CN111415746A - Physical function evaluation model generation method, physical function evaluation method, and physical function evaluation apparatus - Google Patents
Physical function evaluation model generation method, physical function evaluation method, and physical function evaluation apparatus Download PDFInfo
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Abstract
The invention provides a generation method of a physical function evaluation model, which comprises the following steps: collecting sensor data involved in action switching of a user under an evaluation sample set; extracting features of the sensor data; evaluating the physical function of the user by adopting a preset evaluation table to obtain a physical function score; and analyzing the correlation degree of the sensor data characteristics involved in the action switching of the user and the body function score to obtain an evaluation model. The embodiment of the invention carries out quantitative supplement on the basis of the existing assessment of the physical function of the hemiplegic patient, provides objective and quantitative data support for clinical treatment, and improves the effectiveness and the scientificity of the clinical treatment. Meanwhile, the evaluation model is optimized by providing a test of the evaluation model, so that the evaluation model can be closer to objective and actual data, and a more accurate and scientific basis is provided for the subsequent evaluation of the human body function; even the evaluation of the physical functions of healthy people can be performed with good results.
Description
Technical Field
The invention relates to the technical field of rehabilitation, in particular to a body function evaluation model generation and evaluation method and evaluation equipment.
Background
During the clinical rehabilitation treatment of patients with hemiplegia and paraplegia, therapists often need to periodically evaluate the physical state of the patients, and the evaluation items include but are not limited to: balance function, proprioception, core stabilization, motion control, muscle strength, articulation, and the like.
Taking the evaluation of the Balance function of hemiplegic patients as an example, currently, the mainstream practice in the industry is to use evaluation scales such as Berg Balance Scale (BBS) and Fugl-Meyer Balance function Scale (fm.b).
However, the above-mentioned method has obvious defects, that is, the evaluation result using the evaluation scale is greatly influenced by the subjective feeling of the therapist, and the evaluation results of different therapists may slightly differ for the same patient, and most of the evaluation results are qualitative conclusions, and objective and quantitative evaluation results cannot be obtained.
Disclosure of Invention
The embodiment of the invention aims to provide a body function evaluation model generation and evaluation method and evaluation equipment, so as to provide a technical scheme which is safe and convenient to operate and objective and quantitative in result, and is applied to the evaluation of the body function of a hemiplegic patient, so that a quantitative evaluation result is output.
The technical scheme provided by the invention is as follows:
in a first aspect, an embodiment of the present invention provides a method for generating a physical function assessment model, where the method includes:
collecting sensor data involved in action switching of a user under an evaluation sample set;
extracting features of the sensor data;
evaluating the physical function of the user by adopting a preset evaluation table to obtain a physical function score;
and analyzing the correlation degree of the sensor data characteristics involved in the action switching of the user and the body function score to obtain an evaluation model.
Preferably, the extracting the sensor data features specifically comprises the steps of:
and carrying out frequency domain transformation on a time domain signal t formed by a set of the sensor data arranged in time sequence to obtain a frequency spectrum g of the signal, and taking the frequency spectrum g as the characteristic of the sensor data.
Preferably, the analyzing the correlation between the sensor data characteristics involved in the user action switching and the physical function score to obtain the evaluation model comprises the following steps:
obtaining the amplitudes of the sets of sensor data on the frequency components according to the frequency spectrum g, and recording the frequency component sets as { g1, g2, …, gn }, and the amplitude sets of the sensor data on the frequency components as { vx1, vx2, …, vxn }, that is, the amplitudes of the sets of the sensor data on the frequency component g1 are vx1, the amplitudes of the sets of the sensor data on the frequency component g2 are vx2, …, and the amplitudes of the sets of the sensor data on the frequency component gn are vxn; recording the physical function score of the user as y and the score value as vy;
and obtaining the evaluation model by taking the amplitude set { g1, g2, …, gn } of the sensor data on each frequency component as an independent variable and a multidimensional equation which is fitted by taking the body function score y as a dependent variable as a correlation.
