JPWO2013146242A1 - Analytical monitoring system and monitoring method - Google Patents

Abstract

The present invention relates to an analyte monitoring system and a monitoring method. The measurement means (12) calculates the pole information, which is information regarding the arrival time at which the time series of the measurement signal reaches the pole, for each subject. Based on the acquired extreme point information, at least one time zone of the day is determined as a time zone of interest (100, 102, 104) close to the arrival time. The sampling interval (T) in the determined time zone (100, 102, 104) is sequentially set.

Description

  The present invention relates to an analyte monitoring system and a monitoring method for measuring the concentration of an analyte in a subject in accordance with a measurement sampling interval.

  Diabetes, commonly known, results in abnormal metabolism of sugar, protein, fat, etc. for the patient. For example, accumulation and stagnation of blood glucose (blood sugar) may persist in the patient. Therefore, a continuous blood glucose monitoring system {CGM (Continuous Glucose Monitoring)} that measures the concentration of glucose as an analyte (ie, blood glucose level) at a predetermined sampling interval has recently been developed in order to continuously manage blood glucose in patients. ing.

  For example, a blood glucose monitor system proposed in Japanese translations of PCT publication No. 2003-502090 discloses a sensor for measuring blood glucose levels, a monitor transmitter for transmitting measurement signals representing measurement results, and blood glucose levels corresponding to the received measurement signals Is provided. It is described that the monitor device receives and acquires a signal from the monitor transmitter at a predetermined sampling interval set in advance.

  The blood glucose level starts to rise from the time of eating, and the fluctuation rate increases at a predetermined time before and after the highest peak point. After a certain amount of time has elapsed from this peak point, the blood glucose level decreases with a relatively low fluctuation rate. Draw a fluctuation curve. In blood glucose management, it is important to recognize the fluctuation state when the blood glucose level greatly fluctuates after meals and to make use for treatment (for example, instruction on meal contents and meal methods).

  However, in the system proposed in Japanese Translation of PCT International Publication No. 2003-502090, the blood glucose level is sampled at a constant time interval. Therefore, if the blood glucose level is to be measured in detail, it is necessary to sufficiently shorten the sampling interval. In this case, a large amount of blood glucose level data is detected even during a stable period (a period when a certain amount of time has elapsed since the meal time) in which the fluctuation rate of the blood glucose level is small, and the amount of data handled by the system increases, Inconveniences such as increased consumption occur. Conversely, if the blood sugar level sampling interval is lengthened, there is a possibility that fluctuations in the blood sugar level cannot be sufficiently captured.

  Moreover, the life patterns of each subject (patient) are diverse, and for example, the number of meals per day, the intake time, the intake amount, and the presence or absence of snacks may differ depending on the subject. Some people lead a regular life on a daily basis, while others live a regular life. As described above, it is difficult to set a sampling interval suitable for each subject in consideration of all unique life patterns.

  The present invention has been made in view of the above circumstances, and an analyte that can measure and monitor the concentration of an analyte in a timely and efficient manner even when the life pattern of each subject is different. An object is to provide a monitoring system and a monitoring method.

  An analyte monitoring system according to the present invention includes a measuring unit that acquires a measurement signal according to the concentration of an analyte in a subject according to a sampling interval of measurement, and a time series of the measurement signal acquired by the measuring unit. And at least one time of the day based on the pole information acquired by the pole information acquisition means and pole information acquisition means for acquiring the pole information that is information on the arrival time at which the pole reaches the pole Interest time zone determining means for determining a time zone as an interest time zone close to the arrival time; and sampling interval setting means for sequentially setting the sampling interval in the interest time zone determined by the interest time zone determination means. It is characterized by providing.

  Thus, based on the acquired extreme point information, the extreme point information acquisition means for acquiring the extreme point information, which is information on the arrival time at which the time series of the measurement signal reaches the extreme point, for at least one of the days. Interest time zone determination means for determining one time zone as a time zone of interest close to the arrival time is provided, so that it is possible to estimate the life pattern of each subject, and appropriately select the time zone of interest that is important for measurement. Can be determined. Thereby, even if each subject has a different life pattern, the concentration of the analyte can be measured and monitored in a timely and efficient manner.

  Further, the extreme point information acquisition unit is a statistical distribution acquisition unit that acquires a statistical distribution of the arrival time already acquired by the measurement unit as the extreme point information, and the time of interest determination unit is the statistical distribution acquisition It is preferable that at least one time zone in which the arrival time frequency is relatively high is determined as the time zone of interest among the statistical distribution acquired by the unit. Thereby, the life pattern of each subject can be statistically estimated, and the time zone of interest that is important for measurement can be appropriately determined.

  Further, the extreme point information acquisition unit is a variation pattern acquisition unit that acquires a variation pattern of the measurement signal as the extreme point information, and the time of interest determination unit is the variation pattern acquired by the variation pattern acquisition unit. It is preferable that the possibility of reaching the extreme point is predicted, and at least one time zone predicted to be highly likely is determined as the time zone of interest.

  Further, the extreme point information acquisition means is a meal information acquisition unit that acquires meal information related to the subject's meal as the extreme point information, and the interest time zone determination means is the meal information acquisition unit. It is preferable that the meal time is estimated from the meal information, and at least one time zone close to the meal time is determined as the time zone of interest.

  Further, the sampling interval setting means is configured such that an average value of the sampling intervals in the interest time zone determined by the interested time zone determination means is smaller than an average value of the sampling intervals in the remaining time zone. It is preferable to set the sampling interval sequentially. As a result, the number of samples in the time zone of interest is dense and the number of samples in the remaining time zone is sparse, allowing timely quantification without excess or deficiency, greatly reducing power consumption during intermittent quantification. it can.

  Further, the sampling interval setting means can selectively set one of a plurality of sampling intervals including a minimum sampling interval, and the setting frequency of the minimum sampling interval in the time period of interest is the remaining frequency. It is preferable that the sampling interval is sequentially set so as to be higher than the setting frequency of the minimum sampling interval in the time zone.

