CN115153984A - Intelligent artificial limb control method, device, terminal and medium based on electromyographic signals - Google Patents
Intelligent artificial limb control method, device, terminal and medium based on electromyographic signals Download PDFInfo
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- CN115153984A CN115153984A CN202211075911.1A CN202211075911A CN115153984A CN 115153984 A CN115153984 A CN 115153984A CN 202211075911 A CN202211075911 A CN 202211075911A CN 115153984 A CN115153984 A CN 115153984A
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
- A61F2/50—Prostheses not implantable in the body
- A61F2/68—Operating or control means
- A61F2/70—Operating or control means electrical
- A61F2/72—Bioelectric control, e.g. myoelectric
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61F—FILTERS IMPLANTABLE INTO BLOOD VESSELS; PROSTHESES; DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF, TUBULAR STRUCTURES OF THE BODY, e.g. STENTS; ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES; FOMENTATION; TREATMENT OR PROTECTION OF EYES OR EARS; BANDAGES, DRESSINGS OR ABSORBENT PADS; FIRST-AID KITS
- A61F2/00—Filters implantable into blood vessels; Prostheses, i.e. artificial substitutes or replacements for parts of the body; Appliances for connecting them with the body; Devices providing patency to, or preventing collapsing of, tubular structures of the body, e.g. stents
- A61F2/50—Prostheses not implantable in the body
- A61F2/68—Operating or control means
- A61F2/70—Operating or control means electrical
- A61F2002/704—Operating or control means electrical computer-controlled, e.g. robotic control
Abstract
The invention discloses an intelligent artificial limb control method, device, terminal and medium based on electromyographic signals, wherein the method comprises the following steps: acquiring an action template change signal based on the acquired electromyographic signal, wherein the action template change signal comprises at least two continuous matching early warning signals, and the matching early warning signals are that the matching value of the electromyographic signal and a current action template for the intelligent artificial limb is smaller than a preset matching threshold value; when an action template change signal is obtained according to the electromyographic signal, an action template matched with the electromyographic signal is obtained, and a current action template used for the intelligent artificial limb is updated based on the action template; and controlling the motion of the intelligent artificial limb according to the current motion template. Compared with the prior art, the control failure or shaking of the intelligent artificial limb caused by the accidental fluctuation of the electromyographic signals can be prevented, and the stability of controlling the intelligent artificial limb is improved.
Description
Technical Field
The invention relates to the technical field of wearable equipment, in particular to an intelligent artificial limb control method, an intelligent artificial limb control device, an intelligent artificial limb control terminal and an intelligent artificial limb control medium based on electromyographic signals.
Background
Because the intelligent artificial limb needs to be controlled by the electromyographic signals of the wearer, and the electromyographic signals are generated based on the brain activity of the wearer, once the attention of the wearer is not focused or the environment is disturbed, the electromyographic signals are easy to fluctuate, so that the existing actions of the intelligent artificial limb are invalid or shake. For example, when an intelligent artificial limb is used for grabbing an article, if attention is not focused, the electromyographic signals are easy to fluctuate, the grabbed article falls off, and the control stability is poor.
Thus, there is a need for improvements and enhancements to the prior art.
Disclosure of Invention
The invention mainly aims to provide an intelligent artificial limb control method, an intelligent artificial limb control device, an intelligent terminal and a storage medium based on electromyographic signals, and aims to improve the stability of controlling an intelligent artificial limb.
In order to achieve the above object, a first aspect of the present invention provides an intelligent prosthesis control method based on electromyographic signals, wherein the method comprises:
acquiring an action template change signal based on the acquired electromyographic signal, wherein the action template change signal comprises at least two continuous matching early warning signals, and the matching early warning signals are used for representing that the matching value of the electromyographic signal and a current action template for the intelligent artificial limb is smaller than a preset matching threshold value;
when an action template change signal is obtained according to the electromyographic signal, an action template matched with the electromyographic signal is obtained, and a current action template used for the intelligent artificial limb is updated based on the action template;
and controlling the motion of the intelligent artificial limb according to the current motion template.
Optionally, the number of the matching early warning signals included in the action template change signal is obtained according to the current action template; and obtaining the preset matching threshold according to the current action template.