In a second aspect, an embodiment of the present invention provides a method for evaluating a physical function evaluation model, where the method includes:
collecting sensor data when a user performs action switching under a test sample set;
extracting features of the sensor data;
inputting the features into a pre-generated evaluation model to obtain a physical function score output by the evaluation model S0;
evaluating the physical function of the user by adopting a preset evaluation table to obtain a physical function score S1;
if the levels of S0 and S1 are the same levels in the pre-divided capability levels, the evaluation result of the evaluation model is hit.
Preferably, the method further comprises: and calculating the evaluation hit rate of the evaluation model, wherein the evaluation hit rate is the proportion of the number of people in the test sample set which are hit by the evaluation result of the testers to the total number of the testers.
Preferably, the method further comprises: and if the evaluation hit rate calculated in the pre-generated evaluation model is equal to or higher than a preset hit rate threshold value, obtaining a final evaluation model by the pre-generated evaluation model.
In a third aspect, an embodiment of the present invention further provides an evaluation apparatus, where the evaluation apparatus includes:
one or more processors;
one or more memories;
one or more modules stored in a memory and capable of being executed by at least one of the one or more processors to perform the steps of the method of generating a physical function assessment model according to the first aspect.
In a fourth aspect, an embodiment of the present invention further provides an evaluation apparatus, where the evaluation apparatus includes:
one or more processors;
one or more memories;
one or more modules stored in a memory and capable of being executed by at least one of the one or more processors to perform the steps of the method of evaluating a physical function evaluation model according to the second aspect.
In a fifth aspect, embodiments of the present invention also provide a physical function assessment apparatus, including:
the data acquisition modules are used for acquiring sensor data when the user actions are switched;
a central processing module;
a computer readable storage medium for storing one or more computer programs which, when executed by the central processing module upon input of the sensor data, implement the method according to the first aspect.
In a sixth aspect, embodiments of the present invention also provide a physical function assessment apparatus, including:
the data acquisition modules are used for acquiring sensor data when the user actions are switched;
a central processing module;
a computer readable storage medium for storing one or more computer programs which, when executed by the central processing module upon input of the sensor data, implement the method according to the second aspect.
Through the implementation of the aspects, the embodiment of the invention carries out quantitative supplement on the basis of the evaluation of the body function of the existing hemiplegic patient, provides objective and quantitative data support for clinical treatment, and improves the effectiveness and the scientificity of the clinical treatment. Meanwhile, the evaluation model is optimized by providing a test of the evaluation model, so that the evaluation model can be closer to objective and actual data, and a more accurate and scientific basis is provided for the subsequent evaluation of the human body function; even the evaluation of the physical functions of healthy people can be performed with good results.
Drawings
The above-mentioned characteristics, technical features, advantages and implementations of the asynchronous system implementation method, evaluation device and storage medium will be further explained in a clear and easy manner with reference to the accompanying drawings, which illustrate preferred embodiments.
FIG. 1 is a schematic diagram of an evaluation device in an embodiment of the invention;
FIG. 2 is a schematic diagram of another evaluation apparatus in an embodiment of the present invention;
FIG. 3 is a schematic diagram of an evaluation model generation according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of an evaluation model generation flow according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of an evaluation model evaluation flow according to an embodiment of the present invention;
FIG. 6 is a diagram illustrating an application scenario of an evaluation model according to an embodiment of the present invention;
fig. 7 is a schematic structural view of a physical function evaluation apparatus according to an embodiment of the present invention;
fig. 8 is a schematic structural view of another physical function assessment apparatus according to an embodiment of the present invention.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following description will be made with reference to the accompanying drawings. It is obvious that the drawings in the following description are only some examples of the invention, and that for a person skilled in the art, other drawings and embodiments can be derived from them without inventive effort.
For the sake of simplicity, the drawings only schematically show the parts relevant to the present invention, and they do not represent the actual structure as a product. In addition, in order to make the drawings concise and understandable, components having the same structure or function in some of the drawings are only schematically illustrated or only labeled. In this document, "one" means not only "only one" but also a case of "more than one".