  Further, the sampling interval setting means can selectively set one of a plurality of sampling intervals including a maximum sampling interval, and the setting frequency of the maximum sampling interval in the time of interest is the remaining frequency. It is preferable that the sampling interval is sequentially set so as to be lower than the setting frequency of the maximum sampling interval in the time zone.

  Furthermore, it is preferable that the pole information acquisition means acquires the pole information over a plurality of days. Thereby, the tendency of the life pattern of the subject becomes clearer, and the estimation accuracy of each interest time zone is further improved.

  In addition, the time-of-interest determination unit obtains a plurality of divided time zones by dividing a day into a plurality of time zones according to the statistical distribution, and then the statistics of the arrival times in the divided time zones. It is preferable to determine the time zone of interest based on. Thereby, it becomes possible to calculate statistics for each divided time zone having high correlation with the life pattern, and the estimation accuracy of each interested time zone is improved.

  Furthermore, it is preferable that the said interested time zone determination means determines each time zone in which the average value of the said arrival time in each said divided time zone is included as the said interested time zone. Thus, since the average value of the arrival times is included in each interest time zone, the accuracy of capturing the extreme value of the concentration of the analyte is statistically high.

  Furthermore, it is preferable that the said interested time zone determination means determines each time zone which has a time width proportional to the standard deviation of the said arrival time in each said divided time zone as the said interested time zone. Thereby, the width of the time zone of interest can be set appropriately according to the degree of variation in arrival time. For example, when the arrival time variation is large, the accuracy of capturing the extreme value of the concentration of the analyte can be further increased by widening the width of the time of interest.

  Moreover, it is preferable that the said fluctuation pattern acquisition part acquires the time-sequential trend of the said measurement signal as said fluctuation pattern. Considering the time-series trend, it is possible to capture the concentration change globally, and the accuracy of capturing the extreme value of the analyte concentration increases.

  Furthermore, it is preferable that the fluctuation pattern acquisition unit further acquires the continuity of the trend as the fluctuation pattern. Considering the continuity of the trend together, the accuracy of capturing the extreme value of the analyte concentration is further increased.

  Moreover, it is preferable that the said meal information acquisition part acquires the intake time, intake content, or intake of a meal as the said meal information.

  The method for monitoring an analyte according to the present invention includes a step of acquiring a measurement signal corresponding to the concentration of an analyte in a subject according to a measurement sampling interval, and reaching the time point of the acquired time series of the measurement signal reaching a pole. Obtaining pole information, which is information related to time, for each subject, and determining at least one time zone of a day as a time zone of interest close to the arrival time based on the obtained pole information. And sequentially setting a sampling interval in the determined time period of interest.

  According to the analyte monitoring system and the monitoring method of the present invention, the pole information, which is information related to the arrival time at which the time series of the measurement signal reaches the pole, is obtained for each subject, and based on the obtained pole information. Since at least one time zone of a day is determined as the time zone of interest close to the arrival time, the life pattern of each subject can be estimated, and the time zone of interest that is important for measurement is appropriate Can be determined. Thereby, even if each subject has a different life pattern, the concentration of the analyte can be measured and monitored in a timely and efficient manner.

1 is a schematic perspective view of a blood glucose monitor system according to the present embodiment. It is a schematic block diagram of the blood glucose monitoring system shown in FIG. It is a functional block diagram of the monitor apparatus shown in FIG. It is a graph showing an example of a time-dependent change of the blood glucose level in a subject. It is a flowchart with which operation | movement description of the blood glucose monitoring system shown in FIG. 1 is provided. FIG. 6A is a correspondence table showing set values of sampling intervals in each measurement mode. FIG. 6B is a schematic explanatory diagram illustrating an example of determining an interest time zone from the time of one day. It is a flowchart for demonstrating the determination method of the sampling interval shown to step S8 of FIG. It is a detailed flowchart for demonstrating the update rule of the sampling interval shown to step S84 of FIG. It is a graph showing the result of having measured the blood glucose level shown in FIG. 4 sequentially according to the update rule of the sampling interval of FIG. FIG. 10A is a graph plotting the peak points of blood glucose levels over multiple days for the same subject. FIG. 10B is a histogram of arrival times obtained from the plot of FIG. 10A. FIG. 11A and FIG. 11B are schematic diagrams for explaining a specific method of determining a time period of interest.

  DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a method for monitoring an analyte according to the present invention will be described in detail with reference to the accompanying drawings by giving preferred embodiments in relation to a monitor system that implements the method.

  FIG. 1 is a schematic perspective view of a blood glucose monitor system 10 according to the present embodiment. FIG. 2 is a schematic block diagram of the blood glucose monitoring system 10 shown in FIG.

  As shown in FIG. 1, the blood glucose monitoring system 10 includes a sensor 12 (measurement means) that acquires a measurement signal corresponding to the concentration of glucose as an analyte, that is, a blood glucose level, and a measurement signal obtained by the sensor 12 wirelessly. The transmitting / receiving device 14 is configured to transmit, and the monitor device 16 that receives a signal transmitted by the transmitting / receiving device 14 and stores or displays the measured value.

  As the sensor 12, a sensing device capable of optically measuring blood glucose is applied. Specifically, for detection using a phenomenon in which glucose and a labeling compound (fluorescent dye compound: for example, those having a fluorescent residue such as fluorescein-labeled dextran or phenylboronic acid derivative) interact to change the fluorescence intensity Sensor (fluorescence sensor).

  The housing of the sensor 12 is formed in a substantially rectangular shape by a resin material or the like that can block external light, and is attached to a predetermined location (for example, an arm or a flank) of the subject. The contact surface 12a with the subject in the sensor 12 is composed of hydrogel and carbon black. Thereby, while allowing glucose to pass, outside light is blocked.

  As shown in FIG. 2, a measurement unit 18 and an A / D conversion unit 20 are provided inside the housing of the sensor 12. The measurement unit 18 is a contact surface in which a base made of silicon or the like, a light receiving element (for example, a photodiode element), a protective film, a filter, a light emitting element (for example, a light emitting diode element), an indicator layer, and the like are stacked. A puncture needle is provided on the 12a side (both not shown).

