Heart rate acquisition device and bed system

Abstract

To provide a heart rate acquisition device capable of acquiring a heart rate with higher accuracy.SOLUTION: A heart rate acquisition device that acquires a heart rate of a subject on a bed includes: a heart rate waveform acquisition unit that acquires a heart rate waveform indicating a temporal variation of a load value according to the heart rate of the subject on the basis of an output by a load detector provided in the bed; a heart rate cycle estimation unit that obtains an estimation value of a heart rate cycle of the subject on the basis of a transition of the heart rate waveform; and a heart rate calculation unit that calculates the heart rate of the subject on the basis of the heart rate waveform and the estimation value.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a heart rate acquiring device and a bed system. [Background technology]

[0002] 2. Description of the Related Art In the fields of medicine and nursing care, it has been proposed to detect the load of a subject on a bed via a load detector and obtain biometric information of the subject, such as respiratory rate and heart rate, based on the detected load.

[0003] Patent Document 1 discloses a method for calculating an autocorrelation function of a heart rate waveform acquired based on the output of a load detector, and calculating the heart rate of a subject based on the peak of the autocorrelation function. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 2022-72436 Summary of the Invention [Problem to be solved by the invention]

[0005] In obtaining biological information based on load detection, there is a demand for even higher accuracy and efficiency.

[0006] An object of the present invention is to provide a heart rate acquiring device and a bed system that can acquire a heart rate with higher accuracy.

[0007] Another object of the present invention is to provide a heart rate acquiring device and a bed system that can acquire a heart rate more efficiently.

[0008] It is yet another object of the present invention to provide a heart rate acquiring device and a bed system that can more appropriately display the acquired heart rate. [Means for solving the problem]

[0009] According to a first aspect of the present invention, A heart rate acquisition device for acquiring a heart rate of a subject on a bed, comprising: a heartbeat waveform acquiring unit that acquires a heartbeat waveform indicating a time variation of a load value corresponding to the heartbeat of the subject based on an output of a load detector provided on the bed; a cardiac cycle estimation unit that estimates a cardiac cycle of the subject based on transitions in the cardiac waveform; There is provided a heart rate acquiring device including a heart rate calculating unit that calculates the heart rate of the subject based on the heart rate waveform and the estimated value.

[0010] According to a second aspect of the present invention, A heart rate acquisition device for acquiring a heart rate of a subject on a bed, comprising: a heart rate calculation unit that calculates the heart rate of the subject based on a time variation of an output of a load detector provided on the bed according to the heart rate of the subject; a display unit that displays the heart rate calculated by the heart rate calculation unit; A display control unit that controls the display content of the display unit, A heart rate acquisition device is provided in which the display control unit changes the display manner of the heart rate calculated by the heart rate calculation unit on the display unit between a period when the subject is present on the bed and a period when the subject is not present on the bed.

[0011] According to a third aspect of the present invention, A heart rate acquisition device for acquiring a heart rate of a subject on a bed, comprising: a heartbeat waveform acquiring unit that acquires a heartbeat waveform indicating a time variation of a load value corresponding to the heartbeat of the subject based on an output of a load detector provided on the bed; a heart rate calculation unit that calculates a heart rate of the subject based on the heart rate waveform, The calculation of the heart rate in the heart rate calculation unit is calculating an autocorrelation function of the cardiac waveform; detecting a peak in the autocorrelation function; calculating the heart rate based on the position of the detected peak; The calculation of the autocorrelation function is Calculating a first autocorrelation function of the cardiac waveform included in a first time period; calculating a second autocorrelation function of the cardiac waveform included in a second time period after the first time period; calculating a third autocorrelation function of the cardiac waveform included in a third time period after the second time period; Calculating a sum of a first autocorrelation function and a second autocorrelation function at a first time as the autocorrelation function; There is provided a heart rate acquiring device that includes calculating, at a second time point after the first time point, a sum of a second autocorrelation function and a third autocorrelation function as the autocorrelation function.

[0012] According to a fourth aspect of the present invention, A bed and A load detector provided on the bed; There is provided a bed system comprising the heart rate acquisition device according to the first, second or third aspect. Effect of the Invention

[0013] The heart rate acquiring device and bed system of the present invention can acquire the heart rate with higher accuracy.

[0014] The heart rate acquiring device and bed system of the present invention can acquire the heart rate more efficiently.

[0015] The heart rate acquiring device and bed system of the present invention can more appropriately display the acquired heart rate. [Brief description of the drawings]

[0016] [Figure 1] FIG. 1 is a block diagram showing a configuration of a biological information acquiring device according to an embodiment of the present invention. [Diagram 2]FIG. 2 is an explanatory diagram showing the arrangement of the load detector with respect to the bed. [Diagram 3] FIG. 3 is a flowchart showing the steps of acquiring the heart rate of a subject using the biological information acquiring device. [Figure 4] Figures 4(a), 4(b), 4(c), and 4(d) are graphs showing examples of heart rate waveforms based on the outputs from four load detectors placed under the legs of a bed. [Diagram 5] FIG. 5 is a flowchart showing the details of the cardiac cycle estimation process. [Figure 6] FIG. 6 is a graph showing an example of a heart rate waveform, together with the bottom, rising zero crossing points, peak, and falling zero crossing points of the heart rate waveform. [Figure 7] FIG. 7 is a table explaining the tracking of the heartbeat waveform in the heartbeat cycle estimation process, and mainly shows the relationship between the state of the heartbeat waveform and the state transition variables. [Figure 8] Fig. 8(a), Fig. 8(b), and Fig. 8(c) are explanatory diagrams for explaining the significance of the heart rate calculation unit dividing and calculating the autocorrelation function of the heart rate waveform. Fig. 8(a) is a graph explaining the manner in which a part of the autocorrelation function of the heart rate waveform is calculated at time t. Fig. 8(b) is a graph explaining the manner in which a part of the autocorrelation function of the heart rate waveform is calculated at time t+0.5. Fig. 8(c) is a graph explaining the manner in which a part of the autocorrelation function of the heart rate waveform is calculated at time t+1.0. [Figure 9] FIG. 9 is a flowchart showing the details of the heart rate calculation process. [Figure 10] Fig. 10(a) to Fig. 10(h) are explanatory diagrams for explaining the procedure for calculating the autocorrelation function in the heart rate calculation unit. Fig. 10(a) shows an example of a heart rate waveform together with sampled values ​​of the heart rate waveform. Fig. 10(b) to Fig. 10(h) are explanatory diagrams showing the contents of the sampled values ​​stored in an array provided in a specified area of ​​the storage unit in the process of calculating the autocorrelation function. [Figure 11]Fig. 11(a) and Fig. 11(b) are explanatory diagrams for explaining the interpolation process executed in the heart rate calculation process. Fig. 11(a) is a graph showing data points around the peak of the autocorrelation function detected by peak detection. Fig. 11(b) is a graph showing a quadratic curve calculated based on the data points in Fig. 11(a) and the peak of the quadratic curve. [Figure 12] Fig. 12(a) and Fig. 12(b) respectively show the display of the respiratory rate and the heart rate on the display unit. Fig. 12(a) shows the state where the respiratory rate and the heart rate are displayed on the display unit. Fig. 12(b) shows the state where the respiratory rate and the heart rate are not displayed on the display unit. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0017] <Embodiment> A biological information acquiring system 100 (FIG. 1) according to an embodiment of the present invention will be described taking as an example a case in which the system is used together with a bed BD (FIG. 2) to calculate (estimate) the heart rate of a subject S lying on the bed BD.

[0018] [Configuration of Biometric Information Acquisition System 100] 1, the bioinformation acquisition system 100 of this embodiment mainly includes a load detection unit 10, a bioinformation acquisition unit (heart rate acquisition device) 30, and a user terminal 40. The load detection unit 10 and the bioinformation acquisition unit 30 are connected via an A / D conversion unit 20. The bioinformation acquisition unit 30 and the user terminal 40 are connected by wire or wirelessly.