The method, the evaluation equipment and the evaluation method provided by the evaluation equipment provided by the embodiment of the invention supplement the existing body function evaluation means of the hemiplegic patient, add a new objective quantitative data support for clinical treatment, and improve the effectiveness and scientificity of the clinical treatment, the body function of the embodiment of the invention mainly refers to the related functions related to the human body motion system, wherein the human body motion system consists of a central nervous system, a peripheral nervous system, a neuromuscular junction, bones, skeletal muscles, joints, heart and lung and a metabolic support system; the body functions are specifically as follows: balance ability, core stability, muscle strength, cardiopulmonary function, and the like. In addition, besides the physical functions of the hemiplegic patient, the method, the evaluation device and the evaluation method provided by the evaluation device are also suitable for the evaluation of the physical functions of other patients with motor dysfunction, namely, the method, the evaluation device and the evaluation method are not only suitable for the hemiplegic patient, but also suitable for other patients with motor dysfunction, and are suitable for the measurement of a plurality of body functions of the patients
Furthermore, the technical problem to be solved by the technical solution of the method, the evaluation device and the evaluation method provided by the evaluation device provided by the embodiment of the present invention is derived from the problem of generating a physical function evaluation model for patients with hemiplegia or paraplegia, but is also applicable to ordinary people with normal physical states for generating a physical function evaluation model for ordinary people. The evaluation and evaluation equipment provided by the invention is used by ordinary people to output an evaluation result and finish one evaluation, which is equivalent to one physical examination.
As shown in fig. 1 and 2, the method for generating a physical performance assessment model according to an embodiment of the present invention can be performed by using an assessment apparatus, which includes, in addition to the mechanical body of the assessment apparatus shown in fig. 1, a control system shown in fig. 2, the control system including, in addition to a central processing module, a storage module, a plurality of sensors for collecting data, and other external devices, such as a display, a printer, etc.;
in some embodiments, the central processing module may be integrated into an evaluation device, electrically connected to the sensor;
however, in other embodiments, the evaluation device may be external to the evaluation device, and the evaluation device may include several processors, several memory modules, or the several memory modules are external to the evaluation device.
In some embodiments, the mechanical body is designed to have a certain structure, so that a user can be assisted in completing switching actions such as 'sitting and standing', the switching actions are not limited to switching of sitting and standing, and other actions can be performed.
Each module of the control system is fixedly installed with the mechanical body through a certain mechanical interface; the sensors are fixedly installed with the machine body through certain mechanical interfaces; the control system comprises a power management module, a central processing module, a data acquisition module such as a plurality of sensors and a display module, and all the modules are in communication connection and electric connection; the sensors are in communication connection and electric connection with the control system; and other external equipment is in communication connection and electric connection with the control system.
In dependence on the above evaluation apparatus, an embodiment of the present invention provides a method for generating a physical function evaluation model, which is characterized by comprising:
collecting sensor data involved in action switching of a user under an evaluation sample set;
extracting features of the sensor data;
evaluating the physical function of the user by adopting a preset evaluation table to obtain a physical function score;
and analyzing the correlation degree of the sensor data characteristics involved in the action switching of the user and the body function score to obtain an evaluation model.
In a specific embodiment of the present invention, the action switching of the user is "sit-stand switching" as an example, and the user completes the "sit-stand" switching action.
The evaluation model generated by the evaluation model generation method provided by the embodiment of the invention runs in a processor of a control system of the evaluation device of the embodiment of the invention, and the evaluation model outputs evaluation results which relate to one or more body functions, such as: balance ability, core stability, muscle strength, cardiopulmonary function, and the like. It can also be presented to the user by means of a display module of the inventive evaluation device.
The evaluation equipment of the embodiment of the invention can also generate a detailed evaluation result report, and the evaluation report can be printed and output by connecting with external printer evaluation equipment.
