CN111657951B - Respiration monitoring device based on sensor array type arrangement - Google Patents
Respiration monitoring device based on sensor array type arrangement Download PDFInfo
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Abstract
In order to obtain more complete respiratory motion characteristics of a human body, early warning judgment is carried out on respiratory related diseases. The invention provides a respiration monitoring device based on sensor array arrangement, which comprises M inertial sensors, N signal transmitters and a signal receiver, wherein the M inertial sensors are used for acquiring the change characteristics of a human body during respiration and serve as sensor data packets, the N signal transmitters are used for transmitting the sensor data packets acquired by the inertial sensors to the signal receiver, and the signal receiver is used for processing the sensor data packets to obtain accurate human body respiration motion characteristics. The signal receiver comprises a multidimensional data resolving part, a time sequence signal reconstructing part, a fusion signal generating part, an attitude yaw correcting part and a communication part, wherein the multidimensional data resolving part is used for resolving gestures, the time sequence signal reconstructing part is used for filtering, reducing noise and generating a reconstructed time sequence signal, the fusion signal generating part is used for performing angle information fusion processing to generate a fusion signal, the attitude yaw correcting part is used for generating a reset signal, and the communication part is used for receiving and transmitting various signals.
Description
Technical Field
The invention belongs to the technical field of electronic equipment, relates to intelligent wearable equipment, and in particular relates to a respiration monitoring device based on sensor array arrangement.
Background
Respiration is one of the most basic and important vital signs of the human body. In a variety of medical rehabilitation scenarios, variations in respiratory characterization are closely related to the occurrence/progression of disease. Long-term, continuous respiratory monitoring can be used to pre-warn of diseases that are clinically manifested as "dyspnea" and in turn promote the effectiveness and reliability of auxiliary diagnostic work in personalized medicine.
Meanwhile, the breath characterization shows a plurality of modes on different education behaviors and exercise modes, and the systematic analysis and comparison of the modes are helpful for better formulating referenceable teaching and training schemes and policies and improving the scientificity and pertinence of related schemes and policies. Therefore, the extraction and analysis of the breathing related parameters are of great significance in various scenes such as clinical medicine, education and teaching, sports training and the like.
In the prior art, the respiration monitoring equipment based on the pressure sensor is common equipment in the market at present, but the equipment can only monitor the integral deformation caused by respiration; in addition, respiratory monitoring devices based on a single inertial sensor are also unable to monitor the movement patterns of multiple body parts. The design and installation of the above-described devices, however, ignores the importance of the physiological structure of the human body. The small number of measurement points also has limitation in monitoring, and the deformation of different body parts caused by breathing is different and cannot be obtained by monitoring with a single-point inertial sensor or a pressure sensor. While multipoint measurement schemes exist, their installation ignores considerations in human muscle group distribution and movement patterns, as well as bone distribution, so these schemes only stay in improving the accuracy of the measurements that monitor respiration rate. In summary, the above known system cannot monitor the movement conditions of multiple parts of the body caused by respiration at the same time, and cannot provide the respiratory-related muscle movement information, so that the respiratory movement characteristics of the human body cannot be obtained more completely, and errors are easily caused in early warning and judgment of respiratory-related diseases.
Disclosure of Invention
In order to solve the problems, the breath detection device for accurately measuring the breath and other motion characteristics of the human body in various scenes is provided so as to achieve the purpose of scientifically monitoring the breath and other motion characteristics of the human body.
The invention adopts the following technical scheme:
the invention provides a respiration monitoring device based on sensor array arrangement, which is characterized by comprising the following components: the M inertial sensors are respectively fixed on the trunk part of the human body in an array mode according to the muscle groups and skeleton distribution conditions of the human body, and synchronously acquire the inertial sensors to form M groups of sensor data packets; the number of the N signal transmitters is not more than the number of the inertial sensors, and the signal transmitters are in communication connection with the inertial sensors; and the signal receiving equipment is communicated with the signal transmitter, the signal receiving equipment is provided with a multidimensional data resolving part, a time sequence signal reconstructing part and a fusion signal generating part, once the signal transmitter transmits a sensor data packet to the signal receiving equipment, the multidimensional data resolving part performs gesture resolving on the received sensor data packet to obtain a sensor gesture angle time sequence signal, the fusion signal generating part performs angle signal fusion processing on the gesture angle time sequence signal to obtain a fusion signal and takes the fusion signal as a respiratory and movement angle representation of a human body, the time sequence signal reconstructing part adopts various filtering noise reduction strategies to filter and reduce acceleration information in the sensor data packet and takes the reconstruction time sequence signal as a respiratory and movement speed representation of the human body, and the respiratory and movement speed representation of the human body and the respiratory and movement angle representation of the human body are fused to form a respiratory movement representation of the human body.
