CN113694376B - Self-feedback physiotherapy instrument and working method thereof - Google Patents
Self-feedback physiotherapy instrument and working method thereof Download PDFInfo
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- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N1/00—Electrotherapy; Circuits therefor
- A61N1/18—Applying electric currents by contact electrodes
- A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
- A61N1/36—Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
- A61N1/36014—External stimulators, e.g. with patch electrodes
- A61N1/3603—Control systems
- A61N1/36031—Control systems using physiological parameters for adjustment
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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
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
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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
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/021—Measuring pressure in heart or blood vessels
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
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- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/107—Measuring physical dimensions, e.g. size of the entire body or parts thereof
- A61B5/1072—Measuring physical dimensions, e.g. size of the entire body or parts thereof measuring distances on the body, e.g. measuring length, height or thickness
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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
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/14542—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring blood gases
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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
- A61B5/369—Electroencephalography [EEG]
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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
- A61B5/369—Electroencephalography [EEG]
- A61B5/372—Analysis of electroencephalograms
- A61B5/374—Detecting the frequency distribution of signals, e.g. detecting delta, theta, alpha, beta or gamma waves
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4836—Diagnosis combined with treatment in closed-loop systems or methods
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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
Abstract
The invention discloses a self-feedback physiotherapy instrument, which belongs to the technical field of physiotherapy instruments and comprises an information acquisition module, an information processing module and a feedback module; the information acquisition module comprises a data acquisition unit, a brain wave acquisition unit and a heart acquisition unit, wherein the data acquisition unit is used for acquiring data information of a user; the brain wave acquisition unit is used for acquiring brain wave information of a user; the heart acquisition unit is used for acquiring heart information of a user; the information processing module comprises a data processing unit, a brain wave processing unit and a heart processing unit, and the data processing unit is used for preprocessing and calculating the acquired data information to obtain a data coefficient; the brain wave processing unit is used for preprocessing and calculating the collected brain wave information to obtain a brain wave coefficient; the invention also discloses a working method of the self-feedback physiotherapy instrument; the invention is used for solving the technical problem of poor physical therapy effect of the physical therapy instrument in the existing scheme.
Description
Technical Field
The invention relates to the technical field of physiotherapy instruments, in particular to a self-feedback physiotherapy instrument and a working method thereof.
Background
The physiotherapy instrument is a device which acts physical factors on a human body to improve the health state of the human body, and the common physical factors comprise electricity, sound, light, magnetism, water, pressure and the like.
When the existing physiotherapy instrument is used, the comprehensive monitoring and analysis are not carried out on the body states of different users, so that the physiotherapy instrument cannot automatically adjust the physiotherapy of different users, and the physiotherapy effect of the physiotherapy instrument is poor.
Disclosure of Invention
The invention aims to provide a self-feedback physiotherapy instrument and a working method thereof, and solves the following technical problems: how to solve the not good technical problem of physiotherapy effect of physiotherapy equipment among the current scheme.
The purpose of the invention can be realized by the following technical scheme:
a self-feedback physiotherapy instrument comprises an information acquisition module, an information processing module and a feedback module; the information acquisition module comprises a data acquisition unit, a brain wave acquisition unit and a heart acquisition unit, wherein the data acquisition unit is used for acquiring data information of a user; the brain wave acquisition unit is used for acquiring brain wave information of a user; the heart acquisition unit is used for acquiring heart information of a user; the information processing module comprises a data processing unit, a brain wave processing unit and a heart processing unit, and the data processing unit is used for preprocessing and calculating the acquired data information to obtain a data coefficient; the brain wave processing unit is used for preprocessing and calculating the collected brain wave information to obtain a brain wave coefficient; the heart processing unit carries out preprocessing and calculation on the acquired heart information to obtain a heart coefficient; obtaining a feedback value by using the data coefficient, the brain wave coefficient and the heart coefficient; the feedback module adjusts the operation of the physiotherapy instrument according to the feedback value.
The device further comprises a storage module and a prompt module, wherein the storage module is used for storing preset data and acquired data; the prompting module is used for prompting the operation of the physiotherapy instrument.
Furthermore, the data information comprises gender data, age data, height data and weight data of the user; the brain wave information includes brain wave type data and brain wave frequency data of the user; the cardiac information includes heart rate data, blood pressure data, blood oxygen data, and respiration data of the user.
