WO2020223944A1

WO2020223944A1 - System and method for physiological function assessment

Info

Publication number: WO2020223944A1
Application number: PCT/CN2019/086117
Authority: WO
Inventors: 曹文明; 钟建奇; 曹桂涛
Original assignee: 深圳大学
Priority date: 2019-05-09
Filing date: 2019-05-09
Publication date: 2020-11-12

Abstract

Disclosed are a system and method for physiological function assessment. The system comprises a terminal device, a fog server, and a medical center. The system utilizes the terminal device to collect physiological function data of an assessed person, the fog server analyzes the physiological function data to produce a physiological function assessment result, and then the medical center analyzes the physiological function assessment result to produce a physiological health report and transmits to a client associated with the assessed person, thus completing the assessment of the physiological functions of the human body. Compared with the prior art, because fog servers are located at network edges, are widely distributed, have strong mobility, and can be deployed in homes, a user is allowed to complete an assessment of the physiological functions of the human body without leaving home; in addition, owing to the low latency of the fog servers, the response time of a physical function assessment can be increased, thus allowing the physiological function assessment to be performed efficiently and accurately.

Description

Physiological function evaluation system and method

Technical field

The present invention relates to the field of computer technology, in particular to a physiological function evaluation system and method.

Background technique

In the health care system, physiological function assessment is an important step in the prevention and detection of physical diseases. Traditional physiological function assessment requires the assistance of professional medical personnel in a specific medical institution. However, for people with an increasingly faster pace of life, there are many inconvenient.

technical problem

The present invention is to provide a physiological function evaluation system and method, which can efficiently and accurately perform physiological function evaluation.

Technical solutions

In order to achieve the above objective, the first aspect of the present invention provides a physiological function evaluation system. The system includes a terminal device, a fog server, and a medical center. The terminal device is in communication connection with the fog server and the medical center. The server is in communication connection with the medical center;

The terminal device is used to collect physiological function data of the assessed person, and transmit the physiological function data to the fog server;

The fog server is used to receive and analyze the physiological function data, obtain a physiological function evaluation result, and send the physiological function evaluation result to the medical center;

The medical center is used to receive the physiological function evaluation result, analyze the physiological function evaluation result, obtain a physiological health report, and send the obtained physiological health report to the client associated with the assessee end.

Optionally, the system further includes a cloud server, and the cloud server is in communication connection with the fog server and the medical center respectively;

The cloud server is configured to receive target physiological function data sent by the fog server and not processed by the fog server, and analyze the target physiological function data to obtain the target physiological function evaluation result corresponding to the assessee , And send the target physiological function evaluation result to the medical center.

Optionally, the fog server is specifically used for:

Based on the physiological function data, determine the posture characteristics of the evaluable person;

A dynamic time normalization algorithm is used to match the posture feature with the posture feature sample in the preset database to obtain the target posture feature sample;

The corresponding relationship between the preset posture feature sample and the physiological function evaluation result sample is searched, and the physiological function evaluation result sample corresponding to the target posture feature sample is determined as the physiological function evaluation result of the assessed person.

Optionally, the physiological function data includes human bone characteristic information of the assessed person, and the human bone characteristic information includes characteristic information corresponding to elbow joints, shoulder joints, spine, hip joints, and knee joints.

Optionally, the fog server is configured to determine the posture feature of the evaluable person by analyzing the human skeleton feature information.

Optionally, the terminal device includes a camera and/or a sensor.

Optionally, the fog server includes any one or more of routers and switches.

In order to achieve the above objective, the second aspect of the present invention provides a physiological function evaluation method, which is applied to the physiological function evaluation system provided by the first aspect of the present invention, and includes:

Collect the physiological function data of the assessed person by the terminal device, and transmit the physiological function data to the fog server;

The fog server analyzes the physiological function data to obtain a physiological function evaluation result, and sends the physiological function evaluation result to a medical center;

The medical center analyzes the physiological function evaluation result to obtain a physiological health report, and sends the obtained physiological health report to the client associated with the assessee.

Optionally, the method further includes:

After receiving the physiological function data, the fog server determines whether the data processing amount corresponding to the physiological function data is greater than the data processing threshold of the fog server;

If the data processing volume corresponding to the physiological function data is greater than the data processing threshold of the fog server, the fog server sends the physiological function data to a preset cloud server, and the cloud server analyzes the physiological function data.