In several embodiments of the present invention, the sensor placement location and the key data collected can be described as follows:
1) the handrail tension sensors are arranged at the handrails at the two sides, and 2 handrail tension sensors are used for acquiring the tension of the upper limbs at the two sides in the squatting process of the user;
2) the sole pressure sensors are arranged on the pedals at the two sides, and the number of the sole pressure sensors is 2, and the sole pressure sensors are used for acquiring dynamic balance state data of a user in the squatting process.
3) And the limb posture sensors are arranged on the big lower limb, the small lower limb and the trunk at two sides, are 5 in total and are used for acquiring data such as the moving angles and speeds of the hip joint and the knee joint of the two lower limbs in the squatting process of the user.
4) The swing arm position sensor is arranged at the swing arm and is 1 in total, and is used for collecting the completion time of single squatting and rising actions of the user.
The user completes action switching, such as 'sitting and standing' switching action, by means of the evaluation equipment provided by the embodiment of the invention, the control system receives and processes each key data collected by the sensor, the key data are input into an evaluation model (the evaluation model is generated by the evaluation model provided by the embodiment of the invention) operated in the system, the evaluation model outputs an evaluation result, and the evaluation result is displayed to the user through the display module.
It should be noted that the embodiments of the present invention are not limited to the above-mentioned sensor arrangement manner, or the design manner of the evaluation device, or the type of user action switching. In the field of human rehabilitation, it is within the scope of the present invention to use all rehabilitation devices as long as they can provide human body function data for physical rehabilitation training or rehabilitation assistance, and the data of human body functions obtained by sensors or other means as input of evaluation data of the body functions.
As shown in fig. 3, in an embodiment of the present invention, a mature assessment model can be regarded as a black box, which inputs the characteristics of the key data collected by the assessment apparatus provided by the present invention, and outputs the assessment result of the physical performance index corresponding to the assessment model.
The evaluation models can be various, different evaluation models have different functions, and some of the different evaluation models and their functions are described as follows:
"[ tension of armrest, pressure of sole ] - [ balance function, muscle force ]" evaluation model: evaluating the balance function and muscle strength level of the user based on the data characteristics of the armrest tension and the sole pressure of the sitting and standing switching action of the user;
"[ tension of arm, pressure of sole ] - [ balance function ]" -evaluation model: evaluating the balance function of the user based on the data characteristics of the armrest tension and the sole pressure of the sitting and standing switching action of the user;
"[ arm tension ] - [ balance function, muscle strength, proprioception ]" evaluation model: evaluating a balance function, muscle strength level, and proprioception level of the user based on data characteristic of armrest tension of the user's sit-stand switching action;
various evaluation models, and so forth, not to name a few. Namely: as long as the input or output changes, the model and the function of the model change, namely the other model;
the evaluation model is operated in the form of data calculation in the processor of the control system of the evaluation device of the embodiment of the present invention, or in the evaluation device electrically connected to the evaluation device, when the evaluation function of the evaluation device provided by the embodiment of the present invention is to be changed, it is only necessary to change the evaluation model in the control system of the evaluation device provided by the present invention to the evaluation model of the required function. There are various evaluation models, but the generation methods of the evaluation models are all consistent.
For ease of understanding, the following embodiments of the present invention will be described with reference to the "[ handrail tension ] - [ balance function ]" evaluation model as an example;
evaluation model the evaluation model generated by the evaluation model generation method provided by the embodiment of the invention is generated in two stages: a model generation phase and a model evaluation phase.
Under one embodiment of the present invention, an evaluation model generation method is as follows: ,
collecting sensor data involved in action switching of a user under an evaluation sample set;
extracting features of the sensor data;
evaluating the physical function of the user by adopting a preset evaluation table to obtain a physical function score;
and analyzing the correlation degree of the sensor data characteristics involved in the action switching of the user and the body function score to obtain an evaluation model.
