WO2004043249A1

WO2004043249A1 - Organism data sensing device

Info

Publication number: WO2004043249A1
Application number: PCT/JP2003/014341
Authority: WO
Inventors: Akihiko Yanaga
Original assignee: Advanced Medical Inc.
Priority date: 2002-11-14
Filing date: 2003-11-12
Publication date: 2004-05-27
Also published as: JP4423603B2; JPWO2004043249A1

Abstract

A organism data sensing device is provided with at least strain measuring means (100) for measuring the strain of a frame constituting a part of a staying implement (1) such as a bed or a chair where a subject stays, strain variation sensing means (110) for sensing the variation of the measured strain, variation determining means (120) for determining the variation of the sensed strain, and organism data extracting means (130) for extracting organism data on the subject from the determined variation of the strain. An organism signal sensing device for sensing an organism signal representing retirement to bed, leaving from bed, respiratory rate, pulse rate, coughing, snoring, body movement, or roll over by means of an inexpensive sensor.

Description

Description Biometric data detector Technical field

The present invention relates to a biological data detecting device that detects a physiological state of a subject staying on a staying device such as a bed or a chair, for example, a respiratory rate, a pulse rate, snoring, coughing, turning over, and the like. Background art

Conventionally, the weight of a subject who is bedridden is measured by placing the subject on a weighing dish or the like with the help of a caregiver or the like, and the weight change during dialysis is measured by circulating the amount of circulation using a dialyzer. Was calculated.

In addition, it was necessary to attach a respiratory sensor and a pulse sensor to the subject for in vivo measurement. As a living body monitoring device of this type, a living body monitoring device disclosed in Japanese Patent Application Laid-Open No. H10-110465 discloses a card-type main body, a light emitting unit and a light receiving unit for detecting a pulse wave, An electrode for detecting at least one of body fat percentage and skin resistance, a temperature detecting section for detecting body temperature and skin temperature, and at least one of body surface vibration due to heartbeat or respiration and body movement due to body movement. It is equipped with a vibration detection unit for detecting.

However, the conventional weight measurement has a problem that the burden on the caregiver is large and a man is inevitably needed.In addition, when the measurement is performed by attaching the living body monitoring device to the body, it is troublesome for the subject. There was a problem that it promoted. Another problem is that an expensive sensor must be used as a sensor for detection. For this reason, the present invention provides a biological data detecting device capable of detecting a living body data such as a subject's taking off and landing, a respiratory rate, a pulse rate, a cough, a snoring, a body movement, a turning over, and the like with a low-cost sensor. To provide. Disclosure of the invention

Therefore, as shown in FIG. 1, the living body night detection device according to the present invention includes a strain measurement unit 100 that measures the strain of components constituting the staying device 1 such as a bed and a chair where the subject stays. A distortion fluctuation detecting means 110 for detecting a fluctuation amount of the distortion measured by the distortion measuring means 100; and a fluctuation amount detecting means for detecting a fluctuation amount of the distortion detected by the distortion fluctuation detecting means 110. And a biological data detecting means for detecting a biological data of the subject from the amount of change in the distortion detected by the fluctuation detecting means. The apparatus further includes a biological data determination unit 140 that determines biological data detected by the biological data overnight detection unit 130 and, when an abnormality is determined, drives an alarm unit 150. Further, the communication device includes communication means 160 for transmitting the biological data determined by the biological data determination means 140 to a medical center, a care center 170, or the like. Incidentally, it is desirable to use a strain gauge as the strain measuring means 100.

In addition, it is preferable that the distortion fluctuation detecting unit extracts a DC component and an AC component of the distortion measured by the distortion measuring unit.

Further, the biometric data is a detached floor of a subject, and the biometric data detecting means increases a DC component of the strain detected by the strain variation detecting means by a predetermined value or more with absent as a reference value. In this case, it is desirable to detect the implantation of the subject.

Still further, the biological data is a respiratory rate of the subject, and the biological data detecting means includes an AC component of the strain detected by the strain variation detecting means. It is desirable to extract the waveform in the first frequency range from the above, and to detect the respiratory rate from this waveform. The first frequency range is 0.05 Hz to 1.25 Hz, and it is desirable to extract the waveform in this range by filtering. Further, the biological data is the pulse rate of the subject, and the biological data detecting means extracts a waveform in a second frequency range from an AC component of the strain detected by the strain variation detecting means. It is desirable to detect the pulse rate from the waveform. The second frequency range is 0.5 to 4.5 Hz, and it is desirable to extract waveforms within this range by filtering.

