Evaluation device and evaluation system

Abstract

To provide an evaluation device, etc., that can evaluate a patient's sedation scale using simple means. [Solution] An evaluation device comprising a biosignal acquisition unit for acquiring a patient's biosignals and a control unit, wherein the control unit calculates the patient's activity level based on the biosignals acquired from the biosignal acquisition unit, and evaluates the patient's sedation scale (RASS: Richmond Agitation-Sedation Scale) based on the calculated activity level.

Description

Technical Field

[0001] The present invention relates to an evaluation device and the like.

Background Art

[0002] Inventions for determining whether an abnormality has occurred in a user based on a biological information value of a patient or the like are known.

[0003] As a scale for evaluating the sedation state of a patient under sedative use, evaluation by the RASS (Richmond Agitation-Sedation Scale) is used in intensive care units, palliative care, and the like.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Patent Document 2

Non-Patent Documents

[0005]

Non-Patent Document 1

Non-Patent Document 2

Summary of the Invention

[0006] The present disclosure aims to provide an evaluation device, etc., that can evaluate a patient's sedation scale using simple means. [Means for solving the problem]

[0007] The evaluation apparatus disclosed herein comprises a biosignal acquisition unit for acquiring a patient's biosignals and a control unit, wherein the control unit calculates the patient's activity level based on the biosignals acquired from the biosignal acquisition unit, and evaluates the patient's sedation scale (RASS: Richmond Agitation-Sedation Scale) based on the calculated activity level.

[0008] The system of this disclosure includes a sheet-like detection device placed under a patient to detect the patient's body movements, a calculation device that calculates the patient's activity level from the body movements, and an evaluation device that evaluates the patient's sedation scale (RASS: Richmond Agitation-Sedation Scale) based on the activity level. [Effects of the Invention]

[0009] According to this disclosure, it is possible to provide an evaluation device, etc., that can evaluate a patient's sedation scale by simple means. [Brief explanation of the drawing]

[0010] [Figure 1] This is a diagram illustrating the overall structure of the first embodiment. [Figure 2] This is a diagram illustrating the functional configuration of the hardware in the first embodiment. [Figure 3] (a) A diagram illustrating the functional configuration of the software in the first embodiment, and (b) A diagram showing an example of a judgment threshold table. [Figure 4] This is a diagram illustrating RASS in the first embodiment. [Figure 5] This is an operation flow diagram illustrating the processing in the first embodiment. [Figure 6] This is a diagram illustrating an example of the first embodiment. [Figure 7] This is an operation flow diagram illustrating the processing in the second embodiment. [Figure 8] This figure illustrates an example of the third embodiment. [Figure 9] This figure illustrates an example of the fourth embodiment. [Figure 10] This is an operation flow diagram illustrating the processing in the fifth embodiment. [Modes for carrying out the invention]

[0011] Hereinafter, one embodiment for carrying out the present invention will be described with reference to the drawings. Specifically, the case in which the evaluation apparatus of the present invention is applied will be described, but the scope to which the present invention is applicable is not limited to this embodiment.

[0012] The Richmond Agitation-Sedation Scale (RASS) is used to assess the sedation level and the risk of agitation, such as delirium, in patients receiving sedatives. The RASS is a widely used method for evaluating sedation levels in clinical settings such as intensive care units and palliative care, and uses a 10-point scale (-4 to +5) with 0 as the center. It is desirable for staff to periodically (for example, at intervals of one to several hours) assess whether the purpose of sedation has been appropriately achieved in patients.

[0013] Here, since staff members, etc. need to evaluate the patient's score by observing or calling out to the patient for, for example, 30 seconds, it was a problem that the evaluation took a lot of time and effort. In addition, when the staff evaluated that the patient was in a sedated state, they needed to evaluate the sedated state by giving a calling stimulus or a physical stimulus to the patient, but there was a problem that this stimulus also became a burden on the patient.

