JP3809847B1 - Sleep diagnostic device and sleep apnea test device - Google Patents

Abstract

Information required for a sleep apnea test is obtained from a single acceleration sensor.
When the x-axis direction is the patient's left-right direction, the y-axis direction is the patient's height direction, and the z-axis direction is the patient's body thickness direction, x and z obtained from a three-dimensional acceleration sensor 2 are obtained. Using each DC component DCx, DCz, the patient's sleeping posture can be detected from (DCx / (DCx ² + DCz ² ) ^1/2 , DCz / (DCx ² + DCz ² ) ^1/2 ). y, the AC components ACx of z, ACy, filtered at 0.3Hz about lowpass filter ACZ, using the amplified ^output, the patient from ^{(ACx 2 + ACy 2 + ACz} 2) 1/2 of the reciprocal of the peak period The z-component ACz is filtered with a band-pass filter of about 10 to 15 Hz, and the heart rate of the patient is detected from the reciprocal of the peak period of the amplified output. Can be issued.
[Selection] Figure 5

Description

The present invention relates to a device used for sleep diagnosis and sleep apnea syndrome (SAS) diagnosis, and more particularly to improvement of a sensor portion.

  Biological sensors used for at least one of sleep tests and sleep apnea tests include airflow sensors for detecting breathing in the nostrils, tracheal sound sensors for detecting snoring, and respiratory movements. Various sensors such as a respiration sensor and a heart rate sensor for measuring a heart rate are used according to each purpose. In particular, in sleep apnea testing, in order to measure respiratory motion, band-shaped strain gauges are wrapped around the chest and abdomen to measure the phase difference of movement between the chest and abdomen and the magnitude of the motion, and the upper airway It is diagnosed whether it is a so-called obstructive type due to stenosis, or whether it is a so-called central type that stops breathing in the chest and abdomen at the same time when ventilation from the nose and mouth stops. At that time, a posture sensor for measuring the sleeping posture is also used.

  Therefore, in the sleep test and the sleep apnea test, various biosensors are used, which increases the burden on the patient. In particular, when a patient brings an inspection apparatus home to his / her home and wears the sensor himself, a sensor system that obtains more information by reducing the types of biosensors as much as possible is strongly expected.

On the other hand, Patent Document 1 proposes a mid-wake alert determination system that detects body motion using an acceleration sensor and determines mid-wake alert. Further, Patent Document 2 proposes a body motion analysis device that measures the posture and motion of a subject in daily life by analyzing the frequency of an output from an acceleration sensor, respectively.
JP 2002-34955 A JP-A-7-178073

  Therefore, it is conceivable to obtain each biological information used for the sleep test and sleep apnea test using the acceleration sensor as described above. However, the acceleration sensor disclosed in Patent Document 1 only detects body movement, and detects heartbeats and pulses by other detection means, and the above-described problem remains. On the other hand, in Patent Document 2, body motion is detected by a single acceleration sensor, but it detects the standing or sitting of daily life, and it is slight and little change as measured by a sleep apnea test. Body movement cannot be detected. In particular, respiration is slower than heartbeat, and know-how is required to separate signal components.

An object of the present invention is to provide a sleep diagnostic apparatus and a sleep apnea test apparatus that can obtain living body information necessary for sleep diagnosis and sleep apnea test from one acceleration sensor.

Configuration for realizing at least one of functions of the sleep diagnostic apparatus according to the present invention and sleep apnea test apparatus, an acceleration sensor of a three-dimensional, low-pass filter and a band-pass filter for filtering the output of the acceleration sensor, the An amplifier that amplifies the output of the acceleration sensor with a desired gain, and when the x-axis direction is the patient's left-right direction, the y-axis direction is the patient's height direction, and the z-axis direction is the patient's body thickness direction, the tertiary The patient's sleeping posture is detected from the DC components DCx and DCz of x and z obtained from the original acceleration sensor, and the AC components ACx, ACy and ACz of x, y and z are filtered by the low-pass filter, and The respiratory rate of the patient is detected from the output amplified by the amplifier, the AC component ACz of z is filtered by the bandpass filter, and Signal processing means for detecting the heart rate of the patient from the output amplified by the amplifier .