The respiration monitoring device based on the sensor array arrangement has the technical characteristics that the inertial sensor comprises a sucker part made of flexible materials capable of being attached to human skin, a rigid connecting rod part and a sensor body, one end of the rigid connecting rod part is connected to the sucker part, the other end of the rigid connecting rod part is of a buckle structure, and separation and connection with the sensor body are completed through the buckle structure.
The respiration monitoring device based on the sensor array arrangement provided by the invention also has the technical characteristics that the respiration monitoring device further comprises: the sensor layout clothing is provided with a plurality of rigid fixing holes corresponding to the layout positions of all the inertial sensors, wherein the rigid connecting rod passes through the rigid fixing holes and is connected with the sensor body through the buckle structure.
The respiration monitoring device based on the sensor array arrangement provided by the invention has the technical characteristics that the garment for sensor arrangement is also provided with the to-be-selected fixing holes arranged nearby the rigid fixing holes, and the to-be-selected fixing holes are used for the inertial sensor to be replaced to collect and form sensor data packets of the same positions of muscle groups and bones of patients with different morphological characteristics.
The invention provides a respiration monitoring device based on sensor array arrangement, which also has the technical characteristics that the angle signal fusion processing comprises the following steps: s1, decomposing an attitude angle time sequence signal into 9 layers of signals to be processed by adopting a sym5 wavelet basis; step S2, setting zero of high-frequency signals of a first layer and a second layer and low-frequency signals of the lowest layer in signals to be processed, and reconstructing a time sequence signal back to be used as a first signal through a wavelet reconstruction method; step S3, fitting a trend term of the first signal by adopting a first-order linear equation, and removing the trend term to form a second signal; s4, performing signal filtering on the second signal by adopting a median filter to form a third signal; s5, performing signal smoothing on the third signal by using a moving average filter to form a fourth signal; step S6, subtracting the average value of the fourth signal from the fourth signal to form a fifth signal; s7, normalizing the fifth signal to form angle signals in the X-axis, Y-axis and Z-axis directions; and S8, normalizing and fusing the three signals of the angle signal in the X-axis direction, the angle signal in the Y-axis direction and the angle signal in the Z-axis direction based on preset weights to form fusion signals.
The respiration monitoring device based on the sensor array arrangement further has the technical characteristics that the weight acquisition method in the step S8 is any one of artificial given fixed weight, calculation according to signal variation, calculation according to signal variance and noise variance ratio, signal variance and signal range ratio and signal range and noise variance ratio.
The invention provides a respiration monitoring device based on sensor array arrangement, which has the technical characteristics that a sensor data packet comprises acceleration information, angular velocity information and magnetic force information of the position of a corresponding inertial sensor, and gesture resolving at least comprises: step T1, angular velocity and acceleration information in a sensor data packet are processed through a dynamic Kalman filtering algorithm and a complementary filtering algorithm to obtain an attitude angle of an inertial sensor; step T2, filtering and correcting a yaw angle in the attitude angle of the inertial sensor through a magnetic field component, so as to obtain an angle time sequence signal of the inertial sensor; and step T3, filtering the angle time sequence signals in the directions of three axes of the XYZ through a gravity field to obtain an attitude angle time sequence signal.
The respiration monitoring device based on the sensor array arrangement provided by the invention also has the technical characteristics that the plurality of filtering noise reduction strategies comprise: step U1, performing trend item fitting on 6 th order polynomials of acceleration information in a sensor data packet, and removing and forming a first transition signal; step U2, performing 3-layer wavelet decomposition on the first transition signal through a Haar wavelet base, removing a high-frequency signal decomposed by the first layer, and taking the reconstructed time sequence signal as a second transition signal; step U3, smoothing and filtering the second transition signal by adopting a Lowess method to form a third transition signal; and step U4, performing high-frequency signal decomposition on the third transition signal, setting the high-frequency signal to zero, reconstructing the timing signal, and normalizing the timing signal to obtain a reconstructed timing signal.