[0014] Also, since the evaluation of the RASS is personal, there was also a problem that the evaluation changed due to individual differences and experience differences of the staff, etc. who evaluated.

[0015] In order to solve such problems, an evaluation device that can evaluate a sedation scale in a simple manner based on the patient's activity level will be described using the following embodiments. In the following embodiments, as a preferred example, the case of applying to the RASS for palliative care will be described.

[0016] [1. First Embodiment] [1.1 Overall System] FIG. 1 is a diagram for explaining the overall outline of a system 1 to which the evaluation device of the present invention is applied. As shown in FIG. 1, the system 1 has, for example, an evaluation device 10 for evaluating the sedation stage (RASS) of a patient P. The evaluation device 10 may be configured to include a detection device 12 placed between the floor portion of the bed 3 and the mattress 5, and a processing device 14 for processing the value output from the detection device 12. Further, the evaluation device 10 may be constituted by a single detection device 12 having the function of the processing device 14, for example.

[0017] When a patient (hereinafter referred to as "Patient P" as an example), whose sedated state is to be evaluated, is placed on mattress 5, the detection device 12 detects body vibrations (vibrations emitted from the human body) as a biosignal of Patient P. Based on the detected vibrations, Patient P's bioinformation values ​​are calculated. In this embodiment, the detection device 12 may output and display the calculated bioinformation values ​​as Patient P's bioinformation values. Here, the detection device 12 may calculate at least Patient P's activity level, and may also calculate heart rate and respiratory rate.

[0018] Furthermore, since the processing unit 14 can be a general-purpose device, it is not limited to information processing devices such as computers, but may be composed of devices such as tablets or smartphones.

[0019] Furthermore, while it is preferable that the patients are those whose sedation stage is primarily evaluated and who have received sedatives, the study is not necessarily limited to those patients. For example, the study may also include patients who require management of their sedation stage through medication or other means, or patients at risk of developing delirium.

[0020] Here, the detection device 12 is configured in a sheet-like shape to reduce its thickness. As a result, even when placed between the bed 3 and the mattress 5, it can be used without causing discomfort to the patient P, and thus biological information values, including activity levels in bed, can be measured over a long period of time. In other words, biological information values ​​and other data are acquired as part of the patient's condition when the patient is lying down and at rest.

[0021] The detection device 12 only needs to be able to acquire the patient P's biological signals (such as body movement, respiratory movement, and heart rate). In this embodiment, activity level, heart rate, respiratory rate, etc. are calculated based on body vibration, but for example, detection may be done using an infrared sensor, or the patient P's biological signals may be acquired from acquired video, etc., or an actuator with a strain gauge may be used. Alternatively, by utilizing a built-in acceleration sensor, etc., this may be implemented using, for example, a smartphone or tablet placed on the bed 3 (or mattress 5).

[0022] Furthermore, bed 3 can be installed in various locations. For example, bed 3 is typically installed in the hospital where patient P is hospitalized or in the facility where they reside, but in the case of home care, bed 3 may also be installed in the patient's home.

[0023] Furthermore, the evaluation device 10 can communicate with other devices via the network NW. Of the evaluation device 10, the detection device 12 may be connected to the network NW via, for example, the processing device 14, or the detection device 12 may be directly connected to the network NW via the access point 30 using a wireless LAN or the like. Alternatively, the detection device 12 may be directly connected to the network NW by incorporating a communication module capable of communicating with, for example, a mobile communication network (LTE / 4G / 5G / 6G, etc.).

[0024] The network NW can be connected to, for example, a server device 40 and a terminal device 50. The server device 40 may store, for example, biological information values ​​acquired by the evaluation device 10, or the sedation stage evaluated by the evaluation device 10. The server device 40 may also be, for example, an electronic medical record server that stores the user's disease information.

[0025] The terminal device 50 may be, for example, an information processing device such as a smartphone, tablet, or laptop computer used by medical staff such as doctors and nurses. Alternatively, the terminal device 50 may be an information processing device used by facility staff or family members. Furthermore, it may be an information processing device used by the patient themselves for self-checks.

