CN117838119A - Human joint comfort level assessment method and device based on human factor intelligence - Google Patents

Abstract

The application relates to the technical field of multi-mode perception, in particular to a human joint comfort assessment method and device based on human factor intelligence, wherein the method comprises the following steps: and collecting psychological signals and physiological signals of a target person under a plurality of joint angles of each target joint in all target joints, generating all comfort evaluation results of each joint under the plurality of joint angles according to the psychological signals and the physiological signals, fusing all comfort evaluation results of each joint under the plurality of joint angles to obtain a comfort fusion result, and evaluating joint comfort ranges of one or more target joints based on the comfort fusion result. According to the embodiment of the application, the joint comfort degree of each joint of a human body can be evaluated by utilizing various sensing means, so that the accurate and comprehensive human body joint angle comfort range is determined, the data content of the human body joint comfort degree is enriched, the product research and development of the human body posture is more accurate in judging the joint angle, and the health risks caused by poor posture and the like are reduced.

Description

Human joint comfort level assessment method and device based on human factor intelligence

Technical Field

The application relates to the technical field of multi-mode perception, in particular to a human joint comfort assessment method and device based on human factor intelligence.

Background

In people's daily life and work, maintaining a poor posture for a long period of time may cause physical problems such as fatigue, muscle damage, and the like. Therefore, human health protection can be achieved through evaluation and optimization of human comfort.

In the related art, the comfort level evaluation of the joints of the human body can obtain subjective feedback and geometric measurement results of a subject through investigation experiments, and the comfort level of the human body under different postures and motion states is evaluated based on indexes such as subjective scales, joint moments and the like.

However, in the related art, the traditional human joint comfort level evaluation has single data source, cannot comprehensively reflect the physiological and psychological states of the human body, lacks objective and reliable data acquisition modes and diversified variable settings, and is difficult to meet the requirements on the accuracy and universality of the human joint comfort level evaluation result, so that the practicability and the comprehensiveness of the human joint comfort level evaluation result are insufficient, and the need to solve is urgent.

Disclosure of Invention

The application provides a human joint comfort assessment method and device based on human factor intelligence, which are used for solving the problems that in the related technology, the traditional human joint comfort assessment is single in data source, cannot comprehensively reflect the physiological and psychological states of a human body, lacks objective and reliable data acquisition modes and diversified variable settings, is difficult to meet the requirements on the accuracy and universality of the human joint comfort assessment result, and causes the practicability and comprehensiveness of the human joint comfort assessment result to be insufficient.

An embodiment of a first aspect of the present application provides a human joint comfort level assessment method based on artificial intelligence, including the following steps: collecting psychological signals and physiological signals of at least one target person under a plurality of joint angles of each target joint in all target joints; generating all comfort evaluation results of each joint under a plurality of joint angles according to the psychological signals and the physiological signals; and fusing all comfort level evaluation results of each joint under a plurality of joint angles to obtain a comfort level fusion result, and evaluating joint comfort level ranges of one or more target joints based on the comfort level fusion result.

According to the technical means, the joint comfort degree of each joint of the human body can be evaluated by utilizing various sensing means, so that the accurate and comprehensive human body joint angle comfort range is determined, the data content of the human body joint comfort degree is enriched, the product research and development of the human body posture is more accurate in judging the joint angle, and the health risk caused by poor posture and the like is reduced.

Illustratively, prior to collecting the psychological and physiological signals of the at least one target person, further comprising: defining at least one physical environmental condition and/or at least one action environmental condition for the at least one target person to acquire the psychological signal and the physiological signal under the at least one physical environmental condition and/or the at least one action environmental condition.

According to the technical means, physical environment conditions and/or action environment conditions can be defined before psychological signals and physiological signals of the target personnel are collected, so that the psychological signals and the physiological signals are collected, and data samples of the early stage of joint comfort level construction are enriched by adding the limiting conditions in the experimental process of the target personnel, so that joint comfort level assessment is more diversified.

Illustratively, the fusing all comfort level evaluation results of each joint under a plurality of joint angles to obtain a comfort level fusion result, and evaluating a joint comfort level range of one or more target joints based on the comfort level fusion result includes: acquiring physical function conditions of each target person, and adding at least one corresponding comfort influence factor to each comfort evaluation result according to the physical function conditions, the at least one physical environment condition and/or the at least one action environment condition; the comfort level fusion result is constructed by using a comfort level evaluation result containing the at least one comfort level influence factor, so that the joint comfort level range is evaluated based on the comfort level fusion result.