The respiration monitoring device based on the sensor array arrangement further has the technical characteristics that the signal receiving equipment further comprises a gesture yaw correcting part and a communication part, wherein the gesture yaw correcting part is used for generating a reset signal, the communication part outputs the reset signal to a signal transmitter, and the signal transmitter sends the received reset signal to the inertial sensor, so that the inertial sensor is initialized and corrected.
The actions and effects of the invention
According to the respiration monitoring device based on the sensor array arrangement, due to the fact that the respiration monitoring device is provided with the plurality of inertial sensors, the inertial sensors are fixed on the trunk part of a human body based on muscle distribution and movement modes of the human body and skeleton distribution of the inertial sensors, not only can multipoint synchronous real-time monitoring be conducted at the same time, but also positions acquired by the inertial sensors are enabled to be more in accordance with human body characteristics, and therefore more complete human body respiration movement characteristics are obtained. The device is further provided with a signal receiving device which performs gesture resolving, filtering noise reduction and fusion signal processing on information acquired by the plurality of inertial sensors, so that the obtained processing signal, namely respiratory motion characteristics, is more accurate and reasonable.
Drawings
FIG. 1 is a block diagram of a respiratory monitoring device based on an array arrangement of sensors in an embodiment of the invention;
FIG. 2 is a schematic diagram of distribution of the selected fixing holes according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an inertial sensor according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of inertial sensor and signal emitter distribution in an embodiment of the invention;
fig. 5 is a block diagram of a signal receiving apparatus in an embodiment of the present invention;
FIG. 6 is a workflow diagram of multi-dimensional data solver pose solution in an embodiment of the present invention;
fig. 7 is a flowchart of the angle signal fusion process of the fusion signal generation section in the embodiment of the present invention;
FIG. 8 is a flowchart of the operation of filtering and denoising the acceleration signal in the timing signal reconstruction portion in accordance with an embodiment of the present invention; and
fig. 9 is a flow chart of a method of extracting respiratory and other motion features of the human body in an embodiment of the invention.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement of the purposes and the effects of the present invention easy to understand, the respiration monitoring device based on the sensor array arrangement of the present invention is specifically described below with reference to the embodiments and the accompanying drawings.
< example >
Fig. 1 is a block diagram of a respiration monitoring device based on sensor array arrangement in an embodiment of the present invention.
As shown in fig. 1, the respiration monitoring apparatus 100 based on the sensor array arrangement includes M inertial sensors 101, N signal transmitters 102, one signal receiving device 103, and a sensor-layout garment 105 (not shown in the figure), where N is not greater than M, and the correspondence relationship depends on the number of data interfaces of the selected signal transmitters of different types.
The M inertial sensors 101 are connected to the data interfaces of the N signal transmitters 102 through wires, and complete wired communication 104a with the signal transmitters, and the N signal transmitters 102 transmit sensor data packets acquired and formed by the M inertial sensors 101 to the signal receiver 103 through wireless communication 104B;
in this embodiment, the signal receiving device 103 is a computer with a pre-load program installed, and in this embodiment, the signal transmitter is a bluetooth transmitter communicatively connected to the computer with the pre-load program installed, and in this embodiment, the inertial sensor 103.
The sensor-layout garment 105 is an elastic cloth garment, and has rigid fixing holes 44 provided at the layout positions of the inertial sensors 101. And 2 or 4 to-be-selected fixing holes are respectively arranged around each rigid fixing hole in a transverse and longitudinal mode.
FIG. 2 is a schematic diagram of the distribution of the selected fixing holes according to an embodiment of the present invention.
The distribution positions and distribution schemes of the fixing holes to be selected, which are arranged in the sensor-layout garment 105 in this embodiment, are shown in fig. 2. The dashed box is marked as a set of fixation holes, each comprising a centrally located rigid fixation hole 44 and 4 fixation holes to be selected arranged longitudinally and laterally therearound.
Each inertial sensor 101 is disposed at a respective rigid fixation hole 44 on the torso of a person for collecting breathing state information of the person as a sensor data packet.
FIG. 3 is a schematic diagram of an inertial sensor according to an embodiment of the present invention.