The configuration for realizing the function of at least one of the sleep diagnostic apparatus according to the present invention and sleep apnea test apparatus, an acceleration sensor of a three-dimensional, low-pass filter and a band-pass filter for filtering the output of the acceleration sensor An amplifier that amplifies the output of the acceleration sensor with a desired gain, when the x-axis direction is the patient's left-right direction, the y-axis direction is the patient's height direction, and the z-axis direction is the patient's body thickness direction, From (DCx / (DCx ² + DCz ² ) ^1/2 , DCz / (DCx ² + DCz ² ) ^1/2 ) using x and z DC components DCx and DCz obtained from the three-dimensional acceleration sensor , And the AC components ACx, ACy, ACz of x, y, z are filtered by a low-pass filter, and the amplified output is used ( ACx ² + ACy ² + ACz ² ) The patient's respiratory rate is detected from the reciprocal of the peak period of ^1/2 , the AC component ACz of z is filtered by a bandpass filter, and the heart rate of the patient is determined from the reciprocal of the peak period of the amplified output. It is characterized by detecting numbers.

According to the above configuration, when the x-axis direction is the patient's left-right direction, the y-axis direction is the patient's height direction, and the z-axis direction is the patient's body thickness direction, x, obtained from the three-dimensional acceleration sensor Using each DC component DCx, DCz of z, from (DCx / (DCx ² + DCz ² ) ^1/2 , DCz / (DCx ² + DCz ² ) ^1/2 ), the patient's sleeping posture (from the leg side of the patient) Rotation around the height axis (y-axis)), and the AC components ACx, ACy, ACz of x, y, z are filtered by a low-pass filter of about 0.3 Hz, and the amplified output is used. , (ACx ² + ACy ² + ACz ² ) The respiration rate of the patient can be detected from the reciprocal of the peak period of ^1/2 , and the AC component ACz of z is filtered with a bandpass filter of about 10 to 15 Hz, The heart rate of the patient can be detected from the reciprocal of the peak period of the amplified output.

  Therefore, it is possible to obtain living body information necessary for sleep diagnosis and / or sleep apnea test from one acceleration sensor, reduce the burden of sensor mounting and measurement from the patient, and acquire data. It can be expected to reduce errors.

Furthermore, in the configuration for realizing at least one of the functions of the sleep diagnostic apparatus and the sleep apnea test apparatus according to the present invention , the signal processing means includes x, y, and z obtained from the three-dimensional acceleration sensor. Using the output of each DC component DCx, DCy, DCz , the number of times that the combined value of (DCx ² + DCy ² + DCz ² ) ^1/2 exceeds a predetermined threshold is obtained as the number of steps, and gravity can be detected by the DCz component. It is characterized by determining whether a patient is sleeping or getting up from whether it is .

According to the above configuration, when the x-axis direction is the patient's left-right direction, the y-axis direction is the patient's height direction, and the z-axis direction is the patient's body thickness direction, x, obtained from the three-dimensional acceleration sensor Using the outputs of the DC components DCx, DCy, and DCz of y and z, the number of times that the combined value of (DCx ² + DCy ² + DCz ² ) ^1/2 exceeds a predetermined threshold can be obtained as the number of steps. Moreover, it can be determined that the patient is sleeping if it can be detected based on whether or not gravity can be detected with the component of DCz, and is standing up (sitting position) if not detected.

  Therefore, it is possible to diagnose the quality of sleep (whether you are sleeping properly) from the amount of sitting and walking, and the accuracy of diagnosis is improved by excluding the data in sitting position and walking state from the data of apnea diagnosis You can also

Configuration for realizing at least one of functions of the sleep diagnostic apparatus according to the present invention and sleep apnea test apparatus, as described above, x obtained from the acceleration sensor of the three-dimensional, the DC component DCx of z, the DCz The patient's sleeping posture is detected from (DCx / (DCx ² + DCz ² ) ^1/2 , DCz / (DCx ² + DCz ² ) ^1/2 ) , and the AC components ACx, ACy of the x, y, z are detected. , ACz is filtered by a low-pass filter, and the amplified output is used to detect the respiratory rate of the patient from the reciprocal of the peak period of (ACx ² + ACy ² + ACz ² ) ^1/2 , and the AC component ACz of z is banded The patient's heart rate is detected from the reciprocal of the peak period of the amplified output after filtering with a pass filter .

  Therefore, it is possible to obtain living body information necessary for sleep diagnosis and / or sleep apnea test from one acceleration sensor, and to reduce the burden of sensor mounting and measurement from the patient. This can be expected to reduce acquisition errors.

