JP2004024685A - Respiratory monitoring apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a respiratory monitoring apparatus with which accuracy of a respiratory signal can be improved. <P>SOLUTION: From among load signals of a plurality of load sensors 221 provided at a sheet part 2, a control part 3 of the respiratory monitoring apparatus A selects one load sensor 221 whose signal intensity in a respiratory frequency region is larger than that outside of the respiratory frequency region by a prescribed factor, and the respiratory signal is generated based on the load signal outputted from the selected load sensor 221. <P>COPYRIGHT: (C)2004,JPO

Description

[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to a respiratory monitoring device that can monitor a respiratory condition at bedtime.
[0002]
[Prior art]
2. Description of the Related Art As a conventional monitoring device for monitoring a respiratory state during sleep, there is a monitoring device for a respiratory disease disclosed in JP-A-2001-37742. This monitor device is provided under a bedding with a predetermined distribution and includes a plurality of load sensors that output a load signal corresponding to an applied load, and a frequency band corresponding to a respiration rate of a sleeping person from a load signal of the load sensor. The signal is calculated as a respiration signal.
[0003]
When the monitor device calculates a respiratory signal, first, the load signal of the load sensor is frequency-analyzed to calculate a power spectrum in a frequency band corresponding to the respiratory rate. Next, a respiration signal is generated from a load signal of a load sensor having a large power spectrum intensity.
[0004]
[Problems to be solved by the invention]
However, in the above-described conventional monitoring device, a load due to factors other than respiration, for example, a load due to the weight of a sleeping person or a large body motion is applied to the load sensor, and the intensity of the power spectrum in a frequency band corresponding to the respiration rate is large. If this happens, there is a problem that the accuracy of the generated respiratory signal is reduced.
[0005]
The present invention has been made in view of the above points, and has as its object to provide a respiratory monitoring device capable of improving the accuracy of a respiratory signal.
[0006]
[Means for Solving the Problems]
In order to achieve the above object, in the invention described in claim 1,
Under the bedding, installed in a predetermined distribution inside or on the surface, a plurality of load sensors that output a load signal corresponding to the applied load,
Based on a load signal output from the load sensor, a respiration signal generating means for generating a respiration signal corresponding to the respiratory state of the sleeping person,
A load sensor selecting means for selecting a load sensor based on a ratio of a signal strength in a frequency band corresponding to a respiration rate of a sleeper of the load signal to a signal strength outside the frequency band,
The respiratory signal generating means generates a respiratory signal based on a load signal output from the load sensor selected by the load sensor selecting means.
[0007]
According to this, the signal intensity in the frequency band corresponding to the respiratory rate of the sleeping person selects a load sensor that is sufficiently large with respect to the signal intensity outside the frequency band, and the respiration signal is generated by the load signal output from this load sensor. Can be generated.
[0008]
That is, it is possible to generate a respiration signal from a load signal of a load sensor in which applied load fluctuations due to factors other than respiration are small. Therefore, it is possible to improve the accuracy of the respiratory signal generated by the respiratory signal generating means.
[0009]
Further, as in the invention according to claim 2, the load sensor selecting means is configured to determine a ratio of a signal intensity of a frequency band corresponding to a respiration rate of a sleeper of the load signal to a signal intensity of a frequency band higher than the frequency band. May be used to select the load sensor.
[0010]
In addition, as in the invention according to claim 3, specifically, the load sensor selecting means is configured such that the average value of the signal strength of the load signal in the frequency band corresponding to the respiratory rate of the sleeping person is higher than the frequency band. It is possible to select a load sensor having a predetermined magnification or more with respect to the average value of the signal intensity in the frequency band.
[0011]
According to a fourth aspect of the present invention, the load sensor selecting means is configured to determine a ratio of a signal strength of a frequency band corresponding to a respiration rate of a sleeper of the load signal to a signal strength of a frequency band lower than the frequency band. The load sensor may be selected based on the following.