Preferably, the correlation between the data characteristic of the handrail tension sensor of the action switching of the user and the balance function score is analyzed, and the method comprises the following steps:
obtaining the amplitude of the handrail tension sensor data set on each frequency component according to the frequency spectrum g, recording the frequency component diversity as { g1, g2, …, gn }, recording the set of the amplitude of the handrail tension sensor data on each frequency component as { vx1, vx2, …, vxn }, that is, the amplitude of the handrail tension sensor data set on a frequency component g1 is vx1, the amplitude of the handrail tension sensor data set on a frequency component g2 is vx2, and so on; recording the balance function score of the subject as y and the score value as vy;
and (3) fitting a multidimensional equation by taking the frequency forming diversity { g1, g2, …, gn } as an independent variable and taking the balance function score y as a dependent variable to obtain the correlation degree to be solved, namely obtaining the [ handrail tension ] - [ balance function ] "evaluation model.
In further embodiments, the following method may be used to extract the sensor data features:
time-domain signal t formed for a set of time-sequenced sensor data, or spectrum g of t
1) Taking the maximum value of t;
2) taking the minimum value of t;
3) taking the variance of t;
4) taking the average value of t;
5) taking the average value of the amplitude of each component of g;
and so on.
The above-described single or plural combinations are employed as characteristic data required for the embodiments of the present invention.
The embodiment of the invention also provides an evaluation method of the physical function evaluation model, which comprises the following steps:
collecting sensor data when a user performs action switching under a test sample set;
extracting features of the sensor data;
inputting the features into a pre-generated evaluation model to obtain a physical function score output by the evaluation model S0;
evaluating the physical function of the user by adopting a preset evaluation table to obtain a physical function score S1;
if the levels of S0 and S1 are the same levels in the pre-divided capability levels, the evaluation result of the evaluation model is hit.
As shown in fig. 4, taking the balance ability evaluation as an example, the implementation is as follows:
determining an evaluation sample set, wherein a user under the evaluation sample set is a tested patient or a common non-patient;
collecting handrail tension sensor data when a user performs switching actions under a user sample set, and extracting characteristics of the sensor data, wherein the action times are not limited, and the sample numbers are different when the times are different, so that the models have different qualities, and reasonable sample numbers can be collected according to empirical data;
evaluating the balance function of the user by adopting a Berg Balance Scale (BBS) and a Fugl-Meyer balance function scale (FM.B), wherein the BBS scale and the FM.B scale are traditional evaluation means of the balance function, and corresponding traditional evaluation means in the industry can be adopted for other physical function indexes to obtain the balance function score of the user;
and analyzing the correlation between the data characteristics of the armrest tension sensor of the sitting and standing switching action of the user and the balance function score of the subject, namely an evaluation model of ' armrest tension ' -balance function '.
Wherein,
the method for extracting the data characteristics of the handrail tension sensor specifically comprises the following steps:
and performing frequency domain transformation on a time domain signal t formed by a handrail tension sensor data set arranged in a time sequence to obtain a frequency spectrum g of the signal, and taking the frequency spectrum g as the characteristic of the handrail tension sensor data.
As shown in fig. 5, another embodiment is embodied as follows:
determining a test sample set, and acquiring data of the handrail tension sensor when a user, namely a tester, in the test set performs switching actions (the action times are not limited, and if the times are different, the sample numbers are different, and the evaluation results may be different);
extracting the characteristics of the sensor data, inputting the characteristics into a pre-generated evaluation model, and obtaining a physical function score output by the model S0;
taking the balance ability as an example, aiming at all testers, adopting a Berg Balance Scale (BBS) and a Fugl-Meyer balance function scale (FM.B) to evaluate the balance function of a patient, wherein the BBS scale and the FM.B scale are traditional evaluation means, and adopting corresponding industry traditional evaluation means for other physical function indexes to obtain a balance function score S1 of the testers;
reasonably dividing the scores of the balance function indexes into a plurality of grades;
preferably, the dividing method of the balance function is as follows:
assuming that the balance function is fully divided into 100, if the balance function is divided into 5 grades on average, the score range of each grade is: [0,20 ], [20,40 ], [40,60 ], [60,80 ], [80,100 ];
comparing the grades of S0 and S1, if the grades are consistent, the evaluation result of the evaluation model is called as hit.
