CN107241153B - Impedance calculation device and method for body area network channel - Google Patents
Impedance calculation device and method for body area network channel Download PDFInfo
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- CN107241153B CN107241153B CN201710600762.9A CN201710600762A CN107241153B CN 107241153 B CN107241153 B CN 107241153B CN 201710600762 A CN201710600762 A CN 201710600762A CN 107241153 B CN107241153 B CN 107241153B
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- H04B17/391—Modelling the propagation channel
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- H—ELECTRICITY
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- H04B13/00—Transmission systems characterised by the medium used for transmission, not provided for in groups H04B3/00 - H04B11/00
- H04B13/005—Transmission systems in which the medium consists of the human body
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- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/0082—Monitoring; Testing using service channels; using auxiliary channels
- H04B17/0087—Monitoring; Testing using service channels; using auxiliary channels using auxiliary channels or channel simulators
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Abstract
Aiming at the defects of the prior art, the invention provides an impedance calculation device and an impedance calculation method of a body area network channel, wherein the impedance calculation device comprises a computer, a detection unit, a theoretical model unit, an actual measurement model unit and a fitting unit; the calculation method comprises the following steps: obtaining detection signals, obtaining a theoretical model, obtaining an actual measurement model, and establishing fitting of a full path model. The beneficial technical effects are as follows: the invention adopts a simulation mode on the whole communication path to connect the segmented models obtained in the previous 2 steps in series to form a full path model, thereby not only improving the simulation precision, but also reducing the model complexity. The invention provides a detection device suitable for the method.
Description
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to an impedance calculation device and an impedance calculation method for a body area network channel.
Background
With the development and progress of Sensor networks and Wireless communication, wearable or implantable Sensor nodes are becoming more and more popular, so that Wireless Body Area networks (wban) are widely applied to the fields of remote healthcare, special crowd care and the like, and are one of the branches of Wireless Sensor Networks (WSN). IEEE established the IEEE802.15.6 working group in 2007, and released the IEEE802.15.6 standard in 2012, which greatly promoted the development of wireless body area networks. The wireless body area network is a body-centered network, and comprises a wearable sensor on the surface of a body or an implanted sensor implanted in the body, and some possible devices (such as a mobile phone or a computer).
Wireless body area networks are also an important component of the internet of things iot (internet of thining) medical service system: the body physiological data including body temperature, blood pressure, heart rate and the like are observed and collected through various sensor nodes on the surface of the body or in the body, and then the physiological data are transmitted to various communication devices of doctors, guardians and other related personnel, so that the real-time analysis and feedback of the physiological parameters of the body area network user are realized, patients, old people or other special people are better monitored, and the ambulance can be directly dispatched in case of emergency.
In the process of transmitting signals, the transmission channel continuously loses signal energy, and factors influencing signal loss mainly include resistance loss, dielectric loss, radiation loss and the like. The impedance during the transmission of the wireless signal has a great influence on the design of the communication system. If the impedance estimation is too high in the design, the design desire is reserved too much, the system power consumption is too large, and the endurance time of the portable electronic equipment is shortened. If the channel impedance is estimated insufficiently, the impedance is caused to exceed the expected impedance, and the signal attenuation is too large, which directly causes the system to fail.
Existing modeling techniques include: simulation model, experimental model. During long-term use, the following disadvantages exist:
the pure simulation model adopts a pure theoretical model, physiological parameters are assigned to the virtual grid in a finite element modeling mode, and then the signal impedance is deduced by utilizing computer simulation. The disadvantages of this approach are: the accuracy of physiological parameters is difficult to guarantee, and detection on each cell of a body is impossible. Secondly, the modeling on the contact surface of the electrode and the body is difficult.
The experimental model obtains the impedance of the appointed path and the scene through actual measurement. The disadvantages are that: the experimental conditions cannot be met, and because the impedance is expressed differently on different people, different parts, different paths and the like, the experimental model can never meet rich and diverse application scenes.
Disclosure of Invention
In view of the above-mentioned deficiencies of the prior art, the present invention provides an apparatus and a method for calculating impedance of a body area network channel, which are intended to solve the following problems:
a composite modeling mode is adopted, and an experimental model is adopted at an electrode access end, so that the model precision is improved. And aiming at different parts of the body, corresponding measured data is adopted, and model parameters are obtained through fitting.
On the whole communication path, a simulation mode is adopted, and the segmented models obtained in the previous 2 steps are connected in series to form a full path model, so that the simulation precision is improved, and the model complexity is reduced.
A detection device suitable for use in the above method is provided.
The invention has the following specific structure:
an impedance calculation device of a body area network channel comprises a computer, and is provided with a detection unit, a theoretical model unit, an actual measurement model unit and a fitting unit. The specific connection relationship is as follows: the detection unit is connected with a computer, and a theoretical model unit, an actual measurement model unit and a fitting unit are installed in the computer.
A calculation method of an impedance calculation device of a body area network channel is characterized by comprising the following steps:
step 1: and acquiring a detection signal.