Further, the specific steps of preprocessing and calculating the collected data information include: acquiring sex data, age data, height data and weight data in the data information; tagging the gender type in the gender data as XL; setting different gender types to correspond to a gender associated value, matching the gender types in the gender data with a preset gender type table to obtain the corresponding gender associated value, and marking the gender associated value as B1; taking a value of the age in the age data and marking as B2; taking a value of the height in the height data and marking the value as B3; taking a value of the weight in the weight data and marking the value as B4; classifying and combining the marked data to obtain data processing information; and carrying out normalization processing and value calculation on each item of data marked in the data processing information to obtain a data coefficient.
Further, the data coefficient is obtained by calculating the data function
Wherein a1, a2 and a3 are expressed as different proportionality coefficients, μ is expressed as a data compensation factor, and the value range is (0, 10).
Further, the specific steps of preprocessing and calculating the collected brain wave information include: acquiring brain wave type data and brain wave frequency data in brain wave information, and acquiring a brain wave type in the brain wave type data and marking the brain wave type as NDLi, wherein i is 1, 2, 3.. n; setting different brain wave types to correspond to different brain wave type values, matching the brain wave types in the brain wave type data with a preset brain wave type table to obtain corresponding brain wave type values, and marking the values as NLZi; taking values of brain wave frequencies in the brain wave frequency data and marking the values as NDPi; classifying and combining the marked data to obtain brain wave processing information; and carrying out normalization processing and value calculation on various data marked in the brain wave processing information to obtain a brain wave coefficient.
Further, the brain wave coefficient is obtained by calculation of a brain wave function of
Wherein eta is expressed as brain wave compensation factor, and the value range is (0, 20).
Further, the specific steps of preprocessing and calculating the acquired cardiac information include: acquiring heart rate data, blood pressure data, blood oxygen data and respiratory data in the heart information; respectively taking values and marking the heart rate data, the blood pressure data, the blood oxygen data and the respiration data, and marking the heart rate in the heart rate data as D1; labeling the systolic blood pressure in the blood pressure data as D2; labeling the diastolic blood pressure in the blood pressure data as D3; labeling the blood oxygen saturation in the blood oxygen data as D4; labeling the number of breaths in the breath data as D5; classifying and combining the marked data to obtain heart processing information; and carrying out normalization processing and value calculation on various data marked in the heart processing information to obtain a heart coefficient.
Further, the heart coefficients are obtained by a heart function calculation, the heart function being
Wherein b1, b2, b3, b4 and b5 are represented as different proportional coefficients, β is represented as a cardiac compensation factor, the value range is (0,30), D10 is represented as a preset standard heart rate, D20 is represented as a preset standard systolic blood pressure, D30 is represented as a preset standard diastolic blood pressure, D40 is represented as a preset standard oxygen saturation, and D50 is represented as a preset standard number of breaths.
Further, the data coefficient, brain wave coefficient and heart coefficient are used to pass through the formula
Calculating to obtain a feedback value; wherein c1, c2 and c3 are expressed as different proportionality coefficients, alpha is expressed as a correction factor, and the value range is (0, 5);
acquiring a preset feedback range, and marking the minimum value of the feedback range as F1; label the maximum value of the feedback range as F2; matching the feedback value with the feedback range, and generating a first feedback signal if FK is less than F1; if F2 is not less than FK not less than F1, a second feedback signal is generated; generating a third feedback signal if FK > F2; the operation intensity of the physiotherapy instrument is increased according to the first feedback signal, and the operation intensity of the physiotherapy instrument is reduced according to the third feedback signal.
A self-feedback physiotherapy instrument comprises the following specific steps: collecting data information, brain wave information and heart information of a user; respectively preprocessing and calculating the collected data information, brain wave information and heart information to obtain a data coefficient, a brain wave coefficient and a heart coefficient; obtaining a feedback value by using the data coefficient, the brain wave coefficient and the heart coefficient, and analyzing and matching the feedback value to obtain an analysis result; and adjusting the operation of the physiotherapy instrument according to the analysis result.