Optionally, obtaining a duration of the current action template;
and when the duration increases each preset time interval, reducing the preset matching threshold according to the reduction amount of the preset threshold.
Optionally, the obtaining an action template matched with the electromyographic signal includes:
acquiring an action template data set;
and matching the electromyographic signal with an electromyographic signal sample of each action template in the action template data set in sequence to obtain a matching value, and setting the action template as an action template matched with the electromyographic signal when the matching value is greater than or equal to a preset matching threshold value of the action template.
Optionally, the action templates in the action template data set are further provided with a preset matching number, and when the number of the electromyographic signals meeting the matching condition is greater than the preset matching number, the action template is set as the action template matched with the electromyographic signals, where the matching condition is that the matching value between the electromyographic signals and the action template is greater than or equal to the preset matching threshold.
Optionally, the electromyographic signals are acquired at a set sampling frequency of the current motion template.
Optionally, obtaining a matching value of the electromyographic signal and the motion template includes:
respectively obtaining a first electromyographic potential curve and a second electromyographic potential curve based on the electromyographic potential of each sampling point in the electromyographic signal and the electromyographic potential of each sampling point in the electromyographic signal of the action template;
and calculating the fitting degree between the first electromyographic potential curve and the second electromyographic potential curve to obtain the matching value.
The invention provides an intelligent artificial limb control device based on electromyographic signals, in a second aspect, wherein the device comprises:
the system comprises a signal module, a signal processing module and a signal processing module, wherein the signal module is used for obtaining an action template change signal based on an obtained electromyographic signal, the action template change signal comprises at least two continuous matching early warning signals, and the matching early warning signals are that the matching value of the electromyographic signal and a current action template for the intelligent artificial limb is smaller than a preset matching threshold value;
the matching module is used for obtaining an action template matched with the electromyographic signal and updating a current action template for the intelligent artificial limb based on the action template when an action template change signal is obtained according to the electromyographic signal;
and the control module is used for controlling the motion of the intelligent artificial limb according to the current motion template.
A third aspect of the present invention provides an intelligent terminal, where the intelligent terminal includes a memory, a processor, and an intelligent prosthesis control program based on an electromyographic signal, stored in the memory and executable on the processor, and the intelligent prosthesis control program based on the electromyographic signal implements any one of the steps of the intelligent prosthesis control method based on the electromyographic signal when executed by the processor.
A fourth aspect of the present invention provides a computer-readable storage medium, where an intelligent prosthesis control program based on an electromyographic signal is stored on the computer-readable storage medium, and when being executed by a processor, the intelligent prosthesis control program based on the electromyographic signal implements any one of the steps of the intelligent prosthesis control method based on the electromyographic signal.
According to the scheme, when the matching value of the electromyographic signal and the current action template is smaller than the preset matching threshold value, only one matching early warning signal is generated, when at least two matching early warning signals continuously appear, an action template change signal is generated to confirm that the action template needs to be changed, and then the action template matched with the electromyographic signal is obtained and the current action template is updated. Compared with the prior art, the control failure or shaking of the intelligent artificial limb caused by the accidental fluctuation of the electromyographic signals can be prevented, and the stability of controlling the intelligent artificial limb is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
FIG. 1 is a schematic flow chart of an intelligent prosthesis control method based on electromyographic signals according to an embodiment of the invention;
fig. 2 is a schematic flowchart of the process of obtaining the matching value of the electromyogram signal and the motion template in step S200;
FIG. 3 is a schematic structural diagram of an intelligent prosthesis control device based on electromyographic signals according to an embodiment of the present invention;
fig. 4 is a schematic block diagram of an internal structure of an intelligent terminal according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when 8230," or "once" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted depending on the context to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the drawings of the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described and will be readily apparent to those of ordinary skill in the art without departing from the spirit of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.
A muscle is composed of many motor units, one of which contains many muscle fibers. The electromyographic signals measure changes in nerve potential of muscle fibers and neurons in the vicinity of a certain site of a muscle. When a user wears the intelligent artificial limb by using the incomplete limb, the incomplete limb can be controlled by mind to generate corresponding myoelectric signals, and after the myoelectric signals are processed, the intelligent artificial limb can be controlled to make corresponding actions, so that basic functions similar to human limbs are realized to communicate with the external environment.
