CN110251135A - A kind of human motion monitoring of respiration method - Google Patents
A kind of human motion monitoring of respiration method Download PDFInfo
- Publication number
- CN110251135A CN110251135A CN201910560301.2A CN201910560301A CN110251135A CN 110251135 A CN110251135 A CN 110251135A CN 201910560301 A CN201910560301 A CN 201910560301A CN 110251135 A CN110251135 A CN 110251135A
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- Prior art keywords
- monitoring
- respiration
- feature extraction
- human motion
- breathing
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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
- A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
Abstract
The present invention relates to sports equipment fields, disclose a kind of human motion monitoring of respiration method, solve the problems, such as portable and can monitor breathing technique.Include the following steps: S101: mobile phone connects earphone and microphone, S102: sound collecting, S103: feature extraction, S104: sound wave model comparison, S105: judgement monitors whether to terminate.Respiration information is directly acquired by ear microphone, it is easy to carry, movement experience is not influenced, while not needing special smart phone, all there is good compatibility with general mobile phone.By detecting exception after feature extraction, monitoring of respiration calibration is re-started if there is abnormal, until monitoring the validity for successfully having ensured feature extraction.Picture and text model display threshold speech is arranged after being synthesized by image data, and the data exception when detecting movement breathing reminds people to restore correct breathing when being more than threshold value.
Description
Technical field
The present invention relates to sports equipment fields, more specifically, it relates to a kind of human motion monitoring of respiration method.
Background technique
Adhere to that movement can improve our physical qualification, in today that operating pressure increasingly increases, people start weight
The movement of visual gauge rule, but the method for science is needed in motion process, it needs to carry out to exhale during the guidance of profession, such as running
Rule is wanted in suction, prevent from breathing it is improper will cause physical stamina letdown, it is serious or even damage.
Now, people are typically chosen gymnasium the coach of profession are asked to instruct, but many people do not have the time special
It goes to gymnasium to move, occurs monitoring of respiration equipment in the market, generally use approach sensor, the information of real-time monitoring breathing.
However, the sensor needs are connect with dedicated smart phone, and sensor is not readily portable, influences movable body
It tests.
Summary of the invention
In view of the above-mentioned problems, the purpose of the present invention is to provide a kind of human motion monitoring of respiration methods, with equipment
It is portable and the advantages of breathing can be monitored.
Foregoing invention purpose of the invention has the technical scheme that
A kind of human motion monitoring of respiration method, which comprises the steps of:
S101: mobile phone connects earphone and microphone；
S102: sound collecting；
S103: feature extraction；
S104: sound wave model comparison；
S105: judgement monitors whether to terminate.
The S102 step, sound collecting start monitoring system first, carry out monitoring of respiration calibration, then acquire sound wave；
The S103 step, detects exception after feature extraction, re-starts monitoring of respiration calibration if there is abnormal, directly
To monitoring successfully.
Through the above technical solutions, ear microphone directly acquires respiration information, and it is easy to carry, movement experience is not influenced,
Special smart phone is not needed simultaneously, all there is good compatibility with general mobile phone.
Further, the S103 step, setting in motion after monitoring successfully, while sound wave is acquired, sound wave is carried out again
Feature extraction, then carry out waveshape.
Further, the S104 step, breathing modeling is to compare existing respiratory characteristic with Issuance model, is used
Figure or voice shape, which are shown, to be deviateed.
Further, the breathing modeling includes sound collecting, feature extraction, waveshape, respiratory model creation, image
Data Synthesis and Issuance model.
Further, picture and text model display threshold speech is arranged after described image Data Synthesis.
Compared with prior art, the beneficial effects of the present invention are:
(1) respiration information is directly acquired by ear microphone, it is easy to carry, movement experience is not influenced, is not needed simultaneously
Special smart phone all has good compatibility with general mobile phone；
(2) by detecting exception after feature extraction, monitoring of respiration calibration is re-started if there is abnormal, until monitoring
Success, has ensured the validity of feature extraction；
(3) picture and text model display threshold speech is arranged after being synthesized by image data, when detecting movement breathing
People are reminded to restore correct breathing when data exception is more than threshold value.
Detailed description of the invention
Fig. 1 is workflow schematic diagram of the present invention；
Fig. 2 is present invention breathing modeling procedure figure；
Fig. 3 is monitoring of respiration flow chart of the present invention.
Specific embodiment
With reference to the accompanying drawings and examples, the present invention will be described in detail.
Embodiment one
A kind of human motion monitoring of respiration method, includes the following steps:
S101: mobile phone connects earphone and microphone；
S102: sound collecting；
S103: feature extraction；
S104: sound wave model comparison；
S105: judgement monitors whether to terminate.
Sound wave model comparison is creation respiratory model first, then issues respiratory model, and existing breathing acoustic characteristic is mentioned
It takes and is compared afterwards with the respiratory model of publication, if there is deviation, reminded using the form of picture and text or voice.
Sound collecting first starts monitoring system, carries out monitoring of respiration calibration, then acquires sound wave.It is detected after feature extraction
It is abnormal, monitoring of respiration calibration is re-started if there is abnormal, until monitoring successfully.