[Embodiment 1]
FIG. 1 is a block diagram showing an electrical configuration of a sleep apnea test apparatus 1 according to an embodiment of the present invention. The sleep apnea test apparatus 1 uses only the three-dimensional acceleration sensor 2 as a sensor to be attached to the patient in order to detect the heart rate, respiratory rate, and sleeping posture of the patient. Each x, y, z component of the output of the acceleration sensor 2 is input in common to the filters F1 to F3. The outputs of the filters F1 to F3 are amplified with desired gains in the amplifiers A1 to A3, converted into digital values in the analog / digital converters AD1 to AD3, and then provided with a microcomputer and its peripheral circuits. Is input to the arithmetic processing circuit 3 configured as described above. The analog / digital converters AD1 to AD3 and the arithmetic processing circuit 3 analyze the outputs of the sensors, amplifiers and filters as described later, and create data used for sleep diagnosis and / or sleep apnea test. The signal processing means is configured.

  2 and 3 are views showing a state where the acceleration sensor 2 is attached. The acceleration sensor 2 is affixed to the chest of the patient 4, preferably near the left chest heart of the patient 4 with a tape or the like as indicated by reference numeral 2 a in FIG. 2. In addition, preferably, as shown by reference numeral 2b in FIG. 2, it is also provided on the abdomen of the patient 4 so that the phase difference between the movements of the chest and the abdomen can be measured. As for the attachment direction, the x-axis direction is the left-right direction of the patient 4, the y-axis direction is the height direction of the patient 4, and the z-axis direction is the body thickness direction of the patient 4.

  FIG. 4 is a block diagram showing a specific configuration of the filters F1 to F3 and the amplifiers A1 to A3. From the three-dimensional acceleration sensor 2, a reference output ref is output as the output x, y, z of each component. The output ends of the outputs x, y, z, and ref are grounded via capacitors Cx1, Cy1, Cz1, and Cr1 that remove high-frequency signals for bias of the acceleration sensor 2 that is a MEMS (Micro Electro Mechanical Systems) sensor. Yes. For example, Cx1, Cy1, Cz1, Cr1 = 0.01 μF.

  The outputs x and z are output as posture information x and z through resistors Rx1 and Rz1, and are input to the analog / digital converter AD1. Therefore, the filter F1 is a through filter, the gain of the amplifier A1 is 1, and the DC component that occupies most of the output of the acceleration sensor 2 is output as it is. For example, Rx1, Rz1 = 1 kΩ.

  The outputs x, y, and z are output from operational amplifiers OPx, OPy, and OPz that constitute the amplifier A2 via coupling capacitors Cx2, Cy2, and Cz2 that constitute the filter F2, and input resistors Rx2, Ry2, and Rz2, respectively. Each is input to the inverting input terminal. The output ref is input to the non-inverting input terminals of the operational amplifiers OPx, OPy, OPz through input resistors Rx3, Ry3, Rz3 and smoothing capacitors Cx3, Cy3, Cz3. Further, the respective outputs of the operational amplifiers OPx, OPy, OPz are negatively fed back through feedback resistors Rx4, Ry4, Rz4 and feedback capacitors Cx4, Cy4, Cz4 in parallel with each other. The outputs of the operational amplifiers OPx, OPy, OPz are output as respiration information x, y, z via the resistors Rx5, Ry5, Rz5 and input to the analog / digital converter AD2. For example, Cx2, Cy2, Cz2 = 100 μF, Rx2, Ry2, Rz2 = 1 kΩ, Rx3, Ry3, Rz3 = 10 kΩ, Cx3, Cy3, Cz3 = 0.1 μF, and Rx4, Ry4, Rz4 = 300 kΩ, Cx4, Cy4, Cz4 = 0.1 μF, and Rx5, Ry5, Rz5 = 1 kΩ. Accordingly, among the outputs x, y, and z of the acceleration sensor 2, a minute AC component of 0.3 Hz or less superimposed on the DC component is amplified by 300 times and output, and the filter F2 is a low-pass filter.

  Furthermore, the output z is input to the inverting input terminal of the operational amplifier OPz0 constituting the amplifier A3 via the coupling capacitor Cz20 and the input resistor Rz20 constituting the filter F3. The output ref is input to the non-inverting input terminal of the operational amplifier OPz0 via the input resistor Rz30 and the smoothing capacitor Cz30. Further, the respective outputs of the operational amplifier OPz0 are negatively fed back via the feedback resistor Rz40 and the feedback capacitor Cz40 which are parallel to each other. The output of the operational amplifier OPz0 is output as heartbeat information via the resistor Rz50 and input to the analog / digital converter AD3. For example, Cz20 = 10 μF, Rz20 = 1 kΩ, Rz30 = 10 kΩ, Cz30 = 0.1 μF, Rz40 = 400 kΩ, Cz40 = 0.001 μF, and Rz50 = 1 kΩ. Therefore, among the output z of the acceleration sensor 2, a 10 to 15 Hz component of a minute AC component superimposed on the DC component is amplified by 400 times and output, and the filter F3 is a bandpass filter. Become.