[0012]
In addition, as in the invention according to claim 5, specifically, the load sensor selecting means is configured such that the average value of the signal intensity of the load signal in the frequency band corresponding to the respiratory rate of the sleeping person is lower than the frequency band. It is possible to select a load sensor having a predetermined magnification or more with respect to the average value of the signal intensity in the frequency band.
[0013]
The invention according to claim 6 is characterized in that before the load sensor selecting means selects a load sensor, the load sensor selecting means includes a bias component removing means for removing a bias component from the load signal.
[0014]
According to this, for example, even if a bias component is added to the load signal of the load sensor due to the weight of the sleeping person, a large body motion, or the like, this can be removed. Therefore, it is possible to generate a respiratory signal from a load signal without a bias component. In this way, it is possible to further improve the accuracy of the respiratory signal generated by the respiratory signal generating means.
[0015]
Further, in the invention according to claim 7, before the load sensor selecting means selects the load sensor, the load sensor selecting means for extracting the load sensor substantially below the sleeping person based on the load signal is provided. Features.
[0016]
According to this, it is possible for the load sensor extracting unit to select the load sensor by the load sensor selecting unit after extracting the load sensor on which the sleeping person is riding upward based on the load signal. That is, it is possible to select the load sensor by the load sensor selecting unit after excluding the load sensor on which the sleeping person is not riding. Therefore, it is possible to improve the selection speed by the load sensor selection unit.
[0017]
In the invention according to claim 8, when the amplitude of the respiratory signal generated by the respiratory signal generating means is equal to or less than a predetermined value for a predetermined time, the amplitude is based on a new load signal output from the load sensor. And regenerating the respiratory signal.
[0018]
Depending on the relationship between the signal strength in the frequency band corresponding to the respiratory rate and the signal strength outside the frequency band, a load sensor in which the load signal does not include a large amount of the component due to respiration may be selected by the load sensor selection unit. is there. In such a case, generally, the amplitude of the respiratory signal generated by the respiratory signal generating means becomes small.
[0019]
Therefore, when the amplitude of the respiratory signal generated by the respiratory signal generating means is equal to or less than the predetermined value for a predetermined time, it is possible that a load sensor in which the load signal does not include a component due to respiration is selected. It is determined to be high. In such a case, a respiratory signal can be obtained with high reliability by regenerating the respiratory signal based on a new load signal output from the load sensor.
[0020]
In this way, it is possible to further improve the accuracy of the respiratory signal generated by the respiratory signal generating means.
[0021]
According to the ninth aspect of the present invention, there is provided a notifying means for notifying in synchronization with the respiratory signal generated by the respiratory signal generating means.
[0022]
According to this, when the respiration signal synchronized with the respiration is not generated, it is possible to notify the sleeping person or the like by the notification means. Therefore, for example, it is possible to promote an improvement in a state where the respiratory measurement environment is not preferable, for example, when the state of the bedding is inappropriate, and it is possible to prevent the generation of a respiratory signal in an unfavorable state. In this way, the accuracy of the respiratory signal generated by the respiratory signal generating means can be more reliably improved.
[0023]
BEST MODE FOR CARRYING OUT THE INVENTION
Hereinafter, embodiments of the present invention will be described with reference to the drawings.
[0024]
FIG. 1 is a diagram showing an installation state when using a respiration monitoring device A according to an embodiment of the present invention. FIG. 2 is a schematic configuration diagram of the respiration monitoring device A.
[0025]
As shown in FIG. 1, the bed 1 includes a placing section 11 on which a bedding 10 such as a mattress is placed, and a back plate section 12 erected from an end of the placing section 11. The respiration monitoring device A is used by being inserted into a lower portion of the bedding 10 installed on the bed 1. The respiration monitoring device A is installed closer to the back plate 12 than the center of the placement unit 11 so as to correspond to the position of the sleeper from the chest to the abdomen when the sleeper lays down on the bed 1. .
[0026]
As shown in FIG. 2, the respiration monitoring device A includes a seat unit 2 and a control unit 3. The sheet unit 2 is configured by sandwiching a plurality of (three in this example) sensor sheets 22 and a sensor selection unit 23 provided for each sensor sheet 22 between two sheet-shaped protection members 21. Have been.