Further, the breathing modeling includes sound collecting, feature extraction, waveshape, respiratory model creation, image
Data Synthesis and Issuance model.
Further, setting in motion after monitoring successfully, while sound wave is acquired, progress acoustic characteristic extraction again, then into
Row waveshape.Further, breathing modeling is to compare existing respiratory characteristic with Issuance model, with figure or voice
Shape, which is shown, to be deviateed.
Through the above technical solutions, ear microphone directly acquires respiration information, and it is easy to carry, movement experience is not influenced,
Special smart phone is not needed simultaneously, all there is good compatibility with general mobile phone.
More specifically, ear microphone is used as acquisition sound wave, noise reduction can be carried out after sound collecting module acquisition sound wave
Processing is extracted main acoustic signature calculating and is modeled, and established model is issued out as basis of reference.
In sound wave modeling process, when input value is one group of microphone DB value of respiratory and movement state pause judgments in training
Between, sonicated is first normalized sound wave, and shield abdominal respiration and thoracic breathing influences caused by judgement.More
Specifically, it is assumed that original sound wave signal is x (n), and the acoustic signals after normalization are y (n), then the relationship between y (n) and x (n) is
In y (n)=x (n)/max (abs (x)) n ∈ (1, N) formula: the length of n-signal, max () seek the maximum value of vector, and abs () asks exhausted
To value, then the value range of y (n) is [- 1,1].Treated, and sound wave carries out noise reduction process, it is highly preferred that due to threshold denoising
The fast and characteristics such as noise can preferably be inhibited with calculating speed, so selection threshold denoising.
Feature extraction carries out 8 layers of decomposition using UWT processing signal, 8 layers of detail coefficients is taken, more specifically, seeking details system
Several layers of maximum value vector, layer maximum value vector are defined as follows levelmax (k)=max ([swd (1, k) swd (2, k) ... swd
(level, k)]) in k ∈ (1, N) formula: levelmax is layer maximum value vector, and swd is detail coefficients, and N indicates signal length.Again
Seek the shape envelope of layer maximum value vector, shape envelope vector, that is, feature value vector.More specifically, the side of seeking of shape envelope
Formula is that layer maximum value vector is divided into specified number M, takes the maximum value in every part to form a new vector, vector magnitude is
M。
The principle of characteristic matching is that two groups of acoustic characteristic vector Euclidean distances are smaller, indicates that two vectors are more similar, when two
When vector is completely the same, Euclidean distance 0.
Embodiment two
A kind of human motion monitoring of respiration method, more specifically, such as people pass through ear microphone when pressing your body up from the floor with your arms and then lower it slowly
Respiration information is acquired, expiration when moving upwards, air-breathing when moving downward, motion monitoring system will be acted to be plotted in breathing timing
On graphical interfaces, when sporter with act corresponding respiratory model mismatch when give sporter prompt, enable sporter and
When adjustment breathing.
Embodiment three
A kind of human motion monitoring of respiration method, more specifically, people, in road-work, three step air-breathings, three steps are exhaled,
Acquire respiration information by ear microphone, motion detection gyroscope judge the beans-and bullets shooter of user according to gravity sensing, will breathing and
Beans-and bullets shooter is plotted on graphical interfaces, is prompted when sporter mismatches with the corresponding respiratory model of movement to sporter, is made to transport
Dynamic person can adjust breathing in time.
The above is only a preferred embodiment of the present invention, protection scope of the present invention is not limited merely to above-mentioned implementation
Example, all technical solutions belonged under thinking of the present invention all belong to the scope of protection of the present invention.It should be pointed out that for the art
Those of ordinary skill for, several improvements and modifications without departing from the principles of the present invention, these improvements and modifications
It should be regarded as protection scope of the present invention.
Claims (5)
1. a kind of human motion monitoring of respiration method, which comprises the steps of:
S101: mobile phone connects earphone and microphone；
S102: sound collecting；
S103: feature extraction；
S104: sound wave model comparison；
S105: judgement monitors whether to terminate.
The S102 step, sound collecting start monitoring system first, carry out monitoring of respiration calibration, then acquire sound wave；
The S103 step, detects exception after feature extraction, monitoring of respiration calibration is re-started if there is abnormal, until prison
It surveys successfully.
2. human motion monitoring of respiration method according to claim 1, which is characterized in that S103 step, monitoring at
Setting in motion after function, while sound wave is acquired, acoustic characteristic extraction is carried out again, then carries out waveshape.
3. human motion monitoring of respiration method according to claim 2, which is characterized in that the S104 step, breathing are built
Mould is to compare existing respiratory characteristic with Issuance model, is shown and is deviateed with figure or voice shape.
4. human motion monitoring of respiration method according to claim 3, which is characterized in that the breathing modeling includes sound wave
Acquisition, feature extraction, waveshape, respiratory model creation, image data synthesis and Issuance model.
5. human motion monitoring of respiration method according to claim 4, which is characterized in that after described image Data Synthesis
The setting of picture and text model display threshold speech.
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Application publication date: 20190920 |