According to the technical means, according to the physical function conditions, the physical environment conditions and/or the action environment conditions of the target personnel, the corresponding at least one comfort influence factor is added to each comfort evaluation result to construct a comfort fusion result, so that the joint comfort range is evaluated based on the comfort fusion result, the labels and types of the comfort evaluation range are further enriched, and the comfort range database is more comprehensive to adapt to various conditions in practical production and application.

Illustratively, the acquiring psychological and physiological signals of at least one target person at a plurality of joint angles of each of all the target joints includes: detecting whether the at least one target person executes a preset static action or a preset dynamic action; tracking the current action of the at least one target person under the condition that the at least one target person executes the preset static action or the preset dynamic action is detected, and obtaining a plurality of joint angles of at least one target joint corresponding to the current action; and acquiring psychological signals and physiological signals of the at least one target person based on the plurality of joint angles.

According to the technical means, the embodiment of the application can track the current action of the target person under the condition that the target person is detected to execute the preset static action or the preset dynamic action, obtain a plurality of joint angles corresponding to the current action, acquire the psychological signals and the physiological signals of at least one target person, and ensure the comprehensiveness of the comfort data sample by designing different actions in advance, so that the obtained data has more universality.

Illustratively, the acquiring the target person psychological signal and the target person physiological signal of the at least one target person based on the plurality of joint angles includes: obtaining action execution data of the at least one target person based on the current action, and generating a joint performance evaluation result of the at least one target person by the action execution data; judging whether the joint performance evaluation result meets a preset performance requirement or not; and if the joint performance evaluation result does not meet the preset performance requirement, stopping collecting the psychological signals and the physiological signals of the at least one target person.

According to the technical means, the embodiment of the application can obtain the action execution data of the target person based on the current action, the action execution data is used for generating the joint performance evaluation result of the target person, if the joint performance evaluation result does not meet the preset performance requirement, the psychological and physiological signals of the target person are stopped being acquired, so that the target person which does not meet the data acquisition condition is screened out, the accuracy and the effectiveness of the joint comfort data sample are ensured, and the data result is more reliable.

An embodiment of a second aspect of the present application provides a human joint comfort level assessment device based on artificial intelligence, including: the acquisition module is used for acquiring psychological signals and physiological signals of at least one target person under a plurality of joint angles of each target joint in all target joints; the generation module is used for generating all comfort evaluation results of each joint under a plurality of joint angles according to the psychological signals and the physiological signals; the evaluation module is used for fusing all comfort evaluation results of each joint under a plurality of joint angles to obtain a comfort fusion result, and evaluating the joint comfort range of one or more target joints based on the comfort fusion result.

According to the technical means, the joint comfort degree of each joint of the human body can be evaluated by utilizing various sensing means, so that the accurate and comprehensive human body joint angle comfort range is determined, the data content of the human body joint comfort degree is enriched, the product research and development of the human body posture is more accurate in judging the joint angle, and the health risk caused by poor posture and the like is reduced.

Illustratively, the apparatus further comprises: a defining module for defining at least one physical environmental condition and/or at least one action environmental condition for the at least one target person prior to acquiring the psychological and physiological signals of the at least one target person to acquire the psychological and physiological signals under the at least one physical environmental condition and/or the at least one action environmental condition.

According to the technical means, physical environment conditions and/or action environment conditions can be defined before psychological signals and physiological signals of the target personnel are collected, so that the psychological signals and the physiological signals are collected, and data samples of the early stage of joint comfort level construction are enriched by adding the limiting conditions in the experimental process of the target personnel, so that joint comfort level assessment is more diversified.

Illustratively, the evaluation module includes: an adding unit, configured to obtain a physical function condition of each target person, and add, to each comfort evaluation result, a corresponding at least one comfort influence factor according to the physical function condition, the at least one physical environmental condition, and/or the at least one action environmental condition; a construction unit for constructing the comfort level fusion result by using a comfort level evaluation result containing the at least one comfort level influence factor, so as to evaluate the joint comfort level range based on the comfort level fusion result.

According to the technical means, according to the physical function conditions, the physical environment conditions and/or the action environment conditions of the target personnel, the corresponding at least one comfort influence factor is added to each comfort evaluation result to construct a comfort fusion result, so that the joint comfort range is evaluated based on the comfort fusion result, the labels and types of the comfort evaluation range are further enriched, and the comfort range database is more comprehensive to adapt to various conditions in practical production and application.