However, the electromyographic signals are generated based on the brain activity of a wearer, and because distraction or other factors hardly maintain the attention of specific electromyographic signals for a long time, once the attention of the wearer is not concentrated or is interfered by the environment, the electromyographic signals are easy to fluctuate, other control signals are generated, and the existing actions of the intelligent artificial limb are disabled or shaken. For example, when an intelligent artificial limb grabs an article, if attention is not focused, myoelectric signals are easy to fluctuate, and the grabbed article falls off. Therefore, the control stability of the existing control method of the intelligent artificial limb is poor.
In order to improve the stability of controlling the intelligent artificial limb, when the intelligent artificial limb control method is implemented, when the matching value of the electromyographic signal and the current action template used for controlling the intelligent artificial limb is smaller than a preset matching threshold value, only one matching early warning signal is generated, when at least two matching early warning signals continuously appear, the action template needing to be changed is confirmed, and then the action template matched with the electromyographic signal is obtained and the current action template is updated. The control failure or the shaking of the intelligent artificial limb caused by the accidental fluctuation of the electromyographic signals can be prevented, and the stability of controlling the intelligent artificial limb is improved.
Exemplary method
As shown in fig. 1, an embodiment of the present invention provides an intelligent prosthesis control method based on an electromyographic signal, which is deployed on a control terminal of an intelligent prosthesis, and specifically, the method includes the following steps:
step S100: acquiring an action template change signal based on the acquired electromyographic signal, wherein the action template change signal comprises at least two continuous matching early warning signals, and the matching early warning signals are that the matching value of the electromyographic signal and the current action template for the intelligent artificial limb is smaller than a preset matching threshold value;
in particular, electromyographic signals may generally be acquired through electrodes placed on the patient's residual muscles. The electromyographic signals are related to the movement of a human body, and different electromyographic signals can be generated when the limbs do different movements. Namely, different muscle movement states can be generated by different actions of limbs, and the myoelectric signal characteristics corresponding to the different muscle movement states are also different.
In order to facilitate the control of the intelligent prosthesis, different action templates are designed in advance in the embodiment, such as: the method comprises the following steps of grabbing a template, pushing and pulling the template, knocking the template and the like, wherein the template comprises pre-collected myoelectric signals and limb actions corresponding to the myoelectric signals, such as various actions of grabbing, holding, stretching, rotating and the like. By establishing the correlation between the electromyographic signals and the limb actions, the electromyographic signals collected in real time can be matched with the corresponding action template so as to control the actions of the intelligent artificial limb.
Optionally, in order to enable the collected electromyographic signals to be more accurately matched with the motions of the intelligent artificial limb, the pre-collected electromyographic signals can be customized individually, that is, the patient wears the intelligent artificial limb to make corresponding motions, collect corresponding electromyographic signals and update a motion template.
Because the myoelectric signals in the bioelectricity of the human body are weak, after the myoelectric original signals are collected, the myoelectric original signals also need to be preprocessed through amplification, filtering and the like. And then extracting data from the electromyographic signals and storing the data in an electromyographic signal matrix mode. For example: the effective action taking time of a user is two seconds, the sampling rate is set to be 200Hz, the number of channels is set to be 8, and an electromyographic signal is stored by using an 8 multiplied by 400 signal matrix. The rows of the electromyographic signal matrix represent channel labels, and the columns represent sampled electromyographic signal data.
Because each action template corresponds to different actions, some action templates have high action speed and some action templates have low speed, in order to improve the timeliness of the electromyographic signals, the embodiment reads the sampling frequency from the current action template used by the intelligent artificial limb when acquiring the electromyographic signals, and acquires the electromyographic signals at the sampling frequency.
The embodiment uses the action template database to store action templates corresponding to various intelligent artificial limb actions. Each action template comprises electromyographic signals collected when the intelligent artificial limb executes a certain action and corresponding driving signals for controlling the intelligent artificial limb, such as control signals of a motor, an air pump or an oil pressure pump and other mechanisms. The action template database can be a pre-constructed action template standard library and can also be a personalized action template library constructed when the patient uses the intelligent artificial limb for the first time.