[0026] [1.2 Functional Configuration] Next, the functional configuration of the evaluation device 10 in System 1 will be explained using Figures 2 and 3. In this embodiment, the evaluation device 10 includes a detection device 12 and a processing device 14, and each functional unit (process) except for the biosignal acquisition unit 400 may be implemented in either device. In other words, by combining these devices, the evaluation device 10 functions.

[0027] The evaluation device 10 may also perform an alert (notification) action according to the patient's sedation stage. In this case, the recipient of the alert may be a staff member, the patient themselves, or a family member. Furthermore, the method of notification may be simply by sound or screen display, or by sending an alert to a terminal device via email, etc. It may also be possible to send an alert (notification) to other terminal devices, etc.

[0028] [1.2.1 Hardware Configuration] As shown in Figure 2, the evaluation device 10 is configured to include, as necessary, one or more of the following: a control unit 100, a storage unit 200 (storage 210, ROM 220, and RAM 230), a biosignal acquisition unit 400, an input unit 600, an output unit 700, a notification unit 800, and a communication unit 900.

[0029] In the case of Figure 1, the control unit 100, the biosignal acquisition unit 400, and the storage unit are provided in the detection device 12, while the other components may be provided in the processing device 14.

[0030] The control unit 100 controls the entire evaluation device 10. The control unit 100 realizes various functions by reading and executing various programs stored in the memory unit 200 (for example, storage 210 or ROM 220), which is a memory device. The control unit 100 may be realized by one or more control devices / arithmetic units (CPU (Central Processing Unit), SoC (System on a Chip)). Alternatively, the control unit 100 may be composed of a control circuit.

[0031] The memory unit 200 stores various types of information as data. The memory unit 200 is generally a device that includes one or more storage 210, ROM 220, and RAM 230, and stores data in any of them as needed.

[0032] Storage 210 is a non-volatile storage device capable of storing programs and data. For example, it may consist of storage devices such as HDDs (Hard Disk Drives) or SSDs (Solid State Drives). Alternatively, Storage 210 may be configured as an externally connectable USB memory stick or memory card. Furthermore, Storage 210 may be, for example, a storage area located in the cloud.

[0033] ROM220 is a non-volatile memory that can retain programs and data even when the power is turned off.

[0034] RAM230 is the main memory primarily used by the control unit 100 during processing. RAM230 is a rewritable memory that temporarily holds data including programs read from storage 210 and ROM220, as well as execution results.

[0035] The biosignal acquisition unit 400 acquires the biosignals of patient P. In this embodiment, as an example, body vibration, which is a type of biosignal, is acquired using a sensor that detects pressure changes. The acquired body vibration is then converted into bioinformation value data such as respiratory rate, heart rate, and activity level by the control unit 100 and output. Furthermore, based on the body vibration data acquired by the biosignal acquisition unit 400, the control unit 100 can also acquire the user's lying-down state (for example, whether patient P is lying down, in bed, out of bed, or sitting on the edge of the bed, etc.) and, as described later, the sleep state (sleep, wakefulness).

[0036] In this embodiment, the biosignal acquisition unit 400 may, for example, acquire the user's body vibration using a pressure sensor and obtain respiration and heart rate from the body vibration. Alternatively, it may acquire biosignals based on changes in the user's center of gravity (body movement) using a load sensor, or it may acquire biosignals based on the displacement of the body surface or bedding using radar, or it may acquire biosignals based on the sound picked up by a microphone. It is sufficient to acquire the user's biosignals using any of these sensors.

[0037] In other words, the biosignal acquisition unit 400 may be connected to a device such as the detection device 12, or it may be configured to receive biosignals from an external device.

[0038] The input unit 600 is used by the user to input various conditions and to input the operation to start the measurement. The input unit 600 may be implemented by any input means, such as a hardware key or a software key.