[0027]
The sensor sheet 22 includes a plurality of pressure-sensitive elements 221 (in this example, a total of three sheets, 162) of which pressure resistance elements 221 whose electric resistance changes (decreases) in accordance with an applied load are arranged at substantially equal intervals. . In FIG. 2, illustration of a wiring pattern for electrically connecting each pressure-sensitive element 221 and the sensor selection unit 23 is omitted.
[0028]
That is, when a voltage is applied to the circuit including each pressure-sensitive element 221, the electric resistance of the pressure-sensitive element 221 changes according to the applied load, so that the voltage drop value of the pressure-sensitive element 221 increases and decreases. The applied load can be independently detected for each pressure-sensitive element 221 based on the change in the voltage drop value. That is, the pressure-sensitive element 221 is the load sensor according to the present embodiment.
[0029]
The control unit 3 includes an A / D converter 31, a microcomputer 32, a memory 33, and a display unit 34, as shown in the block diagram of FIG. Then, in the control unit 3, the load signals of the respective pressure-sensitive elements 221 of the sensor sheet 22 are sequentially selected by the sensor selection unit 23, and the load signals, which are analog values, are digitally converted via the A / D converter 31. A value converted into a value (hereinafter, AD value) is taken into the microcomputer 32. At this time, the microcomputer 32 supplies a switching signal to the sensor selection unit 23 to switch the load signal to be input.
[0030]
Then, based on the input load signal, the microcomputer 32 performs processing while storing an AD value or the like in the memory 33 as necessary according to a procedure described later, calculates a respiration curve as a respiration signal, and displays the result on a display unit. 34. The display unit 34 displays the respiratory state such as the respiratory intensity as a numerical value or a graph, and sounds a buzzer (not shown).
[0031]
With the configuration described above, the sleeping person can check the respiratory rate, respiratory curve, and the like during sleep that he cannot be aware of without directly wearing a special sensor on the body.
[0032]
Next, the operation of the respiration monitoring device A based on the above configuration will be described.
[0033]
FIG. 4 is a flowchart showing a schematic processing operation of the microcomputer 32. When power is supplied to the power supply circuit of the control unit 3 (not shown), as shown in FIG. 4, the microcomputer 32 first reads the load signals output from the 162 pressure-sensitive elements 221 sequentially (step S1).
[0034]
When the load signal is read, the pressure-sensitive element 221 whose strength of the load signal is equal to or more than a predetermined value (in other words, the voltage drop value in the pressure-sensitive element 221 is equal to or less than a predetermined value) is extracted as an element on which a person is riding upward ( Step S2). That is, step S2 is a load sensor extracting unit that extracts a load sensor substantially below the sleeping person in the present embodiment.
[0035]
After executing Step S2, the bias component is removed from the load signal output from the pressure-sensitive element 221 extracted in Step S2 (Step S3). The load signal output from the pressure-sensitive element 221 includes, in addition to the change component accompanying breathing and the like, a bias component such as a load component due to the weight of the sleeping person and the like applied to each pressure-sensitive element 221. Have been.
[0036]
In step S3, by removing a bias component from the load signal before generating a respiration signal or the like based on the load signal in a step described later, it is possible to improve the detection accuracy of the respiratory state. FIG. 5 shows a flow of the bias component removal processing.
[0037]
When performing the bias component removal shown in step S3, first, as shown in FIG. 5, in order to remove a noise component higher than the frequency (0.2 to 0.5 Hz in this example) corresponding to the respiratory rate. Then, a filtering process using a digital filter is performed (step S31). In this example, a digital filter capable of cutting a frequency band of 3 Hz or more is employed.
[0038]
The graph shown in FIG. 6A is an example of a load signal output from the pressure-sensitive element 221. The result of executing step S31 on this load signal is the graph shown in FIG. 6B.
[0039]
After executing step S31, a filtering process using a digital filter is performed to remove a frequency component corresponding to the approximate respiration rate (step S32). In this example, a digital filter that can cut a frequency band of 0.3 Hz or more in this step is employed.