The invention has the beneficial effects that:
1. the information acquisition module is used for acquiring information of different aspects of a user, and comprises a data acquisition unit, a brain wave acquisition unit and a heart acquisition unit, and the data acquisition unit is used for acquiring data information of the user; collecting brain wave information of a user through a brain wave collecting unit; collecting heart information of a user through a heart collecting unit; by collecting data from different aspects, effective data support can be provided for automatic adjustment of the physiotherapy instrument, so that the adjustment of the physiotherapy instrument is more accurate and efficient;
2. the information processing module comprises a data processing unit, a brain wave processing unit and a heart processing unit, and data coefficients are obtained by preprocessing and calculating the acquired data information through the data processing unit; preprocessing and calculating the collected brain wave information through a brain wave processing unit to obtain a brain wave coefficient; preprocessing and calculating the acquired heart information through a heart processing unit to obtain a heart coefficient; utilize data coefficient, brain wave coefficient and heart coefficient to acquire feedback value, calculate through the data with different aspects, be convenient for carry out the overall analysis to the data of different aspects, each coefficient that will acquire at last carries out simultaneous calculation, can realize carrying out automatic adjustment to the physiotherapy of physiotherapy equipment for physiotherapy equipment can carry out the physiotherapy of pertinence to different users and different health state, need not manual regulation, has improved physiotherapy equipment's physiotherapy effect.
Drawings
The invention will be further described with reference to the accompanying drawings.
Fig. 1 is a block diagram of a self-feedback physiotherapy apparatus according to the present invention.
Fig. 2 is a block diagram of a unit for connecting an information acquisition module and an information processing module according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in 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.
Referring to fig. 1, the present invention is a self-feedback physiotherapy apparatus, including an information acquisition module, an information processing module, a feedback module, a storage module and a prompt module, where the storage module is used to store preset data items and collected data items; the preset data items include but are not limited to a gender type table, a brain wave type table and a feedback range; the collected data includes but is not limited to data information, brain wave information and heart information of the user; the prompting module is used for prompting the operation of the physiotherapy instrument;
in the embodiment, data acquisition, data processing and data analysis are respectively performed from the personal state aspect, the brain wave aspect and the heart aspect of the user, so that the overall state of the user can be obtained, the operation of the physiotherapy instrument can be adjusted according to the feedback of the overall state, different users can be subjected to different degrees of physiotherapy, and the operation effect of the physiotherapy instrument is optimal; can solve the technical problem that the physical therapy effect of the physical therapy instrument is not good because the physical therapy of different degrees can not be carried out according to the physical states of different users in the prior scheme.
Referring to fig. 2, the information acquisition module includes a data acquisition unit, a brain wave acquisition unit and a heart acquisition unit, the data acquisition unit is used for acquiring data information of the user, and the data information includes gender data, age data, height data and weight data of the user; the different sexes, the different ages and the different heights and weights correspond to different physical therapy strengths, for example, the physical therapy strengths which can be accepted by young people and old people are different, and the height data and the weight data can reflect whether the user is fat; the brain wave acquisition unit is used for acquiring brain wave information of a user, and the brain wave information comprises brain wave type data and brain wave frequency data of the user; the heart acquisition unit is used for acquiring heart information of a user, and the heart information comprises heart rate data, blood pressure data, blood oxygen data and respiratory data of the user; wherein, the data information can be manually input by a user or obtained based on big data of the height and weight tester; brain wave information can be acquired through the electrode patch, and the electrode patch is directly contacted with a human body; the heart information can be acquired by a heart detector;
the information processing module comprises a data processing unit, a brain wave processing unit and a heart processing unit, and the data processing unit is used for preprocessing and calculating the acquired data information to obtain a data coefficient; the method comprises the following specific steps:
acquiring sex data, age data, height data and weight data in the data information; tagging the gender type in the gender data as XL; setting different gender types to correspond to a gender associated value, matching the gender types in the gender data with a preset gender type table to obtain the corresponding gender associated value, and marking the gender associated value as B1; taking a value of the age in the age data and marking as B2; taking a value of the height in the height data and marking the value as B3; taking a value of the weight in the weight data and marking the value as B4; classifying and combining the marked data to obtain data processing information; normalizing and evaluating various data marked in the data processing information, and calculating through a data function to obtain a data coefficient, wherein the data function is
Wherein a1, a2 and a3 are expressed as different proportionality coefficients, μ is expressed as a data compensation factor, and the value can be 1.65821; the data coefficient can carry out overall analysis on the physical state of the user;
the brain wave processing unit is used for preprocessing and calculating the collected brain wave information to obtain a brain wave coefficient; the method comprises the following specific steps:
acquiring brain wave type data and brain wave frequency data in brain wave information, and acquiring a brain wave type in the brain wave type data and marking the brain wave type as NDLi, wherein i is 1, 2, 3.. n; setting different brain wave types to correspond to different brain wave type values, matching the brain wave types in the brain wave type data with a preset brain wave type table to obtain corresponding brain wave type values, and marking the values as NLZi; taking values of brain wave frequencies in the brain wave frequency data and marking the values as NDPi; classifying and combining the marked data to obtain brain wave processing information; normalizing and evaluating various items of data marked in the brain wave processing information, and calculating and obtaining a brain wave coefficient through a brain wave function which is
Wherein, η is expressed as brain wave compensation factor, and its value can be 5.68265.