[0039] The output unit 700 is a functional unit for outputting biological information values ​​such as information based on the sedation stage, sleep state, heart rate, and respiratory rate, and for notifying abnormalities. The output unit 700 may be a display device such as a display, or a notification device (sound output device) for issuing alarms, etc. It may also be an external storage device for storing data, or a transmission device for transmitting data over a communication channel, etc. It may also be a communication device for notifying other devices.

[0040] Furthermore, the input unit 600 and output unit 700 may be implemented by other devices. For example, they may be implemented using a terminal device connected via the communication unit 900 (for example, a smartphone or tablet used by a user). In this case, the terminal device may be capable of executing a program that enables the control unit 100, which will be described later, to perform the processing.

[0041] The notification unit 800 provides notifications to users, etc. For example, the notification unit 800 may be a speaker that outputs sound or an LED that is a light-emitting device. The notification unit 800 may also provide notifications to other devices (for example, terminal devices such as a patient's smartphone, a nurse call system, etc.).

[0042] The communication unit 900 communicates with other devices. For example, if the device is nearby, the communication unit 900 provides communication using methods such as wireless LAN (or wired LAN) or Bluetooth®. The communication unit 900 may also be a device that provides short-range wireless communication such as NFC. The communication unit 900 may also provide communication using methods that enable mobile communication such as 4G / LTE / 5G / 6G. The communication unit 900 may also be an interface (e.g., USB) for communicating with other devices.

[0043] [1.2.2 Software Configuration] The software configuration will be explained with reference to Figure 3(a). For example, the control unit 100 realizes each function by executing programs and applications stored in the memory unit 200 (e.g., storage 210, ROM 220, RAM 230).

[0044] The biological information value calculation unit 110 calculates, for example, activity level as a biological information value for patient P. The biological information value calculation unit 110 may also detect body vibrations per sampling unit time from the biological signal acquisition unit 400 and calculate the activity level based on the number of detected body vibrations. Alternatively, the biological information value calculation unit 110 may calculate the activity level from changes in the user's sleeping posture and movements.

[0045] Specifically, the biometric information calculation unit 110 counts the intervals in which there was greater body movement than respiration or heartbeat, using the sensor output value with a resolution of, for example, 16 Hz (16 times per second). At this time, the biometric information calculation unit 110 represents the activity level in counts per minute (counts / min), with a maximum value of 960 (counts / min).

[0046] Alternatively, the biological information calculation unit 160 may calculate the number of seconds of body movement per minute as the activity level by dividing the count per minute by 16. For example, when the threshold for determining a low RASS group is 47 (count / min), dividing by 16 results in 2.9 seconds.

[0047] In this embodiment, the biological information value calculation unit 110 may also extract respiratory and heart rate components from body movements acquired from the biological signal acquisition unit 400 and determine the respiratory rate and heart rate based on the respiratory interval and heart rate interval. Alternatively, the periodicity of body movements may be analyzed (e.g., Fourier transform) and the respiratory rate and heart rate may be calculated from the peak frequencies.

[0048] The sleep state determination unit 120 determines the user's sleep state. For example, the sleep state determination unit 120 determines the user's sleep state based on the biosignal acquired by the biosignal acquisition unit 400. The sleep state determination unit 120 may determine two sleep states: "wakeful" and "sleeping." Furthermore, the sleep state determination unit 120 may further determine the "sleeping" state as "REM sleep" and "non-REM sleep," or it may further determine multiple levels (depth of sleep) within the "sleeping" state.

[0049] Furthermore, the sleep state determination unit 120 may determine whether a person is in a sleep state or a wakeful state based on the magnitude of their activity level and how their activity level changes over time. For example, the sleep state determination unit 120 does not need to determine that a person is in a wakeful state even if there is temporary body movement. The sleep state determination unit 120 may determine that a person is in a wakeful state if the patient P's body movement continues for a certain period of time.