  Therefore, if the structure of the above-mentioned FIG. 4 is schematically shown, it is as shown in FIG. Note that the mounting direction of the acceleration sensor 2 is not limited to the above, and it is only necessary to correspond to the subsequent filters F1 to F3 and the amplifiers A1 to A3. That is, if the output x is input to the coupling capacitors Cz2 and Cz20, the body thickness direction of the patient 4 may be the x direction. Similarly, the left-right direction and the up-down direction may be set in accordance with this.

  The above input signals converted into digital values by the analog / digital converters AD1 to AD3 are taken into the arithmetic processing circuit 3 and used by improving the SN by digital filter processing.

  The arithmetic processing circuit 3 extracts a signal in the vicinity of 0.2 Hz by the digital filter processing from the respiration information x, y, z of 0.3 Hz or less input via the filter F2 and the amplifier A2, and the obtained respiration Is compared with the body motion data during breathing stored in the database in the arithmetic processing circuit 3 and the body motion data during apnea to determine whether the patient 4 is in a breathing state or an apnea state. Estimate either. FIG. 6 shows an example of a signal waveform obtained by passing the outputs x, y, and z from the acceleration sensor 2 through the filter F2 and the amplifier A2 by a solid line. The signal waveform after the digital filter processing by the arithmetic processing circuit 3 is shown in FIG. An example is shown by a broken line. Moreover, the absolute value which synthesize | combined each signal is also shown, and an example of the change of the respiration rate calculated | required in the arithmetic processing circuit 3 from the signal of the absolute value is shown in FIG.

  Further, when the acceleration sensor 2 is arranged in the vicinity of the heart and the abdomen as shown in FIG. 2 and measured, the determination of centrality or obstruction is made from the body motion data in the apnea state by the following procedure. Make it possible. That is, when comparing body movement data from breathing in both parts, in the case of periodic movement, the phase difference of movement is maintained even between acceleration values corresponding to second-order differential values, so the cross-correlation function of both is directly calculated. It is possible. Thereby, it is possible to calculate the phase difference of motion. If the phase difference is greater than or equal to a predetermined threshold, the apnea type can be estimated by comparing the apnea state with the data on the phase difference between central and infarct stored in the database. Yes (FIG. 7 shows data of the vicinity of the heart and the abdomen, but is data of a healthy person).

  Similarly, the arithmetic processing circuit 3 extracts a heartbeat signal around 1 Hz from the heartbeat information around 10 to 15 Hz inputted through the filter F3 and the amplifier A3 by the digital filter processing, and the peak of the obtained heartbeat signal is obtained. As a result, information such as the RR interval can be obtained therefrom. FIG. 8 shows an example of a signal waveform obtained by passing the output z from the acceleration sensor 2 through the filter F3 and the amplifier A3, and an example of a peak-held signal waveform after the digital filter processing by the arithmetic processing circuit 3. ing. Further, FIG. 9 shows an example of a change in heart rate obtained in the arithmetic processing circuit 3 from the signal.

  Furthermore, the arithmetic processing circuit 3 extracts static information of body movement data from the DC component input via the resistors Rx1 and Rz1. FIG. 10 shows an example of signal waveforms of outputs x and z from the acceleration sensor 2 via the resistors Rx1 and Rz1, and an example of a sleeping posture change obtained in the arithmetic processing circuit 3 from the signals. FIG. 10 also shows the output y from the acceleration sensor 2, but since this is a posture change around the body axis (y-axis), this output y hardly changes, and the left-right output x and the front-rear direction It is understood that the output z changes when the sleeping posture is changed. For this reason, the output y is not captured in order to detect a change in sleeping posture.

Hereinafter, a method for analyzing the sleeping posture, the respiratory rate, and the heart rate will be described in detail. First, regarding the sleeping posture, the arithmetic processing circuit 3 takes in the DC components DCx and DCz of x and z every 100 msec to obtain (DCx / (DCx ² + DCz ² ) ^1/2 , DCz / (DCx ² + DCz ^2). ) ^1/2 ), and in the sleeping posture change graph shown in FIG. 10, each sampling timing t is taken in the x-axis direction, and the posture around the body axis (y-axis) of the patient 4 is taken in the y-axis direction. It is represented by a vector having (t, 0) as a start point and the obtained values (DCx / (DCx ² + DCz ² ) ^1/2 , DCz / (DCx ² + DCz ² ) ^1/2 ) as an end point.