  The measurement unit 18 guides blood to the indicator layer through the contact surface 12a by puncturing and placing (that is, embedding) the puncture needle in the subject. The indicator layer is configured to include a fluorescent dye as a labeling compound, whereby glucose that has entered from the contact surface 12a interacts with the labeling compound. When the sensor 12 emits light from the light emitting element of the measurement unit 18 and makes the measurement light incident on the indicator layer, the sensor 12 obtains fluorescence having an intensity corresponding to the glucose concentration. Fluorescence from the indicator layer passes through a filter or the like, is photoelectrically converted by the light receiving element, and is supplied to the A / D conversion unit 20 as a blood glucose level signal.

  As the sensor 12, it is preferable to apply an optical sensor (fluorescent sensor as described above) that can easily vary the blood sugar level sampling interval T. In addition, the form of the sensor 12 is not limited to this, For example, the sensor which measures a blood glucose level electrically (electrochemical system) by the enzyme electrode method using enzymes, such as glucose oxidase (GOD), is applied. May be.

  The A / D conversion unit 20 converts the current value (analog signal) of the blood glucose level detected by the measurement unit 18 into a voltage value, and amplifies the voltage value to convert it into a digital signal. Then, the transmission / reception device 14 acquires a measurement signal (blood glucose level data 66 in FIG. 3, sometimes simply referred to as “blood glucose level”) from the sensor 12.

  The transmission / reception device 14 shown in FIG. 1 is directly connected to one end of the sensor 12 and has a function of controlling blood glucose level measurement by the sensor 12 and transmitting the blood glucose level measured by the sensor 12 to the monitor device 16. The transmitter / receiver 14 is configured in a flat casing so that it can be easily placed on the skin of the subject together with the sensor 12.

  Returning to FIG. 2, a sensor-side control unit 22, a sensor-side storage unit 24, a sensor-side transmission / reception module 26, and a sensor-side power supply 28 are provided inside the housing of the transmission / reception device 14.

  A known microcomputer (microprocessor: MPU) or the like is applied to the sensor side control unit 22 of the transmission / reception device 14. The sensor-side control unit 22 controls the measurement of the blood glucose level by the sensor 12 by operating according to a measurement program (not shown) stored in the sensor-side storage unit 24. The sensor-side control unit 22 has an internal timer (not shown) that uses a processing clock, and measures the blood sugar level based on the sampling interval T by counting by the timer.

  The sensor-side storage unit 24 is configured by a ROM (Read Only Memory) and a RAM (Random Access Memory), and a blood sugar level measurement program is stored in the ROM in advance, and the blood sugar level data 66, the sampling interval data 72, and the like. Is temporarily stored in the RAM.

  The sensor side transmission / reception module 26 has a function of transmitting / receiving data to / from the monitor side transmission / reception module 34 of the monitor device 16. In particular, in the present embodiment, a module that realizes wireless data communication (for example, an RF module that can output and input radio waves in a high frequency band) is applied to the sensor-side transceiver module 26. When blood glucose monitoring is performed, it is predicted that the arrangement position of the monitor device 16 is not so far away from the arrangement position of the sensor 12 and the transmission / reception device 14 (that is, the location of the subject). The module 26 and the monitor-side transmission / reception module 34 may adopt a standard for near field communication (for example, IEEE 802.15).

  As the sensor-side power supply 28, for example, a button-type battery, a round dry battery, a square dry battery, a secondary battery, an external power supply, or the like can be applied. The sensor-side power supply 28 is an internal mechanism (measurement unit 18, A / D conversion unit 20, sensor-side control unit 22, sensor-side storage unit 24, sensor-side transmission / reception module 26, etc.) that is driven by the power of the sensor 12 and the transmission / reception device 14. ) To supply necessary power.

  The monitor device 16 shown in FIG. 1 is configured as a mobile terminal provided with a display panel 36 and operation buttons 38. Returning to FIG. 2, a monitor-side control unit 30, a monitor-side storage unit 32, a monitor-side transmission / reception module 34, a timer 40, a monitor-side power source 42, and the like are disposed inside the housing of the monitor device 16.

  As the monitor-side control unit 30, a known microcomputer or the like is applied in the same manner as the sensor-side control unit 22. The monitor-side control unit 30 performs predetermined processing based on a control program (hereinafter referred to as a control program 44) stored in advance in the monitor-side storage unit 32.

  The control program 44 (see FIG. 3) is a program for controlling the entire blood glucose monitoring system 10 including the sensor 12, the transmission / reception device 14, and the monitoring device 16. That is, the monitor device 16 sets the blood glucose level sampling interval by the sensor 12, stores and displays a plurality of blood glucose level data detected by the sensor 12, or the blood glucose level for an external device (for example, a computer) based on the control program 44. Data transmission or the like can be performed.

  Similarly to the sensor side storage unit 24, the monitor side storage unit 32 includes a ROM and a RAM. The monitor storage unit 32 stores the control program 44 in the ROM in advance, and a plurality of data areas for storing various data measured by the sensor 12 are allocated to an address space on the RAM. .

  The monitor-side transmission / reception module 34 has a function of transmitting / receiving predetermined data based on the operation of the monitor-side control unit 30 (or the sensor-side control unit 22). The monitor-side transmission / reception module 34 is configured to perform wireless data communication with the sensor-side transmission / reception module 26 and to perform wireless data transmission with the external device. Of course, data transmission / reception between the transmission / reception device 14 and the monitor device 16 is not limited to wireless communication, and may be wired communication.

  The display panel 36 (see FIG. 1) is disposed on the upper surface of the housing of the monitor device 16 so as to have a relatively large display area. The display panel 36 is configured by, for example, a liquid crystal monitor, organic EL, inorganic EL, or the like. The display panel 36 is connected to an internal mechanism in the monitor device 16 and is based on the control of the monitor-side control unit 30. Information necessary for blood glucose level monitoring (for example, blood glucose level, date / time, sampling interval, operation procedure, error, etc.) ) Is displayed.

