospital may extract at least two parameters of the human body state time parameter, the motion amount parameter, and the physiological parameter within a preset time period, and perform correlation processing on at least two parameters of the human body state time parameter, the motion amount parameter, and the physiological parameter extracted within the preset time period to obtain the correlation metric.

In some embodiments of the present invention, when the at least two types of parameters include a human body state time parameter and a motion amount parameter, as shown in fig. 8, fig. 8 is an optional flowchart of a method for evaluating a recovery state of a patient in a hospital according to an embodiment of the present invention, and the method may include:

s201, acquiring at least one motion signal of the patient.

In the embodiment of the invention, the preset motion sensor is arranged in the device for evaluating the recovery state of the patient in the hospital, so that the device for evaluating the recovery state of the patient in the hospital can acquire at least one original motion signal of the patient through the preset motion sensor; and filtering the at least one original motion signal to obtain at least one motion signal.

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

In the embodiment of the invention, the assessment device for the recovery state of the patient in the hospital acquires at least one original motion signal of the patient through a preset motion sensor, wherein the at least one original motion signal is an electric signal, and after the assessment device for the recovery state of the patient in the hospital performs hardware filtering and signal amplification on the at least one original motion signal, analog-to-digital conversion is performed to complete filtering and redundancy removal on the at least one original motion signal, and after mode conversion, the at least one motion signal is obtained, so that impurities are removed from the obtained at least one motion signal, and the essence of the motion signal can be better embodied.

In this embodiment of the present invention, the preset motion sensor may be an accelerometer, and the at least one motion signal obtained in this way may be at least one acceleration data.

Illustratively, as shown in fig. 9, the device for evaluating the recovery state of the patient in the hospital acquires at least one original motion signal through an accelerometer preset by the device, then performs hardware filtering on the at least one original motion signal to remove noise, and performs signal method and analog-to-digital conversion to obtain acceleration data (i.e. at least one motion signal).

S202, counting human body state time parameters and motion quantity parameters in a preset time period based on at least one motion signal.

After the estimation device for the recovery state of the patient in the hospital acquires the at least one motion signal, the at least one motion signal is a signal within a preset time period, so that the estimation device for the recovery state of the patient in the hospital can acquire the time parameter of the state of the human body and the motion parameter within the preset time period based on the at least one motion signal.

Specifically, the hospital patient recovery state evaluation device extracts time domain features or frequency domain features of at least one motion signal to obtain motion features, and obtains motion time based on the motion features; and also on the basis of at least one motion signal, counting the motion quantity parameter within a preset time period; determining the time of leaving the bed according to the exercise quantity parameters and the preset rest threshold value; determining the time of lying in bed according to a preset time period and the time of leaving the bed; and the sleeping time can be acquired, and any one or more of the bed leaving time, the moving time, the preset time period, the bed lying time and the sleeping time is/are used as the human body state time parameter.

In this embodiment of the present invention, the apparatus for evaluating the recovery state of the hospital patient extracts a time domain feature or a frequency domain feature of at least one motion signal to obtain a motion feature, and based on the motion feature, obtaining the motion time process may include: the device for evaluating the recovery state of the patient in the hospital extracts a time domain feature and a frequency domain feature (motion feature) from at least one motion signal, judges whether the patient is in the motion state according to the time domain feature or the frequency domain feature, and when the patient is judged to be in the motion state, counts the time of the patient in the motion state to obtain the motion time.

In this embodiment of the present invention, the time domain information may include: searching wave information, amplitude information and time domain characteristics can comprise: counting the mean SMV (Signal magnetic Vector acceleration intensity Vector), SMA (Signal magnetic Area, Area acceleration intensity) of the time domain feature information, and the like, wherein the frequency domain features may include: ultra Low Frequency (VLF, Very Low Frequency), Low Frequency (LF, Low Frequency), High Frequency (HF, High Frequency), TP (Total Power), LF/HF ratio, etc., which are not limited in the embodiments of the present invention.

In the embodiment of the present invention, the process of obtaining the exercise time based on the exercise characteristics by the hospital patient recovery state evaluation device is specifically as follows: the method comprises the steps that an assessment device of the recovery state of a patient in a hospital obtains a preset time characteristic threshold in real time; and when the motion characteristic is greater than a preset time characteristic threshold value, determining the motion state, and recording the duration of the motion state to obtain the motion time.

The hospital patient recovery state evaluation device compares the time domain feature with a preset time domain threshold, judges that the patient is moving and is in a moving state when the time domain feature is larger than the preset time domain threshold, and counts the time of the patient in the moving state to obtain the moving time of the patient. Or the frequency domain characteristic is compared with a preset frequency domain threshold value by the hospital patient recovery state evaluation device, when the frequency domain characteristic is larger than the preset frequency domain threshold value, the patient is judged to be in the motion state, and the motion time of the patient can be obtained by counting the time of the patient in the motion state.

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

For example, for the time domain feature, the device for evaluating the recovery state of the patient in the hospital compares the SMV with a preset time domain threshold (e.g. 30mg), or compares the SMA with a preset time domain threshold (e.g. 9.8 per second), when the SMV or SMA and the preset time domain threshold are met, it can be determined that the patient is in motion and in a motion state, and at this time, the device for evaluating the recovery state of the patient in the hospital counts the time when the patient is in the motion state, and then the motion time can be obtained.

For the frequency domain features, the device for evaluating the recovery state of the patient in the hospital counts time-frequency features (such as HF or LF/HF) in a preset time window, when the frequency domain features are larger than a preset frequency domain threshold (such as 50%), the patient is judged to be in a motion state, and the time when the patient is in the motion state is counted, so that the motion time can be obtained.

In the embodiment of the present invention, the preset motion sensor may include a plurality of types, and at least one motion signal obtained by the preset motion sensor may further count a motion amount parameter, such as a step frequency, a step number, a motion distance, a motion intensity, a motion calorie consumption, and the like. The 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 one preset motion sensor, and the embodiments of the present invention are not limited thereto.

In the embodiment of the present invention, according to clinical experience, the basic activity patterns of the patient after leaving the bed are: walking outside, sitting outside for rest, walking again, resting again, after several cycles, getting back to ward after feeling tired, and resting on lying bed. Illustratively, the determination of the time-to-bed exit may be determined based on such patient usage patterns

The rest time is determined according to the motion quantity parameter and the preset rest threshold value, and the out-of-bed time is determined according to the rest time and the motion time. Counting the time spent in bed: and obtaining the bed leaving time within a preset time period, and obtaining the bed lying time by using the total time-the bed leaving time, namely determining the bed lying time according to the preset time period and the bed leaving time.

