CN115251957A - Method, device and storage medium for adjusting sampling frequency step by step - Google Patents
Method, device and storage medium for adjusting sampling frequency step by step Download PDFInfo
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/389—Electromyography [EMG]
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6802—Sensor mounted on worn items
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
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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
Abstract
The invention discloses a method, a device and a storage medium for gradually adjusting sampling frequency, wherein the method comprises the following steps: acquiring the duration and the initial sampling frequency of electromyographic signal data; obtaining a frequency reduction grade according to the duration of the electromyographic signal data; and obtaining the sampling frequency according to the frequency reduction grade and the initial sampling frequency. According to the invention, by establishing the relationship between the duration time of the electromyographic signal data and the frequency reduction grade, the sampling frequency is adjusted step by step so as to finely control the sampling frequency, and the endurance time of the intelligent artificial limb is improved.
Description
Technical Field
The invention relates to the technical field of intelligent artificial limbs, in particular to a method and a device for adjusting sampling frequency step by step and a storage medium.
Background
The intelligent artificial limb is an intelligent product which utilizes the modern biological electronics technology to connect the human nervous system with an intelligent device so as to replace the missing or damaged body part in a mode of embedding and hearing brain instructions. The intelligent artificial limb can identify the movement intention of the wearer by extracting the neuromuscular signals of the wearer and convert the movement schematic diagram into the movement of the intelligent artificial limb, so that the intelligent artificial limb is smart and intelligent, and the body moves with the mind.
However, during the use of the existing intelligent artificial limb, because the relationship between the electromyogram signal duration of an intelligent artificial limb wearer and the level of the sampling frequency is not established, the sampling frequency cannot be adjusted step by step, so that the sampling frequency cannot be finely controlled, the power consumption is wasted, and the endurance time of the intelligent artificial limb is influenced.
Accordingly, the prior art is yet to be improved and developed.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a method, an apparatus and a storage medium for adjusting a sampling frequency step by step, aiming at solving the problem that the sampling frequency cannot be adjusted step by step in the use process of an intelligent artificial limb, so that the sampling frequency cannot be finely controlled, the power consumption is wasted, and the endurance time of the intelligent artificial limb is affected.
The technical scheme adopted by the invention for solving the technical problem is as follows:
in a first aspect, the present invention provides a method for adjusting a sampling frequency step by step, wherein the method includes:
acquiring the duration and the initial sampling frequency of electromyographic signal data; the initial sampling frequency is the initial frequency for acquiring the electromyographic signal data;
obtaining a frequency reduction grade according to the duration time of the electromyographic signal data; wherein the down-conversion level is a level that reduces the sampling frequency;
and obtaining the sampling frequency according to the frequency reduction grade and the initial sampling frequency.
In one implementation, the acquiring duration and initial sampling frequency of electromyographic signal data includes:
acquiring first electromyographic signal data and obtaining the duration of the first electromyographic signal data;
obtaining a first action template according to the first electromyographic signal data; the first action template is used for storing actions matched with the first electromyographic signal data.
In one implementation manner, before obtaining the down-conversion level according to the duration of the electromyographic signal data, the method further includes:
presetting a frequency reduction template; the frequency reduction template is provided with a corresponding relation between the duration of the electromyographic signal data and the frequency reduction grade.
In one implementation, the deriving a down-conversion level according to the duration of the electromyographic signal data includes:
if the duration time of the electromyographic signal data is greater than or equal to a preset duration time threshold value, matching the duration time of the electromyographic signal data with the frequency reduction template;
and obtaining the frequency reduction grade according to the corresponding relation between the duration of the electromyographic signal data in the frequency reduction template and the frequency reduction grade.