Illustratively, the acquisition module includes: the detection unit is used for detecting whether the at least one target person executes a preset static action or a preset dynamic action; the tracking unit is used for tracking the current action of the at least one target person under the condition that the at least one target person is detected to execute the preset static action or the preset dynamic action, so as to obtain a plurality of joint angles of at least one target joint corresponding to the current action; and the acquisition unit is used for acquiring psychological signals and physiological signals of the at least one target person based on the joint angles.

According to the technical means, the embodiment of the application can track the current action of the target person under the condition that the target person is detected to execute the preset static action or the preset dynamic action, obtain a plurality of joint angles corresponding to the current action, acquire the psychological signals and the physiological signals of at least one target person, and ensure the comprehensiveness of the comfort data sample by designing different actions in advance, so that the obtained data has more universality.

Illustratively, the acquiring unit is specifically configured to: obtaining action execution data of the at least one target person based on the current action, and generating a joint performance evaluation result of the at least one target person by the action execution data; judging whether the joint performance evaluation result meets a preset performance requirement or not; and if the joint performance evaluation result does not meet the preset performance requirement, stopping collecting the psychological signals and the physiological signals of the at least one target person.

According to the technical means, the embodiment of the application can obtain the action execution data of the target person based on the current action, the action execution data is used for generating the joint performance evaluation result of the target person, if the joint performance evaluation result does not meet the preset performance requirement, the psychological and physiological signals of the target person are stopped being acquired, so that the target person which does not meet the data acquisition condition is screened out, the accuracy and the effectiveness of the joint comfort data sample are ensured, and the data result is more reliable.

An embodiment of a third aspect of the present application provides an electronic device, including: the human joint comfort evaluation system comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the program to realize the human joint comfort evaluation method based on human factor intelligence as described in the embodiment.

In a fourth aspect, embodiments of the present application provide a computer readable storage medium storing a computer program which, when executed by a processor, implements a human joint comfort assessment method based on artificial intelligence as above.

According to the embodiment of the application, the joint comfort degree of each joint of a human body can be evaluated by utilizing various sensing means, so that the accurate and comprehensive human body joint angle comfort range is determined, the data content of the human body joint comfort degree is enriched, the product research and development of the human body posture is more accurate in judging the joint angle, and the health risks caused by poor posture and the like are reduced. Therefore, the problems that in the related technology, the traditional human joint comfort level evaluation has single data source, cannot comprehensively reflect the physiological and psychological states of a human body, lacks objective and reliable data acquisition modes and diversified variable settings, is difficult to meet the requirements on the accuracy and universality of the human joint comfort level evaluation result, and causes the practicability and the comprehensiveness of the human joint comfort level evaluation result to be insufficient and the like are solved.

Additional aspects and advantages of the application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the application.

Drawings

The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:

fig. 1 is a flowchart of a human joint comfort assessment method based on artificial intelligence according to an embodiment of the present application;

FIG. 2 is a schematic representation of the pose of a human joint according to one embodiment of the present application;

FIG. 3 is a flow chart of data acquisition for human joint comfort in accordance with one embodiment of the present application;

fig. 4 is a schematic structural diagram of a human joint comfort assessment device based on artificial intelligence according to an embodiment of the present application;

fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and intended for the purpose of explaining the present application and are not to be construed as limiting the present application.

Human joint comfort assessment method and device based on human factor intelligence in the embodiment of the application are described below with reference to the accompanying drawings. Aiming at the problems that in the related technology mentioned in the background technology, the traditional human joint comfort level is single in data source, cannot comprehensively reflect the physiological and psychological states of a human body, lacks objective and reliable data acquisition modes and diversified variable settings, is difficult to meet the requirements on the accuracy and universality of the human joint comfort level evaluation result, and is insufficient in practicality and comprehensiveness of the human joint comfort level evaluation result, the application provides a human joint comfort level evaluation method based on human factor intelligence, which can utilize various perception means to evaluate the joint comfort level of each joint of the human body, so that the accurate and comprehensive human joint angle comfort range is determined, the data content of the human joint comfort level is enriched, the product research and development of the human body posture is more accurate in judging the joint angle, and the health risk caused by poor posture and the like is reduced. Therefore, the problems that in the related technology, the traditional human joint comfort level evaluation has single data source, cannot comprehensively reflect the physiological and psychological states of a human body, lacks objective and reliable data acquisition modes and diversified variable settings, is difficult to meet the requirements on the accuracy and universality of the human joint comfort level evaluation result, and causes the practicability and the comprehensiveness of the human joint comfort level evaluation result to be insufficient and the like are solved.