Further, the biometric data is snoring of a subject, and the biometric data detection means extracts a waveform in a third frequency range from an AC component of the strain detected by the strain variation detecting means, and It is desirable to detect snoring. The biometric data is a subject's cough, and the biometric data determination means extracts a waveform in a third frequency range from an AC component of the strain detected by the strain variation detecting means, and It is desirable to determine a cough. The third frequency range is 20 to 500 Hz, and it is desirable to extract the waveform within this range by filtering. Furthermore, it is desirable to detect cough and snoring based on the magnitude of the fluctuation, the duration of a certain period, and the difference in the envelope.

The biometric data is a body motion of the subject, and the biometric data detecting means detects the body motion of the subject from the DC component of the strain and the AC component of the strain detected by the strain variation detecting means. It is desirable to do. Further, it is preferable that the biometric data is a subject's turnover, and the biometric data detecting means detects the subject's turnover from the DC component of the strain and the AC component of the strain detected by the strain variation detecting means. In the case of body motion, the change in the DC component is smaller than that of turning over, which is the detection criterion for both.However, when the center of gravity is detected as described below, the movement of the center of gravity is smaller than that of body turning. Remarkably expressed.

It is preferable that the distortion is detected in at least two places of the staying device, and that the biometric data determination unit detects a change in the center of gravity of the subject from a difference between the respective distortions. Since the measured value of the strain gauge on the side closer to the center of gravity is larger than the measured value of the strain gauge on the side closer to the center of gravity, the movement of the center of gravity can be detected.

Furthermore, it is preferable that the biometric data is the apnea of the subject, and the biometric data detection means detects the apnea of the subject from at least two phase shifts of the distortion.

It is preferable that the staying device is a bed, and the constituent parts are frames. In addition, it is preferable that the staying device is a bed, and that a constituent component is a floor plate having a predetermined rigidity. BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a schematic block diagram of a living body data detecting device of the present invention; FIG. 2 is an explanatory diagram showing a case where the living body data detecting device of the present invention is mounted on a bed; ) Is a side view, (b) is a front view; FIG. 3 is a schematic configuration diagram of the biometric data detection device; FIG. 4 is a schematic configuration diagram of a CPU of the biometric data detection device. FIG. 5 is a diagram showing a waveform extracted to detect a detached bed; and FIG. 6 is a diagram showing a waveform extracted to detect a respiration rate. FIG. 7 is a diagram showing a waveform extracted to detect a pulse rate; FIG. 8 is a diagram showing a waveform extracted to detect snoring; The figure shows the waveforms extracted to detect cough; FIG. 10 shows the waveforms extracted to detect body movement It is; first 1 Figure is a diagram showing an extracted waveform in order to detect the turn; first 2 diagram (a) (b) is a mounted state of the strain sensor to the floor plate portion 200

Fig. 13 shows the frequency characteristics with respect to the stiffness of the bed; Fig. 14 shows the detection state of respiration and pulsation when the stiffness of the pad is increased. Fig. 15 is a diagram showing the state of detection of respiration and pulsation when the stiffness of the bed is reduced; FIG. 17 is a circuit diagram showing an instrumentation circuit; FIG. 17 is a diagram showing an operation state by an instrumentation circuit; Yes; Figure 19 is a diagram showing waveforms for detecting apnea. BEST MODE FOR CARRYING OUT THE INVENTION

Hereinafter, embodiments of the present invention will be described with reference to the drawings.

As shown in FIGS. 2 (a) and 2 (b), a predetermined position of a staying device for the subject such as a bed and a chair (in this embodiment, a bed, hereinafter, a bed) 1 The strain gauge 3 is arranged in the position. In the embodiment shown in FIG. 2, it is basically preferable that the distortion gauges 3 are arranged on each of the left and right sides of the frame 2 of the bed 1. For example, one may be provided on the head side frame 2 of the blade 1. Each strain gauge 3 is wired to an electric control device housed in a control box 4 provided at a predetermined position of the bed 1. In addition, 5 is a temperature detector for temperature compensation of the strain gauge 3.