[0040]
Explaining with a graph of the load signal as an example, by performing step S32 on the result of the graph of FIG. 6B obtained in step S31, a graph shown in FIG. 6C is obtained as a result.
[0041]
After executing step S32, a bias removal curve is calculated (step S33). In step S33, the result obtained in step S32 (for example, the signal shown in the graph of FIG. 6C) is subtracted from the result obtained in step S31 (for example, the signal shown in the graph of FIG. 6B). Thus, a curve from which the bias component has been removed (exemplified in FIG. 6D) is obtained.
[0042]
In the present embodiment, the bias component is removed by performing the filtering process of the digital filter twice. To remove the bias component, a filtering process using a band-pass filter can be performed. However, this embodiment has the advantage that the filter order can be reduced and the calculation time can be shortened.
[0043]
Step S3 is a bias component removing unit in the present embodiment. In this example, a digital filter capable of cutting a frequency band of 3 Hz or more and a digital filter capable of cutting a frequency band of 0.3 Hz or more are employed. Any filter that cuts the above can be adopted.
[0044]
After step S3 shown in FIG. 4 is executed according to the flow shown in FIG. 5, the pressure-sensitive element 221 from which the load signal required for generating the respiration signal is obtained is selected (step S4). Among the pressure-sensitive elements 221 extracted in step S2, there are some pressure-sensitive elements 221 to which a load is applied by a sleeping person or the like, but a load change (respiratory component) due to respiration is not detected much.
[0045]
In step S4, before generating a respiration signal or the like based on the load signal in a step described later, the pressure-sensitive element 221 that outputs the load signal containing a large amount of respiratory components is selected, so that the detection accuracy of the respiratory state is determined. Can be improved. FIG. 7 shows a flow of the respiration detection sensor (pressure-sensitive element) selection processing.
[0046]
When performing step S4, as shown in FIG. 7, first, frequency analysis is performed on the load signal from which the bias component obtained in step S3 has been removed (step S41). The frequency analysis is performed on each of the load signals output from the pressure-sensitive elements 221 extracted in step S2.
[0047]
The graph shown in FIG. 8A is an example of a load signal output from the pressure-sensitive element 221 and from which the bias component has been removed. The result of executing step S41 for this load signal is the power shown in FIG. 8B. It is a graph of a spectrum.
[0048]
After executing step S41, the average value α of the power spectrum value (signal intensity) in the respiratory frequency (frequency corresponding to the respiratory rate, in this example, 0.2 to 0.5 Hz as described above) is calculated. It is calculated (step S42). In accordance with this, the average value β of the power spectrum values in the frequency range higher than the respiration frequency (frequency higher than 0.5 Hz in this example) is calculated (step S43).
[0049]
After execution of step S43, ten power spectra having a large peak value in the respiratory frequency range of the power spectrum are selected from the top (step S44), and the average value α and the average value β are compared for each of the ten power spectra. Then, a power spectrum in which α is at least 10 times that of β is selected. Then, the pressure-sensitive element 221 corresponding to the selected power spectrum is set as a candidate for a sensor for detecting a respiratory signal (step S45).
[0050]
In steps S44 and S45, as illustrated in FIG. 8C, the relationship between the average value α and the average value β and the peak value are calculated, and the pressure-sensitive elements 221 are narrowed down based on the calculated values.
[0051]
After executing step S45, for each of the power spectra selected in step S45, an average value γ of the power spectrum values in a frequency range lower than the respiration frequency (frequency lower than 0.2 Hz in this example) is calculated (step S46). .
[0052]
After the execution of step S46, the average value α and the average value γ are compared for each of the power spectra, and a power spectrum in which α is 5 or more times γ is selected. Then, the pressure-sensitive element 221 corresponding to the selected power spectrum is used as a sensor for detecting a respiratory signal (step S47).
[0053]
The pressure-sensitive elements 221 not selected in Steps 45 and S47 are affected by body movements other than respiration and are excluded as unfavorable sensors for calculating a respiration signal. In step S47, as illustrated in FIG. 8D, the relationship between the average value α and the average value γ is calculated, and based on this, the pressure-sensitive elements 221 are further narrowed down.