Optionally, the step of analyzing the physiological function data by the fog server to obtain a physiological function evaluation result includes:

Beneficial effect

The physiological function evaluation system provided by the present invention includes a terminal device, a fog server and a medical center. The system uses the terminal device to collect the physiological function data of the assessed person, and then the fog server analyzes the physiological function data to obtain the physiological function evaluation As a result, the medical center analyzes the results of the physiological function assessment to obtain a physiological health report, which is sent to the client associated with the assessed person to complete the assessment of the human physiological function. Compared with the prior art, because the fog server is located at the edge of the network, it is widely distributed and highly mobile, and can be deployed in the home, so that users can complete the assessment of human physiological functions at home without leaving home; in addition, due to fog The server has low latency and can also speed up the response time of physical function evaluation, so that physiological function evaluation can be performed efficiently and accurately.

Description of the drawings

Figure 1 is a schematic structural diagram of a physiological function evaluation system in an embodiment of the present invention;

2 is another schematic diagram of the structure of the physiological function evaluation system in the embodiment of the present invention;

FIG. 3 is a schematic diagram of the steps of the physiological function evaluation method in the embodiment of the present invention;

Fig. 4 is a schematic diagram of a sub-process of the physiological function assessment method in an embodiment of the present invention.

The best mode of the invention

In order to make the objectives, features, and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the description The embodiments are only a part of the embodiments of the present invention, but not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work shall fall within the protection scope of the present invention.

Please refer to FIG. 1, which is a schematic structural diagram of a physiological function evaluation system in an embodiment of the present invention. In this embodiment, the above-mentioned physiological function evaluation system includes a terminal device 101, a fog server 102, and a medical center 103, and a terminal device 101 and a fog server 102 is in communication connection, and the fog server 102 is in communication connection with the medical center 103.

The terminal device 101 is used to collect the physiological function data of the assessed person, and transmit the physiological function data to the fog server 102; the fog server 102 is used to receive and analyze the physiological function data, obtain the physiological function evaluation result, and transfer the physiological function data to the fog server 102; The function evaluation result is sent to the medical center 103; the medical center 103 is used to receive the above-mentioned physiological function evaluation result, analyze the above-mentioned physiological function evaluation result, obtain a physiological health report, and send the obtained physiological health report to be associated with the assessed person Client.

Wherein, the terminal device 101 includes a large number of cameras and/or sensors arranged in the home room for collecting physiological function data of the human body, which are used to collect various physiological function data of the assessed person.

The fog server 102 is composed of some lightweight devices with relatively weak computing power, such as small servers, routers, switches, etc., and the number is large, and all of them can be deployed in the home. At the same time, the fog server 102 uses fog computing. The fog computing is between cloud computing and personal computing. It is a paravirtualized service computing architecture model, emphasizing the number, and it plays a role no matter how weak a single computing node is. Compared with cloud computing, the architecture adopted by fog computing is more distributed and closer to the edge of the network. Fog computing concentrates data, data processing, and applications in devices at the edge of the network, instead of storing almost all of them in the cloud like cloud computing, data storage and processing rely more on local devices rather than servers.

In this embodiment, the fog server 102 is used to process the collected physiological function data, which can quickly and conveniently perform physiological function evaluation.

The medical center 103 receives the physiological function evaluation result sent by the fog server 102, and further analyzes and evaluates it by professional evaluators or professional evaluation instruments, obtains a high-value physiological health report, and feeds it back to the client associated with the evaluator.

Among them, the clients associated with the assessee may include mobile phones, tablets, desktop computers, smart TVs, smart wearable devices (such as health bracelets), etc.

Further, in this embodiment, after the fog server 102 obtains the physiological function evaluation result, it may directly feed back the physiological function evaluation result to the client associated with the assessee.

The physiological function evaluation system provided in this embodiment includes a terminal device 101, a fog server 102, and a medical center 103. The system uses the terminal device 101 to collect the physiological function data of the assessee, and then the fog server 102 performs the physiological function data. Analyze to obtain the physiological function evaluation result, and then the medical center 103 analyzes the physiological function evaluation result to obtain a physiological health report, which is sent to the client associated with the assessed person to complete the evaluation of the human physiological function. Compared with the prior art, because the fog server 102 is located at the edge of the network, it is widely distributed and highly mobile, and can be deployed in the home, so that users can complete the assessment of human physiological functions at home without leaving the house; in addition, because The fog server 102 has low latency and can also speed up the response time of the body function evaluation, so that the physiological function evaluation can be performed efficiently and accurately.