In some embodiments of the invention, the means for assessing the recovery status of the patient in the hospital may receive the time of bed leaving and the time of bed lying as monitored by the bedside or on-board sensors. That is, a sensor, such as a video camera, may be disposed beside the patient bed for observing whether the patient is out of the bed or the lying time on the bed through a video image in real time, and for example, a bed-mounted sensor, such as a bed-mounted electrode detection sensor or a pressure sensor, may be disposed on the patient bed, and a sampling signal of the bed-mounted electrode detection sensor or the pressure sensor may be changed due to the patient being out of the patient bed or lying on the patient bed, and the patient may be determined whether the patient is out of the bed or the lying time on the bed based on the change difference.

S203, carrying out correlation processing on the human body state time parameter and the motion amount parameter extracted in the preset time period to obtain correlation measurement.

After the estimation device for the recovery state of the hospital patient acquires the human body state time parameter and the motion amount parameter, the estimation device for the recovery state of the hospital patient can perform correlation processing according to the human body state time parameter and the motion amount parameter extracted in the preset time period, and correlation measurement is obtained.

In some embodiments of the present invention, when the at least two types of parameters include a human body state time parameter and a physiological parameter, as shown in fig. 10, fig. 10 is an optional flowchart of a method for evaluating a recovery state of a patient in a hospital according to an embodiment of the present invention, and the method may include:

s301, at least one motion signal of the patient is acquired.

Here, the process of acquiring at least one motion signal of the patient by the apparatus for evaluating the recovery state of the patient in the hospital is consistent with the description of S201, and is not described herein again.

S302, counting human body state time parameters in a preset time period based on at least one motion signal.

Here, the process of counting the human state time parameters within the preset time period by the device for evaluating the recovery state of the patient in the hospital based on the at least one motion signal is consistent with the description of "counting the human state time parameters within the preset time period based on the at least one motion signal" in S202, and is not described herein again.

And S303, acquiring the physiological parameters through the biological characteristic sensor.

Here, the sensor in the device for evaluating the recovery state of the hospital patient may further include a biometric sensor, so that the device for evaluating the recovery state of the hospital patient may further acquire the physiological parameter of the patient.

In the embodiment of the present invention, the biometric sensor may include a sleep detection sensor, a heart rate sensor, a pulse sensor, and other sensors capable of detecting physiological parameters of a human body, for example, the electrocardiograph sensor may detect a heart rate and a respiratory rate, the pulse wave detection sensor may obtain a pulse rate, and the electrodes disposed on the patient bed may detect whether the human body is out of the bed to determine a sleep state, and the like.

S304, carrying out correlation processing on the human body state time parameter and the physiological parameter extracted in the preset time period to obtain correlation measurement.

After the human body state time parameter and the physiological parameter are obtained by the hospital patient recovery state evaluation device, the hospital patient recovery state evaluation device can perform correlation processing according to the human body state time parameter and the physiological parameter extracted in the preset time period, and correlation measurement is obtained.

Illustratively, the combination of the human state time parameter and the physiological parameter (heart rate and pulse rate for example) includes: exercise time and heart rate; time to bed and heart rate; bed time and heart rate; presetting a time period and a heart rate; sleep time and heart rate.

Further, in the embodiment of the present invention, the at least two types of parameters may further include: based on the foregoing embodiments, under the premise that how the human body state time parameter, the physiological parameter, and the motion amount parameter are obtained within the preset time period is known, the evaluation device for the recovery state of the patient in the hospital only needs to perform correlation processing on the parameters of different combinations to obtain correlation measurement, and thus the recovery state of the patient can be evaluated, which is not described herein again.

On the other hand, the hospital patient recovery state evaluation device can extract parameters with different dimensions of at least two of the human body state time parameter, the motion quantity parameter and the physiological parameter within a preset time period, and perform correlation processing on the parameters with different dimensions of at least two of the human body state time parameter, the motion quantity parameter and the physiological parameter extracted within the preset time period to obtain correlation measurement.

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 flowchart of a method for evaluating a recovery state of a patient in a hospital according to an embodiment of the present invention, where the method may include:

s401, obtaining human body state time parameters as at least one type of related parameters.

S402, extracting at least two corresponding time parameters in a preset time period from the human body state time parameters to serve as at least two parameters.

S403, performing correlation processing on at least two time parameters extracted in a preset time period to obtain correlation measurement.

In the embodiment of the invention, at least two time parameters in a preset time period are extracted from the human body state parameters acquired by the hospital patient recovery state assessment device and are used as at least two parameters, and finally, correlation processing is carried out based on the at least two time parameters.

It should be noted that, the foregoing embodiments of the process for acquiring the human body state time parameter by the apparatus for evaluating the recovery state of the patient in the hospital have been described, and are not described herein again. The human body state time parameters acquired by the hospital patient recovery state assessment device are one or more of bed leaving time, exercise time, preset time period, bed lying time and sleeping time.

In the embodiment of the invention, the human body state time parameters comprise: an exercise time parameter and a sleep time parameter. Wherein the motion time parameters include: the time of leaving the bed, the time of moving, the time of lying in the bed and the preset time period.

When the human body state time parameter is only the motion time parameter, the acquisition process of at least two parameters is as follows: the hospital patient recovery state evaluation device acquires at least one motion signal of a patient, and extracts time domain features or frequency domain features of the at least one motion signal to obtain motion features; acquiring at least one motion time parameter of at least one dimension statistic representing the motion time parameter in a preset time period based on the motion characteristics; acquiring sleep time parameters of a patient; the sleep time parameter and the at least one movement time parameter are used as at least two time parameters as at least two parameters. Namely, the assessment device for the recovery state of the patient in the hospital acquires at least two of the bed leaving time, the exercise time, the bed lying time and the preset time period as at least two time parameters.

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

the exercise time and the bed exit time;

the exercise time and the preset time period;

leaving the bed for a preset time period;

exercise time and bed rest time;

the time of leaving the bed and the time of lying in the bed;

the time of lying in bed and the preset time period;

the motion time, the bed leaving time and the preset time period;

exercise time, bed-lying time and a preset time period;

exercise time, bed exit time and bed rest time;

leaving time, lying time and preset time period;

the exercise time, the bed leaving time, the bed lying time and the preset time period.