Specifically, fig. 1 is a schematic flow chart of a human joint comfort evaluation method based on human factor intelligence according to an embodiment of the present application.

As shown in fig. 1, the human joint comfort evaluation method based on human factor intelligence comprises the following steps:

in step S101, psychological and physiological signals of at least one target person are acquired at a plurality of joint angles of each of all the target joints.

It is understood that in embodiments of the present application, the joint angle may be an angle at which the target joint, including the wrist, elbow, and shoulder, is made up of different human poses. The wearable wireless motion capture device can be used for capturing the human body of a target person, and confirming the actual joint angle of the target joint. The psychological signals of the target person are collected through the facial expression tracking equipment, and the physiological signals of the target person are collected through the surface myoelectric equipment.

Illustratively, prior to collecting the psychological and physiological signals of the at least one target person, further comprising: at least one physical environmental condition and/or at least one action environmental condition is defined for at least one target person to acquire psychological and physiological signals under the at least one physical environmental condition and/or the at least one action environmental condition.

It can be understood that, in the embodiment of the present application, the physical environmental conditions may be different physical states of the overall environment where the target person is located, for example, natural condition factors such as temperature, humidity, illumination, wind intensity, and the like of the current environment; the action environment conditions can be different states of the environment contacted by the target person in the process of executing the action or the gesture, such as factors of the height of a chair in sitting posture, the angle of a backrest, the hardness of a cushion and the like, the hardness and the stability of the ground in walking and the like, so that psychological signals and physiological signals of the target person are respectively acquired under different physical environment conditions and combinations of the action environment conditions.

The method and the device can limit physical environmental conditions and/or action environmental conditions before the psychological signals and the physiological signals of the target personnel are collected so as to collect the psychological signals and the physiological signals, and the limitation conditions are added in the experimental process of the target personnel, so that data samples of the early construction stage of the joint comfort level are enriched, and the joint comfort level assessment is more diversified.

Illustratively, collecting psychological and physiological signals of at least one target person at a plurality of joint angles of each of all target joints, comprising: detecting whether at least one target person executes a preset static action or a preset dynamic action; under the condition that at least one target person is detected to execute a preset static action or a preset dynamic action, tracking the current action of the at least one target person to obtain a plurality of joint angles of at least one target joint corresponding to the current action; based on the plurality of joint angles, psychological and physiological signals of at least one target person are acquired.

It should be noted that the preset static action and the preset dynamic action may be set by those skilled in the art according to the actual situation, and are not specifically limited herein.

It may be understood that, in the embodiment of the present application, the preset static action may be a static gesture required to be performed on the target person in advance, the preset dynamic action may be a dynamic gesture required to be performed on the target person in advance, and the preset static action and the preset dynamic action may be used to evaluate a motion range, stability, a functional state, and the like of the joint, where the modeling schematic may be modeled in the processing software after tracking the current action of the target person, and the modeling schematic is shown in fig. 2, and is a gesture schematic diagram of a human joint in one embodiment of the present application, including a motion capture modeling schematic diagram of different target joints under different actions.

In the actual execution process, three groups of static action postures (a natural relaxation posture, a limit posture and a comfortable posture) can be designed to be executed as preset static action requirement target personnel, five dynamic postures such as sitting posture, standing, walking, running and jumping are designed to be executed as preset dynamic action requirement target personnel, each posture is at least carried out for 60 seconds, the wearable wireless action capturing equipment captures the human body of the target personnel, corresponding motion data are collected, a plurality of joint angle data of at least one target joint corresponding to the current action are confirmed, physiological signals and psychological signals of the target personnel under the plurality of joint angle data are collected through the facial expression tracking equipment and the surface myoelectric equipment, and each group of physiological signals and psychological signals are data obtained by collecting the target joints under the current action.

Specifically, as shown in fig. 3, a data acquisition flow chart for human joint comfort according to one embodiment of the present application includes:

step S301: and (5) preparing experiments.

The dynamic capturing device and the physiological signal and psychological signal acquisition device are prepared, and each camera can capture the whole test area.

Step S302: fill out a questionnaire.

And filling in a related basic information questionnaire to acquire basic information of the target personnel.

Step S303: the device is worn.

The target personnel need to wear wireless equipment such as dynamic capturing equipment, physiological signal acquisition equipment, psychological signal acquisition equipment and the like.

Step S304: and performing a warm-up activity.

Wherein the target person performs an appropriate warming up activity before the experiment to be ready for the test.