Further, based on the content described in the above embodiment, please refer to FIG. 2. FIG. 2 is another structural diagram of the physiological function evaluation system in the embodiment of the present invention. In this embodiment, the above system further includes a cloud server 104. 104 communicates with the fog server 102 and the medical center 103 respectively.

Wherein, the cloud server 104 is used to receive the target physiological function data sent by the fog server 102 and not processed by the fog server 102, and analyze the target physiological function data to obtain the target physiological function evaluation result corresponding to the assessee, and compare the target physiological function data. The result of the physiological function evaluation is sent to the medical center 103.

In this embodiment, due to the limited processing capacity and storage capacity of the fog server 102, when there are tasks that need to process massive amounts of data or require more computing resources, the fog server 102 cannot process them. These pending data will be processed from the fog through the network. The server 102 is transmitted to the cloud server 104. Since the cloud server 104 adopts cloud computing and has strong computing power, the data to be processed can be effectively processed to obtain the target physiological function evaluation result corresponding to the evaluator.

Among them, the medical center 103 also includes a physiological database, which is used to store reference data for analyzing physiological function data, and synchronize the stored reference data to the fog server 102 and the cloud server 104. The fog server 102 or the cloud server 104 is analyzing In the case of physiological function data, the reference data is used as the basis to analyze the physiological function evaluation results.

Among them, the medical center 103 receives the physiological function evaluation result sent by the fog server 102 or the cloud server 104, and updates the physiological database after further analysis and evaluation by professional evaluators or professional evaluation instruments.

The physiological function evaluation system provided in this embodiment further includes a cloud server 104 for receiving target physiological function data sent by the fog server 102 and not processed by the fog server 102, and analyzing the target physiological function data , The target physiological function evaluation result corresponding to the assessee is obtained. Because the cloud server 104 adopts cloud computing and has strong computing power, it can process target physiological function data that the fog server 102 cannot process, so that the physiological function evaluation can be performed efficiently and accurately.

Further, based on the content described in the above embodiment, this embodiment describes in detail the processing method of the above physiological function data. Among them, the fog server 102 is specifically used for:

Based on the physiological function data, determine the posture feature of the evaluator; use a dynamic time normalization algorithm to match the posture feature with the posture feature sample in the preset database to obtain the target posture feature sample; find the preset The corresponding relationship between the posture feature sample and the physiological function evaluation result sample, and the physiological function evaluation result sample corresponding to the target posture feature sample is determined as the physiological function evaluation result of the evaluable person.

Wherein, the aforementioned physiological function data includes the human bone characteristic information of the assessed person, and the aforementioned human bone characteristic information includes corresponding characteristic information of the elbow joint, shoulder joint, spine, hip joint, and knee joint.

The fog server 102 is used to determine the posture feature of the evaluable person by analyzing the human skeleton feature information.

For example, the Kinect sensor is used to capture the human skeletal feature information of the evaluator in real time. For the posture feature, the remaining 9 joints of the upper body except the head, hands and feet are selected as the feature reference points, and the central point of the torso is taken as the reference point. Calculate the distance from the elbow-wrist joint to the spine point, as the distance feature, there are 4 in total: A1, A2, A3, A4. The movement of the upper limbs mainly revolves around the movement of the elbow joint and the shoulder joint. Therefore, the angle feature is composed of the movement of the above joint points. There are 4 angle features: B1, B2, B3, B4, and then determine the corresponding posture feature of the assessee The sequence is AF={A1, A2, A3, A4, B1, B2, B3, B4}.

Then, select a posture feature sample in the preset database, such as BF={a1, a2, a3, a4, b1, b2, b3, b4}, and then use the DTW algorithm to match. Among them, the DTW algorithm is a method to measure the similarity between two time series, which is one of the template matching methods. The algorithm searches for the difference between two time series with different lengths by extending or shortening the time series. The matching path with the smallest distance between them is used to calculate the distance (similarity) between two time series.