After the detection signal is coupled/conducted to the electrode, the clear detection signal is finally obtained through the amplifying module, the sampling module and the filtering module.
Step 2: and (6) obtaining a theoretical model.
The channel impedance is simulated by a computer by constructing an electrical property model of the body tissue by adopting a finite element simulation method.
And step 3: and (6) obtaining an actual measurement model.
The impedance calculating device is worn at different positions of a body, data of each part is obtained, modeling of each part of the body is respectively carried out by a computer, and prediction parameters of channel quality are obtained.
And 4, step 4: and establishing the fitting of the full path model.
And fitting by combining the prediction parameters of the channel quality and the detection signals after the modeling based on each part of the body is finished, and thus obtaining the impedance of the whole channel, namely, a step of outputting the result in real time after the step of acquiring the actual measurement model is finished.
The acquisition detection signal refers to bioelectrical information of an organism, and the bioelectrical information comprises an in-vivo signal and/or an in-vitro signal.
The theoretical model is a model obtained by mathematical derivation based on finite elements and the like.
The actual measurement model refers to an empirical model, wherein the empirical model contains or does not contain empirical values, and the actual measurement model in the invention
Including an empirical model of a partial body and a full path model consisting of a plurality of body segments.
The full path model refers to an impedance model of a complete channel.
Advantageous technical effects
The method improves the model precision of the electrode contact surface.
More accurate parameters of the body segment model can be obtained by using the methods of experiment respective tests.
On the whole communication path, a simulation mode is adopted, and the segmented models obtained in the previous 2 steps are connected in series to form a full path model, so that the simulation precision is improved, and the model complexity is reduced.
The present invention provides an apparatus for use in the above method.
Drawings
FIG. 1 is a schematic diagram of an exemplary implementation of the process of the present invention.
Detailed Description
The structural features and technical details of the present invention will now be described in detail with reference to the accompanying drawings.
The impedance calculation device for the body area network channel comprises a computer and is characterized by being provided with a detection unit, a theoretical model unit, an actual measurement model unit and a fitting unit. The specific connection relationship is as follows: the detection unit is connected with a computer, and a theoretical model unit, an actual measurement model unit and a fitting unit are installed in the computer.
Further, the detection unit comprises a bioelectric electrode and a bioelectric amplification module. Wherein, the bioelectricity electrode is an electroencephalogram electrode, a myoelectricity electrode and/or an electrocardio electrode.
Furthermore, the detection unit consists of a bioelectricity electrode, a bioelectricity amplification module, a sampling module and a filtering module. Wherein, the bioelectricity electrode comprises an electroencephalogram electrode, a myoelectricity electrode and an electrocardio electrode. The electroencephalogram electrode, the myoelectricity electrode and the electrocardio electrode are respectively connected with the sampling module through a bioelectricity amplifying module. The output end of the sampling module is connected with the input end of the filtering module.
The calculation method of the impedance calculation device of the body area network channel is adopted and comprises the following steps:
step 1: and acquiring a detection signal.
After the detection signal is coupled/conducted to the electrode, the clear detection signal is finally obtained through the amplifying module, the sampling module and the filtering module.
Step 2: and (6) obtaining a theoretical model.
The channel impedance is simulated by a computer by constructing an electrical property model of the body tissue by adopting a finite element simulation method.
And step 3: and (6) obtaining an actual measurement model.
The impedance calculating device is worn at different positions of a body, data of each part is obtained, modeling of each part of the body is respectively carried out by a computer, and prediction parameters of channel quality are obtained.
And 4, step 4: and establishing the fitting of the full path model.
And fitting by combining the prediction parameters of the channel quality and the detection signals after the modeling based on each part of the body is finished, and thus obtaining the impedance of the whole channel, namely, a step of outputting the result in real time after the step of acquiring the actual measurement model is finished.
The acquisition detection signal refers to bioelectrical information of an organism, and the bioelectrical information comprises an in-vivo signal and/or an in-vitro signal.
The theoretical model is a model obtained by mathematical derivation based on finite elements and the like.
The actual measurement model refers to an empirical model, wherein the empirical model contains or does not contain empirical values, and the actual measurement model in the invention comprises an empirical model of a partial body and a full path model consisting of a plurality of body segments.
The full path model refers to an impedance model of a complete channel.
Further, in step 1, the signals to be acquired are: electroencephalogram electrical signals, electromyogram electrical signals, and electrocardio electrical signals. The theoretical model is an electroencephalogram finite element impedance model, an electromyogram finite element impedance model and an electrocardio finite element impedance model.
Further, in step 1, a trigger submodule for detecting is included. The trigger submodule of detection is triggered by 2 factors: passive triggering and active triggering. Passive triggering is a timed trigger caused by a time factor. The active trigger is a timing trigger that is not caused by a time factor.
Further, passive triggering is used to prevent the system from sleeping. Active triggering is a triggering that results from a change in the user's posture, requiring recalculation of the channel impedance. I.e. active triggering is due to triggering caused by other factors of the system.