In one implementation, the obtaining a sampling frequency according to the down-conversion level and the initial sampling frequency includes:
obtaining the sampling frequency of
(ii) a Wherein the content of the first and second substances,
in order to be able to determine the initial sampling frequency,
is a predetermined fixed ratio between the lower one-stage sampling frequency and the adjacent higher one-stage sampling frequency, and
，
is the down conversion level, and
。
in one implementation, the method further comprises:
acquiring second electromyographic signal data, and matching the second electromyographic signal data with the first action template to obtain similarity;
and comparing the similarity with a preset comparison threshold value of a first action template, and if the similarity is smaller than the comparison threshold value of the first action template, gradually adjusting the sampling frequency.
In one implementation, the step-by-step adjusting the sampling frequency if the similarity is smaller than the comparison threshold of the first action template includes:
if the similarity is smaller than the comparison threshold of the first action template, adjusting the sampling frequency to be
(ii) a Wherein, the first and the second end of the pipe are connected with each other,
in order to be able to determine the initial sampling frequency,
is a predetermined fixed ratio between the lower one-stage sampling frequency and the adjacent higher one-stage sampling frequency, and
，
the frequency reduction grade for obtaining the second electromyographic signal data time, and
。
in a second aspect, an embodiment of the present invention further provides an apparatus for adjusting a sampling frequency step by step, where the apparatus includes:
the duration and initial sampling frequency acquisition module is used for acquiring the duration and initial sampling frequency of the electromyographic signal data; the initial sampling frequency is the initial frequency for acquiring the electromyographic signal data;
the frequency reduction grade acquisition module is used for obtaining a frequency reduction grade according to the duration time of the electromyographic signal data; wherein the down-conversion level is a level of reducing the sampling frequency;
and the sampling frequency acquisition module is used for obtaining the sampling frequency according to the frequency reduction grade and the initial sampling frequency.
In a third aspect, an embodiment of the present invention further provides an intelligent prosthesis, where the intelligent prosthesis includes a memory, a processor, and a program of a method for gradually adjusting a sampling frequency, which is stored in the memory and is executable on the processor, and when the processor executes the program of the method for gradually adjusting a sampling frequency, the steps of the method for gradually adjusting a sampling frequency are implemented as in any one of the above.
In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores a program of a method for adjusting a sampling frequency step by step, and when the program of the method for adjusting a sampling frequency step by step is executed by a processor, the steps of the method for adjusting a sampling frequency step by step as described in any one of the above are implemented.
Has the beneficial effects that: compared with the prior art, the invention provides a method for adjusting the sampling frequency step by step, which can adjust the sampling frequency step by establishing the relationship between the duration time of the electromyographic signal data and the frequency reduction grade, realize the fine control of the sampling frequency and improve the endurance time of the intelligent artificial limb. First, the duration of electromyographic signal data is obtained to determine when the intelligent prosthesis wearer maintains the same motion. And then, obtaining a frequency reduction grade according to the duration time of the electromyographic signal data, and realizing the gradual reduction of the sampling frequency by establishing a relation between the duration time of the electromyographic signal data and the frequency reduction grade so as to further realize the fine control of the sampling frequency. And finally, obtaining the sampling frequency according to the frequency reduction grade and the initial sampling frequency, so that the energy consumption can be reduced by adjusting the sampling frequency, and the endurance time of the intelligent artificial limb is prolonged.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart illustrating a method for adjusting a sampling frequency step by step according to an embodiment of the present invention.
Fig. 2 is a network architecture diagram of an apparatus for adjusting a sampling frequency step by step according to an embodiment of the present invention.
Fig. 3 is a schematic block diagram of an intelligent prosthesis provided by an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and effects of the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The current intelligent artificial limb has the advantages that the sampling frequency has a large influence on power consumption during use, the adjusted sampling frequency can be generally directly specified when the sampling frequency is adjusted, a progressive dynamic adjustment process is not adopted, and the sampling frequency cannot be adjusted step by step due to the fact that the relation between the myoelectric signal duration time and the sampling frequency grade of an intelligent artificial limb wearer is not established, so that the problems that fine control can not be carried out on the sampling frequency, the power consumption is wasted, and the endurance time of the intelligent artificial limb is influenced are solved.