When the human body state time parameters comprise a movement time parameter and a sleep time parameter, the acquisition process of at least two parameters is as follows: the method comprises the steps that an assessment device of the recovery state of a patient in a hospital obtains at least one motion signal and sleep time parameters of the patient; extracting time domain characteristics or frequency domain characteristics of at least one motion signal to obtain motion characteristics; acquiring at least one motion time parameter of at least one dimension statistic representing the motion time parameter in a preset time period based on the motion characteristics; the sleep time parameter and the at least one movement time parameter are used as at least two time parameters as at least two parameters.

Wherein the combination of at least one motion time parameter comprises any one of:

the time of the exercise;

the time of leaving the bed;

time spent in bed;

presetting a time period;

the exercise time and the bed exit time;

the exercise time and the preset time period;

leaving the bed for a preset time period;

exercise time and bed rest time;

the time of leaving the bed and the time of lying in the bed;

the time of lying in bed and the preset time period;

the motion time, the bed leaving time and the preset time period;

exercise time, bed-lying time and a preset time period;

exercise time, bed exit time and bed rest time;

leaving time, lying time and preset time period;

In the embodiment of the present invention, the process of specifically obtaining the motion time parameter is described in detail in the foregoing embodiment, and is not described herein again.

In some embodiments of the present invention, when at least one type of parameter is an exercise amount parameter, as shown in fig. 12, fig. 12 is an optional flowchart of a method for evaluating recovery status of a patient in a hospital according to an embodiment of the present invention, where the method may include:

s501, obtaining the motion quantity parameters as at least one type of related parameters.

S502, extracting at least two corresponding motion quantity parameters in a preset time period from the motion quantity parameters to serve as at least two parameters.

S503, performing correlation processing on the at least two motion quantity parameters extracted in the preset time period to obtain correlation measurement.

In the embodiment of the invention, at least two motion parameters in a preset time period are extracted from the motion parameters acquired by the hospital patient recovery state assessment device, and finally, correlation processing is performed based on the at least two motion parameters.

It should be noted that the foregoing embodiments have been described, and the details are not repeated herein, in which the apparatus for evaluating the recovery state of the patient in the hospital acquires the parameter of the amount of exercise. The exercise quantity parameters acquired by the hospital patient recovery state assessment device are one or more of step frequency, step number, exercise distance, exercise strength, exercise calorie consumption and the like.

Further, in the embodiment of the present invention, at least one type of related parameters may further include: a physiological parameter. When at least two parameters are physiological parameters, the estimation device for the recovery state of the patient in the hospital acquires at least two physiological related parameters of the physiological parameters; the at least two physiological relevant parameters are at least one type of relevant parameters, the at least two physiological parameters corresponding to the at least two physiological relevant parameters within the preset time period are extracted from the at least two physiological relevant parameters, and the at least two physiological parameters of the physiological parameters extracted within the preset time period are subjected to correlation processing to obtain the correlation measurement.

In some embodiments of the present invention, referring to fig. 13, fig. 13 is an optional flowchart of the method for evaluating the recovery status of the patient in the hospital according to the embodiments of the present invention, and based on fig. 7, after the apparatus for evaluating the recovery status of the patient in the hospital obtains the correlation metric, S104 or S105 may be further performed. The following were used:

and S104, presenting the relevance measurement.

After the evaluation device for the recovery state of the patient in the hospital obtains the relevance measurement, the relevance measurement can be directly displayed, so that a doctor can visually observe the recovery state of the patient through the relevance measurement, and the visual visualization performance is embodied.

In the embodiment of the present invention, the relevance metric may be directly displayed or played in voice, and may be presented in at least one of the following ways:

sequentially refreshing and displaying the quantitative indexes about the correlation measurement obtained at different moments along with the time change;

the graphical indexes related to the correlation measurement obtained at different moments are sequentially refreshed and displayed along with the time change;

constructing a coordinate system which changes along time, marking quantitative indexes which correspond to different moments and are related to correlation measurement in the coordinate system which changes along time, and forming a change trend graph of the quantitative indexes; and the combination of (a) and (b),

and constructing a time-varying coordinate system, marking graphical indexes related to the correlation measurement corresponding to different moments in the time-varying coordinate system, and forming a variation trend graph of the graphical indexes.

S105, transmitting the correlation measurement to a bedside monitor and/or a central station; such that the correlation metric is presented at the bedside monitor and/or the central station.

The hospital patient recovery state evaluation device can also transmit the correlation measurement to a bedside monitor and/or a central station after obtaining the correlation measurement; such that the correlation metric is presented on the bedside monitor and/or the central station, revealing the intelligent effect of performing the correlation metric on the third party device.

Further, in the embodiment of the present invention, after the evaluation apparatus for the recovery state of the hospital patient acquires the at least two parameters, the process of performing correlation processing and presenting the correlation metric for the at least two parameters may be implemented by a third-party device capable of communicating with the evaluation apparatus for the recovery state of the hospital patient; alternatively, after the hospital patient recovery state evaluation device obtains the at least two parameters and performs correlation processing on the at least two parameters, the process of presenting the correlation metric may be implemented by a third-party device that can communicate with the hospital patient recovery state evaluation device. The specific implementation principle is consistent with the processing principle of the device for evaluating the recovery state of the patient in the hospital, and the details are not repeated here.

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

The following describes the process of the apparatus for evaluating the recovery state of the patient in the hospital according to the two time parameters, wherein the time parameters of the human body state include a first time parameter and a second time.

Referring to fig. 14, fig. 14 is a schematic flow chart of an alternative method for evaluating recovery status of a patient in a hospital according to an embodiment of the present invention, where the method includes:

s601, acquiring 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 time parameters of at least one time dimension in the human body state time parameters.

In the embodiment of the invention, the assessment device for the recovery state of the patient in the hospital acquires at least one motion signal, obtains the time parameter of the human body state based on the at least one motion signal, and extracts at least two dimensions of time of a first time parameter and a second time parameter corresponding to the preset time period from the time parameter of the human body state.