The brain waves can be divided into alpha waves, beta waves, theta waves and delta waves according to the frequency of different waveforms of the brain waves, the different types of brain waves correspond to different frequencies and amplitudes, for example, the frequency of the alpha waves is 8-13Hz, and the amplitude is 20-100 muV; the frequency of the beta wave is 18-30Hz, and the amplitude is 5-20 muV; the product and summation of the brain wave type values corresponding to different types of brain waves and the brain wave frequency can acquire the overall situation of the real-time brain waves, and the physical therapy can be analyzed in terms of the brain waves.
The heart processing unit carries out preprocessing and calculation on the acquired heart information to obtain a heart coefficient; the method comprises the following specific steps:
acquiring heart rate data, blood pressure data, blood oxygen data and respiratory data in the heart information; respectively taking values and marking the heart rate data, the blood pressure data, the blood oxygen data and the respiration data, and marking the heart rate in the heart rate data as D1; labeling the systolic blood pressure in the blood pressure data as D2; labeling the diastolic blood pressure in the blood pressure data as D3; labeling the blood oxygen saturation in the blood oxygen data as D4;labeling the number of breaths in the breath data as D5; classifying and combining the marked data to obtain heart processing information; normalizing and valuing various items of data marked in the heart treatment information, and calculating and acquiring a heart coefficient through a heart function which is
B1, b2, b3, b4 and b5 are represented as different proportional coefficients, β is represented as a cardiac compensation factor, and can take a value of 0.52634, D10 is represented as a preset standard heart rate, D20 is represented as a preset standard blood pressure systolic pressure, D30 is represented as a preset standard blood pressure diastolic pressure, D40 is represented as a preset standard blood oxygen saturation, and D50 is represented as a preset standard respiration frequency; the cardiac coefficient may perform an overall analysis of the cardiac state of the user.
Using data coefficient, brain wave coefficient and heart coefficient through formula
Calculating to obtain a feedback value; wherein c1, c2 and c3 are expressed as different proportionality coefficients, and α is expressed as a correction factor, and the value can be 0.42517.
Wherein, the normal heart rate of healthy adults is 60-100 times/minute, the state of less than 60 times/minute is bradycardia, and the state of more than 100 times/minute is tachycardia; the systolic pressure of normal blood pressure is 90-140mmHg, and the diastolic pressure is 60-90 mmHg; the normal value of blood oxygen saturation is above 95%; normal breathing was 18 breaths/min; in this embodiment, the preset standard heart rate may be 60 times/minute; the preset standard systolic blood pressure is 90 mmHg; the preset standard blood pressure diastolic pressure may be 60 mmHg; the preset standard blood oxygen saturation can be 95%; the preset standard breath times can be 18 times/minute;
acquiring a preset feedback range according to the data coefficients, wherein the preset feedback range is different because the crowd corresponding to different data coefficients is different, and marking the minimum value of the feedback range as F1; label the maximum value of the feedback range as F2; matching the feedback value with the feedback range;
generating a first feedback signal if FK < F1;
if F2 is not less than FK not less than F1, a second feedback signal is generated;
generating a third feedback signal if FK > F2; the first feedback signal, the second feedback signal and the third feedback signal form an analysis result; wherein, when the physiotherapy instrument performs physiotherapy, the physiotherapy is performed by adopting an electrical stimulation mode; the first feedback signal shows that the intensity of the electric stimulation is too small, the physical therapy effect is not good, and the intensity of the electric stimulation needs to be regulated and controlled to be increased; the second feedback signal shows that the intensity of the electric stimulation is normal, and the physiotherapy effect reaches the best; the third feedback signal indicates that the intensity of the electrical stimulation is too large, so that the human body is injured, and the intensity of the electrical stimulation needs to be regulated and reduced.