Therefore, in order to solve the above problem, the present embodiment provides a method for adjusting the sampling frequency step by step. By establishing the relationship between the duration time of the electromyographic signal data and the frequency reduction grade, the sampling frequency can be adjusted step by step, the fine control of the sampling frequency is realized, and the endurance time of the intelligent artificial limb is prolonged. In specific implementation, the embodiment firstly obtains the duration of electromyographic signal data to determine the time for the intelligent prosthesis wearer to keep the same action. And then, a frequency reduction grade is obtained according to the duration time of the electromyographic signal data, and the sampling frequency can be reduced step by establishing a relation between the duration time of the electromyographic signal data and the frequency reduction grade, so that the sampling frequency is finely controlled. And finally, obtaining the sampling frequency according to the frequency reduction grade and the initial sampling frequency, so that the energy consumption can be reduced by adjusting the sampling frequency, and the endurance time of the intelligent artificial limb is prolonged.
Exemplary method
The embodiment provides a method for adjusting the sampling frequency step by step, and the embodiment can be applied to an intelligent artificial limb. As shown in fig. 1, the method comprises the steps of:
s100, acquiring the duration and the initial sampling frequency of electromyographic signal data; the initial sampling frequency is the initial frequency for acquiring the electromyographic signal data.
Electromyographic signal data (EMG) is a superposition of Motor Unit Action Potentials (MUAP) in a multitude of muscle fibers, both temporally and spatially. The surface electromyographic Signal (SEMG) is the comprehensive effect of the EMG of superficial muscles and the electrical activity of nerve trunks on the surface of skin, and can reflect the activity of the neuromuscular to a certain extent. The electromyographic signal data has important practical value in the aspects of clinical medicine, human-computer efficiency, rehabilitation medicine, sports science and the like. In the embodiment, the electromyographic signal data is analyzed to obtain the action information, so that the intelligent artificial limb is controlled.
The intelligent artificial limb periodically acquires electromyographic signal data sent by a wearer according to the sampling frequency, and the electromyographic signal data are acquired more timely when the sampling frequency is higher, but the energy consumption is higher, so that the endurance time of the intelligent artificial limb can be shortened. When the sampling frequency is low, the problem of untimely sampling can be brought while the endurance time of the intelligent artificial limb is prolonged. When the intelligent artificial limb is initialized, the initial sampling frequency is set based on the common use habit of the intelligent artificial limb wearer.
Specifically, in this embodiment, the duration of the electromyographic signal data is first obtained, where the duration is an uninterrupted occurrence time of the same electromyographic signal, and if the intelligent prosthesis wearer sends an electromyographic signal different from the current electromyographic signal, the calculation of the duration is terminated. The embodiment acquires the initial sampling frequency of the intelligent artificial limb as a reference value.
In an implementation manner, the step S100 in this embodiment includes the following steps:
s101, acquiring first electromyographic signal data and obtaining the duration time of the first electromyographic signal data;
specifically, the duration of the first electromyographic signal data is the time for which the timing is started from the time when the first electromyographic signal data is acquired so that the acquired first electromyographic signal data continuously occurs, and when the first electromyographic signal data is terminated, the timing is terminated.
Step S102, obtaining a first action template according to the first electromyographic signal data; the first action template is used for storing actions matched with the first electromyographic signal data.
Specifically, the example firstly obtains the first electromyographic signal data, obtains the duration of the first electromyographic signal data, and simultaneously obtains a first action template matched with the first electromyographic signal through the analysis of the first electromyographic signal data, namely the similarity between the first electromyographic signal data and the first action template is greater than the comparison threshold of the first action template.
For example, the first electromyographic signal data A1 is acquired, and the time for monitoring uninterrupted occurrence of the first electromyographic signal A1 from the moment of acquiring the first electromyographic signal data A1 is 30 seconds, so that the duration of the first electromyographic signal data A1 is 30 seconds, and meanwhile, the initial sampling frequency set when the intelligent artificial limb is initialized is acquired as 3 times/second. And matching the first electromyographic signal data A1 with an action template library to obtain a comparison threshold value of which the similarity between the first electromyographic signal data A1 and the action template B1 exceeds, namely, considering that the first electromyographic signal data A1 is matched with actions in the action template B1, and obtaining the action template B1 as a first action template.