In the embodiment of the present invention, the human body state time parameters include an exercise time parameter and a sleep time parameter, wherein the exercise time parameter may further include: time parameters of multiple dimensions, such as exercise time, time in bed, time out of bed, preset time period, and the like. That is, the device for evaluating the recovery state of the patient in the hospital acquires the first time parameter and the second time parameter from the exercise time parameter and the sleep time parameter.

S602, performing correlation processing on the first time parameter and the second time parameter to obtain correlation measurement; the correlation metric is used to assess the recovery status of the patient.

After the estimation device for the recovery state of the patient in the hospital acquires the first time parameter and the second time parameter, the estimation device for the recovery state of the patient in the hospital can perform related processing on the first time parameter and the second time parameter, so that the correlation measurement for estimating the recovery state of the patient is obtained.

In the embodiment of the invention, the estimation device for the recovery state of the patient in the hospital can obtain a preset correlation algorithm; and calculating the correlation between the first time parameter and the second time parameter by adopting a preset correlation algorithm to obtain correlation measurement. A correlation metric is output and displayed on the monitoring device, the correlation metric including a quantitative indicator and/or a graphical indicator.

In an embodiment of the present invention, the preset correlation algorithm includes at least one of the following: ratio operation, difference operation, integral ratio operation, area ratio operation, integral difference operation, and area difference operation, which are not limited in the embodiments of the present invention.

In some embodiments of the present invention, when the human body state time parameter includes a movement time parameter, the process of S601 may include: s6011-6013. The following were used:

s6011, acquiring at least one motion signal of a patient within a preset time period;

s6012, extracting time domain characteristics or frequency domain characteristics of at least one motion signal to obtain motion characteristics;

s6013, based on the motion characteristics, a first time parameter and a second time parameter which represent motion time parameter statistics in a preset time period are obtained.

In some embodiments of the present invention, the obtaining, based on the motion characteristics, a first time parameter and a second time parameter representing statistics of the motion time parameter within a preset time period includes: determining the movement time according to the movement characteristics; counting the motion quantity parameter in a preset time period based on at least one motion signal; determining the time of leaving the bed according to the exercise quantity parameter, the preset rest threshold value and the exercise time; determining the time of lying in bed according to a preset time period and the time of leaving the bed; and selecting a first time parameter and a second time parameter from the exercise time representing the exercise time parameter, the bed leaving time, the preset time period and the bed lying time.

the exercise time and the bed exit time;

the exercise time and the preset time period;

leaving the bed for a preset time period;

exercise time and bed rest time;

the time of leaving the bed and the time of lying in the bed;

the time of lying in bed and the preset time period.

In some embodiments of the present invention, 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, receives the time of leaving the bed and the time of lying in the bed, which are monitored by the bedside sensor, after obtaining the motion feature and before selecting the first time parameter and the second time parameter from the motion time, the time of leaving the bed, the preset time period and the time of lying in the bed.

In the embodiment of the invention, a bedside sensor is arranged in front of a patient bed, the time of leaving the bed and the time of lying in the bed can be acquired through the bedside sensor, and then the bed time and the time of lying in the bed are sent to an evaluation device for the recovery state of the patient in the bed to be used.

In the embodiment of the present invention, the bedside sensor may be disposed on a patient bed, or may be disposed on a bedside monitor, which is not limited in the embodiment of the present invention. Wherein the equipment where the bedside sensor is located can communicate with the assessment device of the state recovery of the patient in the hospital.

Optionally, the communication mode may include a wireless communication technology, and the embodiment of the present invention is not limited.

In some embodiments of the present invention, when the human body state time parameter includes an exercise time parameter and a sleep time parameter, the process of S601 may include: S6014-S6018. The following were used:

s6014, acquiring a motion signal of a patient within a preset time period;

s6015, extracting time domain characteristics or frequency domain characteristics of one motion signal to obtain first motion characteristics;

s6016, based on the first motion characteristic, a motion time parameter representing the motion time parameter in a preset time period is obtained.

S6017, acquiring sleep time parameters of the patient in a preset time period.

S6018, the sleep time parameter and the exercise time parameter are used 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;

presetting time period and sleep time parameters;

time to leave bed and time to sleep parameters;

time in bed and time in sleep parameters.

It should be noted that, in the embodiment of the present invention, the process of acquiring the human body time parameter and the process of measuring the correlation are discussed in detail in the foregoing embodiment, and are not described again here.

It can be understood that, since the evaluation device for the recovery state of the patient in the hospital can obtain the correlation measurement for evaluating the recovery state of the patient from the correlation processing of the first time parameter and the second time parameter of the state of the human body, the diversity of the correlation measurement is embodied because the correlation measurement considers the two dimensional time parameters and obtains the parameter correlation, and therefore, the mode of evaluating the recovery state of the patient based on the correlation measurement of the multiple dimensions of the first time parameter and the second time parameter is more accurate, namely, the monitoring of the human body from multiple dimensions is realized, the diversity of the monitoring is realized, and the accuracy of evaluating the recovery condition of the human body is improved.

The embodiment of the invention provides a computer-readable storage medium, which stores an evaluation instruction capable of executing the recovery state evaluation of a patient in a hospital, and is used for causing a processor to execute the evaluation method for the recovery state evaluation of the patient in the hospital provided by the embodiment of the invention when the processor is executed.

In some embodiments of the invention, the computer readable storage medium may be memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; or may be various devices including one or any combination of the above memories.

In some embodiments of the invention, the executable hospital patient recovery status assessment instructions may be written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages) in the form of a program, software module, script, or code, and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

As an example, the evaluation instructions of the intra-hospital patient recovery status may, but need not, correspond to a file in a file system, may be stored in a portion of a file holding other programs or data, such as in one or more scripts in a Hypertext Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files storing one or more modules, sub-programs, or portions of code).

As an example, the executable instructions for assessment of the in-hospital patient recovery status may be deployed to be executed on one computing device, or on multiple computing devices located at one site, or distributed across multiple sites and interconnected by a communication network.

The above description is only an example of the present invention, and is not intended to limit the 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

The embodiment of the invention provides a hospital patient recovery state evaluation method, a hospital patient recovery state evaluation device, a hospital patient recovery state evaluation system and a storage medium, wherein the hospital patient recovery state evaluation device can acquire at least two parameters from at least one type of related parameters of human body state time parameters, motion quantity parameters and physiological parameters, obtaining a correlation measure for assessing the recovery status of the patient by correlation processing of at least two parameters, since the correlation metric takes into account at least one class of parameters, and is also a function of the parameters, thus, the diversity of the correlation metrics is embodied, and the way that the correlation metrics obtained based on the correlation of at least two parameters are used for evaluating the recovery state of the patient is more accurate, the human body can be monitored from multiple dimensions, monitoring diversity is realized, and accuracy of evaluating the rehabilitation condition of the human body is improved.