The evaluation hit rate is used to evaluate the quality of the evaluation model. The definition of the evaluation hit rate of the evaluation model is: the ratio of the number of hits in the test subject to the total number of test subjects was evaluated.
Further, the method further comprises: a model of the degree of maturity is generated,
if the evaluation hit rate calculated in the model evaluation stage of the evaluation model formed in the model generation stage is equal to or higher than an expected index which can be set artificially, obtaining a final evaluation model;
otherwise, the generation and the evaluation of the evaluation model are repeated, a new evaluation model is generated, the quality of the model is evaluated again until the model reaches the standard, and the like.
Through the implementation of the aspects, the embodiment of the invention carries out quantitative supplement on the basis of the evaluation of the body function of the existing hemiplegic patient, provides objective and quantitative data support for clinical treatment, and improves the effectiveness and the scientificity of the clinical treatment. Meanwhile, the evaluation model is optimized by providing a test of the evaluation model, so that the evaluation model can be closer to objective and actual data, and a more accurate and scientific basis is provided for the subsequent evaluation of the human body function; even the evaluation of the physical functions of healthy people can be performed with good results.
Based on the method and the evaluation device provided by the invention, an application scene can be derived to provide home rehabilitation service, as shown in fig. 6.
The service can be applied to the scenes of special rehabilitation hospitals, comprehensive hospital rehabilitation departments, community rehabilitation institutions, home rehabilitation and the like. If a new evaluation item is set in a hospital, the item evaluates the body function score of the patient by enabling the hemiplegic patient to complete multiple sitting-standing switching actions without using an evaluation scale, so that the evaluation result is more objective and quantized, and the burden of a rehabilitation therapist is reduced; the system and the method have the advantages that simple and rapid body function index assessment is achieved in a community or family scene, assessment results can be sent to remote hospitals and doctors, long-term tracking and continuous rehabilitation of patients after discharge are facilitated, and overall rehabilitation efficiency and hospital rehabilitation services are improved.
Fig. 7 is a schematic entity structure diagram of an evaluation device according to an embodiment of the present invention, where the evaluation device is installed in a third-party device, such as a mobile terminal, a portable computer, an IPAD, and as shown in fig. 7, the server may include: a processor (processor)610, a communication Interface (Communications Interface)620, a memory (memory)630 and a communication bus 640, wherein the processor 610, the communication Interface 620 and the memory 630 communicate with each other via the communication bus 640. The processor 610 may call logic instructions in the memory 630 to perform the following method: collecting sensor data involved in action switching of a user under an evaluation sample set; extracting features of the sensor data; evaluating the physical function of the user by adopting a preset evaluation table to obtain a physical function score; and analyzing the correlation degree of the sensor data characteristics involved in the action switching of the user and the body function score to obtain an evaluation model. A communication bus 640 is a circuit that connects the described elements and enables transmission between the elements. For example, the processor 610 receives commands from other elements through the communication bus 640, decrypts the received commands, and performs calculations or data processing according to the decrypted commands. The memory 630 may include program modules such as a kernel (kernel), middleware (middleware), an Application Programming Interface (API), and an Application program. The program modules may be comprised of software, firmware or hardware, or at least two of the same. The communication interface 620 connects the evaluation device with other network devices, clients, mobile devices, networks. For example, the communication interface 620 may be connected to a network by wire or wirelessly to connect to external other network devices or user devices. The wireless communication may include at least one of: wireless fidelity (WiFi), Bluetooth (BT), Near Field Communication (NFC), Global Positioning Satellite (GPS) and cellular communications, among others. The wired communication may include at least one of: universal Serial Bus (USB), high-definition multimedia interface (HDMI), asynchronous transfer standard interface (RS-232), and the like. The network may be a telecommunications network and a communications network. The communication network may be a computer network, the internet of things, a telephone network. The evaluation device may be connected to the network via a communication interface 620, and the protocol by which the evaluation device communicates with other network devices may be supported by at least one of an application, an Application Programming Interface (API), middleware, a kernel, and the communication interface 620.