In an implementation manner, the step S100 in this embodiment includes the following steps before:
step S103, presetting a frequency reduction template; the frequency reduction template is provided with a corresponding relation between the duration of the electromyographic signal data and the frequency reduction grade.
Specifically, the duration of the electromyographic signal data can reflect the action intention of the intelligent prosthesis wearer. Generally, if the duration of electromyographic signal data is long, which means that the current action of an intelligent prosthesis wearer is kept unchanged, a low sampling frequency can meet the acquisition requirement; if the duration of the electromyographic signal data is short, the intelligent artificial limb wearer is meant to switch actions frequently, and the sampling requirement can be met only by the high sampling frequency. This requires quantifying the relationship between the duration of electromyogram signal data and the down-conversion level by setting a down-conversion template in advance.
For example, when the electromyogram signal duration is set to be 1-3 seconds, the frequency reduction level is 1-level frequency reduction, when the electromyogram signal duration is 4-6 seconds, the frequency reduction level is 2-level frequency reduction, when the electromyogram signal duration is 7-9 seconds, the frequency reduction level is 3-level frequency reduction, and so on.
It should be noted that, if the user does not set the frequency-reducing template, the factory default template of the intelligent prosthesis is called as the frequency-reducing template. In the frequency reduction template, the corresponding relation between the duration of the electromyographic signal data and the frequency reduction level can be set for different action templates. Therefore, the frequency reduction grade can be adjusted according to different characteristics of different actions, so that accurate control of sampling different sampling frequencies of different action types is realized.
For example, if the action template B1 represents a more frequent action of playing basketball, and the action template B2 represents a relatively static action type such as holding a mouse, the relationship between the duration of the electromyographic signal data in the down-conversion template and the down-conversion level may be set for each of B1 and B2. Specifically, when the action template is B1, the frequency reduction level is 1-level frequency reduction when the electromyogram signal duration is 8-10 seconds, and the frequency reduction level is 2-level frequency reduction when the electromyogram signal duration is 11-20 seconds. When the action template is B2, the frequency reduction grade is 1-level frequency reduction when the duration of the electromyographic signals is 1-2 seconds, and the frequency reduction grade is 2-level frequency reduction when the duration of the electromyographic signals is 3-4 seconds. Therefore, the sampling frequency of the basketball playing motion with the motion template B1 is reduced less, and the sampling frequency of the motion of B2 holding a mouse is reduced more quickly.
S200, obtaining a frequency reduction grade according to the duration time of the electromyographic signal data; wherein the down-conversion level is a level that reduces the sampling frequency.
In an implementation manner, the step S200 in this embodiment includes the following steps:
step S201, if the duration time of the electromyographic signal data is greater than or equal to a preset duration time threshold value, matching the duration time of the electromyographic signal data with the frequency reduction template;
step S202, obtaining the frequency reduction grade according to the corresponding relation between the duration of the electromyographic signal data in the frequency reduction template and the frequency reduction grade.
Specifically, the duration threshold is preset in this embodiment, and is used to limit the duration of the shortest electromyographic signal data that is allowed to be down-converted, so that the fluctuation of the sampling frequency is prevented from being too sensitive. And when the duration of the electromyographic signal data is greater than or equal to a preset duration threshold, matching the duration of the electromyographic signal data with a frequency reduction template, namely finding a frequency reduction grade corresponding to the duration of the electromyographic signal data in the frequency reduction template according to the duration of the electromyographic signal data.