As shown in fig. 3, the inertial sensor 101 includes a sensor body 41, a rigid connecting rod portion 42, and a suction cup portion 43 made of a flexible material that can be fitted to the skin of a human body, and also shows a rigid fixing hole 44 that is fixed to the sensor-distribution garment 105. The size of the disc made of flexible materials which can be attached to the skin is set according to the size and the weight of the sensor, so that the peak pressure when the disc is fixed on a human body is reduced, and the comfort when the disc is fixed on the body is improved. In fig. 3, wavy lines connected to the rigid fixing holes 44 represent the sensor-layout garment 105, and the suction cup portion 43 made of flexible material capable of fitting the skin of the human body is connected to the rigid connecting rod portion 42 and arranged inside the rigid fixing holes 44, and the rigid connecting rod portion 42 extends out of the rigid fixing holes 44 to complete the connection with the sensor body 41 in a fastening manner as shown in fig. 3.
FIG. 4 is a schematic diagram of inertial sensor and signal emitter distribution in an embodiment of the invention.
As shown in fig. 4, the inertial sensors 101 are respectively disposed on the front and back sides of the human torso according to the distribution of the human skeleton and muscle groups, for example, as shown in fig. 4, when the inertial sensors 101 are respectively disposed on the front side of the human body: as shown in fig. 4, the clavicle (11, 12), the sternum: 14. inter-intercostal muscle group: (13, 15), external intercostal muscle group: (16, 17), diaphragmatic muscle group: (18, 19), rectus abdominis muscle group: (110, 111, 114), the group of transverse abdominal muscles: (113, 115) intra-abdominal/external oblique muscle group: (112, 116) and the like: group Fang Ji: (117, 118), latissimus dorsi muscle group: (119, 120) and erector spinal muscle groups: (121, 122) supplementation: the two inertial sensor locations are located respectively on the active sternocleidomastoid muscle (not shown).
When the device in the embodiment detects people with different posture characteristics, the inertial sensor body 41 is separated from the rigid connecting rod part 42 and is fixed at a proper fixed position to be selected again through the buckle structure, so that the respiratory motion characteristic acquisition of the people with different posture characteristics is completed.
In this embodiment, the sensor data packet includes acceleration information, angular velocity information and magnetic force information corresponding to the position of the inertial sensor.
The signal transmitter 102 is configured to receive a sensor data packet sent by the inertial sensor 103 and send the sensor data packet to the signal receiving device.
In this embodiment, the signal transmitter 102 is a bluetooth transmitter, and as shown in fig. 4, the bluetooth transmitter is longitudinally arranged on the front and back of the human torso and is in communication connection with the inertial sensor 101.
Wherein the signal transmitter adopts bluetooth transmitter, and the arrangement is as shown in fig. 4: bluetooth transmitter position: (21, 22, 23) rear inertial sensor arrangement positions are shown in fig. 4: bluetooth transmitter position: (24, 25, 26).
Fig. 5 is a block diagram of a signal receiving apparatus in an embodiment of the present invention.
As shown in fig. 5, the signal receiver 103 includes a multidimensional data resolving unit 11, a fusion signal generating unit 12, a time series signal reconstructing unit 13, a posture yaw correcting unit 14, a communication unit 15, and a control unit 16.
The multidimensional data calculating unit 11 is configured to calculate the posture of the received sensor data packet to obtain a sensor posture angle timing signal.
FIG. 6 is a workflow diagram of multi-dimensional data solver pose solution in an embodiment of the present invention.
As shown in fig. 6, the posture calculation of the multidimensional data calculating section 11 includes the steps of:
and step T1, processing the angular velocity and acceleration information in the sensor data packet through a dynamic Kalman filtering algorithm and a complementary filtering algorithm to obtain an attitude angle of the inertial sensor, and then entering step T2.
The sensor data packet comprises acceleration information ax in the X-axis direction, acceleration information ay in the Y-axis direction and acceleration information az in the Z-axis direction which can be acquired by each of the M inertial sensors; angular velocity information wx in the X-axis direction, angular velocity information wy in the Y-axis direction, and angular velocity information wz in the Z-axis direction; magnetic information mx in the X-axis, magnetic information my in the Y-axis, and magnetic information mz in the Z-axis.
Step T2, filtering and correcting a yaw angle in the attitude angle of the inertial sensor through a magnetic field component, so as to obtain an angle time sequence signal of the inertial sensor, and entering a step T3;
and step T3, filtering the angle time sequence signals in the directions of three axes of the XYZ through a gravity field to obtain an attitude angle time sequence signal, and entering an ending state.