Fig. 8 is a schematic entity structure diagram of an evaluation device according to an embodiment of the present invention, where the evaluation device is installed in a rental server, and as shown in fig. 8, the server may include: a processor (processor)910, a communication Interface (Communications Interface)920, a memory (memory)930, and a communication bus 940, wherein the processor 910, the communication Interface 920, and the memory 930 communicate with each other via the communication bus 940. Processor 910 may invoke logic instructions in memory 930 to perform the following method: collecting sensor data when a user performs action switching under a test sample set; extracting features of the sensor data; inputting the features into a pre-generated evaluation model to obtain a physical function score output by the evaluation model S0; evaluating the physical function of the user by adopting a preset evaluation table to obtain a physical function score S1; if the levels of S0 and S1 are the same levels in the pre-divided capability levels, the evaluation result of the evaluation model is hit. A communication bus 940 is a circuit that connects the described elements and enables transmission between the elements. For example, the processor 910 receives commands from other elements through the communication bus 940, decrypts the received commands, and performs calculations or data processing according to the decrypted commands. The memory 930 may include program modules such as a kernel (kernel), middleware (middleware), an Application Programming Interface (API), and an Application program. The program modules may be comprised of software, firmware or hardware, or at least two of the same. The communication interface 920 connects the evaluation device with other network devices, clients, mobile devices, networks. For example, the communication interface 920 may be connected to a network by wire or wirelessly to connect to external other network devices or user devices. The wireless communication may include at least one of: wireless fidelity (WiFi), Bluetooth (BT), Near Field Communication (NFC), Global Positioning Satellite (GPS) and cellular communications, among others. The wired communication may include at least one of: universal Serial Bus (USB), high-definition multimedia interface (HDMI), asynchronous transfer standard interface (RS-232), and the like. The network may be a telecommunications network and a communications network. The communication network may be a computer network, the internet of things, a telephone network. The evaluation device may be connected to the network via a communication interface 920, and protocols by which the evaluation device communicates with other network devices may be supported by at least one of an application, an Application Programming Interface (API), middleware, a kernel, and the communication interface 920.
Further, an embodiment of the present invention discloses a physical function assessment apparatus, including: the data acquisition modules are used for acquiring sensor data when the user actions are switched; a central processing module; a computer-readable storage medium for storing one or more computer programs, which are executed by the central processing module when the sensor data is input, for example, comprising: collecting sensor data involved in action switching of a user under an evaluation sample set; extracting features of the sensor data; evaluating the physical function of the user by adopting a preset evaluation table to obtain a physical function score; and analyzing the correlation degree of the sensor data characteristics involved in the action switching of the user and the body function score to obtain an evaluation model.
Further, an embodiment of the present invention provides a physical function evaluation apparatus, including: the data acquisition modules are used for acquiring sensor data when the user actions are switched; a central processing module; a computer-readable storage medium for storing one or more computer programs, which are executed by the central processing module when the sensor data is input, for example, to implement: collecting sensor data when a user performs action switching under a test sample set; extracting features of the sensor data; inputting the features into a pre-generated evaluation model to obtain a physical function score output by the evaluation model S0; evaluating the physical function of the user by adopting a preset evaluation table to obtain a physical function score S1; if the levels of S0 and S1 are the same levels in the pre-divided capability levels, the evaluation result of the evaluation model is hit.
Those of ordinary skill in the art will understand that: in addition, the logic instructions in the memory may be implemented in the form of software functional units and may be stored in a computer readable storage medium when sold or used as a stand-alone product. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing an evaluation device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above described embodiments of the evaluation device are merely illustrative, wherein the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing an evaluation device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solution of the present invention, but not for limiting the same, and the above embodiments can be freely combined as required; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention. Without departing from the principle of the invention, several improvements and modifications can be made, and these improvements and modifications should also be construed as the scope of the invention.