For example, when the preset duration threshold is 1 second and the duration of the electromyographic signal is 1-3 seconds, the frequency reduction level is 1-level frequency reduction. When the duration of acquiring the electromyographic signal data A1 is 0.5 second, the duration of the electromyographic signal data does not need to be matched with a frequency reduction template, and the current sampling frequency is kept. When the duration of acquiring the electromyographic signal data A1 is 2 seconds, matching is carried out in a frequency reduction template, and the frequency reduction grade corresponding to the electromyographic signal data A1 is level 1 frequency reduction. If the duration of the electromyogram signal data A1 is extended to 5 seconds, the down-conversion level corresponding to 5 seconds is 2, as can be seen from the above example.
Specifically, if the correspondence between the duration of the electromyographic signal data and the down-conversion level is set in the down-conversion template according to the action template, the corresponding down-conversion level is determined according to the action template, and the sampling frequency is obtained according to the down-conversion level and the initial sampling frequency.
For example, if the action template is B1, the action template B1 represents a basketball playing action, and since the electromyographic signal data generated during the basketball playing is frequent, the down-conversion level of the action template B1 may be set to be lower if the same duration is artificially set. Specifically, a duration threshold value which is preset to be B1 of the action template is 8 seconds, when the duration of the electromyogram signal exceeds 8 seconds, and the action template is matched with the down-conversion level in the down-conversion template, the corresponding relation between the duration of the electromyogram signal data and the down-conversion level is obtained, and accordingly the down-conversion level is 1 level.
And step S300, obtaining a sampling frequency according to the frequency reduction grade and the initial sampling frequency.
Specifically, the frequency reduction level may reflect an amplitude of the reduced sampling frequency, and after the frequency reduction level is obtained, the initial sampling frequency may be further adjusted according to the frequency reduction level to obtain the sampling frequency. In this embodiment, the down-conversion levels are based on the initial sampling frequency.
For example, if the down-conversion level is 3 levels and the initial sampling frequency is 3 times/second, the level of 3 sampling frequencies is adjusted on the basis of 3 times/second to obtain the sampling frequency.
In one implementation manner, the step S300 in this embodiment includes the following steps:
step S301, obtaining the sampling frequency of
(ii) a Wherein the content of the first and second substances,
for the purpose of the initial sampling frequency, the frequency of the sampling,
is a predetermined fixed ratio between the lower one-stage sampling frequency and the adjacent higher one-stage sampling frequency, and
，
is the down conversion level, and
。
specifically, a fixed ratio between a lower one-stage sampling frequency and an adjacent higher one-stage sampling frequency is set, that is, a fixed ratio between the lower one-stage sampling frequency and the adjacent higher one-stage sampling frequency is set
Sampling frequency represented by stage down-conversion level and
the ratio between the sampling frequencies represented by the stepped down stages is a fixed value
. Due to the fact that
Therefore, it is
The sampling frequency represented by the stage down-conversion level is greater than
The sampling frequency represented by the down-conversion level is lower, i.e. the higher the down-conversion level is. Then, the initial sampling frequency is taken as a reference to be adjusted to obtain the sampling frequency of
。
For example, as described in the above example, the initial sampling frequency
Is 3 times/second, if the electromyographic signal data A1 corresponds to the frequency reductionThe level being a level-1 downconversion, i.e.
And is and
then the sampling frequency is adjusted to
Times/second.
In an implementation manner, the method in this embodiment further includes the following steps:
step M100, acquiring second electromyographic signal data, and matching the second electromyographic signal data with the first action template to obtain similarity;
step M200, comparing the similarity with a preset comparison threshold of a first action template, and if the similarity is smaller than the comparison threshold of the first action template, adjusting the sampling frequency step by step.
Specifically, when the first electromyographic signal data is changed, it needs to be determined again whether the first action template is not matched with the second electromyographic signal data acquired again. The determination method is to match the second electromyographic signal data with the first action template to obtain a similarity, wherein the similarity is used for quantifying the similarity of the electromyographic signal data and the action in the action template. If the similarity is smaller than the comparison threshold of the first action template, it indicates that the second electromyographic signal data is not matched with the first action template, that is, the wearer of the intelligent artificial limb has changed a new action, and at this time, the sampling frequency needs to be adjusted step by step. It should be noted that, when the second electromyogram signal data does not match the first action template for a plurality of times, the down-conversion level is only up-regulated by one level each time until the sampling frequency is restored to the original sampling frequency.