After the electromyographic signals are collected, firstly, the electromyographic signals are matched with a current action template used by the intelligent artificial limb, and when a matching value obtained by calculation is greater than or equal to a preset matching threshold value, the collected electromyographic signals are similar to the electromyographic signals of the current action template and are used for maintaining the current action of the intelligent artificial limb; when the matching value obtained by calculation is smaller than a preset matching threshold value, it is indicated that the collected electromyographic signals are not similar to electromyographic signals expected for maintaining the current action of the intelligent artificial limb, and an operator may want to control the intelligent artificial limb to execute another action; an operator may want to maintain the current motion of the intelligent artificial limb, but due to reasons such as distraction, muscle tension and environmental interference, the collected electromyographic signals are subjected to occasional fluctuation, and the next collected electromyographic signal may be similar to the electromyographic signal of the current motion template. If the electromyographic signal is directly used to match with a new action template to control the intelligent artificial limb to execute new action as in the conventional operation, the fluctuation situation above causes the control intelligent control to be wrong, and the grabbed article falls off or the intelligent artificial limb shakes and shakes.
Therefore, in this embodiment, when the matching value between the collected electromyographic signal and the current motion template is smaller than the preset matching threshold, only one matching early warning signal is generated, and only when at least two matching early warning signals continuously appear, a motion template change signal is generated.
The predetermined matching threshold may be a fixed value, such as 80%. Preferably, if the electromyogram signal of the embodiment is matched with the current action template, a preset matching threshold value is read from the action template, so that a lower matching threshold value can be correspondingly set for action templates which have long duration or are easy to cause safety accidents, such as action templates for holding a water cup.
Optionally, in order to enhance the stability of the control, the matching early warning signal may be generated only when the duration of the current motion of the intelligent prosthesis is greater than a preset time threshold, so that the duration of each motion of the intelligent prosthesis satisfies the minimum execution time.
Preferably, the number of the matching warning signals appearing before the generation of the action template change signal is obtained from the current action template, that is, the number of the generated matching warning signals before the generation of the action template change signal is determined by the current action template, so that the stability of some important action templates can be improved.
In one embodiment, the duration of the current action template is also accumulated, and the preset match threshold is decreased according to the preset threshold decrease amount each time the duration is increased by the preset time interval. For example: every time the current action template lasts for more than one minute, the preset match threshold is lowered by 1%.
The method for comparing the electromyographic signals acquired in real time with the electromyographic signals of the current action template to obtain the matching value is not limited, and a neural network can be adopted for comparison: inputting the real-time electromyographic signals and the electromyographic signals of the current action template into a neural network, respectively extracting the characteristic data of the two electromyographic signals, comparing the characteristic data item by item, and then averaging to obtain a matching value.
And if the matching value of the subsequently acquired electromyographic signals and the current action template is greater than or equal to the preset matching threshold after the matching early warning signals are generated, the fluctuation signals can be confirmed to appear, the matching early warning signals are eliminated, and the electromyographic signals corresponding to the matching early warning signals are discarded.
Step S200: when an action template change signal is obtained according to the electromyographic signal, an action template matched with the electromyographic signal is obtained, and a current action template used for the intelligent artificial limb is updated based on the action template;
specifically, obtaining the motion template change signal can confirm that the operator intends to control the intelligent prosthesis to perform a new motion. And then reading an action template data set from the action template database, sequentially matching the electromyographic signals corresponding to the generated matching early warning signals with action templates in the action template data set to obtain action templates meeting matching conditions, and then using the action templates as current action templates used by the intelligent artificial limb to enable the intelligent artificial limb to execute new actions. The matching condition means that the matching value of the electromyographic signal and the electromyographic signal of the action template is larger than or equal to a preset matching threshold value.
The predetermined matching threshold may be a fixed value, such as 80%. Or may be a preset matching threshold read from the action template. So that different matching thresholds can be set for different motion templates.
The method for obtaining the matching value by comparing the electromyographic signals acquired in real time with the electromyographic signals of the action template is not limited, and can adopt a neural network for comparison: inputting the real-time electromyographic signals and the electromyographic signals of the action template into a neural network, respectively extracting the characteristic data of the two electromyographic signals, comparing the characteristic data item by item, and then averaging to obtain a matching value.
Optionally, the action templates in the action template data set are further provided with a preset matching number, and when the number of the electromyographic signals meeting the matching condition is greater than the preset matching number, the action template is used as the action template matched with the electromyographic signals. For example: and after three electromyographic signals which meet the matching condition are set in the action template, the electromyographic signals matched with the action template are considered to be collected.