[0019] The load detection unit 1 includes four load detectors 11, 12, 13, and 14. Each of the load detectors 11, 12, 13, and 14 is a load detector that detects a load using, for example, a beam-shaped load cell. Each of the load detectors 11, 12, 13, and 14 is connected to an A / D conversion unit 20 by wiring or wirelessly.

[0020] As shown in FIG. 2, the four load detectors 11 to 14 are disposed under casters C1, C2, C3, and C4 attached to the lower ends of legs BL1, BL2, BL3, and BL4 at the four corners of the bed BD used by the subject S, respectively.

[0021] The A / D conversion unit 20 is connected by wire or wirelessly to the load detection unit 10 and the biological information acquisition unit 30. The A / D conversion unit 20 includes an A / D converter that converts an analog signal input from the load detection unit 10 into a digital signal.

[0022] The biological information acquiring unit 30 mainly includes a heartbeat waveform acquiring unit 31, a body movement determining unit 32, a heartbeat cycle estimating unit 33, a heart rate calculating unit 34, and a storage unit 35. As an example, the heartbeat waveform acquiring unit 31, the body movement determining unit 32, the heartbeat cycle estimating unit 33, and the heart rate calculating unit 34 are constructed inside a control unit (controller) (not shown) included in the biological information acquiring unit 30. The operations of the heartbeat waveform acquiring unit 31, the body movement determining unit 32, the heartbeat cycle estimating unit 33, and the heart rate calculating unit 34 will be described later.

[0023] The storage unit 35 is a storage device that stores data used in the biometric information acquisition unit 30. The storage unit 35 may be, for example, a hard disk, a non-volatile memory, or the like.

[0024] The user terminal 40 includes a display control unit 41, a display unit 42, a notification unit 43, an input unit 44, and a storage unit 45.

[0025] As an example, the display control unit 41 is constructed inside a control unit (controller) (not shown) included in the user terminal 40. The display control unit 41 acquires various information such as the heart rate acquired by the biological information acquisition unit 30 from the biological information acquisition unit 30, and displays the information on the display unit 42 (described in detail later).

[0026] The display unit 42 visually displays information such as the heart rate acquired from the biological information acquisition unit 30 to a user of the biological information acquisition system 100. The display unit 42 may be, for example, a monitor such as a liquid crystal monitor.

[0027] The notification unit 43 audibly notifies the user of a predetermined event based on information such as the heart rate acquired from the biological information acquisition unit 30. The notification unit 43 may be, for example, a speaker. The display control unit 41 may control the operation of the notification unit 43.

[0028] The input unit 44 is an interface for inputting information to the biometric information acquisition system 100. The input unit 44 may be, for example, a keyboard and a mouse.

[0029] The storage unit 45 is a storage device that stores data used in the user terminal 40. The storage unit 45 may be, for example, a hard disk, a non-volatile memory, or the like.

[0030] [Operation of Biometric Information Acquisition System 100] The operation of acquiring the heart rate of a subject lying in bed using the biological information acquiring system 100 having such a configuration will be described.

[0031] Acquiring the heart rate of a subject S using the bioinformation acquisition system 100 includes a load detection process S1, a heart rate waveform acquisition process S2, a body movement determination process S3, a heart rate cycle estimation process S4, a heart rate calculation process S5, and a display process S6, as shown in the flowchart of Figure 3.

[0032] In summary, in a load detection step S1, the load of the subject S is detected using the load detectors 11-14. In a heartbeat waveform acquisition step S2, a heartbeat waveform is extracted by filtering from the temporal fluctuation of the detected values ​​of the load detectors 11-14. In a body movement determination step S3, the presence or absence of body movement of the subject S is determined based on the amplitude of the heartbeat waveform. In a heartbeat cycle estimation step S4, the heartbeat cycle of the subject S is estimated based on the heartbeat waveform. In a heartbeat calculation step S5, the heartbeat of the subject S is calculated based on the heartbeat waveform, the presence or absence of body movement, and the estimated value of the heartbeat cycle. In a display step S6, the calculated heartbeat is displayed on the display unit 42.

[0033] [Load detection process S1] In the load detection process S1, the load of the subject S on the bed BD is detected using load detectors 11, 12, 13, and 14. The load of the subject S on the bed BD is distributed and applied to the load detectors 11 to 14 arranged under the legs BL1 to BL4 at the four corners of the bed BD, and is detected in a distributed manner by these.

[0034] Each of the load detectors 11 to 14 detects a load (load change) and outputs it as an analog signal to the A / D conversion unit 20. The A / D conversion unit 20 converts the analog signal into a digital signal with a sampling period of, for example, 5 milliseconds (0.005 seconds), and outputs the digital signal (hereinafter referred to as "load signal") to the bioinformation acquisition unit 30. Hereinafter, the load signals obtained by digitally converting the analog signals output from the load detectors 11, 12, 13, and 14 in the A / D conversion unit 20 will be referred to as load signals s1, s2, s3, and s4, respectively.

[0035] [Heartbeat waveform acquisition step S2] In the heartbeat waveform acquiring step S2, the heartbeat waveform acquiring section 31 acquires the heartbeat waveform of the subject S from each of the load signals s1 to s4.

[0036] In this specification and the present invention, the term "heartbeat waveform" refers to a waveform showing the temporal variation of a load value according to the heartbeat of a subject. One cycle of the heartbeat waveform corresponds to one cycle of the heartbeat. The amplitude of the heartbeat waveform correlates with the amount of blood flowing with one beat. If other conditions are the same, the greater the amount of blood flowing with a beat, the greater the amplitude of the heartbeat waveform.

[0037] Specifically, the heartbeat waveform acquisition unit 31 acquires the heartbeat waveform, for example, by the following method.

[0038] Since the human heart beats about 40 to 150 times per minute, the frequency of the human heart beat is about 0.66 to 2.5 Hz (hereinafter referred to as the "heart beat band"). Therefore, the heart beat waveform acquisition unit 31 extracts components having frequencies in the heart beat band from the load signals s1 to s4 using a band pass filter, and sets the extracted components as the heart beat waveforms HW1 to HW4.

[0039] Examples of a heartbeat waveform HW1 extracted from a weight signal s1, a heartbeat waveform HW2 extracted from a weight signal s2, a heartbeat waveform HW3 extracted from a weight signal s3, and a heartbeat waveform HW4 extracted from a weight signal s4 are shown in Figures 4(a), 4(b), 4(c), and 4(d), respectively. The heartbeat waveforms HW1 to HW4 shown in Figures 4(a) to 4(d) are the heartbeat waveforms of subject S during the same period (time 0 s to time 30 s).

[0040] Furthermore, the heartbeat waveform acquisition unit 31 performs downsampling on each of the acquired heartbeat waveforms HW1 to HW4 to reduce the processing load. In this embodiment, sampling frequency conversion is performed to change the sampling period from 5 milliseconds (0.005 seconds) to 10 milliseconds (0.01 seconds). Note that downsampling does not necessarily have to be performed.

[0041] [Body movement determination process S3] In the body movement determination step S3, the body movement determination section 32 determines whether or not the subject S is moving based on a comparison between the amplitudes AM of the heartbeat waveforms HW1 to HW4 and a threshold value.

[0042] Here, in this invention and this specification, "body movement" refers to the movement of the subject's head, torso (trunk), and limbs. Movements of organs, blood vessels, etc., associated with breathing, heartbeat, etc., are not included in body movement. As an example, body movement can be classified into large body movements that involve movement of the subject's torso (trunk) and small body movements that only involve movement of the subject's limbs and head. An example of large body movement is turning over in bed or getting up, and an example of small body movement is movement of the limbs and head while sleeping.

[0043] The body movement determination unit 32 determines the presence or absence of body movement based on a comparison between the amplitude AW of the heartbeat waveforms HW1 to HW4 and a threshold. Specifically, for example, when the amplitude AW of at least one of the heartbeat waveforms HW1 to HW4 is larger than the positive body movement threshold THp or smaller than the negative body movement threshold THn, it is determined that the subject S is moving.