Step S305: three sets of static gestures are completed.

The target person completes three groups of static action postures including a natural posture, a limit posture and a comfortable posture aiming at different joints, and corresponding movement data are collected.

Step S306: a dynamic gesture is performed.

The target person performs five dynamic postures of sitting posture, standing, walking, running and jumping, and corresponding exercise data are collected.

Step S307: fill out the scale questionnaire.

The target personnel fill out the scale questionnaire and score and grade the three static gestures and the five dynamic gestures.

According to the method and the device, the current action of the target person can be tracked under the condition that the target person is detected to execute the preset static action or the preset dynamic action, the multiple joint angles corresponding to the current action are obtained, the psychological signals and the physiological signals of at least one target person are obtained, the comprehensiveness of the comfort data sample is guaranteed through designing different actions in advance, and the obtained data has universality.

Illustratively, acquiring the target person psychological signal and the target person physiological signal of the at least one target person based on the plurality of joint angles comprises: obtaining action execution data of at least one target person based on the current action, and generating joint performance evaluation results of the at least one target person by the action execution data; judging whether the joint performance evaluation result meets the preset performance requirement or not; and if the joint performance evaluation result does not meet the preset performance requirement, stopping collecting psychological signals and physiological signals of at least one target person.

It should be noted that the preset performance requirement may be set by those skilled in the art according to the actual situation, and is not specifically limited herein.

It may be understood that in the embodiment of the present application, motion execution data may be collected during the process of executing the current motion by the target person, so as to perform joint performance evaluation, that is, determine whether the joint performance of the target person meets the experimental requirement required for executing the current motion, that is, ensure that the target joint of the target person is healthy and has no obvious pathological problem, and if the joint performance evaluation result does not meet the preset performance requirement, consider that the target joint of the target person does not meet the experimental requirement required for executing the current motion, and stop collecting the psychological signal and the physiological signal of the target person.

Specifically, as shown in table 1, table 1 is a preset static motion schematic table, and the target person can perform joint angle changes of different target joints by using the static motion related in table 1, and measure angle data corresponding to different motions to obtain motion execution data.

TABLE 1

As shown in table 2, table 2 is a preset dynamic data record table, and the dynamic data of the target person under the preset dynamic actions such as sitting, standing, walking, running, jumping and the like can be recorded by using table 2 to obtain the action execution data. Where stride represents the distance each step is forward, stride frequency represents the number of steps taken per minute, gait stability represents the standard deviation of various parameters, and appropriate software may be used to analyze the collected data to derive various parameters such as stride, stride frequency, gait stability, etc.

TABLE 2

Posture of human	Stride (cm)	Step frequency (step/minute)	Gait stability (SD, standard deviation)
				Sitting posture
Standing up
				Walking on foot
Running
				Jumping

It should be noted that, in the process of executing the current action by the target person, guidance and supervision are required by the professional person. And gradually increasing the load and difficulty when carrying out dynamic posture experiments so as to adapt to the physical condition and the capacity level of target personnel.

According to the method and the device, the action execution data of the target personnel can be obtained based on the current action, the joint performance evaluation result of the target personnel is generated by the action execution data, and if the joint performance evaluation result does not meet the preset performance requirement, the psychological signals and the physiological signals of the target personnel are stopped being acquired, so that the target personnel which do not meet the data acquisition condition are screened out, the accuracy and the effectiveness of the joint comfort data sample are ensured, and the data result is more reliable.

In step S102, all comfort evaluation results of each joint at a plurality of joint angles are generated from the psychological and physiological signals.

It will be appreciated that in embodiments of the present application, the resulting psychological and physiological signal data may be analyzed and tested for significance using common statistical methods such as mean, variance, standard error, etc.

Specifically, the analysis can be performed based on sEMG (Surface electromyography, surface electromyographic signal) data as an example: correlation analysis, which is used to study the relationship between the muscle contraction intensity and the angle of the joint ROM (Range of Motion), and the Pierson correlation coefficient or the Szelman grade correlation coefficient between the muscle sEMG signal and the angle of the ROM can be calculated; multiple regression analysis can be used to investigate the effect of muscle contraction strength and other possible factors on joint ROM angle. The muscle sEMG signals and the individual difference of target personnel can be used as independent variables, and the ROM angle is used as a dependent variable to establish a multiple regression model; analysis of variance may be used to verify whether there are significant differences between different actions and different joints, and whether these differences are related to muscle contraction intensity and scale scores, which may be performed using the different actions and different joints as factors and the muscle sEMG signals and scale scores as covariates. The specific data statistics method should be determined according to experimental design and experimental results to ensure accuracy and reliability of data, and factors such as distribution condition and sample size of data need to be considered when determining the data statistics method.