In this embodiment, the DTW algorithm can be used to find the sequence sample that is most similar to the sequence corresponding to the posture feature of the assessee from the preset database, and the physiological function evaluation result sample corresponding to the sequence sample is determined as the being Physiological function evaluation result of the evaluator.

In the physiological function evaluation system provided in this embodiment, the fog server 102 determines the posture feature of the evaluable person based on physiological function data, and then uses a dynamic time-alignment algorithm to perform calculations on the posture feature and the posture feature samples in the preset database. Match, obtain the target posture feature sample, find the corresponding relationship between the preset posture feature sample and the physiological function evaluation result sample, and then determine the physiological function evaluation result sample corresponding to the target posture feature sample as the physiological function of the assessed person evaluation result.

Further, based on the above embodiment, the embodiment of the present invention also provides a physiological function evaluation method, which can be applied to the physiological function evaluation system provided in the above embodiment. For details, refer to FIG. 3, which is an example of the present invention. Schematic diagram of the steps of the physiological function assessment method, the method includes:

Step 301: Collect physiological function data of the assessee by the terminal device, and transmit the physiological function data to the fog server.

Step 302: The fog server analyzes the physiological function data to obtain a physiological function evaluation result, and sends the physiological function evaluation result to a medical center.

Step 303: The medical center analyzes the physiological function evaluation result to obtain a physiological health report, and sends the obtained physiological health report to the client associated with the assessee.

The physiological function evaluation method provided in this embodiment includes collecting physiological function data of the assessee by a terminal device, and transmitting the physiological function data to the fog server, and the fog server analyzes the physiological function data to obtain the physiological function evaluation As a result, the result of the physiological function evaluation is sent to the medical center; the medical center analyzes the result of the physiological function evaluation to obtain a physiological health report, and sends the obtained physiological health report to the association with the assessee Client. Compared with the prior art, because the fog server is located at the edge of the network, it is widely distributed and highly mobile, and can be deployed in the home, so that users can complete the assessment of human physiological functions at home without leaving home; in addition, due to fog The server has low latency and can also speed up the response time of physical function evaluation, so that physiological function evaluation can be performed efficiently and accurately.

Further, based on the foregoing embodiment, the foregoing physiological function evaluation method further includes:

After receiving the physiological function data, the fog server determines whether the data processing volume corresponding to the physiological function data is greater than the data processing threshold of the fog server; if the data processing volume corresponding to the physiological function data is greater than the data processing threshold of the fog server, then The fog server sends the physiological function data to a preset cloud server, and the cloud server analyzes the physiological function data.

In this embodiment, due to the limited processing capacity and storage capacity of the fog server, when there is a task that needs to process massive amounts of data or requires more computing resources, the fog server cannot process it. The pending data will be transmitted from the fog server through the network. As for the cloud server, because the cloud server adopts cloud computing and has strong computing power, the data to be processed can be effectively processed, and the target physiological function evaluation result corresponding to the assessee can be obtained.

Further, based on the above embodiment, refer to FIG. 4, which is a schematic diagram of a sub-process of the physiological function evaluation method in an embodiment of the present invention. In this embodiment, the fog server described in step 302 analyzes the physiological function data to obtain physiological function data. Performance evaluation results, including:

Step 401: Determine the posture feature of the assessee based on the physiological function data.

Step 402: Use a dynamic time normalization algorithm to match the posture feature with a posture feature sample in a preset database to obtain a target posture feature sample.

Step 403: Search for the correspondence between the preset posture feature sample and the physiological function evaluation result sample, and determine the physiological function evaluation result sample corresponding to the target posture feature sample as the physiological function evaluation result of the evaluator.

The physiological function evaluation method provided in this embodiment determines the posture feature of the assessee based on the physiological function data, and then uses the dynamic time normalization algorithm to match the posture feature with the posture feature samples in the preset database to obtain the target The posture feature sample searches for the corresponding relationship between the preset posture feature sample and the physiological function evaluation result sample, and then the physiological function evaluation result sample corresponding to the target posture feature sample is determined as the physiological function evaluation result of the assessee.

In the several embodiments provided in this application, it should be understood that the disclosed device and method may be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the modules is only a logical function division, and there may be other divisions in actual implementation, for example, multiple modules or components may be combined or It can be integrated into another system, or some features can be ignored or not implemented. In addition, the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or modules, and may be in electrical, mechanical or other forms.

The modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, that is, they may be located in one place, or they may be distributed to multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.

In addition, the functional modules in each embodiment of the present invention may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware or software functional modules.

If the integrated module is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the technical solution of the present invention essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium , Including several instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disks or optical disks and other media that can store program codes.

It should be noted that for the foregoing method embodiments, for simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described sequence of actions. Because according to the present invention, certain steps can be performed in other order or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the involved actions and modules are not necessarily all required by the present invention.

In the above-mentioned embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in an embodiment, reference may be made to related descriptions of other embodiments.

The above is a description of a physiological function evaluation system and method provided by the present invention. For those skilled in the art, according to the ideas of the embodiments of the present invention, there will be changes in the specific implementation and the scope of application. In summary The content of this specification should not be construed as a limitation of the present invention.

Claims

A physiological function evaluation system, wherein the system includes a terminal device, a fog server, and a medical center, the terminal device is in communication connection with the fog server and the medical center, and the fog server is connected to the medical center. Communication connection

The terminal device is used to collect physiological function data of the assessed person, and transmit the physiological function data to the fog server;

The fog server is used to receive and analyze the physiological function data, obtain a physiological function evaluation result, and send the physiological function evaluation result to the medical center;

The medical center is used to receive the physiological function evaluation result, analyze the physiological function evaluation result, obtain a physiological health report, and send the obtained physiological health report to the client associated with the assessee end.
The system according to claim 1, wherein the system further comprises a cloud server, and the cloud server is in communication connection with the fog server and the medical center respectively;

The cloud server is configured to receive target physiological function data sent by the fog server and not processed by the fog server, and analyze the target physiological function data to obtain the target physiological function evaluation result corresponding to the assessee , And send the target physiological function evaluation result to the medical center.
The system according to claim 1, wherein the fog server is specifically configured to:

Based on the physiological function data, determine the posture characteristics of the evaluable person;

A dynamic time normalization algorithm is used to match the posture feature with the posture feature sample in the preset database to obtain the target posture feature sample;

The corresponding relationship between the preset posture feature sample and the physiological function evaluation result sample is searched, and the physiological function evaluation result sample corresponding to the target posture feature sample is determined as the physiological function evaluation result of the assessed person.
The system according to claim 3, wherein the physiological function data includes the human bone characteristic information of the assessed person, and the human bone characteristic information includes elbow joints, shoulder joints, spine, hip joints, and knee joints. Characteristic information.
The system according to claim 4, wherein the fog server is used to determine the posture characteristics of the evaluable person by analyzing the human skeleton characteristic information.
The system according to any one of claims 1 to 5, wherein the terminal device comprises a camera and/or a sensor.
The system according to claim 6, wherein the fog server comprises any one or more of routers and switches.
A physiological function evaluation method, wherein the method is applied to the physiological function evaluation system according to any one of claims 1 to 7, and the method comprises:

Collect the physiological function data of the assessed person by the terminal device, and transmit the physiological function data to the fog server;

The fog server analyzes the physiological function data to obtain a physiological function evaluation result, and sends the physiological function evaluation result to a medical center;

The medical center analyzes the physiological function evaluation result to obtain a physiological health report, and sends the obtained physiological health report to the client associated with the assessee.
The method according to claim 8, wherein the method further comprises:

After receiving the physiological function data, the fog server determines whether the data processing amount corresponding to the physiological function data is greater than the data processing threshold of the fog server;

If the data processing volume corresponding to the physiological function data is greater than the data processing threshold of the fog server, the fog server sends the physiological function data to a preset cloud server, and the cloud server analyzes the physiological function data.
8. The method according to claim 8, wherein the step of analyzing the physiological function data by the fog server to obtain a physiological function evaluation result comprises:

Based on the physiological function data, determine the posture characteristics of the evaluable person;

A dynamic time normalization algorithm is used to match the posture feature with the posture feature sample in the preset database to obtain the target posture feature sample;

The corresponding relationship between the preset posture feature sample and the physiological function evaluation result sample is searched, and the physiological function evaluation result sample corresponding to the target posture feature sample is determined as the physiological function evaluation result of the assessed person.