[0044] The body movement thresholds THp and THn can be set arbitrarily. Specifically, for example, taking into consideration the magnitude of the past amplitude AM of the heartbeat waveforms HW1 to HW4, an appropriate value can be set at which it can be determined that the subject S has a body movement when the amplitude AM (positive value) is greater than the positive threshold, and an appropriate value can be set at which it can be determined that the subject S has a body movement when the amplitude AM (negative value) is less than the negative threshold. It is also possible to use only a positive threshold and determine that the subject S has a body movement when the absolute value of the amplitude AM is greater than the threshold.

[0045] The body movement determination section 32 sets a body movement occurrence flag during a period in which it is determined that a body movement has occurred in the subject S. The body movement occurrence flag is set in a predetermined area secured in the storage section 35, for example.

[0046] [Heartbeat cycle estimation step S4] In the cardiac cycle estimation step S4, the cardiac cycle estimation section 33 estimates the cardiac cycle of the subject S based on the cardiac waveforms HW1 to HW4.

[0047] As described above, one cycle of the heartbeat waveform corresponds to one cycle of the heartbeat. Therefore, the heartbeat cycle estimation unit 33 tracks at least one transition of the heartbeat waveforms HW1 to HW4 and calculates the interval (length) of one cycle, thereby estimating the heartbeat cycle of the subject S.

[0048] Specifically, the cardiac cycle estimation unit 33 estimates the cardiac cycle of the subject S, for example, according to the procedure shown in the flowchart of Fig. 5. Here, an example will be described in which the cardiac cycle of the subject S is estimated by tracking the transition of the cardiac waveform HW1 (Fig. 6).

[0049] In the cardiac cycle estimation step S4, the cardiac cycle estimation unit 33 constantly executes a waveform transition tracking step S41. In the waveform transition tracking step S41, the cardiac cycle estimation unit 33 tracks the transition of the cardiac waveform HW1 based on the sign of the slope of the cardiac waveform HW1, the sign of the cardiac waveform HW1, and the state transition variable WS (FIG. 7).

[0050] Specifically, the cardiac cycle estimation unit 33 sequentially identifies the bottom b of the cardiac waveform HW1, the zero cross point rx at the rising edge of the cardiac waveform HW1 (hereinafter referred to as the "rising zero cross point rx"), the peak p of the cardiac waveform HW1, and the zero cross point fx at the falling edge of the cardiac waveform HW1 (hereinafter referred to as the "falling zero cross point fx").

[0051] Here, the state transition variable WS is a variable that indicates the state of the heartbeat waveform HW1. When the state transition variable WS is "1", the heartbeat waveform HW1 is in a state moving from the bottom b to the rising zero cross point rx. When the state transition variable WS is "2", the heartbeat waveform HW1 is in a state moving from the rising zero cross point rx to the peak p. When the state transition variable WS is "3", the heartbeat waveform HW1 is in a state moving from the peak p to the falling zero cross point fx. When the state transition variable WS is "4", the heartbeat waveform HW1 is in a state moving from the falling zero cross point fx to the bottom b.

[0052] Specifically, for example, the cardiac cycle estimation unit 33 identifies the bottom b, the rising zero cross point rx, the peak p, and the falling zero cross point fx as follows: Here, an example will be described in which a bottom b(n) that is the nth bottom b, a rising zero cross point rx(n) that is the nth rising zero cross point, a peak p(n) that is the nth peak p, and a falling zero cross point fx(n) that is the nth falling zero cross point fx are identified.

[0053] (1) Identifying bottom b 6 and 7, the cardiac cycle estimation unit 33 detects at a certain point in time when the state transition variable WS is "4", the sign of the slope of the cardiac waveform HW1 changes from negative to positive, and the amplitude AM of the cardiac waveform HW1 at that point in time is equal to or greater than the threshold value TH b(n) If the bottom amplitude threshold is less than the threshold TH (bottom amplitude threshold), it is determined that the bottom b(n) of the heart rate waveform HW1 exists at the relevant time point. b(n) For example, the amplitude AM of the respiratory waveform HW1 at bottom b(n-1) identified one cycle ago b(n-1) It can be one third of that.

[0054] When the bottom b(n) is identified, the cardiac cycle estimation unit 33 estimates the amplitude AM b(n) in the storage unit 35. In addition, the state transition variable WS is changed from "4" to "1." When the state transition variable WS is "1", the cardiac cycle estimation unit 33 waits for the arrival of the rising zero cross point rx.

[0055] (2) Identifying the rising zero crossing point rx When, at a certain point in time, the state transition variable WS is “1” and the sign of the heartbeat waveform HW1 changes from negative to positive, the cardiac cycle estimation unit 33 determines that a rising zero crossing point rx(n) exists at that point in time.

[0056] When the cardiac cycle estimation unit 33 identifies the rising zero-crossing point rx(n), it changes the state transition variable WS from "1" to "2." When the state transition variable WS is "2," the cardiac cycle estimation unit 33 waits for the arrival of a peak p.

[0057] (3) Identification of peak p The cardiac cycle estimation unit 33 detects whether or not, at a certain point in time, the state transition variable WS is “2”, the sign of the slope of the cardiac waveform HW1 changes from positive to negative, and the amplitude AM of the cardiac waveform HW1 at that point in time is equal to or smaller than the threshold value TH p(n) If the peak amplitude threshold is greater than the threshold TH (peak amplitude threshold), it is determined that a peak p(n) of the heartbeat waveform HW1 exists at the time point. p(n) For example, the amplitude AM of the respiratory waveform HW1 at the peak p(n-1) identified one cycle ago p(n-1) It can be one third of that.

[0058] When the peak p(n) is identified, the cardiac cycle estimation unit 33 estimates the amplitude AM p(n) in the storage unit 35. In addition, the state transition variable WS is changed from "2" to "3." When the state transition variable WS is "3," the cardiac cycle estimation unit 33 waits for the arrival of a falling zero cross point fx.

[0059] (4) Identifying the falling zero cross point fx When, at a certain point in time, the state transition variable WS is “3” and the sign of the cardiac waveform HW1 changes from positive to negative, the cardiac cycle estimation unit 33 determines that a falling zero cross point fx(n) exists at that point in time.

[0060] When the cardiac cycle estimation unit 33 identifies the falling zero-cross point fx(n), it changes the state transition variable WS from "3" to "4." When the state transition variable WS is "4," the cardiac cycle estimation unit 33 waits for the arrival of the bottom b.

[0061] The cardiac cycle estimation unit 33 executes step S42 in parallel with the waveform transition tracking step S41, and determines whether or not the falling zero cross point fx has been identified in the waveform transition tracking step S41.

[0062] If the cardiac cycle estimation unit 33 determines that the falling zero cross point fx has not been identified (S42: NO), it executes step S42 again. If the cardiac cycle estimation unit 33 determines that the falling zero cross point fx has been identified (S42: YES), it proceeds to step S43.

[0063] In step S43, the cardiac cycle estimation unit 33 determines whether or not the cardiac waveform HW1 satisfies a predetermined condition in one cycle immediately before the identified zero crossing point fx.

[0064] Specifically, the cardiac cycle estimation unit 33 determines whether the amplitude AM (positive value) of the peak p identified in the immediately preceding cycle is smaller than the body movement threshold THp and whether the amplitude AM (negative value) of the bottom b identified in the immediately preceding cycle is larger than the body movement threshold THn. The peak p and bottom b identified in the immediately preceding cycle are, for example, p(n) and b(n) at the timing when the falling zero cross point fx(n) is identified. The body movement thresholds THp and THn may be the same values ​​as the body movement thresholds THp and THn used in the body movement determination step S3.