The fusion signal generation unit 12 performs an angle signal fusion process on the posture angle sequence signal to obtain a fusion signal, and the fusion signal is used as a representation of the breathing and movement angle of the human body.
Fig. 7 is a flowchart of the angle signal fusion processing of the fusion signal generation section in the embodiment of the present invention.
As shown in fig. 7, the angle signal fusion process of the fusion signal generation section 12 includes the steps of:
s1, decomposing an attitude angle time sequence signal into 9 layers of signals to be processed by adopting a sym5 wavelet basis, decomposing the reconstructed time sequence signal to be 0.1Hz at the lowest, and then entering a step S2;
step S2, setting zero of high-frequency signals of a first layer and a second layer of signals to be processed and low-frequency signals of a lowest layer, reconstructing a time sequence signal back to be used as a first signal through a wavelet reconstruction method, and entering step S3;
step S3, fitting the trend term of the time sequence signal reconstructed in the step S2 by adopting a first-order linear equation, removing the trend term to form a second signal, and entering the step S4;
step S4, performing signal filtering on the second signal by adopting a median filter to form a third signal, and entering step S5;
step S5, adopting a moving average filter to carry out signal smoothing on the third signal to form a fourth signal, and entering step S6;
step S6, subtracting the average value of the fourth signal from the fourth signal to form a fifth signal, and entering step S7;
step S7, forming X, Y and Z-direction rotation angle signals in the normalized range of the fifth signal, wherein the normalized range is 0-1, and the step S8 is performed;
and S8, normalizing and fusing three signals of the rotation angle in the X-axis direction, the rotation angle in the Y-axis direction and the rotation angle in the Z-axis direction based on preset weights to form a fused signal, and entering an ending state.
In this embodiment, the weight acquisition method in step S8 is to manually give a fixed weight. In other embodiments of the present invention, the weight obtaining method may further be calculated according to a signal variation, calculated according to a signal variance and a noise variance ratio, a signal variance and a signal range ratio, or a signal range and a noise variance ratio. For example: performing signal variance estimation and noise variance estimation on the fifth signal; and taking the mean value or the median of the upper and lower signal envelopes for the fifth signal, and then calculating the mean value difference of the upper and lower envelopes. The weight acquisition method of the invention includes but is not limited to the above manner.
The time sequence signal reconstruction part 13 is used for filtering and denoising the acceleration signals in the sensor data packet by adopting various filtering and denoising strategies, generating a reconstructed time sequence signal and representing the respiration and movement speed of the human body.
Fig. 8 is a flowchart of the operation of the speed signal adding filter noise reduction in the time series signal reconstruction section in the embodiment of the present invention.
As shown in fig. 8, the posture calculation of the time-series signal reconstruction section 13 includes the steps of:
step U1, performing trend item fitting on 6 th order polynomials of acceleration signals in a sensor data packet, removing and forming a first transition signal, and entering a step U2;
step U2, carrying out 3-layer wavelet decomposition on the first transition signal through a Haar wavelet base, removing the high-frequency signal decomposed by the first layer, taking the reconstructed time sequence signal as a second transition signal, and then entering step U3;
step U3, performing smooth filtering on the transition signal II by adopting a Lowess method to form a transition signal III, and then entering a step U4;
and step U4, carrying out high-frequency signal decomposition on the transition signal III, setting the high-frequency signal to zero, reconstructing the time sequence signal, normalizing the time sequence signal to a range of 0-1 to obtain a reconstructed time sequence signal, and entering an end state.
The breathing and movement speed representation of the human body and the breathing and movement angle representation of the human body are fused to be used as the breathing movement representation of the human body.
After acquiring the respiratory motion characterization of the human body, the posture yaw correcting unit 14 initializes and corrects the sensor data packet sent from the signal transmitter 102, and generates a reset signal.
Once the attitude yaw correction section 14 generates the reset signal, the communication section 15 transmits the reset signal to the signal transmitter 102, and the signal transmitter 102 transmits the reset signal to the inertial sensor 101, so that the inertial sensor 101 completes initialization and correction.
The control unit 16 is connected to and controls the multidimensional data resolving unit 11, the fusion signal generating unit 12, the time series signal reconstructing unit 13, the attitude yaw correcting unit 14, and the communication unit 15.
Fig. 9 is a flow chart of a method of extracting respiratory and other motion features of the human body in an embodiment of the invention.