[0054]
After executing step S47, the pressure sensing element 221 (sensor number) selected in step S47 and its load signal are stored in the memory 33 (step S48). Further, among the pressure-sensitive elements 221 selected in step S47, the pressure-sensitive element having the largest peak value of the power spectrum is selected and used as a reference sensor for calculating a respiration curve described later (step S49).
[0055]
Step S4 in FIG. 4 showing the flow in FIG. 7 is the load sensor selecting means in the present embodiment.
[0056]
After executing step S4 shown in FIG. 4 according to the flow shown in FIG. 7, next, a respiration curve, which is a respiration signal, is calculated (step S5). FIG. 9 shows the flow of the respiration curve calculation process.
[0057]
When step S5 is executed, as shown in FIG. 9, first, a cross-correlation function regarding the load signal after removing the bias component of the pressure-sensitive element selected as the reference sensor in step S4 and another pressure-sensitive element is calculated. Then, the phase difference between the load signal output from the other pressure-sensitive element and the load signal output from the reference sensor is calculated (step S51).
[0058]
After executing step S51, it is next determined whether or not the load signal has a phase substantially opposite to that of the reference sensor. Specifically, it is determined whether or not the phase difference is in the range of 9/20 to 11/20 cycle (π ± π / 10) (step S52). If the phase difference is within this range, the phase difference is stored in the memory 33 as a pressure-sensitive element for detecting the opposite phase (step S53).
[0059]
If it is determined in step S52 that the phase difference is not within the above range, it is determined whether or not the load signal has substantially the same phase as the reference sensor. Specifically, it is determined whether or not the phase difference is within a range of ± 1/20 cycle (0 ± π / 10) (step S54). If the phase difference is within this range, the phase difference is stored in the memory 33 as a pressure-sensitive element for detecting the same phase (step S55).
[0060]
The step of selecting the pressure-sensitive element based on the phase difference is executed for all the pressure-sensitive elements 221 selected in step S4, and when this is completed (step S56), the respiration curve is calculated (step S57).
[0061]
In step S57, the AD value after removing the bias component of the load signal output from the pressure-sensitive element that detects the opposite phase is multiplied by -1 and then added, and the load output from the pressure-sensitive element that detects the same phase is added. The AD values after the removal of the bias component of the signal are added, and the sum of these AD values is divided by the number of pressure-sensitive elements determined to detect the opposite phase or the same phase to obtain the value of the respiration curve.
[0062]
Note that step S5 in FIG. 4 whose flow is shown in FIG. 9 is a respiration signal generation unit in the present embodiment.
[0063]
When step S5 shown in FIG. 4 is executed according to the flow shown in FIG. 9, it is determined whether the state where the amplitude of the respiration curve calculated in step S5 is equal to or smaller than a predetermined value has continued for a predetermined time (for example, 30 seconds) or more (step S6). .
[0064]
When the load variation accompanying respiration is not so much applied to the pressure-sensitive element 221 selected by the flow up to step S4 described above (for example, any of the pressure-sensitive elements 221 of the sensor sheet 22 is accompanied by respiration). In general, when the load variation is not so much applied, the value (amplitude) of the respiration curve calculated in step S5 becomes extremely small.
[0065]
Therefore, when it is determined in step S6 that the state where the amplitude of the respiration curve is equal to or less than the predetermined value has continued for the predetermined time or more, the process returns to step S1. That is, a new load signal is input, and the respiration curve is calculated again based on the load signal (re-calculation of the respiration curve is performed again).
[0066]
If the determination is negative in step S6, the respiration curve intensity is output to the display unit 34 (step S7), and this is displayed on the display unit 34.
[0067]
After executing step S7, a buzzer (not shown) provided in the control unit 3 is sounded in synchronization with the respiration curve to notify a sleeping person or the like (step S8). By performing a buzzer sound synchronized with the respiratory curve in step S8, when there is a problem such as when the bedding environment is unfavorable, or when the location where the respiratory monitoring device is installed is unfavorable, the problem is improved. Can be prompted. FIG. 10 shows a flow of a respiratory curve notification process.