[0065] The cardiac cycle estimation unit 33 also determines whether the interval PR of the immediately preceding cycle is within a predetermined range. The interval PR of the immediately preceding cycle is, for example, the length (time) from the falling zero cross point fx(n-1) to the falling zero cross point fx(n) at the timing when the falling zero cross point fx(n) is identified.

[0066] If the amplitude AM (positive value) of the peak p identified in the immediately preceding cycle is greater than the body movement threshold THp, and / or if the amplitude AM (negative value) of the bottom b identified in the immediately preceding cycle is smaller than the body movement threshold THn, or if the interval PR of the immediately preceding cycle is not within a predetermined range (S43: NO), the cardiac cycle estimation unit 33 returns to step S42.

[0067] If the amplitude AM (positive value) of the peak p identified in the immediately preceding cycle is equal to or less than the body movement threshold THp, the amplitude AM (negative value) of the bottom b identified in the immediately preceding cycle is equal to or greater than the body movement threshold THn, and the interval PR of the immediately preceding cycle is within a predetermined range (S43: YES), the cardiac cycle estimation unit 33 proceeds to step S44. Specifically, for example, if the interval PR of the immediately preceding cycle is equal to or greater than a predetermined value, the cardiac cycle estimation unit 33 determines that the PR is within the predetermined range.

[0068] In step S44, the cardiac cycle estimation unit 33 determines whether the fluctuation ratio of the interval PR of the immediately preceding cycle to the interval PR of the cycle immediately preceding the cycle is within a predetermined range. Note that, when the interval PR of the immediately preceding cycle is the length (time) from the falling zero cross point fx(n-1) to the falling zero cross point fx(n), the interval PR of the cycle immediately preceding the cycle is the length (time) from the falling zero cross point fx(n-2) to the falling zero cross point fx(n-1).

[0069] Specifically, for example, when the fluctuation ratio of the interval PR of the immediately preceding cycle to the interval PR of the cycle immediately preceding the cycle is 50% or more and 200% or less (i.e., when the interval PR of the immediately preceding cycle is 1 / 2 or more and 2 times or less than the interval PR of the cycle immediately preceding the cycle), the cardiac cycle estimation unit 33 determines that the fluctuation ratio of the interval PR of the immediately preceding cycle to the interval PR of the cycle immediately preceding the cycle is within a predetermined range.

[0070] If the cardiac cycle estimation unit 33 determines that the fluctuation ratio of the interval PR of the immediately preceding cycle to the interval PR of the cycle immediately preceding that cycle is not within a predetermined range (S44: NO), it returns to step S42. If the cardiac cycle estimation unit 33 determines that the fluctuation ratio of the interval PR of the immediately preceding cycle to the interval PR of the cycle immediately preceding that cycle is within a predetermined range (S44: YES), it proceeds to step S45.

[0071] In step S45, the cardiac cycle estimation unit 33 stores the interval PR of the immediately preceding cycle in a predetermined area of ​​the storage unit 35. At this time, if intervals PR for eight cycles have already been stored in that area, the interval PR for the oldest cycle is deleted. That is, storage in the storage unit 35 is performed in a FIFO manner.

[0072] In step S46, the cardiac cycle estimation unit 33 determines whether or not intervals PR for eight cycles are stored in a predetermined area of ​​the storage unit 35. If intervals RP for eight cycles are stored in a predetermined area of ​​the storage unit 35 (S46: YES), the cardiac cycle estimation unit 33 outputs the median value of PR for eight cycles as an estimate of the cardiac cycle of the subject S to the heart rate calculation unit 34 (step S47). If periods RP for eight cycles are not stored in the predetermined area of ​​the storage unit 35 (S46: NO), the cardiac cycle estimation unit 33 returns to step S42.

[0073] [Heart rate calculation process S5] In the heart rate calculation process S5, the heart rate calculation unit 34 calculates (estimates) the heart rate of the subject S based on the temporal fluctuation of the heart rate waveforms HW1 to HW4, the estimated heart rate value estimated in the heart rate cycle estimation process S4, and the presence or absence of body movement of the subject S.

[0074] The heart rate calculation unit 34 calculates the heart rate of the subject S based on the following principle, in brief.

[0075] First, the heart rate calculation section 34 calculates an autocorrelation function (autocorrelation coefficient) in the time domain for each of the heart rate waveforms HW1 to HW4.

[0076] The calculated autocorrelation function indicates the degree of agreement between each of the heartbeat waveforms HW1 to HW4 and a waveform obtained by shifting the heartbeat waveform by a predetermined lag time in the time axis direction, using the lag time as a variable. A certain periodic waveform and a waveform obtained by shifting the same waveform by the lag time in the time axis direction have the highest degree of agreement when the lag time is equal to the period of the waveform. Therefore, the value of the lag time at which the autocorrelation function shows a peak indicates the period of each of the heartbeat waveforms HW1 to HW4.

[0077] In view of the above, the heart rate calculation unit 34 detects peaks of the autocorrelation function for each of the heart rate waveforms HW1 to HW4, determines the lag time corresponding to the detected peak as the period of the heart rate waveform, and calculates an estimated value of the heart rate of the subject S based on the determined period.

[0078] In this embodiment, the heart rate calculation unit 34 calculates the autocorrelation function using a calculation window of 1.65 seconds. That is, the autocorrelation function is calculated with a lag time ranging from 0 seconds to 1.65 seconds. The human heart rate is usually at least about 40 beats / min, and the period of the heart rate waveform is at most about 1.5 seconds. Therefore, by calculating the autocorrelation function using a calculation window of 1.65 seconds, it is possible to accurately obtain the period of the heart rate waveform while suppressing an increase in the amount of calculation processing.

[0079] Furthermore, in this embodiment, the heart rate calculator 34 divides and calculates the autocorrelation function to suppress an increase in the amount of calculation processing. This concept will be described with reference to Figs. 8(a) to 8(c).

[0080] In the state shown in Fig. 8(a), the autocorrelation function ACF(t) between the waveform w(t) for 0.5 seconds from time t to the past and the waveform W(t) for 1.65 seconds from time t to the past is calculated. Also, in the state shown in Fig. 8(b), the autocorrelation function ACF(t+0.5) between the waveform w(t+0.5) for 0.5 seconds from time t+0.5 to the past and the waveform W(t+0.5) for 1.65 seconds from time t+0.5 to the past is calculated. Furthermore, in the state shown in Fig. 8(c), the autocorrelation function ACF(t+1.0) between the waveform w(t+1.0) for 0.5 seconds from time t+1.0 to the past and the waveform W(t+1.0) for 1.65 seconds from time t+1.0 to the past is calculated.

[0081] Now, in the state shown in Fig. 8(c), consider calculating the autocorrelation function between the waveform for 1.5 seconds from time t+1.0 to the past and the waveform W(t+1.0) for 1.65 seconds from time t+1.0 to the past. In this case, as can be seen from Fig. 8(a) to Fig. 8(c), the calculated autocorrelation function is equal to the sum of the autocorrelation function ACF(t), the autocorrelation function ACF(t+0.5), and the autocorrelation function ACF(t+1.0).

[0082] 8(c), when the autocorrelation function of the waveform for 1.5 seconds from time t+1.0 is calculated using a calculation window of 1.65 seconds, the amount of calculation increases if the autocorrelation function of the waveform for 1.5 seconds from time t+1.0 and the waveform W(t+1.0) for 1.65 seconds from time t+1.0 is calculated. On the other hand, the amount of calculation can be reduced by calculating the autocorrelation function ACF(t+1.0) of the waveform w(t+1.0) for 0.5 seconds from time t+1.0 and the waveform W(t+1.0) for 1.65 seconds from time t+1.0 and adding it to the already calculated autocorrelation functions ACF(t) and ACF(t+0.5).

[0083] In this way, at each timing when the autocorrelation function is calculated, the heart rate calculation unit 34 of this embodiment does not calculate the autocorrelation function for the entire waveform that is the target at that timing, but calculates the autocorrelation function for a most recent part of the waveform that is the target at that timing, and adds it to the autocorrelation function calculated at the previous timing, thereby suppressing an increase in the amount of calculation processing.