FIG. 3 is a block diagram of the electric control device arranged in the control box 4. The components of the signal output from the strain gauge 3 are emphasized by the DC amplifier 10 and the AC amplifier 12, and are converted into digital signals by the AD converter 14. The digital signal is sent to the CPU 20 and subjected to various processes to calculate a predetermined output signal. The signal is displayed on the display / print unit 30 by the command of the switch unit 40, and is displayed on the communication unit. The information is sent to the medical center and the care center 170 via the port 160. When an abnormality is found in the biometric data detected by the CPU 20, the alarm unit 150 issues an alarm and simultaneously sends a notification to the center 170 via the communication unit 160. The processing performed by the CPU 20 will be described in detail. As shown in FIG. 4, the digital signal changed by the AD converter 14 is a digital signal for departure and landing (D / F) A predetermined signal, a DC component, and an AC component are extracted by 50, and in particular, the DC component is extracted in a level extraction block 60, and a detached floor of the subject is determined in a detached floor detection block 70. As shown in FIG. 5, the implantation is detected when the DC component of the distortion variation becomes a predetermined value or more and the AC component of the distortion variation expresses a positive component, and conversely, the DC component returns to the normal value. In addition, leaving the bed is detected when a negative component appears in the AC component of the distortion variation.

When the biometric data is breathing, the respiratory D / F 51 and the waveform extraction block 61 extract frequencies in the range of 0.05 to 1.25 Hz, and the waveform as shown in Fig. 6 is extracted. . Then, the respiratory rate detection block 71 detects the time between the peaks (bottoms) of the extracted waveform, and calculates the respiratory rate per minute based on the detected time. Also, the number of peaks (bottoms) per minute may be counted. Thus, the determined respiration rate and waveform can be stored in the storage circuit of the CPU 20.

When the biological data is a pulse rate, a frequency in the range of 0.5 to 4.5 Hz is extracted by the pulse D / F 52 and the waveform extraction block 62, and a waveform as shown in FIG. 7 is extracted. You. Then, the pulse rate detection block 72 detects the time between the peaks (bottoms) of the extracted waveform, and calculates the pulse rate per minute based on this. Also, the number of peaks (bottoms) per minute may be counted. Thus, the obtained pulse rate and waveform are It can also be stored in the storage circuit of the CPU 20.

When the biological data is snoring, the frequency in the range of 20 to 500 Hz is extracted by the snoring D / F 53 and the waveform extraction block 63, and the waveform as shown in FIG. 8 is obtained. Is extracted. In the snoring detection program 73, snoring is detected based on the sustainability of a certain period, the cycle (repetition period), the manner of the envelope (envelope), etc., and the number of times per minute, one hour, and one sleep is counted. If necessary, this waveform is stored together with the above detection result.

If the living body is a cough, the cough D / F 54 and the waveform extraction block 64 extract frequencies in the range of 20 to 500 Hz, as shown in Fig. 9. Waveform is extracted. Then, in the cough detection block 74, cough is detected based on the duration of a certain period, the period (repetition period), the manner of the envelope (envelope), etc., and the number of times per minute, hour, and sleep is counted. If necessary, this waveform is stored together with the above detection result.

When the biometric data is body motion, a waveform as shown in FIG. 10 is extracted by the body motion DZF 55 and the waveform extraction block 65. As a result, the body motion detection block 75 detects the subject's body motion because the DC component has a small variation and the AC component has a large variation.

In addition, when the living body data is turned over, a waveform as shown in FIG. 11 is extracted by the turnover D / F 56 and the waveform extraction block 66. Thus, the turnover detection block 76 detects the subject's turnover because the DC component fluctuates greatly and the AC component fluctuates greatly.

The biometric data detected as described above is sent to the abnormality determination block 80, and is compared with, for example, a predetermined threshold value. When the threshold value is the upper limit, when the threshold value is exceeded, or when the threshold value is exceeded. If the value is lower than the threshold value, the alarm unit 150 is activated, and the communication unit is provided with communication means such as a mobile phone, a PHS, a telephone line, and a wireless communication. By operating 160, the detected biological data is transmitted to the sensor 170 together with the abnormal signal.