Claims (10)
1. A method of generating a physical function assessment model, the method comprising:
collecting sensor data involved in action switching of a user under an evaluation sample set;
extracting features of the sensor data;
evaluating the physical function of the user by adopting a preset evaluation table to obtain a physical function score;
and analyzing the correlation degree of the sensor data characteristics involved in the action switching of the user and the body function score to obtain an evaluation model.
2. The method for generating a physical function assessment model according to claim 1, wherein said extracting sensor data features comprises in particular the steps of:
and carrying out frequency domain transformation on a time domain signal t formed by a set of the sensor data arranged in time sequence to obtain a frequency spectrum g of the signal, and taking the frequency spectrum g as the characteristic of the sensor data.
3. The method for generating a physical function assessment model according to claim 2, wherein the step of analyzing the correlation between the sensor data characteristics involved in the user action switching and the physical function score to obtain the assessment model comprises the following steps:
obtaining the amplitudes of the sets of sensor data on the frequency components according to the frequency spectrum g, and recording the frequency component sets as { g1, g2, …, gn }, and the amplitude sets of the sensor data on the frequency components as { vx1, vx2, …, vxn }, that is, the amplitudes of the sets of the sensor data on the frequency component g1 are vx1, the amplitudes of the sets of the sensor data on the frequency component g2 are vx2, …, and the amplitudes of the sets of the sensor data on the frequency component gn are vxn; recording the physical function score of the user as y and the score value as vy;
and obtaining the evaluation model by taking the amplitude set { g1, g2, …, gn } of the sensor data on each frequency component as an independent variable and a multidimensional equation which is fitted by taking the body function score y as a dependent variable as a correlation.
4. A method of evaluating a physical function evaluation model, the method comprising:
collecting sensor data when a user performs action switching under a test sample set;
extracting features of the sensor data;
inputting the features into a pre-generated evaluation model to obtain a physical function score output by the evaluation model S0;
evaluating the physical function of the user by adopting a preset evaluation table to obtain a physical function score S1;
if the levels of S0 and S1 are the same levels in the pre-divided capability levels, the evaluation result of the evaluation model is hit.
5. The method of evaluating a physical function evaluation model according to claim 4, further comprising: and calculating the evaluation hit rate of the evaluation model, wherein the evaluation hit rate is the proportion of the number of people in the test sample set which are hit by the evaluation result of the testers to the total number of the testers.
6. The method of evaluating a physical function evaluation model according to claim 5, further comprising: if the evaluation hit rate calculated in the pre-generated evaluation model is equal to or higher than a preset hit rate threshold value, the pre-generated evaluation model obtains a final evaluation model, otherwise, the evaluation model is optimized.
7. An evaluation apparatus, characterized in that the evaluation apparatus comprises:
one or more processors;
one or more memories;
one or more modules stored in a memory and capable of being executed by at least one of the one or more processors to perform the steps of the method of generating a physical function assessment model according to any one of claims 1 to 3.
8. An evaluation apparatus, characterized in that the evaluation apparatus comprises:
one or more processors;
one or more memories;
one or more modules stored in a memory and capable of being executed by at least one of the one or more processors to perform the steps of the assessment method of the physical function assessment model according to any one of claims 4 to 6.
9. A physical function evaluation apparatus characterized in that the evaluation apparatus comprises:
the data acquisition modules are used for acquiring sensor data when the user actions are switched;
a central processing module;
a computer readable storage medium storing one or more computer programs which, when executed by the central processing module upon input of the sensor data, implement the method according to any one of claims 1 to 3.
10. A physical function evaluation apparatus characterized in that the evaluation apparatus comprises:
the data acquisition modules are used for acquiring sensor data when the user actions are switched;
a central processing module;
computer-readable storage medium for storing one or more computer programs, which are executed by the central processing module when the sensor data are input, for implementing the method according to any one of claims 4 to 6.
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