Next, with respect to the respiratory rate, as shown in FIG. 11, the arithmetic processing circuit 3 first initializes a variable i representing timing to 1 in step S1, and thereafter, every 100 msec, in step S2, x, y , Z, and AC components ACx, ACy, ACz, and (ACx ² + ACy ² + ACz ² ) ^1/2 are obtained. This is the absolute value Bi.

  Subsequently, in step S3, the moving average value Bmean over the data of the previous sampling number is updated, and in step S4, the average value Bmean is subtracted from the absolute value Bi to perform zero point shift. This is set as a correction value B0i. In step S5, a low-pass filter process of 0.3 Hz is performed on the correction value B0i, and this is set as a filtering value BFi.

  When the filtering process is performed in steps S2 to S5 as described above, in step S11, the standard deviation Bσ over the data of the predetermined number of samplings is updated, and in step S12, the standard deviation Bσ is determined as a predetermined threshold Th. Is added to the threshold value BTh.

  In step S13, it is determined whether or not the current filtering value BFi exceeds the threshold value BTh. If it exceeds the threshold value BTh, it is further compared with the previous filtering value BFi-1 in step S14. In step S15, the peak value BP is updated to the current filtering value BFi, and in step S16, a flag F indicating that the peak value BP exists is set to 1. When the current filtering value BFi is less than or equal to the threshold value BTh in step S13 and from step S16, the process proceeds to step S17, 1 is added to the variable i, the process returns to step S2, and the next measured acceleration value is obtained. It is taken in.

  On the other hand, if the current filtering value BFi is equal to or lower than the previous filtering value BFi-1 in step S14, the process proceeds to step S18, where it is determined whether or not the flag F is set to 1, and is not set. In this case, it is determined that the acceleration is monotonously decreasing, and the process returns from step S17 to step S2, and the next measured value of acceleration is taken in.

  On the other hand, if the flag F is set to 1 in step S18, it is determined that the acceleration peak has already been detected and then decreased, and in step S19, the peak value BP is detected. In step S20, the cycle BT (k) from the timing Bτ (k−1) at which the previous peak value BP was detected is obtained. In step S21, the reciprocal number of the cycle BT (k) is obtained to obtain the current respiratory rate Bf (k) per minute, and then the process returns to step S1 to perform the next peak detection.

  FIG. 12 is a flowchart for explaining a heart rate analysis method. The analysis method of FIG. 12 is similar to the respiration rate analysis method shown in FIG. 11 described above, and the corresponding parts are indicated by adding the suffix a to the same step number. The arithmetic processing circuit 3 first initializes a variable i representing timing to 1 in step S1a, and thereafter takes in the AC component ACz in step S2a every 5 msec, and sets this as the current value Hi.

  In step S3a, the moving average value Hmean over the data of the previous sampling number is updated. In step S4a, the average value Hmean is subtracted from the value Hi, and a zero point shift is performed. This is set as a correction value H0i. In step S5a, a 10 Hz low-pass filter process is performed on the correction value H0i, which is set as a filtering value HFi.

  In the heart rate analysis shown in FIG. 12, the filtered value HFi is further subtracted from the value Hi in step S6, and as a result, a filtered value HFi 'subjected to high-pass filtering of 10 Hz or more is obtained. In step S7a, a 15 Hz low-pass filter process is performed on the filtering value HFi ', and the result of the band-pass filtering process is set as a filtering value HFi' '.

  When the filtering process is performed in steps S2a to S7 as described above, in step S11a, the standard deviation Hσ over the data of the previous sampling number is updated, and in step S12a, the standard deviation Hσ is determined as the predetermined threshold Th. Is added to the threshold value HTh.

  In step S13a, it is determined whether or not the current filtering value HFi '' exceeds the threshold value HTh. If it is exceeded, it is further compared with the previous filtering value HFi-1 '' in step S14a. In step S15a, the peak value HP is updated to the current filtering value HFi '', and a flag F indicating that the peak value HP exists is set to 1 in step S16a. When the current filtering value HFi ″ is less than or equal to the threshold value HTh in step S13a, the process proceeds from step S16a to step S17a, 1 is added to the variable i, the process returns to step S2a, and the next acceleration is measured. Value is taken in.