  The operation button 38 includes a plurality of push buttons and is disposed on the upper surface of the housing together with the display panel 36. Thus, the user can press the operation button 38 while confirming information displayed on the display panel 36. Of course, the monitor device 16 is not limited to the configuration of the display panel 36 and the operation buttons 38 described above. For example, by adopting a touch panel type display panel, display and operation required in blood glucose level monitoring may be performed integrally.

  The timer 40 is provided for managing the time (date and time) in the monitor device 16. The timer 40 is configured to automatically measure time regardless of whether the power of the monitor device 16 is turned on or off.

  Various power sources can be applied to the monitor-side power source 42 in the same manner as the sensor-side power source 28. The monitor-side power source 42 supplies necessary power to internal mechanisms (the monitor-side control unit 30, the monitor-side storage unit 32, the monitor-side transmission / reception module 34, the display panel 36, the timer 40, etc.) that are driven by the power of the monitor device 16. Supply.

  The blood glucose monitoring system 10 sets the blood sugar level sampling interval T by linking the above-described components, and discretely detects a plurality of blood sugar levels based on the sampling interval T. Hereinafter, the measurement of the analyte (including the blood glucose level) according to the sampling interval T may be referred to as “sampling”. The setting process of the sampling interval T is executed by the monitor device 16 (control program 44).

  FIG. 3 is a functional block diagram of the monitor device 16 shown in FIG.

  By executing the control program 44, the monitor-side control unit 30 causes the statistical distribution calculation unit 46, the fluctuation pattern acquisition unit 47, the interested time zone determining unit 48 (interesting time zone determining means), and the sampling interval setting unit 50 (sampling interval setting). Each function as a means).

  The statistical distribution calculator 46 calculates a statistical distribution at a time (hereinafter referred to as arrival time) when the time series of the measurement signal already acquired by the sensor 12 reaches a peak (also referred to as a pole). Note that the “arrival time” in this specification may be either the time to reach the maximum point or the time to reach the minimum point. Specifically, the statistical distribution calculation unit 46 creates a peak point detection unit 52 that detects a peak in the time series of the measurement signal, and a histogram (statistic distribution) regarding the arrival time of the peak detected by the peak point detection unit 52. And a histogram creation unit 54.

  The fluctuation pattern acquisition unit 47 acquires the fluctuation pattern of the measurement signal. As a specific example of the fluctuation pattern, a time series trend of the measurement signal or continuity of the trend may be included. Here, “trend” means a fluctuation tendency of blood glucose level (concentration) in a predetermined time width.

  The interest time zone determination unit 48 determines at least one time zone of the day as an interest time zone close to the arrival time based on the pole information described later. Specifically, the interested time zone determining unit 48 divides the day into a plurality of time zones according to the histogram, and each time zone (hereinafter, divided time) divided by the time zone sorting unit 56. And a time zone calculation unit 58 that calculates each specific time zone based on the arrival time statistic.

  Further, the interested time zone determination unit 48 predicts the possibility of reaching a peak from the variation pattern acquired by the variation pattern acquisition unit 47, and determines at least one time zone predicted to be highly likely as the interested time zone. May be determined as Furthermore, the interested time zone determining unit 48 estimates the meal time from the meal information acquired by the later-described meal information acquiring unit 74, and determines at least one time zone close to this meal time as the interested time zone. Good.

  The sampling interval setting unit 50 selectively sequentially sets one of a plurality of sampling intervals T including a minimum sampling interval (Ts) and / or a maximum sampling interval (Tl). Specifically, the sampling interval setting unit 50 updates the sampling interval T according to the determination result by the change necessity determination unit 60 that determines whether or not to change the current sampling interval T and the change necessity determination unit 60. And an interval updating unit 62.

  In the data storage area 64 of the monitor-side storage unit 32, various data used for calculation for determining the sampling interval are stored. The various data includes blood glucose level data 66 that is a time series of measurement signals, peak point data 68 related to the peak point of blood glucose level data 66, interest time zone data 70 related to the time zone of interest, and sampling intervals corresponding to each measurement mode. Sampling interval data 72, which is T, is included.

  The operation button 38 functions as a meal information acquisition unit 74 that acquires information about the meal of the subject (hereinafter referred to as meal information). Examples of meal information include meal intake time, intake content, intake amount, and the like.

  Note that the statistical distribution calculation unit 46, the variation pattern acquisition unit 47, and the meal information acquisition unit 74 each provide information on the arrival time (pole information) at which the time series of the measurement signal acquired by the sensor 12 reaches the extreme point for each subject. It is one form of the pole information acquisition means to acquire.

  The blood glucose monitoring system 10 according to the present embodiment is basically configured as described above. Subsequently, the operation will be described with reference to the flowcharts of FIGS. 5, 7, and 8 and other drawings as appropriate.

  It is assumed that the blood glucose level to be measured has actually changed along the shape of the graph shown in FIG. The horizontal axis of this graph is time, and the vertical axis of the graph is blood glucose level (unit: mg / dl). This change indicates a change over time in blood glucose level in the body after the meal after the subject completes the intake of the meal at 13:00. The blood glucose level starts to rise from the time of eating, and the fluctuation rate increases at a predetermined time before and after the highest peak point. After a certain amount of time has elapsed from this peak point, the blood glucose level decreases with a relatively low fluctuation rate. Draw a fluctuation curve.

  In step S <b> 1 of FIG. 5, the sensor-side power supply 28 and the monitor-side power supply 42 are turned on in response to a user operation. Thereby, the sensor 12, the transmission / reception device 14, and the monitor device 16 are started.

  In step S2, the monitor-side control unit 30 performs initial settings necessary for blood glucose level measurement. For example, the monitor-side control unit 30 temporarily stores various setting values input via the operation buttons 38 in the data storage area 64.

  As shown in FIG. 6A, a plurality of sampling intervals Ts, Tm, and Tl are set as the sampling interval data 72, respectively. For example, it is assumed that the sampling interval Ts (minimum sampling interval) is set to Ts = 1 (minute) in the measurement mode (hereinafter referred to as S mode) with a short interval (Short Interval). Further, it is assumed that the sampling interval Tm is set to Tm = 5 (minutes) in the middle interval measurement mode (hereinafter referred to as M mode). Furthermore, it is assumed that the sampling interval Tl (maximum sampling interval) is set to Tl = 15 (minutes) in a long interval measurement mode (hereinafter referred to as L mode).