[0068]
When step S8 is executed, first, as shown in FIG. 10, it is determined whether or not the measurement is within a predetermined time (in this example, the time of 10 cycles of respiration) (step S81). The start of measurement refers to a point in time when it is first determined to be no in step S6 and a respiration curve starts to be generated normally.
[0069]
If it is determined as NO at step S81, the subsequent steps are not executed. This is to prevent the sleeping person from going to sleep when the predetermined time has elapsed since the start of the measurement, and to prevent the sleeping sound of the sleeping person from being disturbed by the sound of the buzzer.
[0070]
If it is determined in step S81 that it is within a predetermined time from the start of measurement, it is determined whether the value of the respiration curve is positive or negative (step S82), and the buzzer sounds only when the value is positive (step S83). In steps S82 and S83, the buzzer sounds only when the respiratory curve is positive, so that a notification synchronized with the respiratory curve (respiratory signal) can be performed.
[0071]
In this example, the notification is performed by buzzer sounding, but the notification may be performed by blinking an LED or the like. Step S8 in FIG. 4 showing the flow in FIG. 10 is a notification unit in the present embodiment.
[0072]
According to the above configuration and operation, in steps S4 and S5, the pressure-sensitive element 221 whose signal strength in the frequency band corresponding to the respiratory rate of the sleeping person is sufficiently large with respect to the signal strength outside the frequency band is selected. It is possible to generate a respiration signal (respiration curve) from the load signal output from the pressure-sensitive element. That is, it is possible to generate a respiratory signal from the load signal of the pressure-sensitive element 221 in which the applied load changes little due to factors other than respiration.
[0073]
In step S3, the bias component can be removed from the load signal. Therefore, it is possible to generate a respiratory signal from the load signal from which the bias component has been removed.
[0074]
Further, when it is determined in step S6 that a pressure-sensitive element in which the component due to breathing is not so much included in the load signal has been selected in step S4, a new load signal output from the pressure-sensitive element is selected. Based on this, the respiration signal can be regenerated.
[0075]
In addition to this, in step S8, by notifying the sleeping person or the like in synchronization with the respiration signal, it is possible to encourage the measurement environment to be improved when the measurement environment of the respiration signal is not preferable.
[0076]
As a result, the accuracy of the respiratory signal is improved, and a highly reliable respiratory signal can be obtained.
[0077]
In addition, before executing the flow after step S3, in step S2, the pressure-sensitive element 221 substantially below the sleeping person (the sleeping person is on the top) is extracted. Then, the subsequent flow is executed only for the load signals of the pressure-sensitive elements narrowed down. Therefore, the processing speed can be improved.
[0078]
(Other embodiments)
In the above embodiment, after calculating the average values α and β of the power spectrums derived by the frequency analysis in step S41 (steps S42 and S43), the power spectrums having the top 10 peak values are selected (step S44). However, steps S42 and S43 may be executed after executing step 44.
[0079]
In the above-described embodiment, the pressure-sensitive element is selected from the ratio of the average value α to the average value β and the ratio of the average value α to the average value γ in step S4. However, the pressure-sensitive element is selected from only one of the ratios. It may be something.
[0080]
Further, in the above-described embodiment, real values such as ten, five times, ten times, and ± 1/20 cycle are mere examples, and the respiration monitoring device A includes the characteristics of the pressure-sensitive element 221 and the configuration of the sensor sheet 22. Can be appropriately set in accordance with the various characteristics.
[0081]
In the above-described embodiment, the pressure-sensitive elements that output load signals having substantially the same phase and substantially the opposite phase as the respiratory body motion signal of the reference sensor are selected, and the respiration curve is calculated based on those load signals. Select only pressure-sensitive elements that output load signals of approximately the same phase, or select only pressure-sensitive elements that output load signals of approximately the opposite phase, and calculate the respiration curve based on one of these load signals It may be.
[0082]
The load sensor is not limited to the pressure-sensitive type, but may be any sensor that can detect local loads at a plurality of places of the bedding, such as a capacitance type sensor and a strain gauge. Further, the number of sensors is not limited to 162, but can be arbitrarily increased or decreased.