[0084] Specifically, for example, the heart rate calculation unit 34 calculates the heart rate of the subject S in the following procedure in accordance with the flowchart shown in FIG.

[0085] In step S51, the heart rate calculation unit 34 sequentially calculates the autocorrelation function between the latest 0.5 second waveform and the past 1.65 seconds waveform of each of the heart rate waveforms HW1 to HW4. Specifically, the calculation is performed as follows, for example, using an array AR stored in the storage unit 35. Here, the calculation regarding the heart rate waveform HW1 is explained as an example. The calculation regarding the heart rate waveform HW2 to HW4 is similar.

[0086] The array AR (FIG. 10(b)) can store 165 elements. The array AR stores sampled values ​​a(n) (n=1, 2, ... 165) of the amplitude AM of the heartbeat waveform HW1 every 0.01 seconds (i.e., the sampling period after downsampling in the waveform acquisition step S2). Each sampled value stored in the array AR corresponds to 1.65 seconds of the heartbeat waveform HW1 (FIG. 10(a)).

[0087] During the period in which the body movement determination flag is set by the body movement determining section 32, zero is stored as the sampling value a(n) of the amplitude AR.

[0088] First, the heart rate calculation unit 34 shifts the array AR by −164 times to obtain an array AR 164 (Fig. 10(c)). Then, the array AR 164The sampling value a (165) is accumulated for each element of and the accumulation result is stored in the accumulation array AAR (FIG. 10(d)). At this time, the data stored in the accumulation array AAR indicates the autocorrelation function calculated for the latest 0.01 second of the heartbeat waveform HW1 using a calculation window of 1.65 seconds.

[0089] Next, the heart rate calculation unit 34 shifts the array AR by −163 times to obtain an array AR 163 (Fig. 10(e)). Then, the array AR 163 The sampling value a (164) is accumulated for each element of and the accumulated result is added to the accumulation array AAR (FIG. 10(f)). At this time, the data stored in the accumulation array AAR indicates the autocorrelation function calculated for the latest 0.02 second of the heartbeat waveform HW1 using a calculation window of 1.65 seconds.

[0090] Similarly, the heart rate calculation unit 34 shifts the array AR −N times (N=162, 161, . . . , 115) to obtain an array AR N Then, create the array AR N The heart rate calculation unit 34 repeats these steps, and in the 50th step, the heart rate calculation unit 34 shifts the array AR by -115 times to obtain an array AR 115 (Fig. 10(g)). Then, the array AR 115 The value of a(116) is accumulated for each element of and the accumulated result is added to the accumulation array AAR (FIG. 10(h)). At this time, the data stored in the accumulation array AAR indicates the autocorrelation function calculated for the latest 0.5 second of the heartbeat waveform HW1 using a calculation window of 1.65 seconds.

[0091] In step S52, the heart rate calculation unit 34 judges whether or not 50 integration results (0.5 seconds) have been added to the integration array AAR. If 50 integration results (0.5 seconds) have not been added, the process returns to S51, and if 50 integration results (0.5 seconds) have been added, the calculation results stored in the integration array AAR are stored in the storage unit 35 (S53).

[0092] The heart rate calculation unit 34 executes steps S52 and S53 for each of the heart rate waveforms HW1 to HW4. Hereinafter, the autocorrelation functions calculated in a 1.65 second calculation window for the 0.5 second heart rate waveforms HW1, HW2, HW3, and HW4 stored in step S53 will be referred to as partial autocorrelation functions PAF1, PAF2, PAF3, and PAF4, respectively.

[0093] The heart rate calculation unit 34 uses a FIFO method to store the partial autocorrelation functions PAF1 to PAF4 in the storage unit 35. In the storage unit 35, an area capable of storing 16 each of the autocorrelation functions PAF1 to PAF4 is defined.

[0094] In step S54, the heart rate calculation unit 34 calculates autocorrelation functions AF1, AF2, AF3, and AF4 by adding up the 16 autocorrelation functions PAF1, PAF2, PAF3, and PAF4 stored in the storage unit 35. The heart rate calculation unit 34 stores the calculated autocorrelation functions AF1 to AF4 in the storage unit 35. The autocorrelation functions AF1 to AF4 respectively indicate autocorrelation functions calculated over a 1.65-second calculation window of the most recent 8 seconds of heart rate waveforms HW1 to HW4.

[0095] In step S55, the heart rate calculation unit 34 calculates a total autocorrelation function AF by adding up the autocorrelation functions AF1 to AF4 stored in the storage unit 35. The heart rate calculation unit 34 stores the calculated total autocorrelation function AF in the storage unit 35.

[0096] In step S56, the heart rate calculation unit 34 determines whether the period during which body movement occurs in the most recent 8 seconds (hereinafter referred to as the "calculation target time") relevant to the calculation of the autocorrelation functions AF1 to AF4 and the total autocorrelation function AF is shorter than one-third of the entire period (8 seconds).

[0097] When the heart rate calculation unit 34 determines that the body movement occurrence period is equal to or greater than one third of the entire calculation target period (S56: NO), it outputs an error (S58). This is because, during a period in which the subject S is moving, the heart rate waveform is disturbed by the influence of the body movement, making it difficult to determine the heartbeat period and calculate the heart rate with high accuracy.

[0098] When the heart rate calculation unit 34 determines that the body movement occurrence period is shorter than one third of the entire calculation target period (S56: YES), it calculates the heart rate of the subject S in step S57. The heart rate calculation unit 34 detects the peak based on the autocorrelation functions AF1 to AF4 and the total autocorrelation function AF by using at least one of the following (i) to (iv).

[0099] (i) Among the heartbeat waveforms HW1 to HW4, the waveform with the greatest signal amplitude power during the calculation period is determined, and the autocorrelation function corresponding to the determined waveform is used. In this case, for example, if it is determined that the heartbeat waveform HW1 has the greatest signal amplitude power, the autocorrelation function AF1 is used.

[0100] (ii) Among the autocorrelation functions AF1 to AF4, the one having the largest absolute peak value is used.

[0101] (iii) The autocorrelation function AF1 is normalized by the power of the signal amplitude of the heartbeat waveform HW1, and similarly, the autocorrelation functions AF2 to AF4 are normalized by the power of the signal amplitude of the heartbeat waveform HW2 to HW4, respectively. Then, of the normalized autocorrelation functions AF1 to AF4, the one with the largest peak absolute value is used.

[0102] (iv) A total autocorrelation function AF is used, which improves the signal-to-noise ratio and increases the accuracy of heart rate calculation.

[0103] Specifically, for example, the heart rate calculation unit 34 calculates the heart rate of the subject S through the following steps. Here, calculation using the autocorrelation function AF1 will be described. The calculation method described below can be similarly applied to any of the above (i) to (iv).

[0104] First, the heart rate calculation unit 34 performs peak detection on the autocorrelation function AF1. At this time, the heart rate calculation unit 34 determines the range in which to perform peak detection, taking into consideration the estimated value of the heart rate period of the subject S estimated in the heart rate period estimation step S4.

[0105] As described above, the peak of the autocorrelation function AF1 is considered to appear at a position corresponding to the period of the heartbeat waveform HW1. Therefore, the heart rate calculation unit 34 takes into consideration the estimated value of the heartbeat period of the subject S (i.e., the period of the heartbeat waveform HW1) estimated in the heartbeat period estimation step S4, and limits the range in which peak detection is performed to the periphery of the estimated value. This makes it possible to increase the reliability of the detection result while reducing the burden of calculation processing in peak detection.

[0106] Next, the heart rate calculation section 34 performs an interpolation process of the autocorrelation function AF1 before and after the detected peak.

[0107] Each of the autocorrelation functions AF1 to AF4 and the total autocorrelation function AF is based on at least one of the heartbeat waveforms HW1 to H4, which are represented with a sampling period of 0.01 seconds. Therefore, the data points of the autocorrelation functions AF1 to AF4 and the total autocorrelation function AF are also obtained at intervals of 0.01 seconds.