As shown in fig. 9, the method for extracting respiratory and other motion characteristics of a human body by using the respiratory monitoring device based on sensor array arrangement comprises the following steps:
in step 207, the attitude yaw correcting unit 14 generates a reset signal at the same time, and the communication unit 15 outputs the reset signal to the inertial sensor 103, thereby completing the initial reset and entering the end state.
In the above workflow, the reset signal is output to the inertial sensor 103 to facilitate the next detection, so that the detection result is more accurate.
Example operation and Effect
According to the respiration monitoring device based on the sensor array arrangement, as the inertial sensors are arranged on the muscle groups and bones of the human body in an array manner, and meanwhile, multipoint monitoring can be completed, compared with a traditional detection mode, the respiration monitoring device based on the sensor array arrangement has the advantages that the positions acquired by the inertial sensors are more in accordance with the characteristics of the human body, and the respiration monitoring quality is higher; thus obtaining more complete respiratory movement characteristics of the human body.
Further, the posture offset correction part sends a reset signal to the inertial sensor through the signal transmitter to finish correction and reset of the inertial sensor, so that data measured by the sensor each time are more accurate.
In the embodiment, the clothes for sensor arrangement are made of elastic materials, a plurality of positions to be selected are preset on the clothes, the arrangement positions of the inertial sensors can be changed according to the posture characteristics of different body types of people, the breathing movement characteristics of the different body types of people are collected, and the accuracy of the breathing movement characteristics of the different body types of people is guaranteed.
In the embodiment, the multi-dimensional data resolving part performs dynamic Kalman filtering algorithm, complementary filtering algorithm and gravity field filtering used for gesture resolving, so that the obtained gesture angle time sequence signal is more accurate.
In the embodiment, the accuracy of the obtained reconstructed time sequence signal is further enhanced due to the manners of fitting trend terms, wavelet decomposition filtering, high-frequency signal decomposition, time sequence signal reconstruction and the like used by the time sequence signal reconstruction part for filtering and noise reduction.
In the embodiment, the fusion signal obtained by the fusion signal generating part in the modes of decomposing the reconstructed time sequence signal, fitting and dividing the trend term, signal smoothing, signal variance estimation, noise variance estimation, signal weighting normalization and the like by adopting the sym5 wavelet basis for the angular velocity signal fusion processing has the characteristics of high precision and high accuracy.
The above examples are only for illustrating the specific embodiments of the present invention, and the present invention is not limited to the description scope of the above examples.
For example, in the above embodiments, the multi-inertial sensor deployment locations are focused on the muscle groups and skeletal distribution locations of the upper body of the patient. In other embodiments of the invention, other inertial sensor control locations are provided, such as at other muscle groups and bone distribution locations, to better capture the motion breath state of the person during motion.
In the above embodiment, the multiple inertial sensors synchronously acquire information of the positions of the multiple inertial sensors as sensor data packets. In other schemes of the invention, the multi-inertial sensor can only collect the information of the position of the multi-inertial sensor as a sensor data packet according to the working requirement.
Claims (9)
1. A respiration monitoring device based on sensor array formula is arranged for monitor human respiratory condition, its characterized in that includes:
the M inertial sensors are respectively fixed on the trunk part of the human body in an array mode according to the muscle groups and skeleton distribution conditions of the human body, and synchronously acquire the inertial sensors to form M groups of sensor data packets;
the number of the N signal transmitters is not more than the number of the inertial sensors, and the signal transmitters are in communication connection with the inertial sensors; and
a signal receiving device in communication with said signal transmitter,
wherein the signal receiving apparatus has a multidimensional data resolving section, a time series signal reconstructing section, and a fusion signal generating section,
once the signal transmitter transmits the sensor data packet to the signal receiving apparatus, and the multidimensional data resolving section performs attitude resolution on the received sensor data packet to obtain a sensor attitude angle timing signal,
the fusion signal generating part performs angle signal fusion processing on the gesture angle time sequence signal to obtain a fusion signal which is used as the breathing and movement angle representation of the human body,
the time sequence signal reconstruction part adopts various filtering noise reduction strategies to filter and reduce noise of the sensor data packet to generate a reconstructed time sequence signal which is used as the representation of the breathing and the movement speed of the human body,
and fusing the breathing and movement speed representation of the human body with the breathing and movement angle representation of the human body to serve as the breathing movement representation of the human body.