In step S103, the comfort level fusion results are obtained by fusing all the comfort level evaluation results of each joint under a plurality of joint angles, and the joint comfort level range of one or more target joints is evaluated based on the comfort level fusion results.

It may be appreciated that in the embodiment of the present application, according to all the comfort level evaluation results obtained in the foregoing steps, different comfort level evaluation results of each target joint may be integrated to evaluate a joint comfort level range of one or more target joints, where the results obtained in the evaluation may be actually generated and applied, for example, the joint comfort level range may be used to provide important references and guidance for developing a model machine of a virtual person, and provide data support for the comprehensive comfort level system.

In the actual execution process, the comfort level of different joint angles can influence the comprehensive comfort of a person, and when the angles of all joints of the body are in a comfortable range, the human body can feel more comfortable, and the balance and stability of the body can be better kept. Conversely, when the angle of a certain joint of the body is too large or too small, discomfort and pain may result, thereby affecting the comfort of the whole body. Therefore, when various activities or works are performed, the body posture and the angles of the joints should be noted to ensure the comfort and health of the body, as shown in table 3, the reference values of the common joint angles of the human body are listed in the table below, and the reference values of the natural posture and the limit posture range of the common joint of the human body can be used for comparing and adjusting with the acquired joint comfort data to obtain the final comfort range evaluation result.

TABLE 3 Table 3

The application takes the joint angle as an independent variable and takes the comprehensive comfort level of the human body formed by physiological signals and psychological signals as an independent variable. The comprehensive comfort level of the human body under different joint angles is tested and analyzed, the influence of the different joint angles on the human body can be known, reasonable postures and action modes can be found, the burden of the joints is reduced, the comfort level of the human body is improved, the comfort state of the joints of the human body is more comprehensively known through the cooperative application of the multi-mode sensing means, the optimal environmental conditions and the optimal posture range are determined, and beneficial scientific support is provided for subsequent product research and development and application.

Illustratively, fusing all comfort assessment results for each joint at a plurality of joint angles to obtain a comfort fusion result, and evaluating a joint comfort range for one or more target joints based on the comfort fusion result, comprising: acquiring physical function conditions of each target person, and adding at least one corresponding comfort influence factor to each comfort evaluation result according to the physical function conditions, at least one physical environment condition and/or at least one action environment condition; a comfort fusion result is constructed using the comfort evaluation result including the at least one comfort influence factor to evaluate the joint comfort range based on the comfort fusion result.

It can be understood that in the embodiment of the present application, the physical function condition of the target person may be the age, sex, height, weight, etc. of the target person, and the defined physical environment condition and the action environment condition are combined together to be used as the comfort level influencing factor, and the comfort level influencing factor is used to fuse to obtain the comfort level evaluation result, so as to evaluate the joint comfort level range.

According to the method and the device, the comfort level fusion result can be built by adding at least one corresponding comfort level influence factor to each comfort level evaluation result according to the physical function condition, the physical environment condition and/or the action environment condition of the target person, so that the joint comfort level range is evaluated based on the comfort level fusion result, the labels and types of the comfort level evaluation range are further enriched, and the comfort level range database is more comprehensive so as to adapt to various conditions in actual production application.

According to the human joint comfort level assessment method based on human factor intelligence, which is provided by the embodiment of the application, the joint comfort level of each joint of a human body can be assessed by utilizing various sensing means, so that the accurate and comprehensive human joint angle comfort range is determined, the data content of the human joint comfort level is enriched, the product research and development of the human body posture is more accurate in judging the joint angle, and the health risks caused by poor posture and the like are reduced. Therefore, the problems that in the related technology, the traditional human joint comfort level evaluation has single data source, cannot comprehensively reflect the physiological and psychological states of a human body, lacks objective and reliable data acquisition modes and diversified variable settings, is difficult to meet the requirements on the accuracy and universality of the human joint comfort level evaluation result, and causes the practicability and the comprehensiveness of the human joint comfort level evaluation result to be insufficient and the like are solved.

Next, a human joint comfort level assessment device based on artificial intelligence according to an embodiment of the present application will be described with reference to the accompanying drawings.

Fig. 4 is a schematic structural diagram of a human joint comfort level assessment device based on artificial intelligence according to an embodiment of the present application.