[0108] Here, as a result of peak detection for the autocorrelation function AF1, it is assumed that the data point of the amplitude af(p) shown in Fig. 11(a) is detected as a peak. At this time, the amplitude af(p-1) at the data point immediately before the amplitude af(p) and the amplitude af(p+1) at the data point immediately after the amplitude af(p) are both smaller than the amplitude af(p), so when only these three data points are viewed, the amplitude af(p) appears to correspond to the peak. However, since the data points of the autocorrelation function AF1 are spaced at 0.01 second intervals, the true peak of the autocorrelation function AF1 may exist between the amplitude af(p) and the amplitude af(p-1), or between the amplitude af(p) and the amplitude af(p+1).

[0109] Therefore, the heart rate calculation unit 34 performs an interpolation process on the autocorrelation function AF1 to find the true peak PK of the autocorrelation function AF1. Specifically, the interpolation process is performed by fitting an upwardly convex quadratic function F (FIG. 11(b)) to the curve of the autocorrelation function AF1 in the vicinity of the peak detected by peak detection. This results in the following equation indicating the deviation OS between the peak detected by peak detection and the true peak PK.

number

[0110] Here, Ts is the sampling period of the data points of the autocorrelation function AF1 (0.01 [s] in this embodiment).

[0111] 11(b) shows a state where the quadratic function F is fitted by the interpolation process. The heart rate calculation unit 34 detects the peak PK of the quadratic function F as the true peak.

[0112] Next, the heart rate calculation unit 34 determines the lag time L corresponding to the true peak (i.e., the peak PK of the quadratic function F) as the period T of the heart rate of the subject S. Then, the heart rate HR [bpm] of the subject S is calculated using the following (Equation 2). [Number 2] (Formula 2) HR=60 / T [bpm]

[0113] The heart rate calculation section 34 sequentially calculates the heart rate HR based on at least one of the sequentially calculated autocorrelation functions AF1 to AF4 and the total autocorrelation function AF. The heart rate calculation section 34 calculates the heart rate HR, for example, once every 0.01 seconds.

[0114] [Display process S6] In the display step S6, the display control unit 41 of the user terminal 40 sequentially acquires the heart rate HR sequentially calculated by the heart rate calculation unit 34 from the bioinformation acquisition unit 30, and displays it on the display unit 42. In the display step S6, in addition to or instead of displaying using the display unit 42, a notification may be performed using the notification unit 43. In this case, for example, the display control unit 41 emits a notification sound when the heart rate HR of the subject S deviates from a predetermined range, and notifies the user of the bioinformation acquisition system 100, such as a doctor, nurse, or caregiver, of the abnormal heart rate state.

[0115] Specifically, the display control unit 41 performs display in the following manner, for example.

[0116] In this embodiment, the display control unit 41 sequentially acquires the heart rate HR calculated by the heart rate calculation unit 34, stores it in the memory unit 45, and displays the median value of multiple heart rates HR for the most recent minute on the display unit 42 (FIG. 12(a)). This makes it possible to suppress the effects of momentary fluctuations in the heart rate HR due to disturbances, etc. This also leads to the suppression of false alarms when the alarm unit 43 issues an audio alarm when the heart rate HR exceeds a predetermined threshold.

[0117] Furthermore, the display control unit 30 does not display the heart rate HR on the display unit 42 during a period when the subject S is not on the bed BD (FIG. 12(b)). Specifically, the period when the subject S is not on the bed BD may be, for example, a period when the bioinformation acquisition unit 30 (respiratory rate calculation unit, body weight calculation unit) is not calculating the respiratory rate of the subject S, a period when the body weight of the subject S detected by the load detection unit 1 is equal to or less than a predetermined value, etc.

[0118] Specifically, for example, the bioinformation acquiring unit 30 may sequentially calculate the position of the center of gravity of the subject S based on the load signals s1 to s4, and calculate the respiratory rate of the subject S based on the temporal fluctuation of the position of the center of gravity of the subject S according to the breathing of the subject S. Alternatively, the bioinformation acquiring unit 30 may perform Fourier analysis on at least one of the load signals s1 to s4, identify a peak frequency appearing in a frequency band corresponding to breathing, and calculate the respiratory rate of the subject S by regarding the identified peak frequency as the frequency of breathing of the subject S.

[0119] The biological information acquiring section 30 can calculate the weight of the subject S by adding up the load signals s1 to s4.

[0120] The bioinformation acquiring unit 30 may calculate the heart rate based on external disturbances (such as air vibrations caused by the operation of surrounding devices such as an air conditioner) even during periods when the subject S is not present on the bed BD. Therefore, by stopping the display of the heart rate HR on the display unit 42 during a predetermined period when it can be assumed that the subject S is not present on the bed BD, it is possible to prevent erroneous display of the heart rate HR.

[0121] The advantages of the biometric information acquisition system 100 of this embodiment are summarized below.

[0122] In the bioinformation acquisition system 100 of this embodiment, first, in a heartbeat cycle estimation step S4, the heartbeat cycle of the subject S is estimated based on the heartbeat waveform HW1, etc. Then, peak detection of the autocorrelation function AF1, etc. is performed within a range that matches the estimated heartbeat cycle, and the heart rate HR of the subject S is calculated based on the detected peak. In this way, the bioinformation acquisition system 100 of this embodiment performs peak detection of the autocorrelation function AF1, etc., taking into consideration the heartbeat cycle estimated in advance, so that even if the heartbeat waveform HW1, etc. is distorted and the periodicity is disturbed, the peak position of the autocorrelation function AF1, etc. can be determined with high accuracy and the heart rate HR can be calculated with high accuracy. In addition, the calculation processing load of the peak detection is small.

[0123] In the heart rate calculation step S5, the bioinformation acquisition system 100 of this embodiment does not calculate the entire autocorrelation function for the target period at once, but divides it into partial autocorrelation functions, calculates them, and adds them together. Therefore, the autocorrelation function at each timing can be calculated with a smaller amount of calculation. In this way, the small calculation load is particularly advantageous when the bioinformation acquisition system 100 is implemented as an embedded program of a microcomputer.

[0124] In the heart rate calculation step S5, the biological information acquisition system 100 of this embodiment detects a true peak by performing an interpolation process, and calculates the heart rate HR of the subject S based on the true peak. Therefore, the heart rate HR of the subject S can be obtained with higher accuracy.

[0125] In the display step S6, the bioinformation acquiring system 100 of this embodiment stops displaying the heart rate HR on the display unit 42 during a predetermined period during which it can be assumed that the subject S is not present on the bed BD. Therefore, the bioinformation acquiring system 100 of this embodiment can prevent erroneous display of the heart rate HR.

[0126] <Modification> The biometric information acquisition system 100 of the above embodiment may also adopt the following modified aspects.

[0127] In the cardiac cycle estimation step S4 of the above embodiment, the cardiac cycle estimation unit 33 determines whether the interval between the falling zero crossing points fx in the immediately preceding cycle, the peak p, the bottom b, and the like satisfy predetermined conditions each time the cardiac cycle estimation unit 33 identifies a falling zero crossing point fx. However, this is not limiting. A similar determination may be made each time a rising zero crossing point rx is identified.

[0128] In the cardiac cycle estimation step S4 of the above embodiment, the determination as to whether the amplitude AM (positive value) at the peak p is smaller than the body movement threshold THp and / or the determination as to whether the amplitude AM (negative value) at the bottom b is larger than the body movement threshold THn may be omitted. In the cardiac cycle estimation step S4 of the above embodiment, the determination as to whether the fluctuation ratio of the interval PR of the immediately preceding cycle to the interval PR of the cycle immediately preceding that cycle is within a predetermined range may be omitted.