For example, the second electromyographic signal data is obtained as A2, the A2 is matched with the first motion template B1, the similarity is 80%, it can be known that the A2 and the B1 cannot be matched according to a preset comparison threshold of 88%, the motion of the intelligent prosthesis wearer is changed, if the down-conversion level is level 2 at this time, the down-conversion level is adjusted to level 1, and the sampling frequency corresponding to the level 1 down-conversion level is obtained again. If the second electromyographic signal data is detected to be A3 again, matching the A3 with the first action template B1 to obtain that the similarity is 60%, and according to the preset comparison threshold value of 88%, the A3 and the B1 can not be matched, and the action of the intelligent prosthesis wearer is changed again, so that the sampling frequency is adjusted to be the initial sampling frequency.
In one implementation manner, the step M200 in this embodiment includes the following steps:
step M201, if the similarity is smaller than the comparison threshold of the first action template, adjusting the sampling frequency to be
(ii) a Wherein the content of the first and second substances,
for the purpose of the initial sampling frequency, the frequency of the sampling,
is a predetermined fixed ratio between the lower one-stage sampling frequency and the adjacent higher one-stage sampling frequency, and
，
the frequency reduction grade for obtaining the second electromyographic signal data time, and
。
specifically, the sampling frequency is adjusted step by step in this embodiment, and if the down-conversion level at the time of acquiring the second electromyographic signal data is as follows
When the similarity is smaller than the comparison threshold of the first action template, the comparison result is considered asThe motion of the user is changed, the duration of the first electromyogram signal data is set to 0, and the sampling frequency is adjusted to
So as to realize the step-by-step adjustment of the sampling frequency until the original sampling frequency is restored.
For example, if the frequency reduction level at the time of acquiring the second electromyographic signal data A2 is as follows
When the similarity 80% between the second electromyographic signal data A2 and the first action template B1 is smaller than the comparison threshold value 88%, the duration time of the first electromyographic signal data is set to 0, and the sampling frequency is adjusted to be 0
Second/second, the current downconversion level is 1. If the second electromyographic signal data A4 is continuously acquired, when the similarity 90% of the second electromyographic signal data A4 and the first action template B1 is greater than the comparison threshold value 88%, keeping the current sampling frequency as
Times/second. If the second electromyographic signal data A4 is continuously acquired, when the similarity 70% between the second electromyographic signal data A4 and the first action template B1 is smaller than the comparison threshold value 88%, the sampling frequency is adjusted to be
Second/second, i.e., adjusted to the initial sampling frequency.
Exemplary devices
As shown in fig. 2, the present embodiment also provides an apparatus for adjusting a sampling frequency step by step, the apparatus including:
a duration and initial sampling frequency acquisition module 10, configured to acquire a duration and an initial sampling frequency of electromyographic signal data; the initial sampling frequency is the initial frequency for acquiring the electromyographic signal data;
the frequency reduction grade acquisition module 20 is configured to obtain a frequency reduction grade according to the duration of the electromyographic signal data; wherein the down-conversion level is a level that reduces the sampling frequency;
and the sampling frequency obtaining module 30 is configured to obtain a sampling frequency according to the frequency reduction level and the initial sampling frequency.
In one implementation, the duration and initial sampling frequency acquisition module 10 includes:
the duration acquisition unit is used for acquiring first electromyographic signal data and obtaining the duration of the first electromyographic signal data;
the first action template acquisition unit is used for obtaining a first action template according to the first electromyographic signal data; the first action template is used for storing actions matched with the first electromyographic signal data.
In one implementation, the step-by-step adjusting the sampling frequency further includes:
the frequency reducing template obtaining unit is used for presetting a frequency reducing template; the frequency reduction template is provided with a corresponding relation between the duration of the electromyographic signal data and the frequency reduction grade.