The feedback module adjusts the operation of the physiotherapy instrument according to the feedback value, increases the operation intensity of the physiotherapy instrument according to the first feedback signal, and decreases the operation intensity of the physiotherapy instrument according to the third feedback signal.
A self-feedback physiotherapy instrument comprises the following specific steps: collecting data information, brain wave information and heart information of a user; respectively preprocessing and calculating the collected data information, brain wave information and heart information to obtain a data coefficient, a brain wave coefficient and a heart coefficient; obtaining a feedback value by using the data coefficient, the brain wave coefficient and the heart coefficient, and analyzing and matching the feedback value to obtain an analysis result containing a first feedback signal, a second feedback signal and a third feedback signal; adjusting the operation of the physiotherapy instrument according to the analysis result, increasing the operation intensity of the physiotherapy instrument according to the first feedback signal, and reducing the operation intensity of the physiotherapy instrument according to the third feedback signal.
The formulas in the invention are all a formula which is obtained by removing dimensions and taking numerical value calculation, and software simulation is carried out by collecting a large amount of data to obtain the formula closest to the real condition, and the preset proportionality coefficient and the threshold value in the formula are set by the technical personnel in the field according to the actual condition or are obtained by simulating a large amount of data.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and the like are to be construed broadly and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be directly connected or indirectly connected through an intermediate member, or they may be connected through two or more elements. The specific meaning of the above terms in the present invention can be understood in a specific case by those skilled in the art.
While one embodiment of the present invention has been described in detail, the description is only a preferred embodiment of the present invention and should not be taken as limiting the scope of the invention. All equivalent changes and modifications made within the scope of the present invention shall fall within the scope of the present invention.
Claims (8)
1. A self-feedback physiotherapy apparatus, comprising: the information acquisition module is used for acquiring data information, brain wave information and heart information of a user; the information processing module comprises a data processing unit, a brain wave processing unit and a heart processing unit, and the data processing unit is used for preprocessing and calculating the acquired data information to obtain a data coefficient; the brain wave processing unit is used for preprocessing and calculating the collected brain wave information to obtain a brain wave coefficient; the heart processing unit carries out preprocessing and calculation on the acquired heart information to obtain a heart coefficient; obtaining a feedback value by using the data coefficient, the brain wave coefficient and the heart coefficient; the feedback module adjusts the operation of the physiotherapy instrument according to the feedback value, so that the physiotherapy instrument keeps the most appropriate operation state for different users;
the information processing module comprises a data processing unit, a brain wave processing unit and a heart processing unit, and the data processing unit is used for preprocessing and calculating the acquired data information to obtain a data coefficient; the method comprises the following specific steps:
acquiring sex data, age data, height data and weight data in the data information; tagging the gender type in the gender data as XL; setting different gender types to correspond to a gender correlation value, and matching the gender types in the gender data with a preset gender type table to obtainThe corresponding gender associated value and labeled B1; taking a value of the age in the age data and marking as B2; taking a value of the height in the height data and marking the value as B3; taking a value of the weight in the weight data and marking the value as B4; classifying and combining the marked data to obtain data processing information; normalizing and evaluating various data marked in the data processing information, and calculating through a data function to obtain a data coefficient, wherein the data function is
(ii) a Wherein a1, a2 and a3 are expressed as different proportionality coefficients, mu is expressed as a data compensation factor, and the value is 1.65821; the data coefficient can carry out overall analysis on the physical state of the user;
the brain wave processing unit is used for preprocessing and calculating the collected brain wave information to obtain a brain wave coefficient; the method comprises the following specific steps:
acquiring brain wave type data and brain wave frequency data in brain wave information, and acquiring a brain wave type in the brain wave type data and marking the brain wave type as NDLi, wherein i is 1, 2, 3.. n; setting different brain wave types to correspond to different brain wave type values, matching the brain wave types in the brain wave type data with a preset brain wave type table to obtain corresponding brain wave type values, and marking the values as NLZi; taking values of brain wave frequencies in the brain wave frequency data and marking the values as NDPi; classifying and combining the marked data to obtain brain wave processing information; normalizing and evaluating various items of data marked in the brain wave processing information, and calculating and acquiring a brain wave coefficient through a brain wave function