[0050] The user status acquisition unit 130 acquires the user's status. The user's status is the overall state of the user, and for example, by using a load sensor installed on the bed 3, the unit acquires whether the user is out of bed or in bed. The user status acquisition unit 130 may also acquire the user's sleeping posture and sleeping position when the user is in bed. In addition to load sensors, the user status acquisition unit 130 may also acquire the user's status based on biosignals acquired by the biosignal acquisition unit 400, as described above. Furthermore, the user's status may include whether the user is sleeping or awake, based on the user's sleep state determined by the sleep state determination unit 120. The user status acquisition unit 130 may also acquire whether the user is out of bed or in bed based on activity level.

[0051] The RASS evaluation unit 140 determines the RASS, which is the user's sedation scale. The RASS evaluation unit 140 determines, for example, which RASS group the user's RASS belongs to, based on thresholds stored in the determination threshold table 206. The processing of the RASS evaluation unit 140 will be described later. Here, a RASS group refers to dividing the RASS scale into multiple groups.

[0052] The disease information acquisition unit 150 acquires disease information, which is information relating to the user's illness. The disease information acquisition unit 150 may, for example, connect to an electronic medical record server to acquire the user's disease information. Alternatively, the disease information acquisition unit 150 may acquire disease information by referring to information entered by a doctor or other medical professional. In this embodiment, the disease information acquisition unit 150 may acquire the type and amount of drugs such as anesthetics and sedatives administered to the user as disease information.

[0053] Furthermore, the storage 210 stores biometric data 202, user status data 204, and judgment threshold table 206, and reserves space for the parameter buffer area 208.

[0054] The biological information data 202 stores information about biological information values ​​calculated by the control unit 100 from acquired biological signals (body movement), such as activity level. In this embodiment, activity level is stored as information about biological information values, but respiratory rate, heart rate, etc., may also be stored. Furthermore, it is preferable that the biological information data 202 is stored in a time series at predetermined intervals.

[0055] The user status data 204 stores the user's status. The user status acquired by the user status acquisition unit 130 stores whether the user is "in bed" or "out of bed". Furthermore, the user status data 204 may also store the sleep state determined by the sleep state determination unit 120 as part of the user's status. For example, when the user status acquisition unit 130 determines that the user is "in bed", the sleep state determined by the sleep state determination unit 120 may be stored. It is also preferable that the user status data 204 is stored chronologically at predetermined intervals.

[0056] The judgment threshold table 206 is a table that stores the thresholds used by the control unit 100 (RASS evaluation unit) when determining a patient's RASS. An example of the judgment threshold table 206 is shown in Figure 3(b).

[0057] The judgment threshold table stores a first judgment threshold (for example, "47") and a second judgment threshold (for example, "66").

[0058] In this embodiment, the patient's RASS (Responsible Activity Score) stores activity thresholds that divide them into low RASS, medium RASS, and high RASS groups. The relationship between the RASS groups and the RASS score will be explained with reference to Figure 4. Normally, the RASS score is divided from "+4" to "-5". Here, the high RASS group refers to, for example, RASS scores from "+4" to "+1". The medium RASS group refers to, for example, RASS scores from "0" to "-2". The low RASS group refers to, for example, RASS scores from "-3" to "-5".

[0059] Note that the RASS scores and terminology in Figure 4 are examples only and are based on the Japanese Society of Respiratory Therapy's guidelines for sedation during mechanical ventilation (2007). Therefore, other definitions may be used for the RASS score divisions and terminology. For example, when applying RASS to palliative care, a score of "-5" may be used as the term "unable to wake."

[0060] In this embodiment, values ​​below the first judgment threshold are designated as the low RASS group. Values ​​above the second judgment threshold are designated as the high RASS group. Values ​​between the first and second judgment thresholds are designated as the medium RASS group.

[0061] In this embodiment, the RASS scale is divided into three groups. This is the most effective division method, as will be described in the later examples, but it may also be divided into two or four groups. Furthermore, the RASS scale and the RASS groups may coincide.