In one implementation, the down-conversion level obtaining module 20 includes:
the matching unit is used for matching the duration time of the electromyographic signal data with the frequency reduction template if the duration time of the electromyographic signal data is greater than or equal to a preset duration time threshold value;
and the frequency reduction grade acquisition unit is used for acquiring the frequency reduction grade according to the corresponding relation between the duration of the electromyographic signal data in the frequency reduction template and the frequency reduction grade.
In one implementation, the sampling frequency acquisition module 30 includes:
a sampling frequency obtaining unit for obtaining the sampling frequency of
(ii) a Wherein the content of the first and second substances,
for the purpose of the initial sampling frequency, the frequency of the sampling,
is a fixed ratio between a preset lower one-stage sampling frequency and an adjacent higher one-stage sampling frequency, and
，
is the down conversion level, and
。
in one implementation manner, the apparatus for gradually adjusting the sampling frequency further includes:
the similarity obtaining unit is used for obtaining second electromyographic signal data and matching the second electromyographic signal data with the first action template to obtain similarity;
and the sampling frequency adjusting unit is used for comparing the similarity with a preset comparison threshold of a first action template, and if the similarity is smaller than the comparison threshold of the first action template, the sampling frequency is adjusted step by step.
In one implementation, the sampling frequency adjustment unit includes:
a sampling frequency adjusting subunit, configured to adjust the sampling frequency to be equal to the first action template if the similarity is smaller than the comparison threshold of the first action template
(ii) a Wherein the content of the first and second substances,
for the purpose of the initial sampling frequency, the frequency of the sampling,
is a fixed ratio between a preset lower one-stage sampling frequency and an adjacent higher one-stage sampling frequency, and
，
the frequency reduction grade for obtaining the second electromyographic signal data time, and
。
based on the above embodiments, the present invention further provides an intelligent prosthesis, whose functional block diagram can be shown in fig. 3. The intelligent artificial limb comprises a processor, a memory, a network interface and a sensor which are connected through a system bus. Wherein the processor of the intelligent prosthesis is used for providing calculation and control capability. The memory of the intelligent artificial limb comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the intelligent artificial limb is used for communicating with an external terminal through network connection. The computer program is executed by a processor to implement a method of adjusting the sampling frequency step by step. The sensor of the intelligent artificial limb is arranged in the intelligent artificial limb in advance and used for detecting myoelectric control signals of internal equipment.
It will be appreciated by those skilled in the art that the schematic block diagram shown in fig. 3 is only a block diagram of a portion of the structure associated with the inventive arrangements and is not intended to limit the intelligent prostheses to which the inventive arrangements may be applied, and that a particular intelligent prosthesis may include more or fewer components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, an intelligent prosthesis is provided, the intelligent prosthesis includes a memory, a processor and a program stored in the memory and executable on the processor for adjusting a sampling frequency step by step, and when the processor executes the program for adjusting the sampling frequency step by step, the following operation instructions are implemented:
acquiring the duration and the initial sampling frequency of electromyographic signal data; the initial sampling frequency is the initial frequency for acquiring the electromyographic signal data;
obtaining a frequency reduction grade according to the duration time of the electromyographic signal data; wherein the down-conversion level is a level of reducing the sampling frequency;
and obtaining the sampling frequency according to the frequency reduction grade and the initial sampling frequency.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, operational databases, or other media used in embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct Rambus Dynamic RAM (DRDRAM), and Rambus Dynamic RAM (RDRAM).
In summary, the present invention discloses a method, an apparatus and a storage medium for adjusting a sampling frequency step by step, wherein the method comprises: acquiring the duration and the initial sampling frequency of electromyographic signal data; obtaining a frequency reduction grade according to the duration time of the electromyographic signal data; and obtaining the sampling frequency according to the frequency reduction grade and the initial sampling frequency. According to the method, the relation between the electromyographic signal data duration and the frequency reduction grade is established, so that the sampling frequency is adjusted step by step, the sampling frequency is finely controlled, and the endurance time of the intelligent artificial limb is prolonged.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, and not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for incrementally adjusting a sampling frequency, the method comprising:
acquiring the duration and the initial sampling frequency of electromyographic signal data; the initial sampling frequency is the initial frequency for acquiring the electromyographic signal data;
obtaining a frequency reduction grade according to the duration time of the electromyographic signal data; wherein the down-conversion level is a level that reduces the sampling frequency;
and obtaining the sampling frequency according to the frequency reduction grade and the initial sampling frequency.