Step S300: and controlling the motion of the intelligent artificial limb according to the current motion template.
Specifically, after the action template currently used by the intelligent artificial limb is obtained, the driving signal included in the current action template is searched, and the driving signal is used as a signal source to drive a motor, an air pump or an oil pressure pump and other mechanisms of the corresponding power joint, so that the purpose of controlling the motion of the intelligent artificial limb is achieved.
Optionally, although the matching value of the collected electromyographic signals and the electromyographic signals of the current action template meets a preset matching threshold, the energy values of the electromyographic signals are still different, and the intensity of the intelligent artificial limb action, such as the force for grasping an object, can be controlled according to the ratio of the energy value of the electromyographic signals to the energy value of the electromyographic signals of the current action template.
As can be seen from the above, in this embodiment, the electromyographic signal is not directly analyzed, and then the intelligent artificial limb is controlled according to the analysis result, but the intelligent artificial limb is controlled to maintain the current motion through the motion template on the basis of the pre-constructed motion template, so that the intelligent artificial limb maintains the current motion in the process of electromyographic signal delay matching. The myoelectric signal is not matched with the action template, and the new action template is matched only when the myoelectric signal is not matched with the action template for a plurality of times by using time inertia delay, so that the action stability of the intelligent artificial limb is prevented from being influenced by severe fluctuation of the signal.
In one embodiment, as shown in fig. 2, calculating a matching value between the electromyographic signal and the motion template specifically includes the following steps:
step S210: respectively obtaining a first electromyographic potential curve and a second electromyographic potential curve based on the electromyographic potential of each sampling point in the electromyographic signal and the electromyographic potential of each sampling point in the electromyographic signal of the action template;
step S220: and calculating the fitting degree between the first electromyographic potential curve and the second electromyographic potential curve to obtain a matching value.
Specifically, when the electromyographic signals are collected, a plurality of sampling points need to be set, because each electromyographic signal sampling point can collect electromyographic potential data, the electromyographic potential data of the sampling points are connected, and an electromyographic potential curve can be obtained. The electromyographic signals in the action template are processed in the same way, and another electromyographic potential curve can be obtained. And calculating the fitting degree of the two curves to obtain the matching value of the electromyographic signal and the action template.
According to the method, the electromyographic potentials of the sampling points in the electromyographic data are connected into the electromyographic potential curve, so that the matching value is calculated according to the existing curve fitting degree algorithm, the calculation is simple, and the efficiency is high.
Furthermore, no matter what kind of electrodes are adopted, the detected signals are the vector sum of the myoelectric potentials generated by a plurality of movement units, and different myoelectric potential vectors have different influences on the action of the intelligent artificial limb, namely the weight of each myoelectric potential vector is different. Therefore, in one embodiment, when calculating the curve fitting degree, weighting processing is also performed according to the weight of each electromyogram potential, and a matching value of the electromyogram signal and the action template is obtained. The matching accuracy is improved, the fluctuation of the myoelectric signals of partial myoelectric potential caused by muscle tension can be weakened, and the misjudgment caused by the muscle tension is reduced.
Exemplary device
As shown in fig. 3, in correspondence to the above-mentioned intelligent prosthesis control method based on electromyographic signals, an embodiment of the present invention further provides an intelligent prosthesis control device based on electromyographic signals, where the intelligent prosthesis control device based on electromyographic signals includes:
a signal module 600, configured to obtain an action template change signal based on the obtained myoelectric signal, where the action template change signal includes at least two continuous matching early warning signals, and the matching early warning signal is that a matching value between the myoelectric signal and a current action template for an intelligent prosthesis is smaller than a preset matching threshold;
the matching module 610 is used for obtaining an action template matched with the electromyographic signal and updating a current action template for the intelligent artificial limb based on the action template when an action template change signal is obtained according to the electromyographic signal;
and the control module 620 is used for controlling the motion of the intelligent artificial limb according to the current motion template.
Specifically, in this embodiment, the specific functions of each module of the intelligent prosthesis control device based on the electromyographic signals may refer to the corresponding descriptions in the intelligent prosthesis control method based on the electromyographic signals, and are not described herein again.