  In step S3, the interested time zone determining unit 48 determines at least one specific time zone (interesting time zone) from the time of one day (from 0:00 to 24:00). Here, the time zone of interest means a time zone for a medical worker or subject to watch the change in blood glucose level. In other words, the time zone of interest is also a time zone in which the occurrence of a peak is predicted in the time series of measurement signals.

  In the present embodiment, the interest time zone determination unit 48 determines the interest time zone in advance (so-called statically) before measuring the blood glucose level, and immediately sets the interest time zone according to the blood glucose level fluctuation pattern (so-called so-called static). Note that it is determined dynamically). A specific determination method by the interested time zone determination unit 48 will be described later in detail.

  As shown in FIG. 6B, the interested time zone determination unit 48 selects three specific time zones from the time of the day, specifically, a time zone from 8:00 to 10:00 (specific time zone 100 ), The time zone from 13:00 to 15:00 (specific time zone 102), and the time zone from 19:15 to 20:45 (specific time zone 104) are determined. On the other hand, a time zone excluding the specific time zones 100, 102, and 104 in the time of the day is referred to as a remaining time zone 106. Specifically, the remaining time zone 106 includes a time zone from 10:00 to 13:00 (first residual time zone 108), and a time zone from 15:00 to 19:15 (second residual time zone). 110) and a time zone (third remaining time zone 112) from 20:45 to the next 8:00.

  In step S <b> 4, the sensor 12 starts measuring the blood glucose level of the subject based on the operation control by the sensor side control unit 22. At this time, the sensor-side control unit 22 acquires data necessary for measurement, such as an initial value of the sampling interval T, from the monitor device 16 side.

  In step S5, the sensor side control unit 22 determines whether or not to execute sampling. Specifically, the sensor-side control unit 22 counts the number of pulses of the clock signal input from a clock generator (not shown) and reaches the count upper limit (corresponding to the sampling interval T when converted to time). In this case, it is determined that sampling can be executed. In this case, the process proceeds to the next step (S6). On the other hand, if it is determined that the count upper limit has not yet been reached, the process stays at step S5.

  In addition, in this embodiment, although the structure which discriminate | determines execution timing is taken in the sensor side control part 22 side, you may discriminate | determine in the monitor apparatus 16 side (monitor side control part 30). In this case, the monitor device 16 needs to send an instruction signal to the effect of sampling execution to the transmission / reception device 14.

  In step S <b> 6, the sensor 12 acquires the current measurement signal in accordance with an instruction from the sensor-side control unit 22 and samples the blood sugar level. Electric power is supplied from the transmission / reception device 14 to the light emitting element of the sensor 12, and the measurement light is irradiated to optically measure the blood glucose level of the subject. Then, the sensor side control unit 22 temporarily stores the acquired measurement signal in the sensor side storage unit 24.

  In step S <b> 7, the monitor device 16 acquires the measurement signal temporarily stored in step S <b> 6 via the sensor side transmission / reception module 26 and the monitor side transmission / reception module 34. Then, the monitor-side control unit 30 stores the received measurement signal in the data storage area 64 as blood glucose level data 66.

  In step S8, the sampling interval setting unit 50 determines the next sampling interval T. For example, the sampling interval setting unit 50 selects the sampling interval T from Ts, Tm, and Tl based on various information such as the latest time series and current time of the blood glucose level data 66 acquired in step S7.

  In step S9, the sensor-side power supply 28 and the monitor-side power supply 42 are turned off in accordance with the user's operation. Thereby, each operation | movement of the sensor 12, the transmission / reception apparatus 14, and the monitor apparatus 16 is stopped.

  Next, the method for determining the sampling interval T in step S8 in FIG. 5 will be described in detail with reference to the flowcharts in FIGS. Here, in conjunction with the determination process of the sampling interval T, the time-series peak point (blood glucose level and time data pair) of the blood glucose level data 66 is detected and stored as necessary.

  In step S <b> 81 of FIG. 7, the monitor-side control unit 30 reads the blood sugar level data 66 in the data storage area 64. As the blood glucose level data 66 to be read, not only the current value but also a past measurement value (for example, 10 times) may be read.

  In step S82, the monitor-side control unit 30 determines whether or not the current sampling interval T is Ts (S mode). When T = Ts is satisfied, monitoring of the peak point by the peak point detection unit 52 is started or continued (step S83), and the process proceeds to the next step (S84). On the other hand, when (T = Tm) or (T = Tl) is satisfied, the process directly proceeds to step S84 without executing step S83.

  In step S83, the peak point detection unit 52 monitors the peak point of the blood glucose level data 66. Specifically, the peak point detection unit 52 determines whether or not it is a peak point (maximum value or minimum value) in a time series of blood glucose levels sequentially acquired after the monitoring start time. If the peak point is determined, the monitor-side control unit 30 associates the blood glucose level with the current time of the timer 40 and temporarily stores it in the data storage area 64.

  In step S84, the sampling interval setting unit 50 updates the sampling interval T. More specifically, the change necessity determination unit 60 performs sampling from the viewpoint of [1] an attribute of the current time (specific time zone 100 and the like, an elapsed time since meal), and [2] a blood glucose level trend (fluctuation tendency). It is determined whether or not the interval T needs to be changed.

  In FIG. 8, the change necessity determination unit 60 determines whether or not the current time belongs to the specific time zones 100, 102, and 104 (step S101). When it is determined that they belong to any one (YES), the interval update unit 62 sets the next sampling interval T to a value corresponding to the S mode, that is, T = Ts (step S103), and then performs the process of step S84. finish.

  On the other hand, when it is determined that it does not belong, the change necessity determination unit 60 further determines whether or not the current time belongs to a predetermined range calculated from the time of eating a meal, for example, a range of 30 minutes to 3 hours after eating. (Step S102). Prior to this determination, according to the input operation of the user, the interested time zone determination unit 48 estimates the meal time from the meal information acquired by the meal information acquisition unit 74, and selects at least one time zone close to this meal time. It is determined in advance as an interest time zone.