Claims

A method of assessing the recovery status of a patient in a hospital, the method comprising:

acquiring 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 time parameters of at least one time dimension in human body state time parameters;

and performing correlation processing on the first time parameter and the second time parameter to obtain a correlation metric, wherein the correlation metric is used for evaluating the recovery state of the patient.
The method according to claim 1, wherein the human body state time parameter comprises a motion time parameter, and the acquiring a first time parameter and a second time parameter of the corresponding human body state time parameter within a preset time period comprises:

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

extracting time domain characteristics or frequency domain characteristics of the at least one motion signal to obtain motion characteristics;

and acquiring the first time parameter and the second time parameter which represent the statistics of the motion time parameter in the preset time period based on the motion characteristics.
The method according to claim 1, wherein the human body state time parameters include an exercise time parameter and a sleep time parameter, and the acquiring the first time parameter and the second time parameter of the corresponding human body state time parameters within the preset time period includes:

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

extracting time domain characteristics or frequency domain characteristics of the motion signal to obtain first motion characteristics;

acquiring a motion time parameter representing the motion time parameter in the preset time period based on the first motion characteristic;

acquiring a sleep time parameter of the patient within the preset time period;

taking the sleep time parameter and the one exercise time parameter as the first time parameter and the second time parameter.
The method according to claim 2, wherein the obtaining the first time parameter and the second time parameter characterizing the statistics of the motion time parameter within the preset time period based on the motion characteristics comprises:

determining the movement time according to the movement characteristics;

counting the motion quantity parameter in the preset time period based on the at least one motion signal;

determining the time of leaving the bed according to the exercise quantity parameter, a preset rest threshold value and the exercise time;

determining the time of lying in bed according to the preset time period and the time of leaving the bed;

selecting the first time parameter and the second time parameter from the exercise time, the bed leaving time, the preset time period and the bed lying time which characterize the exercise time parameter.
The method according to claim 4, wherein after the extracting the time domain feature or the frequency domain feature of the at least one motion signal to obtain the motion feature and before the selecting the first time parameter and the second time parameter from the motion time, the bed exit time, the preset time period and the bed in time, the method further comprises:

and receiving the bed leaving time and the bed lying time which are monitored by the transmission of the bedside sensor.
The method of claim 4, wherein the combination of the first time parameter and the second time parameter is any one of:

the movement time and the bed exit time;

the movement time and the preset time period;

the bed leaving time and the preset time period;

the exercise time and the bed rest time;

the time out of bed and the time in bed;

the bed-lying time and the preset time period.
The method of claim 1, wherein the correlating the first time parameter and the second time parameter to obtain a correlation metric comprises:

acquiring a preset correlation algorithm;

and calculating the correlation between the first time parameter and the second time parameter by adopting the preset correlation algorithm to obtain the correlation measurement.
The method of claim 1, wherein,

the correlation metric is output and displayed on a monitoring device, and comprises a quantitative index and/or a graphical index.
A method of assessing the recovery status of a patient in a hospital, the method comprising:

acquiring at least one type of relevant parameters of human body state time parameters, motion quantity parameters and physiological parameters;

extracting at least two corresponding parameters in a preset time period from the at least one type of related parameters; and the combination of (a) and (b),

and carrying out correlation processing on the basis of the at least two corresponding parameters in the preset time period to obtain a correlation metric, wherein the correlation metric is used for evaluating the recovery state of the patient.
The method according to claim 9, wherein the obtaining at least one type of relevant parameters among the human body state time parameter, the motion amount parameter and the physiological parameter, and extracting at least two corresponding parameters within a preset time period from the at least one type of relevant parameters includes:

acquiring at least two parameters of the human body state time parameter, the motion quantity parameter and the physiological parameter; and the combination of (a) and (b),

and extracting at least two parameters respectively corresponding to the preset time period from the at least two types of parameters, wherein each type of related parameter correspondingly has at least one parameter.
The method of claim 9, wherein the performing correlation processing based on the at least two parameters corresponding to the preset time period to obtain a correlation metric includes at least one of:

obtaining a quantitative index related to the correlation measurement based on at least two corresponding parameters in the preset time period; and the combination of (a) and (b),

and obtaining a graphical index related to the correlation measurement based on the corresponding at least two parameters in the preset time period.
The method of claim 9, wherein said extracting at least two parameters corresponding to a preset time period from the at least one type of related parameters comprises:

acquiring the human body state time parameters as the at least one type of related parameters; and the combination of (a) and (b),

and extracting at least two corresponding time parameters within a preset time period from the human body state time parameters to serve as the at least two parameters.
The method of claim 12, wherein the correlating based on the at least two parameters corresponding to the preset time period to obtain a correlation metric comprises:

and performing correlation processing on the at least two time parameters extracted in the preset time period to obtain a quantitative index related to the correlation measurement.
The method of claim 9, wherein said extracting at least two parameters corresponding to a preset time period from the at least one type of related parameters comprises:

acquiring the motion quantity parameter as the at least one type of related parameter;

and extracting at least two corresponding motion quantity parameters within a preset time period from the motion quantity parameters to serve as the at least two parameters.
The method of claim 14, wherein the performing correlation processing based on the at least two parameters corresponding to the preset time period to obtain a correlation metric comprises:

and performing correlation processing on the at least two motion quantity parameters extracted within the preset time period to obtain the correlation measurement.
The method according to claim 12, wherein the human body state time parameters include motion time parameters, and the extracting at least two corresponding time parameters within a preset time period from the human body state time parameters as the at least two parameters includes:

acquiring at least one motion signal of the patient;

extracting time domain characteristics or frequency domain characteristics of the at least one motion signal to obtain motion characteristics;

and acquiring at least two time parameters representing at least two dimension statistics of the motion time parameters in the preset time period based on the motion characteristics, wherein the at least two time parameters are used as the at least two parameters.
The method according to claim 12, wherein the human body state time parameters include a motion time parameter and a sleep time parameter, and the extracting at least two corresponding time parameters within a preset time period from the human body state time parameters as the at least two parameters includes:

acquiring at least one motion signal of the patient, and extracting time domain characteristics or frequency domain characteristics of the at least one motion signal to obtain motion characteristics;

acquiring at least one motion time parameter representing at least one dimension statistic of the motion time parameter in the preset time period based on the motion characteristics;

acquiring sleep time parameters of the patient;

and taking the sleep time parameter and the at least one motion time parameter as the at least two time parameters.
The method of claim 10, wherein the at least two types of parameters comprise at least one of:

the human body state time parameter and the exercise amount parameter, the human body state time parameter and the physiological parameter, the exercise amount parameter and the physiological parameter, and the human body state time parameter, the exercise amount parameter and the physiological 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 motion amount parameter, the obtaining at least two types of parameters of the human body state time parameter, the motion amount parameter and the physiological parameter includes:

acquiring at least one motion signal of the patient;

and counting the human body state time parameter and the motion quantity parameter in the preset time period based on the at least one motion signal.
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 at least two types of parameters of the human body state time parameter, the motion amount parameter and the physiological parameter includes:

acquiring at least one motion signal of the patient;

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

and acquiring the physiological parameters through a biological characteristic sensor.
The method of any one of claims 16, 17, 19 or 20, wherein said acquiring at least one motion signal of the patient comprises:

acquiring the at least one raw motion signal of the patient by a preset motion sensor;

and filtering the at least one original motion signal to obtain the at least one motion signal.
The method according to claim 16, wherein the obtaining, as the at least two parameters, the at least two time parameters characterizing at least two dimensional statistics of the human body state time parameter within the preset time period based on the motion characteristics includes:

obtaining movement time based on the movement characteristics;

counting the motion quantity parameter in the preset time period based on the at least one motion signal;

determining the time of leaving the bed according to the exercise quantity parameter, a preset rest threshold value and the exercise time;

determining the time of lying in bed according to the preset time period and the time of leaving the bed;

and taking any at least two combinations of the bed leaving time, the exercise time, the preset time period and the bed lying time as the at least two time parameters of the human body state time parameters, and taking the at least two time parameters as the at least two parameters.
The method of claim 22, wherein said deriving a motion time based on said motion characteristics comprises:

acquiring a preset time characteristic threshold in real time;

and when the motion characteristic is larger than the preset time characteristic threshold value, determining the motion state, and recording the duration of the motion state to obtain the motion time.
The method according to claim 23, wherein after obtaining the exercise time based on the exercise characteristics and before combining any at least two of the bed exit time, the exercise time, the preset time period and the bed rest time as the at least two time parameters in the human body state time parameters, the method further comprises:

and receiving the bed leaving time and the bed lying time which are transmitted and monitored by a bedside sensor or a bed-mounted sensor.
The method of claim 9, wherein the performing correlation processing based on the at least two parameters corresponding to the preset time period to obtain a correlation metric includes:

acquiring a preset correlation algorithm;

and calculating the correlation of at least two corresponding parameters in the preset time period by adopting the preset correlation algorithm to obtain the correlation measurement.
The method of claim 25, wherein the pre-set correlation algorithm comprises at least one of: ratio operation, difference operation, integral ratio operation, area ratio operation, integral difference operation and area difference operation.
The method of claim 9, wherein after the correlation processing based on the at least two parameters corresponding to the preset time period to obtain the correlation metric, the method further comprises:

presenting the relevance metric in at least one of:

sequentially refreshing and displaying the quantitative indexes about the correlation measurement obtained at different moments along with the time change;

the graphical indexes related to the correlation measurement obtained at different moments are sequentially refreshed and displayed along with the time change;

constructing a coordinate system which changes along time, marking quantitative indexes which correspond to different moments and are related to correlation measurement in the coordinate system which changes along time, and forming a change trend graph of the quantitative indexes; and the combination of (a) and (b),

and constructing a time-varying coordinate system, marking graphical indexes related to the correlation measurement corresponding to different moments in the time-varying coordinate system, and forming a variation trend graph of the graphical indexes.
The method of claim 9, wherein after the correlation processing based on the at least two parameters corresponding to the preset time period to obtain the correlation metric, the method further comprises:

transmitting 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.
A system for assessing the recovery status of a patient in a hospital, the system comprising: at least one wearable device worn on a patient;

the wearable device is used for acquiring at least one type of relevant parameters of human body state time parameters, motion quantity parameters and physiological parameters; extracting at least two corresponding parameters within a preset time period from the at least one type of related parameters; and performing correlation processing based on the at least two corresponding parameters in the preset time period to obtain a correlation metric, wherein the correlation metric is used for evaluating the recovery state of the patient.
The system of claim 29, wherein,

the at least one wearable device is further configured to perform correlation processing based on the at least two corresponding parameters within the preset time period, and present the correlation metric after the correlation metric is obtained.
The system of claim 29, wherein the system further comprises: a bedside monitor in communication with the at least one wearable device;

the wearable device is used for extracting at least two corresponding parameters within a preset time period from the at least one type of related parameters and then transmitting the at least two parameters to the bedside monitor;

the bedside monitor is used for performing correlation processing on the at least two parameters to obtain the correlation measurement and presenting the correlation measurement.
The system of claim 29 or 31, wherein the system further comprises: a central station in communication with the at least one wearable device;

the wearable device is used for extracting at least two corresponding parameters within a preset time period from the at least one type of related parameters and then transmitting the at least two parameters to the central station;

the central station is used for carrying out correlation processing on the at least two parameters to obtain the correlation measurement and presenting the correlation measurement.
The system of claim 29, wherein the system further comprises: a bedside monitor in communication with the at least one wearable device;

the wearable device is further configured to perform correlation processing based on the at least two corresponding parameters within the preset time period to obtain correlation metrics, and then transmit the correlation metrics to the bedside monitor;

the bedside monitor is configured to present the correlation metric.
The system of claim 29 or 33, wherein the system further comprises: a central station in communication with the at least one wearable device;

the wearable device is further configured to perform correlation processing based on the at least two corresponding parameters within the preset time period to obtain correlation metrics, and then transmit the correlation metrics to the central station;

the central station is configured to present the relevance metric.
The system of claim 29, wherein,