Further, by selecting the switch unit 40, the present biometric data or the past biometric data can be displayed on the display or printed via the display / print unit 30.

Further, when the strain gauges 3 (3a, 3b) are arranged on both sides of the bed 1, the strain gauge of the strain gauge 3a arranged on one side and the strain gauge 3b arranged on the other side. It can also compare with the degree of distortion and detect rollover based on the relative fluctuation.

A bed 1 shown in FIGS. 12 (a) and 12 (b) is an embodiment in which a strain gauge 3 is arranged on the bottom surface of a plate 6 having a predetermined rigidity. In this embodiment, what is shown in FIG. 13 shows the rigidity and frequency characteristics of the floor plate 6 of the bed 1. As is clear from this figure, in the characteristic SH when the rigidity of the floorboard 6 is increased, since the amplitude is small with respect to the frequency, as shown in FIG. 14, the breathing (0.05 to: L. 25 Hz) , Pulsation (1.5 to 12.5 Hz), snoring (40 to 80 Hz), coughing (l to 80 Hz :), body motion (0.05 to 80 Hz), etc. Become.

In addition, as shown in FIG. 13, in the characteristic SL when the rigidity of the floor plate 6 is reduced, the amplitude becomes larger with respect to the frequency, so that as shown in FIG. 15, although the respiration signal can be detected well, It becomes impossible to detect weak signals such as pulsation signals. For this reason, the bed 1 itself has rigidity that is appropriate for detection. In Bed 1, which has proper stiffness, an appropriate amplitude can be obtained for the frequency as shown by SA in Fig. 13, so that a signal containing a pulsation waveform and an expiration waveform is obtained as shown in Fig. 16. It is something that can be done.

The instrument circuit shown in Fig. 17 is used to amplify a weak signal from the strain gauge 3 using an AC circuit. The amplifier will saturate or will exceed the input range of the AD converter in the post-processing, causing the waveform to be undetectable. This time is determined by the time constant of the AC coupling. For example, when recognizing a respiratory waveform, the time constant is about 3.2 seconds (fc = 0.05 Hz). If the amplifier gain is set to 100 times, the ADC input of the excessive input will saturate. The duration is 320 seconds. After this time, it cannot be recognized as a waveform.

Therefore, an instant circuit for shortening the time constant under a predetermined condition is provided. In the impedance circuit shown in FIG. 16, the switch U 2 is normally in the off state, and the signal input from IN has a time constant determined by C 1 and R 1 of 1 (= C 1 X 1). Input to operational amplifier U 1 and output from amplified OUT (A DC). In the case of the non-inverting amplification by the operational amplifier U1, the amplifier gain (A) is obtained by 1 + R4 / R3.

If the operational amplifier U1 saturates due to excessive input and the ADC value exceeds the limit, the switch U2 is switched by the CPU, and the time constant is 2 (= C1X (R1R2) / (1+ R 2)) becomes smaller. Note that R 2 << R 1. In this case, VI is 1/2 of the ADC reference voltage (Vref).

As a result, as shown in Fig. 18, the switch U2 is turned on at the stage of (0) when an excessive input is input, and the switch U2 is turned off when the AD conversion input becomes Vref / 2. This enables waveform recognition in a very short time. In FIG. 18, the solid line indicates the case without an instrument circuit, and indicates that the AD conversion input is saturated until a predetermined time t 2 set by the time constant (320 seconds in this embodiment). . When there is an instrument circuit indicated by a broken line, for example, when C 1 = 1〃F, R 1 = 3.2ΜΩ, and R 2 = 1ΚΩ, the time constant 2 becomes 0.001 seconds. The time until the detectable time t1 shown in FIG. 17 is 0.63 seconds. As described above, by providing the instrument circuit, the undetectable time can be shortened, so that appropriate detection of the biological data can be performed.

FIG. 19 shows a method of determining sleep apnea. In FIG. 19, S1 indicates a signal from the strain sensor 3 arranged near the foot, and S2 indicates a signal from the strain sensor 3 arranged near the head. Normally, in the case of normal breathing, the phases of the two are almost the same, as indicated by Bwl and Bw2.