Wherein eta is expressed as brain wave compensation factor and takes 5.68265;
the brain waves can be divided into alpha waves, beta waves, theta waves and delta waves according to the frequency of different waveforms of the brain waves, the different types of brain waves correspond to different frequencies and amplitudes, for example, the frequency of the alpha waves is 8-13Hz, and the amplitude is 20-100 muV; the frequency of the beta wave is 18-30Hz, and the amplitude is 5-20 muV; the product and summation of the brain wave type values corresponding to different types of brain waves and the brain wave frequency can obtain the overall situation of real-time brain waves, and the physical therapy can be analyzed from the brain wave aspect;
the heart processing unit carries out preprocessing and calculation on the acquired heart information to obtain a heart coefficient; the method comprises the following specific steps:
acquiring heart rate data, blood pressure data, blood oxygen data and respiratory data in the heart information; respectively taking values and marking the heart rate data, the blood pressure data, the blood oxygen data and the respiration data, and marking the heart rate in the heart rate data as D1; labeling the systolic blood pressure in the blood pressure data as D2; labeling the diastolic blood pressure in the blood pressure data as D3; labeling the blood oxygen saturation in the blood oxygen data as D4; labeling the number of breaths in the breath data as D5;
classifying and combining the marked data to obtain heart processing information; normalizing and valuing various items of data marked in the heart treatment information, and calculating and acquiring a heart coefficient through a heart function which is
(ii) a B1, b2, b3, b4 and b5 are represented as different proportional coefficients, beta is represented as a heart compensation factor and takes a value of 0.52634, D10 is represented as a preset standard heart rate, D20 is represented as a preset standard blood pressure systolic pressure, D30 is represented as a preset standard blood pressure diastolic pressure, D40 is represented as a preset standard blood oxygen saturation, and D50 is represented as a preset standard respiration frequency; the heart coefficient can carry out overall analysis on the heart state of the user;
using data coefficient, brain wave coefficient and heart coefficient through formula
Calculating to obtain a feedback value; wherein c1, c2 and c3 are expressed as different proportionality coefficients, and alpha is expressed as a correction factor and takes the value of 0.42517.
2. The self-feedback physiotherapy instrument according to claim 1, further comprising a storage module and a prompt module, wherein the storage module is used for storing preset data and collected data; the prompting module is used for prompting the operation of the physiotherapy instrument.
3. The self-feedback physiotherapy apparatus according to claim 2, wherein the data information comprises sex data, age data, height data and weight data of the user; the brain wave information includes brain wave type data and brain wave frequency data of the user; the cardiac information includes heart rate data, blood pressure data, blood oxygen data, and respiration data of the user.
4. The self-feedback physiotherapy instrument as claimed in claim 3, wherein the pre-processing and calculating of the collected data information comprises: acquiring sex data, age data, height data and weight data in the data information; marking the gender type in the gender data and the gender associated value corresponding to the gender type; respectively carrying out value taking and marking on the age in the age data, the height in the height data and the weight in the weight data to obtain data processing information; and carrying out normalization processing and value calculation on each item of data marked in the data processing information to obtain a data coefficient.
5. The self-feedback physiotherapy instrument as claimed in claim 4, wherein the pre-processing and calculating of the collected brain wave information comprises: acquiring brain wave type data and brain wave frequency data in brain wave information, and marking the brain wave type in the brain wave type data and a brain wave type value corresponding to the brain wave type data; carrying out value taking and marking on brain wave frequencies in the brain wave frequency data; obtaining brain wave processing information; and carrying out normalization processing and value calculation on various data marked in the brain wave processing information to obtain a brain wave coefficient.
6. The self-feedback physiotherapy apparatus of claim 5, wherein the pre-processing and calculating of the collected cardiac information comprises: acquiring heart rate data, blood pressure data, blood oxygen data and respiratory data in the heart information; respectively carrying out value taking and marking on the heart rate data, the blood pressure data, the blood oxygen data and the respiratory data to obtain heart processing information; and carrying out normalization processing and value calculation on various data marked in the heart processing information to obtain a heart coefficient.
7. The self-feedback physiotherapy instrument according to claim 6, wherein the feedback value is matched with a preset feedback range to obtain an analysis result including the first feedback signal, the second feedback signal and the third feedback signal.
8. The self-feedback physiotherapy apparatus of claim 7, wherein the operation intensity of the physiotherapy apparatus is increased according to the first feedback signal, and the operation intensity of the physiotherapy apparatus is decreased according to the third feedback signal until the feedback value corresponding to the operation intensity falls within the predetermined feedback range.
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