the wearable device is specifically configured to obtain a quantitative index related to the correlation metric based on the at least two corresponding parameters within the preset time period; and obtaining a graphical index related to the correlation metric based on the corresponding at least two parameters in the preset time period.
The system of claim 29, wherein,

the wearable device is specifically used for acquiring the human body state time parameter as the at least one type of relevant parameter; and the combination of (a) and (b),

extracting at least two corresponding time parameters within a preset time period from the human body state time parameters to serve as the at least two parameters; and performing correlation processing on the at least two time parameters extracted in the preset time period to obtain a quantitative index related to the correlation measurement.
The system of claim 29, wherein,

the wearable device is specifically configured to extract at least two motion parameters corresponding to a preset time period from the motion parameters, use the at least two motion parameters as the at least two parameters, and perform correlation processing on the at least two motion parameters extracted within the preset time period to obtain the correlation metric.
The system of claim 36, wherein the human state time parameter comprises a motion time parameter;

the at least one wearable device is further specifically configured to acquire at least one motion signal of the patient; extracting time domain characteristics or frequency domain characteristics of the at least one motion signal to obtain motion characteristics; and acquiring at least two time parameters representing at least two dimension statistics of the motion time parameters in the preset time period based on the motion characteristics, wherein the at least two time parameters are used as the at least two parameters.
The system of claim 36, wherein the human state time parameters include an exercise time parameter and a sleep time parameter;

the at least one wearable device is further specifically configured to acquire at least one motion signal of the patient; extracting time domain characteristics or frequency domain characteristics of the at least one motion signal to obtain motion characteristics; acquiring at least one motion time parameter representing at least one dimension statistic of the motion time parameter in the preset time period based on the motion characteristics; acquiring a sleep time parameter of the patient within the preset time period; and taking the sleep time parameter and the at least one motion time parameter as the at least two time parameters.
The system of claim 35, wherein the at least two types of parameters include at least one of:

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

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

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

the wearable device is further specifically configured to obtain a movement time based on the movement characteristics; counting the motion quantity parameter in the preset time period based on the at least one motion signal; determining the time of leaving the bed according to the exercise quantity parameter, a preset rest threshold value and the exercise time; determining the time of lying in bed according to the preset time period and the time of leaving the bed; and taking any at least two combinations of the bed leaving time, the exercise time, the preset time period and the bed lying time as the at least two time parameters of the human body state time parameters, and taking the at least two time parameters as the at least two parameters.
The system of claim 44, wherein,

the wearable device is further specifically used for acquiring a preset time characteristic threshold in real time; and when the motion characteristic is larger than the preset time characteristic threshold value, determining the motion state, and recording the duration of the motion state to obtain the motion time.
The system of claim 45, wherein,

the wearable device is further configured to receive the bed leaving time and the bed lying time monitored by the transmission of the bed side sensor or the bed-mounted sensor after obtaining the exercise time based on the exercise characteristics and before taking any at least two combinations of the bed leaving time, the exercise time, the preset time period and the bed lying time as the at least two time-related parameters of the human body state time parameters.
The system of claim 29, wherein,

the wearable device is specifically used for acquiring a preset correlation algorithm; and calculating the correlation of at least two corresponding parameters in the preset time period by adopting the preset correlation algorithm to obtain the correlation measurement.
The system of claim 35, wherein,

presenting the relevance metric in at least one of:

sequentially refreshing and displaying the quantitative indexes about the correlation measurement obtained at different moments along with the time change;

the graphical indexes related to the correlation measurement obtained at different moments are sequentially refreshed and displayed along with the time change;

constructing a coordinate system which changes along time, marking quantitative indexes which correspond to different moments and are related to correlation measurement in the coordinate system which changes along time, and forming a change trend graph of the quantitative indexes; and the combination of (a) and (b),

and constructing a time-varying coordinate system, marking graphical indexes related to the correlation measurement corresponding to different moments in the time-varying coordinate system, and forming a variation trend graph of the graphical indexes.
An apparatus for assessing the recovery status of a patient in a hospital, the apparatus comprising:

the acquisition part is configured to acquire at least one type of related parameters of human body state time parameters, motion quantity parameters and physiological parameters;

the extraction part is configured to extract at least two corresponding parameters in a preset time period from the at least one type of related parameters;

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

the acquisition part is specifically configured to acquire at least two parameters of the human body state time parameter, the motion quantity parameter and the physiological parameter; and the combination of (a) and (b),

and extracting at least two parameters respectively corresponding to the preset time period from the at least two types of parameters, wherein each type of related parameter correspondingly has at least one parameter.
The apparatus of claim 50, wherein,

the correlation part is specifically configured to obtain a quantitative index related to a correlation metric based on at least two corresponding parameters within the preset time period; and the combination of (a) and (b),

and obtaining a graphical index related to the correlation measurement based on the corresponding at least two parameters in the preset time period.
The apparatus of claim 49, wherein,

the acquisition part is specifically configured to acquire the human body state time parameter as the at least one type of related parameter; and the combination of (a) and (b),

and extracting at least two corresponding time parameters within a preset time period from the human body state time parameters to serve 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 of claim 49, wherein,

the acquisition part is specifically configured to acquire the motion amount parameter as the at least one type of related parameter; and extracting at least two corresponding motion quantity parameters within a preset time period from the motion quantity parameters to serve as the at least two parameters.
The apparatus of claim 54, wherein,

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

the acquisition section is further specifically configured to acquire at least one motion signal of the patient; extracting time domain characteristics or frequency domain characteristics of the at least one motion signal to obtain motion characteristics; and acquiring at least two time parameters representing at least two dimension statistics of the motion time parameters in the preset time period based on the motion characteristics, wherein the at least two time parameters are used as the at least two parameters.
The apparatus of claim 52, wherein the human state time parameters include an exercise time parameter and a sleep time parameter;

the acquiring part is further specifically configured to acquire at least one motion signal of the patient, and extract a time domain feature or a frequency domain feature of the at least one motion signal to obtain a motion feature; acquiring at least one motion time parameter representing at least one dimension statistic of the motion time parameter in the preset time period based on the motion characteristics; acquiring sleep time parameters of the patient; and taking the sleep time parameter and the at least one motion time parameter as the at least two time parameters.
The apparatus of claim 50, wherein,