Based on the above embodiment, the present invention further provides an intelligent terminal, and a schematic block diagram thereof may be as shown in fig. 4. The intelligent terminal comprises a processor, a memory, a network interface and a display screen which are connected through a system bus. Wherein, the processor of the intelligent terminal is used for providing calculation and control capability. The memory of the intelligent terminal comprises a nonvolatile storage medium and an internal memory. The nonvolatile storage medium stores an operating system and an intelligent artificial limb control program based on electromyographic signals. The internal memory provides environment for the operation of an operating system in a nonvolatile storage medium and an intelligent artificial limb control program based on electromyographic signals. The network interface of the intelligent terminal is used for being connected and communicated with an external terminal through a network. The intelligent artificial limb control program based on the electromyographic signals realizes the steps of any one of the intelligent artificial limb control methods based on the electromyographic signals when being executed by a processor. The display screen of the intelligent terminal can be a liquid crystal display screen or an electronic ink display screen.
It will be understood by those skilled in the art that the block diagram shown in fig. 4 is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation to the intelligent terminal to which the solution of the present invention is applied, and a specific intelligent terminal may include more or less components than those shown in the figure, or combine some components, or have a different arrangement of components.
In one embodiment, an intelligent terminal is provided, where the intelligent terminal includes a memory, a processor, and an intelligent prosthesis control program based on electromyographic signals, stored in the memory and executable on the processor, and when executed by the processor, the intelligent prosthesis control program based on electromyographic signals performs the following operations:
acquiring an action template change signal based on the acquired electromyographic signal, wherein the action template change signal comprises at least two continuous matching early warning signals, and the matching early warning signal is that the matching value of the electromyographic signal and a current action template for the intelligent artificial limb is smaller than a preset matching threshold value;
when an action template change signal is obtained according to the electromyographic signal, an action template matched with the electromyographic signal is obtained, and a current action template used for the intelligent artificial limb is updated based on the action template;
and controlling the motion of the intelligent artificial limb according to the current motion template.
Optionally, the number of the matching early warning signals included in the action template change signal is obtained according to the current action template; and obtaining the preset matching threshold according to the current action template.
Optionally, obtaining a duration of the current action template;
and when the duration is increased by a preset time interval, reducing the preset matching threshold according to a reduction amount of a preset threshold.
Optionally, the obtaining an action template matched with the electromyographic signal includes:
acquiring an action template data set;
and matching the electromyographic signal with an electromyographic signal sample of each action template in the action template data set in sequence to obtain a matching value, and setting the action template as an action template matched with the electromyographic signal when the matching value is greater than or equal to a preset matching threshold value of the action template.
Optionally, the action templates in the action template data set are further provided with a preset matching number, when the number of the electromyographic signals meeting the matching condition is greater than the preset matching number, the action template is set as an action template matched with the electromyographic signals, and the matching condition is that the matching value of the electromyographic signals and the action template is greater than or equal to the preset matching threshold.
Optionally, the acquiring the electromyographic signal includes:
and acquiring an electromyographic signal at the set sampling frequency of the current action template.
Optionally, obtaining a matching value of the electromyographic signal and the motion template includes:
respectively obtaining a first electromyographic potential curve and a second electromyographic potential curve based on the electromyographic potential of each sampling point in the electromyographic signal and the electromyographic potential of each sampling point in the electromyographic signal of the action template;
and calculating the fitting degree between the first electromyographic potential curve and the second electromyographic potential curve to obtain the matching value.
The embodiment of the invention also provides a computer-readable storage medium, wherein an intelligent prosthesis control program based on the electromyographic signal is stored on the computer-readable storage medium, and when being executed by a processor, the intelligent prosthesis control program based on the electromyographic signal realizes the steps of any intelligent prosthesis control method based on the electromyographic signal provided by the embodiment of the invention.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by functions and internal logic of the process, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
It should be clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional units and modules is only used for illustration, and in practical applications, the above functions may be distributed as different functional units and modules according to needs, that is, the internal structure of the apparatus may be divided into different functional units or modules to implement all or part of the above described functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art would appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the above modules or units is only one type of logical function division, and the actual implementation may be implemented by another division manner, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed.