[0129] In the cardiac cycle estimation step S4 of the above embodiment, the median value of the intervals PR for eight cycles stored in the storage unit 35 is set as the estimated value of the cardiac cycle of the subject S, but this is not limited to this. The number of intervals PR stored in the storage unit 35 may be any multiple number, or may be just one. The cardiac cycle estimation unit 33 may set the median or average value of any multiple number of intervals PR as the estimated value of the cardiac cycle of the subject S.

[0130] In the cardiac cycle estimation step S4 of the above embodiment, the cardiac cycle estimation unit 33 estimates the cardiac cycle of the subject S using the cardiac waveform HW1, but is not limited to this. The cardiac cycle estimation unit 33 can estimate the cardiac cycle of the subject S using at least one of the cardiac waveforms HW1 to HW4.

[0131] In the heart rate calculation process S5 of the above embodiment, the heart rate calculation unit 34 sequentially calculates partial autocorrelation functions PAF1 to PAF4 of the respiratory waveforms HW1 to HW4 for the latest 0.5 seconds and the respiratory waveforms HW1 to HW4 for the past 1.65 seconds, and adds them together for 8 seconds to calculate autocorrelation functions AF1 to AF4, but this is not limited to this.

[0132] The period for which the partial autocorrelation functions PAF1 to PAF4 are calculated is not limited to 0.5 seconds and can be any period. Also, the period for which the autocorrelation functions AF1 to AF4 are calculated is not limited to 8 seconds and can be any period.

[0133] That is, the heart rate calculation unit 34 may take any of the following forms: calculating partial autocorrelation functions PAF1 to PAF4 (first autocorrelation functions) of heart rate waveforms HW1 to HW1 included in a predetermined period (first period); calculating partial autocorrelation functions PAF1 to PAF4 (second autocorrelation functions) of heart rate waveforms HW1 to HW4 included in a predetermined period (second period) after the predetermined period; calculating partial autocorrelation functions PAF1 to PAF4 (third autocorrelation functions) of heart rate waveforms HW1 to HW4 included in a predetermined period (third period) after the predetermined period; calculating a sum of the first autocorrelation function and the second autocorrelation function as autocorrelation functions AF1 to AF4 at a predetermined timing (first time); and calculating a sum of the second autocorrelation function and the third autocorrelation function as autocorrelation functions AF1 to AF4 at a predetermined timing (second time) thereafter.

[0134] In the heart rate calculation step S5 of the above embodiment, the heart rate calculation unit 34 may calculate the autocorrelation functions AF1 to AF4 each time, instead of calculating the partial autocorrelation functions PAF1 to PAF4. In this case, for example, the autocorrelation functions calculated in a 1.65 second calculation window of the latest 8 seconds of heart rate waveforms HW1 to HW4 are calculated every 0.5 seconds.

[0135] In the heart rate calculation step S5 of the above embodiment, when the heart rate calculation unit 34 determines that the body movement occurrence period is equal to or greater than one third of the entire calculation target period (S56: YES), it outputs an error (S58). However, this is not limited thereto, and the heart rate calculation unit 34 may output an error in step S56 when the body movement occurrence period is an arbitrary proportion (1 / 2, 1 / 4, etc.) of the calculation target period. The heart rate calculation unit 34 may also output an error when at least a portion of the calculation target period is a body movement occurrence period.

[0136] In the heart rate calculation step S5 of the above embodiment, the heart rate calculation unit 34 does not need to perform the interpolation process. In this case, the peak of the autocorrelation function detected by the peak detection is used to determine the heart rate period T of the subject S and calculate the heart rate HR [bpm] of the subject S.

[0137] In the above embodiment, the display control unit 30 does not display the heart rate HR on the display unit 42 during the period when the subject S is not on the bed BD. However, this is not limited to this. The display control unit 30 may adopt any mode that causes the display mode of the heart rate HR on the display unit 42 to differ between the period when the subject S is on the bed BD and the period when the subject S is not on the bed BD.

[0138] Specifically, for example, the display control unit 30 may perform normal display while the subject S is on the bed BD, and may perform display in red or blinking while the subject S is not on the bed BD. Note that in this specification and the present invention, "non-display" is also considered to be one aspect of the display method. In this way, by making the display mode of the heart rate HR when the subject S is not on the bed different from the display mode of the heart rate HR when the subject S is on the bed, the user or the like can intuitively understand that the displayed heart rate is not that of the subject S.

[0139] The biological information acquiring section 30 of the above embodiment may not have the body movement determining section 32. In this case, the process related to the body movement determination of the above embodiment may not be executed.

[0140] In the heart rate information acquisition system 100 of the above embodiment, the heart rate calculation unit 34 calculates the heart rate based on the calculation of the autocorrelation value, but this is not limited to this. Various methods can be used to calculate the heart rate based on the heart rate waveform.

[0141] Specifically, for example, the heart rate calculation unit 34 may perform Fourier analysis on at least one of the load signals s1 to s4, identify a peak frequency that appears in a frequency band corresponding to the heart rate, and calculate the respiratory rate of the subject S by regarding the identified peak frequency as the frequency of the heart rate of the subject S.

[0142] In this embodiment, when identifying the peak frequency, the estimated value of the cardiac cycle of the subject S estimated in the cardiac cycle estimation step S4 may be taken into consideration.

[0143] In this specification and the present invention, a negative amplitude value being smaller than a threshold value (negative value) means that the absolute value of the negative amplitude value is greater than the absolute value of the threshold value (negative value). The comparison of the amplitude value (negative value) with the threshold value (negative value) as defined in the present invention includes a mode in which the absolute value of the amplitude value (negative value) is compared with the absolute value of the threshold value (negative value).

[0144] In the biometric information acquiring system 100 of the above embodiment, a single biometric information acquiring unit 30 is connected to the user terminal 40, but this is not limited thereto. A plurality of biometric information acquiring units 30 may be connected to the user terminal 40. Alternatively, the biometric information acquiring unit 30 and the user terminal 40 may be integrated, and the user terminal 40 may be regarded as a part of the heart rate acquiring unit of the present invention.

[0145] The bioinformation acquisition system 100 of the above embodiment does not necessarily have to include all of the load detectors 11 to 14, and may only have at least one of the load detectors 11 to 14. The load detectors do not necessarily have to be placed at the four corners of the bed, and may be placed at any position so as to detect the load of the subject on the bed and its fluctuation. The load detectors 11 to 14 are not limited to load sensors using beam-type load cells, and for example, force sensors may also be used.

[0146] In the biological information acquisition system 100 of the above embodiment, the load detection unit 1 may be a plurality of pressure-sensitive sensors (pressure sensors) arranged in a matrix under the sheet.

[0147] The load detectors 11 to 14 may be combined with the bed BD either integrally or detachably to configure a bed system BDS (FIG. 2) consisting of the bed BD and the biological information acquisition system 100 of this embodiment.

[0148] The display control unit 41 and the display unit 42 of the above embodiment may be combined with any heart rate calculation unit to configure a heart rate calculation device. Such a heart rate calculation device can more appropriately display the acquired heart rate.

[0149] In the biological information acquisition device 30 of the above embodiment, the cardiac cycle estimation unit 33 may be omitted. In this case, too, the heart rate calculation unit 34 can acquire the heart rate more efficiently.

[0150] As long as the characteristics of the present invention are maintained, the present invention is not limited to the above-described embodiments, and other forms conceivable within the scope of the technical idea of ​​the present invention are also included within the scope of the present invention. [Explanation of symbols]

[0151] 1 Load detection unit; 11, 12, 13, 14 Load detector; 3 Biometric information acquisition unit; 31 Heart rate waveform acquisition unit; 32 Body movement determination unit; 33 Heart rate cycle estimation unit; 34 Heart rate calculation unit; 35 Memory unit; 40 User terminal; 41 Display control unit; 42 Display unit; 43 Notification unit; 44 Input unit; 45 Memory unit; BD bed; BDS bed system

Claims

1. A heart rate acquisition device for acquiring a heart rate of a subject on a bed, a heartbeat waveform acquiring unit that acquires a heartbeat waveform indicating a temporal variation in a load value corresponding to the heartbeat of the subject based on an output of a load detector provided on the bed; a cardiac cycle estimation unit that estimates the cardiac cycle of the subject based on transitions in the cardiac waveform; a heart rate calculation unit that calculates the heart rate of the subject based on the heart rate waveform and the estimated value.