As shown in fig. 4, the human joint comfort level assessment device 10 based on human intelligence includes: the system comprises an acquisition module 100, a generation module 200 and an evaluation module 300.

The acquisition module 100 is configured to acquire psychological signals and physiological signals of at least one target person at a plurality of joint angles of each of all target joints.

The generating module 200 is configured to generate all comfort evaluation results of each joint under a plurality of joint angles according to the psychological signals and the physiological signals.

The evaluation module 300 is configured to fuse all the comfort evaluation results of each joint under multiple joint angles to obtain a comfort fusion result, and evaluate the joint comfort range of one or more target joints based on the comfort fusion result.

Illustratively, the apparatus 10 further comprises: the module is defined.

Wherein the limiting module is used for limiting at least one physical environment condition and/or at least one action environment condition for at least one target person before the psychological signal and the physiological signal of the at least one target person are acquired, so as to acquire the psychological signal and the physiological signal under the at least one physical environment condition and/or the at least one action environment condition.

Illustratively, the assessment module 300 includes: an adding unit and a constructing unit.

The adding unit is used for obtaining the physical function condition of each target person, and adding at least one corresponding comfort influence factor to each comfort evaluation result according to the physical function condition, at least one physical environment condition and/or at least one action environment condition.

And a construction unit for constructing a comfort level fusion result using the comfort level evaluation result including at least one comfort level influence factor to evaluate the joint comfort level range based on the comfort level fusion result.

Illustratively, the acquisition module 100 includes: the device comprises a detection unit, a tracking unit and an acquisition unit.

The detection unit is used for detecting whether at least one target person executes a preset static action or a preset dynamic action.

The tracking unit is used for tracking the current action of the at least one target person under the condition that the at least one target person is detected to execute the preset static action or the preset dynamic action, and obtaining a plurality of joint angles of the at least one target joint corresponding to the current action.

And the acquisition unit is used for acquiring psychological signals and physiological signals of at least one target person based on the plurality of joint angles.

Illustratively, the acquisition unit is specifically configured to: obtaining action execution data of at least one target person based on the current action, and generating joint performance evaluation results of the at least one target person by the action execution data; judging whether the joint performance evaluation result meets the preset performance requirement or not; and if the joint performance evaluation result does not meet the preset performance requirement, stopping collecting psychological signals and physiological signals of at least one target person.

It should be noted that the foregoing explanation of the embodiment of the human joint comfort level evaluation method based on human factor intelligence is also applicable to the human joint comfort level evaluation device based on human factor intelligence of this embodiment, and will not be repeated here.

According to the human joint comfort level assessment device based on human factor intelligence, provided by the embodiment of the application, the joint comfort level of each joint of a human body can be assessed by utilizing various sensing means, so that the accurate and comprehensive human joint angle comfort range is determined, the data content of the human joint comfort level is enriched, the product research and development of the human body posture is more accurate in judging the joint angle, and the health risks caused by poor posture and the like are reduced. Therefore, the problems that in the related technology, the traditional human joint comfort level evaluation has single data source, cannot comprehensively reflect the physiological and psychological states of a human body, lacks objective and reliable data acquisition modes and diversified variable settings, is difficult to meet the requirements on the accuracy and universality of the human joint comfort level evaluation result, and causes the practicability and the comprehensiveness of the human joint comfort level evaluation result to be insufficient and the like are solved.

Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device may include:

memory 501, processor 502, and a computer program stored on memory 501 and executable on processor 502.

The processor 502 implements the human joint comfort assessment method based on human intelligence provided in the above embodiment when executing a program.

Further, the electronic device further includes:

a communication interface 503 for communication between the memory 501 and the processor 502.

Memory 501 for storing a computer program executable on processor 502.

The memory 501 may include high-speed RAM memory and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.

If the memory 501, the processor 502, and the communication interface 503 are implemented independently, the communication interface 503, the memory 501, and the processor 502 may be connected to each other via a bus and perform communication with each other. The bus may be an industry standard architecture (Industry Standard Architecture, abbreviated ISA) bus, an external device interconnect (Peripheral Component Interconnect, abbreviated PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, abbreviated EISA) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, only one thick line is shown in fig. 5, but not only one bus or one type of bus.

Alternatively, in a specific implementation, if the memory 501, the processor 502, and the communication interface 503 are integrated on a chip, the memory 501, the processor 502, and the communication interface 503 may perform communication with each other through internal interfaces.