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

the acquisition section is further specifically configured to acquire at least one motion signal of the patient; and counting the human body state time parameter and the motion quantity parameter in the preset time period based on the at least one motion signal.
The apparatus according to claim 58, wherein when the at least two types of parameters include the human state time parameter and the physiological parameter;

the acquisition section is further specifically configured to acquire at least one motion signal of the patient; counting the human body state time parameter in the preset time period based on the at least one motion signal; and acquiring the physiological parameter through a biological characteristic sensor.
The apparatus of any one of claims 56, 57, 59, or 60,

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

the acquisition part is further specifically configured to obtain a movement time based on the movement characteristics; counting the motion quantity parameter in the preset time period based on the at least one motion signal; determining the time of leaving the bed according to the exercise quantity parameter, a preset rest threshold value and the exercise time; determining the time for lying in bed according to the preset time period and the time for leaving the bed; and any at least two combinations of the bed leaving time, the exercise time, the preset time period and the bed lying time are used as the at least two time parameters of the human body state time parameters and used as the at least two parameters.
The apparatus according to claim 62, wherein,

the acquisition part is also specifically configured to acquire a preset time characteristic threshold in real time; and when the motion characteristic is larger than the preset time characteristic threshold value, determining the motion state, and recording the duration of the motion state to obtain the motion time.
The apparatus of claim 63, wherein the apparatus further comprises: a receiving section;

the receiving part is configured to receive the bed leaving time and the bed lying time which are monitored by a bedside sensor in a transmission mode after obtaining the exercise time based on the exercise characteristics and before taking any at least two combinations of the bed leaving time, the exercise time, the preset time period and the bed lying time as the at least two time parameters in the human body state time parameters.
The apparatus of claim 49, wherein,

the correlation part is specifically configured to obtain a preset correlation algorithm; and calculating the correlation of at least two corresponding parameters in the preset time period by adopting the preset correlation algorithm to obtain the correlation measurement.
The apparatus of claim 66, wherein,

the correlation metric is output and displayed on a monitoring device, and comprises a quantitative index and/or a graphical index.
The apparatus of claim 49, wherein the apparatus further comprises: a presentation section;

the presenting part is configured to present the correlation metric after performing correlation processing based on at least two corresponding parameters within a preset time period to obtain the correlation metric, wherein the manner of presenting the correlation metric at least adopts one of the following manners: sequentially refreshing and displaying the quantitative indexes about the correlation measurement obtained at different moments along with the time change; the graphical indexes related to the correlation measurement obtained at different moments are sequentially refreshed and displayed along with the time change; constructing a coordinate system which changes along time, marking quantitative indexes which correspond to different moments and are related to correlation measurement in the coordinate system which changes along time, and forming a change trend graph of the quantitative indexes; and constructing a time-varying coordinate system, marking graphical indexes related to the correlation measurement corresponding to different moments in the time-varying coordinate system, and forming a variation trend graph of the graphical indexes.
The apparatus of claim 49, wherein the apparatus further comprises: a transmission section;

the sending part is configured to perform correlation processing based on at least two corresponding parameters in a preset time period to obtain correlation measurement, and then transmit the correlation measurement 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 apparatus for assessing the recovery status of a patient in a hospital, the apparatus comprising:

the acquisition part is configured to acquire a first time parameter and a second time parameter of a human body state time parameter corresponding to a preset time period; the first time parameter and the second time parameter respectively represent time parameters of at least one time dimension in human body state time parameters;

a correlation part 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 assess the recovery status of the patient.
The apparatus according to claim 69, wherein the human state time parameter comprises a motion time parameter;

the acquisition part is specifically configured to acquire at least one motion signal of the patient within the preset time period; extracting time domain characteristics or frequency domain characteristics of the at least one motion signal to obtain motion characteristics; and acquiring the first time parameter and the second time parameter which represent the statistics of the motion time parameter in the preset time period based on the motion characteristics.
The apparatus of claim 69, wherein the body state time parameters include an exercise time parameter and a sleep time parameter;

the acquisition part is specifically configured to acquire a motion signal of the patient within the preset time period; extracting time domain characteristics or frequency domain characteristics of the motion signal to obtain first motion characteristics; acquiring a motion time parameter representing the motion time parameter in the preset time period based on the first motion characteristic; acquiring a sleep time parameter of the patient within the preset time period; taking the sleep time parameter and the one exercise time parameter as the first time parameter and the second time parameter.
The apparatus of claim 70, wherein,

the acquisition part is further specifically configured to determine a movement time according to the movement characteristics; counting the motion quantity parameter in the preset time period based on the at least one motion signal; determining the time of leaving the bed according to the exercise quantity parameter, a preset rest threshold value and the exercise time; determining the time for lying in bed according to the preset time period and the time for leaving the bed; and selecting the first time parameter and the second time parameter from the exercise time, the bed leaving time, the preset time period and the bed lying time which characterize the exercise time parameter.
The apparatus of claim 72, wherein the apparatus further comprises: a receiving section;

the receiving part is configured to receive the bed leaving time and the bed lying time which are monitored by the transmission of the bed side sensor after the time domain feature or the frequency domain feature of the at least one motion signal is extracted to obtain the motion feature and before the first time parameter and the second time parameter are selected from the motion time, the bed leaving time, the preset time period and the bed lying time.
The apparatus of claim 72,

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

the movement time and the bed exit time;

the movement time and the preset time period;

the bed leaving time and the preset time period;

the exercise time and the bed rest time;

the time out of bed and the time in bed;

the bed-lying time and the preset time period.
The apparatus of claim 69, wherein,

the correlation part is specifically configured to obtain a preset correlation algorithm; and calculating the correlation between the first time parameter and the second time parameter by adopting the preset correlation algorithm to obtain the correlation measurement.
The apparatus of claim 75, wherein the apparatus further comprises: a presentation section;

the presenting part is configured to output and display the correlation metric on the monitoring equipment, and the correlation metric comprises a quantitative index and/or a graphical index.
An apparatus for assessing the recovery status of a patient in a hospital, the apparatus comprising:

the memory is used for storing an evaluation instruction capable of executing the recovery state of the patient in the hospital;

a processor for implementing the method of any one of claims 1 to 8 or the method of any one of claims 9 to 28 when executing the executable instructions for assessing the recovery status of a patient in a hospital stored in the memory.
A computer readable storage medium having stored therein executable instructions for assessing a patient's in-hospital recovery status for causing a processor to perform the method of any one of claims 1 to 8 or the method of any one of claims 9 to 28 when executed.