The integrated modules/units described above, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium and can implement the steps of the embodiments of the method when the computer program is executed by a processor. The computer program includes computer program code, and the computer program code may be in a source code form, an object code form, an executable file or some intermediate form. The computer readable medium may include: any entity or device capable of carrying the above-mentioned computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signal, telecommunication signal, software distribution medium, etc. It should be noted that the contents of the computer-readable storage medium can be increased or decreased as required by the legislation and patent practice in the jurisdiction.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art; the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein.
Claims (10)
1. An intelligent artificial limb control method based on electromyographic signals is characterized by comprising the following steps:
acquiring an action template change signal based on the acquired electromyographic signal, wherein the action template change signal comprises at least two continuous matching early warning signals, and the matching early warning signals are used for representing that the matching value of the electromyographic signal and a current action template for the intelligent artificial limb is smaller than a preset matching threshold value;
when an action template change signal is obtained according to the electromyographic signal, an action template matched with the electromyographic signal is obtained, and a current action template used for the intelligent artificial limb is updated based on the action template;
and controlling the motion of the intelligent artificial limb according to the current motion template.
2. An intelligent prosthetic control method based on electromyographic signals according to claim 1, wherein the number of the matching pre-warning signals included in the motion template modification signal is obtained according to the current motion template; and obtaining the preset matching threshold according to the current action template.
3. An intelligent prosthetic control method based on electromyographic signals, according to claim 1, further comprising:
obtaining the duration of the current action template;
and when the duration increases each preset time interval, reducing the preset matching threshold according to the reduction amount of the preset threshold.
4. An intelligent prosthetic control method based on electromyographic signals according to claim 1, wherein the obtaining an action template matched with the electromyographic signals comprises:
acquiring an action template data set;
and sequentially matching the electromyographic signals with electromyographic signal samples of each action template in the action template data set to obtain a matching value, and setting the action template as an action template matched with the electromyographic signals when the matching value is greater than or equal to a preset matching threshold value of the action template.
5. An intelligent artificial limb control method based on electromyographic signals according to claim 4, wherein the action templates in the action template data set are further provided with a preset matching number, and when the number of electromyographic signals meeting a matching condition is greater than the preset matching number, the action template is set as an action template matched with the electromyographic signals, and the matching condition is that the matching value of the electromyographic signals and the action template is greater than or equal to the preset matching threshold.
6. An intelligent prosthetic control method based on electromyographic signals according to claim 1, wherein the electromyographic signals are acquired at a set sampling frequency of the current motion template.
7. An intelligent prosthetic control method based on electromyographic signals according to claim 1, wherein obtaining a matching value of the electromyographic signals to the action template comprises:
respectively obtaining a first electromyographic potential curve and a second electromyographic potential curve based on the electromyographic potential of each sampling point in the electromyographic signal and the electromyographic potential of each sampling point in the electromyographic signal of the action template;
and calculating the fitting degree between the first electromyographic potential curve and the second electromyographic potential curve to obtain the matching value.
8. Intelligent artificial limb control device based on electromyographic signals, characterized in that the device comprises:
the system comprises a signal module, a signal processing module and a signal processing module, wherein the signal module is used for obtaining an action template change signal based on an obtained electromyographic signal, the action template change signal comprises at least two continuous matching early warning signals, and the matching early warning signals are that the matching value of the electromyographic signal and a current action template for the intelligent artificial limb is smaller than a preset matching threshold value;
the matching module is used for obtaining an action template matched with the electromyographic signal and updating a current action template for the intelligent artificial limb based on the action template when an action template change signal is obtained according to the electromyographic signal;
and the control module is used for controlling the motion of the intelligent artificial limb according to the current motion template.
9. An intelligent terminal, characterized in that the intelligent terminal comprises a memory, a processor and an intelligent artificial limb control program based on electromyographic signals, wherein the intelligent artificial limb control program based on electromyographic signals is stored on the memory and can run on the processor, and when the intelligent artificial limb control program based on electromyographic signals is executed by the processor, the steps of the intelligent artificial limb control method based on electromyographic signals according to any one of claims 1 to 7 are realized.
10. Computer readable storage medium, characterized in that the computer readable storage medium stores thereon an intelligent artificial limb control program based on electromyographic signals, the intelligent artificial limb control program based on electromyographic signals implementing the steps of the intelligent artificial limb control method based on electromyographic signals according to any one of claims 1 to 7 when being executed by a processor.
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