When a subject staying on bed 1 causes closed apnea, a phase shift occurs between Bw l 'and B w 2', as shown in Fig. 19. Therefore, if there is a phase shift between the upper and lower waveforms, it can be determined that the apnea is closed. When the respiratory waveform signal disappears, it can be determined that the patient has central apnea. Furthermore, if both closed apnea and central apnea are detected, it can be determined that the patient has mixed apnea. Industrial applicability

As described above, according to the present invention, a strain gauge is attached to a staying device such as a bed or a chair in which a subject stays, and the strain gauge detects a variation in strain of the staying device, thereby detecting a living body. Since the data can be detected overnight, it is possible to easily detect biometric data and to achieve a significant cost reduction.

Claims

The scope of the claims

1. A distortion measuring means for measuring distortion of a part constituting a staying device in which a subject stays,

Distortion variation detecting means for detecting a variation amount of the distortion measured by the distortion measuring means;

A fluctuation amount detecting means for detecting a fluctuation amount of the distortion detected by the distortion fluctuation detecting means,

A biometric data detection unit including at least a biometric data detection unit configured to detect a biometric data of a subject from the variation detected by the variation detection unit.

2. A biometric data judging means for judging the biometric data detected by the biometric data detecting means and, when an abnormality is judged, driving an alarm means. 2. The biological data detection device according to claim 1, wherein:

3. The biometric data detection according to claim 2, further comprising communication means for transmitting the biometric data determined by the biometric data determination means to a medical center, a care center, or the like. apparatus.

4. The distortion variation detection means according to claim 1, 2 or 3, wherein the distortion variation detection means extracts a DC component and an AC component of the distortion measured by the distortion measurement means. Biometric data detection device.

5. The biometric data is a detached floor of the subject, and the biometric data detection unit increases a DC component of the strain detected by the strain variation detection unit by a predetermined value or more with the absence of the component as a reference value. 5. The living body data detection apparatus according to claim 4, wherein in this case, the implantation of the subject is detected.

6. The biometric data is the respiratory rate of the subject, and the biometric data detection unit is configured to calculate, from the AC component of the strain detected by the strain variation detection unit, 6. The biological data detection device according to claim 4, wherein a waveform in a first frequency range is extracted, and a respiratory rate is detected from the waveform.

7. The biometric data is the pulse rate of the subject, and the biometric data detection means extracts a waveform in a second frequency range from the AC component of the strain detected by the strain variation detection means. 7. The biological data detecting device according to claim 4, wherein the pulse rate is detected from the waveform.

8. The biometric data is a subject's snoring, and the biometric data detecting means extracts a waveform in a third frequency range from an AC component of the strain detected by the strain variation detecting means, and snores from this waveform. The biological data detecting device _{c according} to any one of claims 4 to 7, wherein the biological data detecting device _c detects

9. The biometric data is a subject's cough, and the biometric data detection unit extracts a waveform in a third frequency range from an AC component of the strain detected by the strain variation detection unit. The biological data detection device according to any one of claims 4 to 8, wherein the biological data detection device c detects

10. The second frequency range is higher than the first frequency range, and the third frequency range is higher than the second frequency range. The biological data detection device according to any one of the above items.

11. The living body image is a body motion of the subject, and the living body image detecting means calculates the body of the subject from the DC component and the AC component of the strain detected by the strain variation detecting means. The biological data detection device according to any one of claims 4 to 10, which detects movement.

12. The living body data is a turn of the subject, and the biometric data detecting means detects the turn of the subject from the DC component and the AC component of the strain detected by the strain variation detecting means. The biological data detection device according to any one of claims 4 to 11.

13. The strain measuring means detects at least two strains of components constituting the staying device, and the living body data detecting means detects a change in the center of gravity of the subject from a difference between the respective strains. The living body data detection apparatus according to any one of claims 2 to 12, characterized in that:

14. The living body data is a subject's apnea, and the biological data detecting means detects the subject's apnea from a phase shift of at least two force points. The biological data detection device according to any one of Items 2 to 13 above.

15. The living body detection apparatus according to any one of claims 1 to 14, wherein the staying device is a bed, and a constituent component is a frame.

16. The biometric data detection according to any one of claims 1 to 14, wherein the staying device is a bed, and a constituent component is a floor plate having a predetermined rigidity. apparatus.