  On the other hand, if the current filtering value HFi '' is less than or equal to the previous filtering value HFi-1 '' in step S14a, the process proceeds to step S18a, and it is determined whether or not the flag F is set to 1. If it is not set, it is determined that the acceleration is monotonously decreasing, and the process returns from step S17a to step S2a, and the next measured value of acceleration is taken in.

  On the other hand, if the flag F is set to 1 in step S18a, it is determined that the acceleration peak has already been detected and then decreased, and in step S19a, the peak value HP is detected. In step S20a, the cycle HT (k) from the timing Hτ (k-1) at which the previous peak value HP was detected is obtained. Further, after obtaining the current heart rate Hf (k) per minute by obtaining the reciprocal of the period HT (k) in step S21a, the process returns to step S1a to perform the next peak detection.

  Thus, by sensing acceleration values of two or more axes in the acceleration sensor 2, it becomes possible to determine the sleeping posture from the gravitational acceleration component, and further increasing the dimension to three axes, filtering and appropriately amplifying the respiratory data and Heart rate data can be obtained and correlated, and information on a living body necessary for sleep diagnosis and / or sleep apnea test can be obtained from one acceleration sensor 2. The burden of mounting and measurement can be reduced, and it can be expected to reduce data acquisition errors.

[Embodiment 2]
FIG. 13 is a block diagram showing an electrical configuration of a sleep apnea test apparatus 31 according to another embodiment of the present invention. The sleep apnea test apparatus 31 is similar to the sleep apnea test apparatus 1 described above, and corresponding portions are denoted by the same reference numerals and description thereof is omitted. This sleep apnea test apparatus 31 uses only the three-dimensional acceleration sensor 2 similar to the sleep apnea test apparatus 1 described above, and it should be noted that the patient's rising, rising and walking are detected. For this reason, each x, y, z component of the output of the acceleration sensor 2 is taken in by the amplifier A11 from the filter F11, converted into a digital value by the analog / digital converter AD11, and then input to the arithmetic processing circuit 3a.

  FIG. 14 is a block diagram showing a specific configuration of the filters F1 to F3 and F11 and the amplifiers A1 to A3 and A11. The outputs x, y, and z of the acceleration sensor 2 are also output as walking information x, y, and z through the resistors Rx11, Ry11, and Rz11 and input to the analog / digital converter AD11. Therefore, the filter F11 is a through filter, the gain of the amplifier A11 is 1, and the DC component that occupies most of the output of the acceleration sensor 2 is output as it is. For example, Rx11, Ry11, Rz11 = 1 kΩ.

  If the structure of this FIG. 14 is shown typically, it will come to show in FIG. The arithmetic processing circuit 3a extracts body motion data from the DC component input via the resistors Rx11, Ry11, Rz11. FIG. 16 shows an example of signal waveforms of outputs x, y, and z from the acceleration sensor 2 via the resistors Rx11, Ry11, and Rz11, and an example of body movement obtained from the signals in the arithmetic processing circuit 3a. Yes. The example of FIG. 16 shows an example in which the analog / digital converter AD11 captures the output of the acceleration sensor 2 with 10 bits, that is, 1024 gradations, and the vertical axis represents this, and therefore, the intermediate 512 level. Is at 0 level. The horizontal axis is time, and the unit is 100 msec.

  Here, the output z in the front-rear direction can be determined that the patient is sleeping if gravity is detected. If the gravity is not detected, the output z is raised (sitting) or standing. And can be used to select diagnostic data, as will be described in detail later. In FIG. 16, since it corresponds to about 125 levels per 1G, it is understood that a 1G change occurs in the DC components DCz and DCy of z and y from “backward” to “bed sitting”. In this way, as in the case of FIG. 10 described above, it is possible to determine the change in the sleeping posture or the rising from the DC components DCx and DCz of x and z from the acceleration sensor 2.

  Further, if a DC component DCy of y is added thereto, it can be determined that the user is walking. Since the change in acceleration due to walking is much larger than that due to breathing and heartbeat, as described above, the filter F11 in FIG. 13 can be a through filter, and the amplifier A11 can also have a gain of 1.