2. The sensor array arrangement-based respiration monitoring device of claim 1, wherein:
wherein the inertial sensor comprises a sucker part made of flexible materials which can be attached to the skin of a human body, a rigid connecting rod part and a sensor body,
one end of the rigid connecting rod part is connected with the sucker part,
the other end of the rigid connecting rod part is provided with a buckling structure, and the separation and connection with the sensor body are completed through the buckling structure.
3. The sensor array arrangement-based respiration monitoring device of claim 2, further comprising:
a sensor-mounting garment having a plurality of rigid mounting holes corresponding to mounting positions of the inertial sensors,
the rigid connecting rod passes through the rigid fixing hole and is connected with the sensor body through the buckle structure.
4. A respiration monitoring device based on a sensor array arrangement according to claim 3, characterized in that:
the garment for sensor arrangement further comprises a to-be-selected fixing hole which is arranged nearby the rigid fixing hole and used for enabling the inertial sensor to replace the to-be-selected fixing hole to collect and form sensor data packages of the same positions of the muscle groups and the bones of patients with different posture characteristics.
5. The sensor array arrangement-based respiration monitoring device of claim 1, wherein:
the angle signal fusion processing comprises the following steps:
s1, decomposing the attitude angle time sequence signal into 9 layers of signals to be processed by adopting a sym5 wavelet basis;
step S2, setting zero of high-frequency signals of a first layer and a second layer and low-frequency signals of the lowest layer in the signals to be processed, and reconstructing a time sequence signal back to be used as a first signal through a wavelet reconstruction method;
step S3, fitting a trend term of the first signal by adopting a first-order linear equation, and removing the trend term to form a second signal;
s4, performing signal filtering on the second signal by adopting a median filter to form a third signal;
s5, performing signal smoothing on the third signal by using a moving average filter to form a fourth signal;
step S6, subtracting the mean value of the fourth signal from the fourth signal to form a fifth signal;
s7, normalizing the fifth signal to form angle signals in the X-axis, Y-axis and Z-axis directions;
and S8, normalizing and fusing the three signals of the angle signal in the X-axis direction, the angle signal in the Y-axis direction and the angle signal in the Z-axis direction based on preset weights to form the fused signal.
6. The sensor array arrangement-based respiration monitoring device of claim 5, wherein:
the weight obtaining method in the step S8 is any one of artificial fixed weight, calculation according to signal variation, calculation according to signal variance and noise variance ratio, signal variance and signal range ratio and signal range and noise variance ratio.
7. The sensor array arrangement-based respiration monitoring device of claim 1, wherein:
wherein the sensor data packet comprises acceleration information, angle information and magnetic force information corresponding to the position of the inertial sensor,
the gesture resolution includes at least:
step T1, processing the angle information and the acceleration information in the sensor data packet through a dynamic Kalman filtering algorithm and a complementary filtering algorithm to obtain attitude angle data of the inertial sensor;
step T2, filtering and correcting yaw angle data in the attitude angle of the inertial sensor by using the magnetic force information, so as to obtain an angle time sequence signal of the inertial sensor;
and step T3, filtering the angle time sequence signals in the directions of three axes of XYZ through a gravity field to obtain the attitude angle time sequence signals.
8. The sensor array arrangement-based respiration monitoring device of claim 7, wherein:
wherein the plurality of filtering noise reduction strategies includes:
step U1, performing trend item fitting on 6-order polynomials of acceleration information of the position of each sensor in the sensor data packet, and removing the trend item to form a first transition signal;
step U2, performing 3-layer wavelet decomposition on the first transition signal through a Haar wavelet base, removing a high-frequency signal decomposed by the first layer, and taking the reconstructed time sequence signal as a second transition signal;
step U3, smoothing and filtering the second transition signal by adopting a Lowess method to form a third transition signal;
and step U4, carrying out high-frequency signal decomposition on the third transition signal, setting the high-frequency signal to zero, reconstructing the high-frequency signal back to a time sequence signal, and normalizing the time sequence signal after the high-frequency signal is set to zero and reconstructed to obtain a normalized time sequence signal.
9. The sensor array arrangement-based respiration monitoring device of claim 1, wherein:
wherein the signal receiving apparatus further includes a posture yaw correcting section and a communication section,
the attitude yaw correction section is configured to generate a reset signal,
the communication section outputs the reset signal to the signal transmitter,
and the signal transmitter transmits the received reset signal to the inertial sensor, so that the inertial sensor is initialized and corrected.
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