  If it is determined that it belongs to this time of interest (YES), the interval update unit 62 sets the next sampling interval T to a value corresponding to the S mode, that is, T = Ts (step S103), and then in step S84. The process ends.

  On the other hand, when it is determined that it does not belong (NO), the fluctuation pattern acquisition unit 47 acquires the fluctuation pattern (trend and its continuity) from the latest blood glucose level data 66 and then changes the information to determine whether or not the change is necessary. To supply. Then, the interested time zone determining unit 48 predicts the possibility of reaching the peak point from the obtained variation pattern, and dynamically determines at least one time zone predicted to be highly likely as the interested time zone. To do.

  Next, the change necessity determination unit 60 determines whether T = Tl (L mode) and whether the latest time series of the blood glucose level data 66 is in an upward trend (step S104). For example, when the current value is increased by a predetermined value (for example, 20 [mg / dl]) or more compared to the previous value, the change necessity determination unit 60 may determine that the current value is an upward trend. If it is determined that the trend is an upward trend, the interval updating unit 62 sets the next sampling interval T to a value corresponding to the M mode, that is, T = Tm (step S106). And the process of step S84 is complete | finished.

  On the other hand, if it is determined not to belong, it is determined whether T = Ts (S mode) and whether the latest time series of the blood glucose level data 66 is in a downward trend (step S105). For example, when the determination result indicating that the current value is smaller than the previous value is obtained a plurality of times (for example, three times) continuously, or the blood glucose level at the peak point is set to a predetermined value (for example, If it is below 20 [mg / dl]), it may be determined that the trend is a downward trend. If it is determined that the trend is a downward trend, the interval update unit 62 sets the next sampling interval T to a value corresponding to the M mode, that is, T = Tm (step S106). And the process of step S84 is complete | finished.

  Next, the change necessity determination unit 60 determines whether or not T = Tm (M mode) (step S107). When it is determined that T = Tm, the change necessity determination unit 60 further determines whether or not the trend of the blood glucose level data 66 is continued (step S108).

  For example, the change necessity determination unit 60 continuously obtains a determination result indicating that the current value has increased by a predetermined value (for example, 10 [mg / dl]) or more compared to the previous value a plurality of times (for example, three times). In this case, it may be determined that the upward trend is continuing. In this case, the interval update unit 62 changes the current sampling interval T = Tm to the next sampling interval T = Ts (step S109). Note that the interested time zone determination unit 48 may determine a time zone within a predetermined range calculated from this time point as the interested time zone.

  For example, if the determination result indicating that the current value is smaller than the previous value is obtained continuously several times (for example, 5 times), the change necessity determination unit 60 compares the current value with a predetermined value (for example, 10 [mg / dl]) When the determination result is lower than a certain number of times (for example, 3 times) continuously, or a predetermined value (for example, 30 [mg / dl]) or more from the blood glucose level at the peak point If the determination result indicating that the downward trend has been obtained is obtained a plurality of times (for example, three times), it may be determined that the downward trend is continuing. In this case, the interval update unit 62 changes the current sampling interval T = Tm to the next sampling interval T = Tl (step S110).

  For example, when the sampling interval T is set to T = Tm continuously a plurality of times (for example, 10 times), the change necessity determination unit 60 may determine that the flat trend is continuing. In this case, the interval update unit 62 changes the current sampling interval T = Tm to the next sampling interval T = Tl (step S110).

  On the other hand, when none of the above-described conditions is satisfied, the interval update unit 62 maintains the sampling interval T without changing it, assuming that the blood glucose level trend is in a transient state. Note that even when the sampling interval T is different from Tm in step S107, that is, when (T = Ts) or (T = Tl) is satisfied, the sampling interval T is not changed (step S111).

  In this way, the sampling interval setting unit 50 sequentially determines the sampling interval T (step S84 in FIGS. 7 and 8). When at least the value of the sampling interval T is changed, the monitor device 16 sends the updated value of the sampling interval T toward the transmitting / receiving device 14 side.

  Returning to FIG. 7, in step S <b> 85, the monitor-side control unit 30 refers to the update result in step S <b> 84 and determines whether or not there is a predetermined change in the measurement mode. Specifically, it is determined by the operation of the sampling interval setting unit 50 whether or not the sampling interval T has been changed from Ts (S mode) to another value {Tm (M mode) or Tl (L mode)}. If there is no predetermined change, the operation of step S8 is terminated without executing steps S86 and S87.

  On the other hand, when there is a predetermined change, the peak point detection unit 52 interrupts monitoring of the peak point, assuming that the S mode has been canceled (step S86). Thereafter, the monitor-side control unit 30 stores the blood glucose level and the current time temporarily stored at the time of the above monitoring in the data storage area 64 as peak point data 68 (peak value and arrival time). Each peak value is the maximum value (or minimum value) within the range of one monitoring time (partial time series). That is, the peak point data 68 corresponds to each data of local maximum points (or local minimum points) in the entire time series.

  In this way, the sampling interval setting unit 50 determines the sampling interval T (step S8 in FIGS. 5 and 7).

  FIG. 9 is a graph showing the result of sequentially measuring the blood glucose level shown in FIG. 4 according to the method for updating the sampling interval T in FIG. For convenience of explanation, this figure shows a schematic measurement result, which is different from the actual sampling interval T.

  As understood from comparison with the graph of FIG. 4 (solid curve), the blood glucose level is measured with high accuracy in spite of a steep change with time. The band graph at the top of the figure represents the transition state of the measurement mode. A hatched zone with a large number of diagonal lines represents a measurement time zone in the S mode (T = Ts). A hatched band with a small number of diagonal lines represents a measurement time band in the M mode (T = Tm). A zone without hatching represents a measurement time zone in the L mode (T = Tl).

  As can be understood from the figure, the average value of the sampling intervals T in the specific time zones 100, 102, 104 as the time zone of interest is smaller than the average value of the sampling intervals T in the remaining time zone 106. . That is, the concentration of the analyte can be measured and monitored in a timely and efficient manner by making the number of samples in the specific time zones 100, 102, and 104 dense and making the number of samples in the remaining time zone 106 sparse.