2. The method for gradually adjusting the sampling frequency according to claim 1, wherein the acquiring the duration and the initial sampling frequency of the electromyographic signal data comprises:
acquiring first electromyographic signal data and obtaining the duration of the first electromyographic signal data;
obtaining a first action template according to the first electromyographic signal data; the first action template is used for storing actions matched with the first electromyographic signal data.
3. The method for gradually adjusting the sampling frequency according to claim 1, wherein before obtaining the down-conversion level according to the duration of the electromyographic signal data, the method further comprises:
presetting a frequency reduction template; the frequency reduction template is provided with a corresponding relation between the duration of the electromyographic signal data and the frequency reduction grade.
4. The method for gradually adjusting sampling frequency according to claim 3, wherein the obtaining of the frequency reduction level according to the duration of the electromyographic signal data comprises:
if the duration time of the electromyographic signal data is greater than or equal to a preset duration time threshold value, matching the duration time of the electromyographic signal data with the frequency reduction template;
and obtaining the frequency reduction grade according to the corresponding relation between the duration of the electromyographic signal data in the frequency reduction template and the frequency reduction grade.
5. The method of adjusting the sampling frequency step by step according to claim 2, wherein the obtaining the sampling frequency according to the down-conversion level and the initial sampling frequency comprises:
obtaining the sampling frequency of
(ii) a Wherein, the first and the second end of the pipe are connected with each other,
in order to be able to determine the initial sampling frequency,
is a predetermined fixed ratio between the lower one-stage sampling frequency and the adjacent higher one-stage sampling frequency, and
，
is the down conversion level, and
。
6. the method for incrementally adjusting sampling frequency as recited in claim 5, further comprising:
acquiring second electromyographic signal data, and matching the second electromyographic signal data with the first action template to obtain similarity;
and comparing the similarity with a preset comparison threshold value of a first action template, and if the similarity is smaller than the comparison threshold value of the first action template, gradually adjusting the sampling frequency.
7. The method of claim 6, wherein the step-by-step adjusting the sampling frequency if the similarity is smaller than the comparison threshold of the first motion template comprises:
if the similarity is smaller than the comparison threshold of the first action template, adjusting the sampling frequency to be
(ii) a Wherein the content of the first and second substances,
in order to be able to determine the initial sampling frequency,
is a predetermined fixed ratio between the lower one-stage sampling frequency and the adjacent higher one-stage sampling frequency, and
，
for obtaining the frequency reduction grade of the second electromyographic signal data time, and
。
8. an apparatus for incrementally adjusting a sampling frequency, the apparatus comprising:
the duration and initial sampling frequency acquisition module is used for acquiring the duration and initial sampling frequency of the electromyographic signal data; the initial sampling frequency is the initial frequency for acquiring the electromyographic signal data;
the frequency reduction grade acquisition module is used for acquiring a frequency reduction grade according to the duration time of the electromyographic signal data; wherein the down-conversion level is a level that reduces the sampling frequency;
and the sampling frequency acquisition module is used for obtaining the sampling frequency according to the frequency reduction grade and the initial sampling frequency.
9. An intelligent prosthesis, comprising a memory, a processor and a program of a method of incrementally adjusting sampling frequency stored in the memory and executable on the processor, the processor when executing the program of the method of incrementally adjusting sampling frequency implementing the steps of the method of incrementally adjusting sampling frequency as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, having stored thereon a program of a method of stepwise adjusting a sampling frequency, which when executed by a processor, carries out the steps of the method of stepwise adjusting a sampling frequency according to any of claims 1-7.
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