Then, using each DC component DCx, DCy, DCz, as shown in FIG. 15, the walking component extraction unit 32 extracts a composite value of (DCx ² + DCy ² + DCz ² ) ^1/2 as a walking component, and peaks. The measurement unit 33 obtains the number of steps that exceeds a predetermined threshold as the number of steps. Here, when the acceleration sensor 2 can detect the DC component, the gravitational acceleration 1G becomes the composite value even if the user is not walking, and the 1G is always included in the composite value even if the user is walking. . Therefore, in order for the peak measurement unit 33 to determine one step, the threshold is set to 2G, for example. As a result, it is possible to detect only the body movement by removing the influence of the gravitational acceleration as an offset.

  FIG. 17 shows an example of a change in the DC component DCy of y. In the sleeping state, as indicated by reference symbol γ1, the DC component DCy of y is almost 0, and when it rises, an offset corresponding to the gravitational acceleration occurs as indicated by reference symbol γ2. Then, when walking, the acceleration periodically rises and falls around γ2. The peak measurement part 33 can determine that it is walking when the periodic peak appears, and can count the number of steps by counting the number of the peaks. The determination of the peak can be performed using a flag as in the determination of the respiration rate shown in FIG. 11 and the determination of the heart rate in FIG.

  This makes it possible to accurately obtain data such as the number of toilets and the number of times people have been woken up, which can only be obtained through an interview, and the quality of sleep can be determined based on the number of sitting positions and walking. It can be grasped in total.

  In addition, as shown in FIG. 18, the diagnosis accuracy can be improved by excluding the data in the sitting position or the walking state from the data of the apnea diagnosis. FIG. 18 shows how the breathing data shown in FIG. 8 changes when walking, and the data in the sitting position or walking state is excluded from the diagnosis. That is, in FIG. 18, only data in the sections indicated as “backward” and “leftward” are used for diagnosis. Thus, a more accurate diagnosis can be performed by feeding back to the diagnosis that the patient is sitting or walking.

  FIG. 18 also shows an example in which the analog / digital converter AD2 takes in the output of the acceleration sensor 2 in 10 bits, that is, 1024 gradations, and the vertical axis represents this, as in FIG. Therefore, the intermediate 512 level is 0 level. The horizontal axis is time, and the unit is 100 msec. However, this respiration data is amplified 300 times by the amplifier A2, and is partially saturated unlike the above-described FIG.

It is a block diagram which shows the electrical constitution of the sleep apnea inspection apparatus which concerns on one Embodiment of this invention. It is a typical side view which shows the attachment state of an acceleration sensor. It is a typical perspective view which shows the attachment state of an acceleration sensor. It is a block diagram which shows the specific structure of the filter and amplifier in the sleep apnea test | inspection apparatus shown in FIG. FIG. 5 is a block diagram schematically showing the configuration of FIG. 4. It is a wave form diagram which shows an example of the signal waveform which passed the low-pass filter and the amplifier from the output from an acceleration sensor, and the signal waveform which digitally processed it. It is a wave form diagram which shows an example of the change of the respiration rate calculated | required from the waveform shown in FIG. It is a wave form diagram which shows an example of the signal waveform which passed the band-pass filter and the amplifier the output from an acceleration sensor, and the digital filter process of it. FIG. 7 is a waveform diagram showing an example of a change in heart rate obtained from the waveform shown in FIG. 6. It is a wave form diagram which shows an example of the signal waveform of the DC component output from an acceleration sensor, and an example of the sleeping posture change calculated | required from the signal. It is a flowchart for demonstrating the analysis method of a respiration rate. It is a flowchart for demonstrating the analysis method of a heart rate. It is a block diagram which shows the electric constitution of the sleep apnea test | inspection apparatus which concerns on the other form of implementation of this invention. It is a block diagram which shows the specific structure of the filter and amplifier in the sleep apnea test | inspection apparatus shown in FIG. FIG. 15 is a block diagram schematically showing the configuration of FIG. 14. It is a wave form diagram which shows an example of the signal waveform of the DC component output from an acceleration sensor, and an example of the body movement calculated | required from the signal. It is a wave form diagram of the DCy component from the said acceleration sensor at the time of a walk. FIG. 9 is a waveform diagram showing how the breathing data shown in FIG. 8 changes when walking.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1,31 Sleep apnea test apparatus 2 Acceleration sensor 3, 3a Arithmetic processing circuit 4 Patient 32 Walking component extraction part 33 Peak measurement part A1-A3, A11 Amplifier AD1-AD3, AD11 Analog / digital converter F1-F3, F11 Filter OPx, OPy, OPz, OPz0 Operational amplifier

Claims (6)