  Further, the setting frequency of the minimum sampling interval (Ts) in each specific time zone 100, 102, 104 is higher than the setting frequency of the minimum sampling interval (Ts) in the remaining time zone 106. Furthermore, the setting frequency of the maximum sampling interval (Tl) in each specific time zone 100, 102, 104 is lower than the setting frequency of the maximum sampling interval (Tl) in the remaining time zone 106.

  By the way, there are various life patterns of each subject (patient). For example, the number of meals per day, intake time, intake amount, and the presence or absence of snacks may differ depending on the subject. Some people lead a regular life on a daily basis, while others live a regular life. Thus, it is difficult to set in advance a sampling interval T suitable for each subject in consideration of all unique life patterns.

  Therefore, in this embodiment, the peak point data 68 is sequentially stored for each subject, and a time period of interest suitable for each subject is determined. Hereinafter, the specific method of step S3 of FIG. 5 is demonstrated, referring FIG. 10A-FIG. 11B.

  FIG. 10A is a graph plotting the peak points of blood glucose levels over multiple days for the same subject. As shown in the figure, the entire plot is roughly classified into three plot groups, that is, a first plot group 120, a second plot group 122, and a third plot group 124. That is, it is presumed that the subject regularly ingested meals three times in the morning, noon, and night during the day. Based on this graph example, it demonstrates below.

  First, the histogram creation unit 54 creates a statistical distribution of the obtained peak point data 68, for example, a histogram in which one day is divided every hour. Then, as shown in FIG. 10B, a histogram having three peaks (9 o'clock, 13 o'clock, and 20 o'clock) in one day is obtained. Note that this statistical distribution is not limited to a histogram, and various distributions using statistical methods can be used.

  Then, the time zone division unit 56 sets a plurality of division time zones based on the histogram created by the histogram creation unit 54. The time zone division unit 56 determines three division time zones in consideration of the frequency density. Specifically, the time zone division unit 56 is in the middle (11:00) between the mode value in the first plot group 120 (9 o'clock) and the mode value in the second plot group 122 (13:00). First division line 126 is set. In addition, the time zone section 56 is in the middle (16:30) between the mode value (13:00) in the second plot group 122 and the mode value (20:00) in the third plot group 124. A second dividing line 128 is set. Further, the third dividing line 130 is set between the mode value in the third plot group 124 (20 o'clock) and the mode value in the first plot group 120 (9 o'clock) (2:30). To do.

  It should be noted that the time zone sorting unit 56 does not have to include all the time zones of the day in the sorting target. For example, in a subject who does not have a habit of eating meals at midnight, the midnight time zone may be excluded. Thereby, the blood glucose level data 66 resulting from irregular snacks can be excluded, and the estimation accuracy of the specific time zones 100 and 104 is further improved.

  Thereafter, the time zone calculator 58 calculates a time zone in which the arrival time frequency is relatively high. Specifically, the time zone calculation unit 58 calculates the specific time zones 100, 102, and 104 for each of the three divided time zones. For example, regarding the segment time zone (night time zone) defined by the second segment line 128 and the third segment line 130, the time zone calculation unit 58 uses the statistics of the third plot group 124 to calculate the specific time zone 104. Calculate center and time span. Here, the statistic may be, for example, a standard deviation, an average value, a mode value, a center value, a maximum value, a minimum value, or a combination thereof.

  In the example of FIG. 11A, the center of the specific time zone 104 is the average value t1 of the distribution 140 of the third plot group 124. Further, the time width of the specific time zone 104 is the standard deviation σ1 of the distribution 140.

  In addition, regarding the segment time zone (morning time zone) defined by the third segment line 130 and the first segment line 126, the time zone calculation unit 58 uses the statistics of the first plot group 120 to calculate the specific time zone 100. Calculate center and time span. In the example of FIG. 11B, the center of the specific time zone 100 is the average value t2 of the distribution 142 of the first plot group 120. Further, the time width of the specific time zone 100 is the standard deviation σ2 (> σ1) of the distribution 142.

  As can be understood from the figure, the specific time zones 100 and 104 include average values t1 and t2 of arrival times in the divided time zones, respectively. This statistically increases the accuracy of capturing the maximum value (or minimum value) of the analyte concentration.

  Further, the time widths of the specific time zones 100 and 104 are respectively proportional to the standard deviations σ1 and σ2 of the arrival times in the respective time zones. Thereby, the width of the time zone of interest can be set appropriately according to the degree of variation in arrival time.

  Specifically, as in the example of FIG. 11A, the number of samples around the specific time period 104 can be reduced by narrowing the width of the specific time period 104 with relatively small statistical variation, and the power consumption Can be reduced. Moreover, the peak point after a meal can be caught reliably by making the width | variety of the specific time slot | zone 100 with relatively large statistical dispersion wide like the example of FIG. 11B.

  As described above, the extreme point information acquisition unit (the statistical distribution calculation unit 46, the variation pattern acquisition unit 47, and the meal information acquisition) that acquires, for each subject, the extreme point information that is information on the arrival time at which the time series of the measurement signal reaches the extreme point Section 74) and the interest time zone determination for deciding at least one time zone of the day as an interest time zone (specific time zones 100, 102, 104) close to the arrival time based on the acquired pole information. The life pattern of each subject can be estimated and the specific time zones 100, 102, and 104 that are important for measurement can be determined appropriately. Thereby, even if each subject has a different life pattern, the concentration of the analyte can be measured and monitored in a timely and efficient manner.

  In addition, the sampling interval T is sequentially set so that the average value of the sampling intervals T in the determined specific time zones 100, 102, and 104 is smaller than the average value of the sampling intervals T in the remaining time zone 106. Since the sampling interval setting unit 50 is provided, the number of samples in the specific time zones 100, 102, and 104 is made dense and the number of samples in the remaining time zone (remaining time zone 106) is sparse, so that timely determination without excess or deficiency This makes it possible to significantly reduce power consumption during intermittent quantification.