The processor 502 may be a central processing unit (Central Processing Unit, abbreviated as CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, abbreviated as ASIC), or one or more integrated circuits configured to implement embodiments of the present application.

The present embodiment also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the human joint comfort assessment method based on artificial intelligence as above.

In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.

Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "N" is at least two, such as two, three, etc., unless explicitly defined otherwise.

Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and additional implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order from that shown or discussed, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.

Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or N wires, a portable computer cartridge (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.

It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. As with the other embodiments, if implemented in hardware, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.

Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.

In addition, each functional unit in each embodiment of the present application may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product.

The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, or the like. Although embodiments of the present application have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives, and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.

Claims (10)

1. The human joint comfort level assessment method based on human factor intelligence is characterized by comprising the following steps of:

collecting psychological signals and physiological signals of at least one target person under a plurality of joint angles of each target joint in all target joints;

generating all comfort evaluation results of each joint under a plurality of joint angles according to the psychological signals and the physiological signals;

and fusing all comfort level evaluation results of each joint under a plurality of joint angles to obtain a comfort level fusion result, and evaluating joint comfort level ranges of one or more target joints based on the comfort level fusion result.

2. The method of claim 1, further comprising, prior to collecting the psychological and physiological signals of the at least one target person:

Defining at least one physical environmental condition and/or at least one action environmental condition for the at least one target person to acquire the psychological signal and the physiological signal under the at least one physical environmental condition and/or the at least one action environmental condition.

3. The method of claim 2, wherein said fusing all comfort assessment results for each joint at a plurality of joint angles to obtain a comfort fusion result, and evaluating a joint comfort range for one or more target joints based on the comfort fusion result, comprises:

acquiring physical function conditions of each target person, and adding at least one corresponding comfort influence factor to each comfort evaluation result according to the physical function conditions, the at least one physical environment condition and/or the at least one action environment condition;

the comfort level fusion result is constructed by using a comfort level evaluation result containing the at least one comfort level influence factor, so that the joint comfort level range is evaluated based on the comfort level fusion result.

4. The method of claim 1, wherein the acquiring psychological and physiological signals of at least one target person at a plurality of joint angles of each of all target joints comprises:

Detecting whether the at least one target person executes a preset static action or a preset dynamic action;

tracking the current action of the at least one target person under the condition that the at least one target person executes the preset static action or the preset dynamic action is detected, and obtaining a plurality of joint angles of at least one target joint corresponding to the current action;

and acquiring psychological signals and physiological signals of the at least one target person based on the plurality of joint angles.

5. The method of claim 4, wherein the acquiring the target person psychological signal and the target person physiological signal of the at least one target person based on the plurality of joint angles comprises:

obtaining action execution data of the at least one target person based on the current action, and generating a joint performance evaluation result of the at least one target person by the action execution data;

judging whether the joint performance evaluation result meets a preset performance requirement or not;

and if the joint performance evaluation result does not meet the preset performance requirement, stopping collecting the psychological signals and the physiological signals of the at least one target person.

6. Human joint comfort level evaluation device based on human factor intelligence, characterized by comprising:

the acquisition module is used for acquiring psychological signals and physiological signals of at least one target person under a plurality of joint angles of each target joint in all target joints;

the generation module is used for generating all comfort evaluation results of each joint under a plurality of joint angles according to the psychological signals and the physiological signals;

the evaluation module is used for fusing all comfort evaluation results of each joint under a plurality of joint angles to obtain a comfort fusion result, and evaluating the joint comfort range of one or more target joints based on the comfort fusion result.

7. The apparatus as recited in claim 6, further comprising:

a defining module for defining at least one physical environmental condition and/or at least one action environmental condition for the at least one target person prior to acquiring the psychological and physiological signals of the at least one target person to acquire the psychological and physiological signals under the at least one physical environmental condition and/or the at least one action environmental condition.

8. The apparatus of claim 7, wherein the evaluation module comprises:

an adding unit, configured to obtain a physical function condition of each target person, and add, to each comfort evaluation result, a corresponding at least one comfort influence factor according to the physical function condition, the at least one physical environmental condition, and/or the at least one action environmental condition;

a construction unit for constructing the comfort level fusion result by using a comfort level evaluation result containing the at least one comfort level influence factor, so as to evaluate the joint comfort level range based on the comfort level fusion result.

9. An electronic device, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the artificial intelligence based human joint comfort assessment method according to any one of claims 1-5.

10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program is executed by a processor for implementing the artificial intelligence based human joint comfort assessment method according to any one of claims 1-5.