[0083]
Further, in the above-described embodiment, an example in which the calculated respiration intensity is displayed on the display unit 34 has been described. However, for example, a dedicated window is set on the TV screen and displayed in the window. May be displayed. Further, the respiration signal may be stored in a storage medium and used as diagnostic data by a doctor. Further, the diagnostic data may be transmitted to a hospital or the like using a public line or the like.
[Brief description of the drawings]
FIG. 1 is an explanatory diagram illustrating an installation state of a respiration monitoring device A according to an embodiment of the present invention.
FIG. 2 is a schematic configuration diagram of a respiration monitor device A according to an embodiment of the present invention.
FIG. 3 is a block diagram showing a schematic circuit configuration of the respiration monitoring device A.
FIG. 4 is a flowchart showing a schematic processing operation of a microcomputer 32;
FIG. 5 is a flowchart illustrating a bias component removal processing operation of the microcomputer 32;
FIG. 6 is a graph illustrating a bias component removal process according to a processing procedure.
FIG. 7 is a flowchart showing a respiration detection sensor selection processing operation of the microcomputer 32;
FIG. 8 is a graph according to a processing procedure for explaining a respiration detection sensor selection processing.
FIG. 9 is a flowchart showing a respiratory curve calculation processing operation of the microcomputer 32;
FIG. 10 is a flowchart showing a respiratory curve notification processing operation of the microcomputer 32;
[Explanation of symbols]
A respiratory monitoring device 2 sheet unit 3 control unit 22 sensor sheet 32 microcomputer 34 display unit 221 pressure-sensitive element (load sensor)

Claims (9)

Under the bedding, installed in a predetermined distribution inside or on the surface, a plurality of load sensors that output a load signal corresponding to the applied load,
A respiratory monitoring device comprising:
A load sensor selection unit that selects the load sensor based on a ratio of a signal strength of a frequency band corresponding to a respiration rate of the sleeping person of the load signal to a signal strength outside the frequency band,
The respiration signal generator, wherein the respiration signal generator generates the respiration signal based on a load signal output from the load sensor selected by the load sensor selector. The load sensor selecting unit selects the load sensor based on a ratio of a signal intensity of a frequency band corresponding to the respiration rate of the sleeping person of the load signal to a signal intensity of a frequency band higher than the frequency band. The respiratory monitoring device according to claim 1, wherein: The load sensor selection means, the average value of the signal intensity of the frequency band corresponding to the respiratory rate of the sleeping person of the load signal, the average value of the signal intensity of the frequency band higher than the frequency band, a predetermined magnification or more The respiration monitoring device according to claim 2, wherein the load sensor is selected. The load sensor selecting means selects the load sensor based on a ratio of a signal intensity of a frequency band corresponding to the respiration rate of the sleeping person of the load signal to a signal intensity of a frequency band lower than the frequency band. The respiratory monitoring device according to any one of claims 1 to 3, wherein: The load sensor selection means, the average value of the signal intensity of the frequency band corresponding to the respiratory rate of the sleeping person of the load signal, the average value of the signal intensity of the frequency band lower than the frequency band, a predetermined magnification or more The respiratory monitoring device according to claim 4, wherein the load sensor is selected. 6. The apparatus according to claim 1, further comprising a bias component removing unit configured to remove a bias component from the load signal before the load sensor selecting unit selects the load sensor. Respiratory monitoring device. 2. The apparatus according to claim 1, further comprising: a load sensor extracting unit configured to extract the load sensor substantially below the sleeping person based on the load signal before the load sensor selecting unit selects the load sensor. A respiratory monitoring device according to any one of claims 6 to 6. When the amplitude of the respiration signal generated by the respiration signal generation means is equal to or less than a predetermined value for a predetermined time, a respiration signal is generated again based on a new load signal output from the load sensor. The respiratory monitoring device according to any one of claims 1 to 7, wherein: The respiratory monitoring device according to any one of claims 1 to 8, further comprising: a notifying unit that performs notification in synchronization with the respiratory signal generated by the respiratory signal generating unit.

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