Further, in step 3, the actual measurement model z(s) is specifically:
the actual measurement model Z(s) is used for constructing impedance models of body joints, body segments and electrode contact surfaces, D and E are real number parameters, s is Laplace modulus, Pn is pole n, and Res is real number or complex number pair. Furthermore, the actual measurement model z(s) is constructed by acquiring the impedance of the body joint, the body segment and the electrode contact surface by using an actual measurement method, and then obtaining the specific values of the parameters by using a data fitting method.
Subsequently, a model of the entire communication path is constructed from the functional expression PL (d),
PL (d) ═ PL0+10nlog10(d/d0) (formula 2)
The model is used to model the entire communication path. d is the communication path length, d0 is the length of the nominal communication path, PL0 is the impedance value of the nominal communication path, PL0 is z(s).
Furthermore, the step of obtaining the actual measurement model is performed in the system setting stage. Wearing the impedance calculation device at different positions of the body of a person to be detected, acquiring detection signals and transmitting the detection signals to a computer for processing: obtaining the modeling of each part of the detected person body:
the way of modeling by computer is:
the system is based on after acquiring the detection signal
Fitting is performed to obtain the formulaThe specific value of the medium coefficient. And then using the obtained specific value as a prediction parameter of the channel quality in the subsequent time.
Example 1
Referring to fig. 1, a typical embodiment of the present invention is shown. The meanings of the numbers in the figures are given in the following table:
the formula employed in this embodiment is:
the model is used for constructing impedance models of joints, body sections and electrode contact surfaces of the body, D and E are real number parameters, s is Laplace modulus, Pn is pole n, and Res is real number or complex number pair. The construction method comprises the steps of firstly obtaining the impedance of a body joint, a body section and an electrode contact surface by adopting an actual measurement method, and then obtaining the specific values of the parameters by utilizing a data fitting method.
PL(d)＝PL0+10nlog10(d/d0) (2)
The above model is used to model the entire communication path. d is the communication path length, d0 is the length of the nominal communication path, and PL0 is the impedance value of the nominal communication path.
Claims (3)
1. A calculation method of an impedance calculation device of a body area network channel comprises a computer, a detection unit, a theoretical model unit, an actual measurement model unit and a fitting unit; the detection unit is connected with a computer, and a theoretical model unit, an actual measurement model unit and a fitting unit are installed in the computer; the detection unit comprises a bioelectricity electrode and a bioelectricity amplification module; wherein, the bioelectricity electrode is an electroencephalogram electrode, a myoelectricity electrode and/or an electrocardio electrode; the method is characterized by comprising the following steps:
step 1: acquiring a detection signal;
after the detection signal is coupled/conducted to the electrode, a clear detection signal is finally obtained through the amplification module, the sampling module and the filtering module;
step 2: acquiring a theoretical model;
simulating channel impedance by a computer by constructing an electrical property model of body tissues by adopting a finite element simulation method;
and step 3: obtaining an actual measurement model;
wearing the impedance calculation device at different positions of a body and acquiring data of each part, and respectively modeling each part of the body by a computer to acquire a prediction parameter of channel quality;
the actual measurement model Z(s) is specifically as follows:
the actual measurement model Z(s) is used for constructing impedance models of body joints, body segments and electrode contact surfaces, D and E are real number parameters, s is Laplace modulus, Pn is pole n, and Res is real number or complex number pair;
when an actual measurement model Z(s) is constructed, firstly, the impedance of a body joint, a body section and an electrode contact surface is obtained by adopting an actual measurement method, and then the specific values of the parameters are obtained by utilizing a data fitting method;
subsequently, a model of the entire communication path is constructed from the functional expression PL (d),
PL (d) ═ PL0+10nlog10(d/d0) (formula 2)
The model is used to build a model of the entire communication path; d is the communication path length, d0 is the length of the nominal communication path, PL0 is the impedance of the nominal communication path, PL0 is Z(s)
And 4, step 4: establishing fitting of a full path model;
after the modeling based on each part of the body is completed, fitting is carried out by combining the prediction parameters of the channel quality and the detection signals, and the impedance of the whole channel is obtained, namely, the step of outputting the result in real time after the step of acquiring the actual measurement model is completed;
the acquisition detection signal refers to bioelectrical information of an organism, and the bioelectrical information comprises an in-vivo signal and/or an in-vitro signal;
the theoretical model is a model obtained by mathematical derivation by adopting finite elements;
the actual measurement model is an empirical model which contains or does not contain empirical values, and comprises an empirical model of a part of body and a full path model consisting of a plurality of body segments;
the full path model refers to an impedance model of a complete channel.
2. The method of claim 1, wherein in step 1, the signals to be acquired are: electroencephalogram, electromyogram, and electrocardio signals; the theoretical model is an electroencephalogram finite element impedance model, an electromyogram finite element impedance model and an electrocardio finite element impedance model.
3. The method of claim 1, wherein in step 1, the method comprises a trigger submodule for detecting; the trigger submodule of detection is triggered by 2 factors: passive triggering and active triggering; passive triggers are timed triggers caused by time factors; the active trigger is a timing trigger that is not caused by a time factor.
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