2. 2. The heart rate acquisition device according to claim 1, wherein the cardiac cycle estimation unit determines the estimated value based on identifying a bottom of the heart rate waveform, a rising zero crossing point of the heart rate waveform, a peak of the heart rate waveform, and a falling zero crossing point of the heart rate waveform.

3. 3. The heart rate acquisition device according to claim 2, wherein the cardiac cycle estimation unit determines the interval between two consecutive rising zero crossing points or two consecutive falling zero crossing points as the estimated value when the interval between the two consecutive rising zero crossing points or two consecutive falling zero crossing points is within a predetermined range, the amplitude of the cardiac waveform at the bottom between the two consecutive rising zero crossing points or the two consecutive falling zero crossing points is smaller than a bottom amplitude threshold, and the amplitude of the cardiac waveform at the peak between the two consecutive rising zero crossing points or the two consecutive falling zero crossing points is greater than a peak amplitude threshold.

4. 4. The heart rate acquisition device of claim 3, wherein the cardiac cycle estimation unit determines the interval between the two consecutive rising zero crossing points or the two consecutive falling zero crossing points as the estimated value when the amplitude of the heart rate waveform at the bottom between the two consecutive rising zero crossing points or the two consecutive falling zero crossing points is greater than a bottom body motion threshold and the amplitude of the heart rate waveform at the peak between the two consecutive rising zero crossing points or the two consecutive falling zero crossing points is smaller than a peak body motion threshold.

5. 5. The heart rate acquisition device according to claim 3, wherein the cardiac cycle estimation unit determines that the interval between the two consecutive rising zero crossing points or the two consecutive falling zero crossing points is within the predetermined range when the interval between the two consecutive rising zero crossing points or the two consecutive falling zero crossing points is equal to or greater than a predetermined value.

6. 4. The heart rate acquisition device according to claim 3, wherein the cardiac cycle estimation unit sequentially identifies the rising zero cross point or the falling zero cross point and calculates the interval between the two consecutive rising zero cross points or the two consecutive falling zero cross points, and determines that the interval is within a predetermined range when a fluctuation ratio of the interval calculated at a certain timing to the interval calculated immediately before the timing is within the predetermined range.

7. The calculation of the heart rate by the heart rate calculation unit is calculating an autocorrelation function of the cardiac waveform; detecting a peak in the autocorrelation function; calculating the heart rate based on the position of the detected peak; The heart rate acquisition device according to claim 1 , wherein the heart rate calculation unit determines a range in which the peak detection is performed based on the estimated value.

8. In the calculation of the heart rate by the heart rate calculation unit, calculating the heart rate based on the position of the detected peak performing an interpolation process around the detected peak; The heart rate acquiring device according to claim 7 , further comprising: calculating the heart rate based on the position of the peak identified by the interpolation process.

9. The calculation of the autocorrelation function in the heart rate calculation unit is calculating a first autocorrelation function of the cardiac waveform included in a first time period; calculating a second autocorrelation function of the cardiac waveform included in a second time period after the first time period; calculating a third autocorrelation function of the cardiac waveform included in a third time period after the second time period; calculating a sum of a first autocorrelation function and a second autocorrelation function at a first time as the autocorrelation function; The heart rate acquiring device according to claim 7 or 8, further comprising: calculating, at a second time point after the first time point, a sum of the second autocorrelation function and the third autocorrelation function as the autocorrelation function.

10. the load detector includes a first load detector and a second load detector; the heartbeat waveform acquisition unit acquires a first heartbeat waveform based on an output of a first load detector and a second heartbeat waveform based on an output of a second load detector; The heart rate acquiring device according to claim 7 , wherein the autocorrelation function calculated by the heart rate calculating unit is a sum of an autocorrelation function of a first heart rate waveform and an autocorrelation function of a second heart rate waveform.

11. a body movement determination unit that determines whether or not the subject is moving based on a comparison between the amplitude of the heartbeat waveform and a body movement threshold; The heart rate acquisition device according to claim 7 , wherein the heart rate calculation unit does not calculate the heart rate based on the autocorrelation function when a proportion of a period during which the subject is experiencing body movement during a period for which the autocorrelation function is calculated is equal to or greater than a threshold value.

12. a display unit that displays the heart rate calculated by the heart rate calculation unit; a display control unit that controls the display content of the display unit, The heart rate acquisition device according to claim 1, wherein the display control unit changes the display mode of the heart rate calculated by the heart rate calculation unit on the display unit between a period when the subject is present on the bed and a period when the subject is not present on the bed.

13. a weight calculation unit that calculates a weight of the subject based on an output of the load detector and / or a respiratory rate calculation unit that calculates a respiratory rate of the subject based on an output of the load detector, The heart rate acquisition device of claim 12, wherein the display control unit determines that the subject is not present on the bed if the calculated weight of the subject is below a threshold value and / or if the respiratory rate of the subject is not calculated.

14. the heart rate calculation unit sequentially calculates the heart rate; The heart rate acquiring device according to claim 12 or 13, wherein the display control unit displays a median value of the plurality of heart rates calculated sequentially on the display unit.

15. A heart rate acquisition device for acquiring a heart rate of a subject on a bed, a heart rate calculation unit that calculates the heart rate of the subject based on a temporal variation in an output of a load detector provided on the bed according to the heart rate of the subject; a display unit that displays the heart rate calculated by the heart rate calculation unit; a display control unit that controls the display content of the display unit, The display control unit changes the display manner of the heart rate calculated by the heart rate calculation unit on the display unit between a period when the subject is present on the bed and a period when the subject is not present on the bed.

16. a weight calculation unit that calculates a weight of the subject based on an output of the load detector and / or a respiratory rate calculation unit that calculates a respiratory rate of the subject based on an output of the load detector, The heart rate acquisition device of claim 15, wherein the display control unit determines that the subject is not present on the bed if the calculated weight of the subject is below a threshold value and / or if the respiratory rate of the subject is not calculated.

17. the heart rate calculation unit sequentially calculates the heart rate; The heart rate acquiring device according to claim 15 or 16, wherein the display control unit displays a median value of the plurality of heart rates calculated sequentially on the display unit.

18. A heart rate acquisition device for acquiring a heart rate of a subject on a bed, a heartbeat waveform acquiring unit that acquires a heartbeat waveform indicating a temporal variation in a load value corresponding to the heartbeat of the subject based on an output of a load detector provided on the bed; a heart rate calculation unit that calculates the heart rate of the subject based on the heart rate waveform, The calculation of the heart rate by the heart rate calculation unit is calculating an autocorrelation function of the cardiac waveform; detecting a peak in the autocorrelation function; calculating the heart rate based on the position of the detected peak; The calculation of the autocorrelation function is calculating a first autocorrelation function of the cardiac waveform included in a first time period; calculating a second autocorrelation function of the cardiac waveform included in a second time period after the first time period; calculating a third autocorrelation function of the cardiac waveform included in a third time period after the second time period; calculating a sum of a first autocorrelation function and a second autocorrelation function at a first time as the autocorrelation function; A heart rate acquisition device that includes calculating, at a second time point after the first time point, a sum of a second autocorrelation function and a third autocorrelation function as the autocorrelation function.

19. In the calculation of the heart rate by the heart rate calculation unit, calculating the heart rate based on the position of the detected peak performing an interpolation process around the detected peak; The heart rate acquiring device according to claim 18 , further comprising: calculating the heart rate based on the position of the peak identified by the interpolation process.

20. The bed and a load detector provided on the bed; A bed system comprising the heart rate acquisition device according to claim 1 , 15 or 18 .

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