  Furthermore, by acquiring the pole information over a plurality of days by the pole information acquisition means, the tendency of the life pattern of the subject becomes clearer and the estimation accuracy of the specific time zone 100 and the like is further improved.

  In addition, this invention is not limited to embodiment mentioned above, Of course, it can change freely in the range which does not deviate from the main point of this invention.

  For example, when applying glucose as an analyte, as described above, attention is paid to each local maximum point as a time-series peak point of a measurement signal in order to grasp a rising tendency of a blood sugar level. On the other hand, when it is desired to grasp the downward trend of the concentration of the analyte, attention may be paid to each local minimum point as a time series peak point of the measurement signal.

  In the present embodiment, the sensor 12 having the characteristic that the concentration of the analyte increases as the value of the measurement signal increases (so-called monotonic increase characteristic) is adopted, but the opposite characteristic (so-called monotonous decrease characteristic) is provided. Needless to say, the present invention can also be applied to the sensor 12.

Claims (15)

Measurement means (12) for acquiring a measurement signal according to the concentration of the analyte in the subject according to the sampling interval (T) of the measurement;
Extreme point information acquisition means (46, 47, 74) for acquiring, for each subject, extreme point information, which is information related to the arrival time at which the time series of the measurement signal acquired by the measurement means (12) reaches the extreme point;
Based on the extreme point information acquired by the extreme point information acquisition means (46, 47, 74), at least one time zone in one day is set as an interested time zone (100, 102, 104) close to the arrival time. A time zone determining means (48) for determining;
Sampling interval setting means (50) for successively setting the sampling interval (T) in the time of interest (100, 102, 104) determined by the time of interest determination means (48). Analyst monitor system (10). The monitoring system (10) according to claim 1,
The pole information acquisition means (46, 47, 74) is a statistical distribution acquisition unit (46) that acquires the statistical distribution of the arrival time already acquired by the measurement means (12) as the pole information,
The interested time zone determining means (48) selects at least one time zone having a relatively high frequency of arrival time from the statistical distribution obtained by the statistical distribution obtaining unit (46). 100, 102, 104) An analyte monitoring system (10) characterized in that The monitoring system (10) according to claim 1,
The pole information acquisition means (46, 47, 74) is a fluctuation pattern acquisition unit (47) that acquires a fluctuation pattern of the measurement signal as the pole information.
The interested time zone determining means (48) predicts the possibility of reaching the extreme point from the fluctuation pattern acquired by the fluctuation pattern acquisition unit (47), and at least one time when the possibility is predicted to be high An analyte monitoring system (10), characterized in that a band is determined as the time of interest (100, 102, 104). The monitoring system (10) according to claim 1,
The pole information acquisition means (46, 47, 74) is a meal information acquisition unit (74) that acquires meal information relating to the meal of the subject as the pole information.
The interest time zone determining means (48) estimates a meal time from the meal information acquired by the meal information acquisition unit (74), and determines at least one time zone close to the meal time as the interest time zone (100). , 102, 104), and an analyte monitoring system (10). In the monitor system (10) according to any one of claims 1 to 4,
In the sampling interval setting means (50), the average value of the sampling intervals (T) in the interested time zones (100, 102, 104) determined by the interested time zone determining means (48) is the remaining time zone. The analyte monitoring system (10), wherein the sampling interval (T) is sequentially set so as to be smaller than an average value of the sampling interval (T) in (106). The monitoring system (10) according to claim 5,
The sampling interval setting means (50) can selectively set one of a plurality of sampling intervals (Tl, Tm, Ts) including a minimum sampling interval (Ts), and the time period of interest (100, 102, 104) so that the setting frequency of the minimum sampling interval (Ts) is higher than the setting frequency of the minimum sampling interval (Ts) in the remaining time zone (106). The monitor system (10) for an analyte characterized by the fact that it is set in succession. The monitoring system (10) according to claim 5 or 6,
The sampling interval setting means (50) can selectively set one of a plurality of sampling intervals (Tl, Tm, Ts) including a maximum sampling interval (Tl), and the time period of interest (100, 102, 104) such that the setting frequency of the maximum sampling interval (Tl) is lower than the setting frequency of the maximum sampling interval (Tl) in the remaining time zone (106). The monitor system (10) for an analyte characterized by the fact that it is set in succession. In the monitor system (10) according to any one of claims 1 to 7,
The analyte monitoring system (10), wherein the pole information acquisition means (46, 47, 74) acquires the pole information over a plurality of days. The monitoring system (10) according to claim 2,
The time-of-interest determination means (48) obtains a plurality of divided time zones by dividing a day into a plurality of time zones according to the statistical distribution, and then calculates the arrival time statistics in each of the divided time zones. An analyte monitoring system (10) characterized in that said time of interest (100, 102, 104) is determined based on a quantity. The monitoring system (10) according to claim 9,
The interested time zone determining means (48) determines each time zone including an average value of the arrival times in each of the divided time zones as the interested time zone (100, 102, 104). Analytical monitor system (10). The monitor system (10) according to claim 9 or 10,
The interested time zone determining means (48) determines each time zone having a time width proportional to the standard deviation of the arrival time in each of the divided time zones as the interested time zone (100, 102, 104). An analyte monitoring system (10) characterized by: The monitoring system (10) according to claim 3,
The analyte monitoring system (10), wherein the variation pattern acquisition unit (47) acquires a time-series trend of the measurement signal as the variation pattern. The monitoring system (10) according to claim 12,
The analyte monitoring system (10), wherein the variation pattern acquisition unit (47) further acquires the continuity of the trend as the variation pattern. The monitor system (10) according to claim 4,
The analyte monitor system (10), wherein the meal information acquisition unit (74) acquires a meal intake time, intake content, or intake as the meal information. Obtaining a measurement signal according to the concentration of the analyte in the subject according to the measurement sampling interval (T);
Acquiring, for each subject, pole information, which is information relating to the arrival time at which the time series of the acquired measurement signal reaches the pole;
Determining at least one time zone of a day as a time zone of interest (100, 102, 104) close to the arrival time based on the acquired pole information;
And successively setting a sampling interval (T) in the determined time of interest (100, 102, 104).

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