A three-dimensional acceleration sensor,
A low-pass filter and a band-pass filter for filtering the output of the acceleration sensor;
An amplifier that amplifies the output of the acceleration sensor with a desired gain;
When the x-axis direction is the patient's left-right direction, the y-axis direction is the patient's height direction, and the z-axis direction is the patient's body thickness direction, the x and z DC components DCx obtained from the three-dimensional acceleration sensor , DCz is detected from the patient's sleeping posture, each x, y, z AC component ACx, ACy, ACz is filtered by the low-pass filter, and the patient's respiratory rate is detected from the output amplified by the amplifier, A sleep diagnosis apparatus comprising: signal processing means for filtering the AC component ACz of z with the band-pass filter and detecting a heart rate of a patient from an output amplified by the amplifier . A three-dimensional acceleration sensor,
A low-pass filter and a band-pass filter for filtering the output of the acceleration sensor;
An amplifier that amplifies the output of the acceleration sensor with a desired gain;
When the x-axis direction is the patient's left-right direction, the y-axis direction is the patient's height direction, and the z-axis direction is the patient's body thickness direction, the x and z DC components DCx obtained from the three-dimensional acceleration sensor , DCz, (DCx / (DCx ² + DCz ² ) ^1/2 , DCz / (DCx ² + DCz ² ) ^1/2 ), The patient's sleeping posture is detected, and the AC components ACx, ACy, ACz of x, y, z are filtered by the low-pass filter, and further, the output amplified by the amplifier is used (ACx ² + ACy ² + ACz ² ) ^1/2 A signal for detecting a patient's respiration rate from the reciprocal of the peak period, filtering the AC component ACz of z with the band-pass filter, and further detecting the heart rate of the patient from the reciprocal of the peak period of the output amplified by the amplifier And a sleep diagnostic apparatus. The signal processing means uses the outputs of the DC components DCx, DCy, DCz of x, y, z obtained from the three-dimensional acceleration sensor, and a combined value of (DCx ² + DCy ² + DCz ² ) ^1/2 is obtained. The sleep diagnosis according to claim 1 or 2 , wherein the number of steps exceeding a predetermined threshold is obtained as the number of steps, and whether the patient is sleeping or rising is determined from whether or not gravity can be detected by a component of DCz. apparatus. A three-dimensional acceleration sensor,
A low-pass filter and a band-pass filter for filtering the output of the acceleration sensor;
An amplifier that amplifies the output of the acceleration sensor with a desired gain;
When the x-axis direction is the patient's left-right direction, the y-axis direction is the patient's height direction, and the z-axis direction is the patient's body thickness direction, the x and z DC components DCx obtained from the three-dimensional acceleration sensor , DCz is detected from the patient's sleeping posture, each x, y, z AC component ACx, ACy, ACz is filtered by the low-pass filter, and the patient's respiratory rate is detected from the output amplified by the amplifier, A sleep apnea examination apparatus comprising: signal processing means for filtering the AC component ACz of z with the band-pass filter and detecting a heart rate of the patient from the output amplified by the amplifier. A three-dimensional acceleration sensor,
A low-pass filter and a band-pass filter for filtering the output of the acceleration sensor;
An amplifier that amplifies the output of the acceleration sensor with a desired gain;
When the x-axis direction is the patient's left-right direction, the y-axis direction is the patient's height direction, and the z-axis direction is the patient's body thickness direction, the x and z DC components DCx obtained from the three-dimensional acceleration sensor , DCz, (DCx / (DCx ² + DCz ² ) ^1/2 , DCz / (DCx ² + DCz ² ) ^1/2 ), The patient's sleeping posture is detected, and the AC components ACx, ACy, ACz of x, y, z are filtered by the low-pass filter, and further, the output amplified by the amplifier is used (ACx ² + ACy ² + ACz ² ) ^1/2 A signal for detecting a patient's respiration rate from the reciprocal of the peak period, filtering the AC component ACz of z with the band-pass filter, and further detecting the heart rate of the patient from the reciprocal of the peak period of the output amplified by the amplifier A sleep apnea test apparatus comprising: a processing means. The signal processing means uses the outputs of the DC components DCx, DCy, and DCz of x, y, and z obtained from the three-dimensional acceleration sensor to (DCx ² + DCy ² + DCz ² ) ^1/2 The number of times that the combined value of the above exceeds a predetermined threshold is obtained as the number of steps, and it is determined whether the patient is sleeping or rising from whether or not gravity can be detected by the component of DCz. The sleep apnea test apparatus described.