[0062] [1.3 Processing Flow] The RASS evaluation process in this embodiment will now be described. Note that, in the description of the process, although it is a process executed as appropriate by the functional unit shown in Figure 3 (for example, the RASS evaluation unit 140), for the sake of explanation, it will be described as being executed by the control unit 100.

[0063] [1.3.1 Overall Flow] Figure 5 is an operation flow illustrating the RASS evaluation process of this embodiment. The control unit 100 acquires the activity level (S102). For example, the control unit 100 may calculate the activity level using the bio-information value calculation unit 110 at predetermined intervals (e.g., every second). Alternatively, the control unit 100 may calculate the activity level at intervals of, for example, every 5 seconds or every 10 seconds. Furthermore, the control unit 100 may calculate the activity level at intervals shorter than 1 second (e.g., 100 milliseconds).

[0064] When the control unit 100 determines that the activity level is below the first threshold (S104; Yes), it evaluates the patient as belonging to the low RASS group (S106). Here, the first threshold is, for example, "47".

[0065] Next, if the control unit 100 determines that the activity level is below the second threshold (S108; Yes), it evaluates the patient as being in the moderate RASS group (S108; Yes → S110). In other words, if the activity level is above the first threshold but below the second threshold, the control unit 100 evaluates the patient as being in the moderate RASS group.

[0066] The control unit 100 then evaluates the patient as belonging to the high RASS group when the activity level is above the second threshold, i.e., when the activity level is above the second threshold.

[0067] In this embodiment, the control unit 100 compares the activity level with the judgment threshold to evaluate the low RASS group, medium RASS group, and high RASS group, but several methods of evaluation are possible.

[0068] For example, the control unit 100 identifies the median value from the measured activity levels and divides the RASS groups based on the proportion around the median. For instance, the control unit 100 uses the median activity level as the center and designates 30% of the total values ​​that include the median as the medium RASS group. The control unit 100 then identifies the group with values ​​lower than the medium RASS group as the low RASS group and the group with values ​​higher than the medium RASS group as the high RASS group.

[0069] Alternatively, the control unit 100 may simply use the standard deviation (σ) to group the individuals. For example, the control unit 100 may use the individual's activity level determined over a specific past period (e.g., the past 7 days) to evaluate whether the current activity level is high (high RASS group) or low (low RASS group) for that individual. For example, the control unit 100 may classify an individual as either a low RASS group or a high RASS group if the measured activity level exceeds 2σ of the activity level over the specific period.

[0070] Furthermore, when dividing these groups, the control unit 100 may sort the measured RASS values ​​of multiple people in descending order of activity level, rather than dividing them between individuals, and evaluate them in order from those with the highest activity levels.

[0071] Furthermore, the control unit 100 may use the trained model to evaluate the low RASS group, the medium RASS group, and the high RASS group. For example, the trained model is generated using the patient's activity level and multiple parameters (e.g., biological information, medication information) as explanatory variables, and the patient's RASS score determined by staff as training data. The control unit 100 can obtain the patient's RASS score by inputting at least the activity level into the trained model. This allows the control unit 100 to use the trained model to evaluate the low RASS group, the medium RASS group, and the high RASS group.

[0072] [1.4 Examples] Here, as an example, the relationship between activity level and RASS score is shown in the graph in Figure 6. The graph in Figure 6, shown as an example, is based on the average values ​​measured using the RASS for palliative care in 971 terminally ill cancer patients (551 men, 420 women) with an average age of 74.2 years. When the average values ​​were plotted, the high RASS group (RASS score of 1 or higher) was characterized at R10, the medium RASS group (RASS score of -2 to 0) was characterized at R12, and the low RASS group was characterized at R14.

[0073] In other words, the control unit 100 can evaluate whether the patient's RASS score falls into the high RASS group, the moderate RASS group, or the low RASS group, based on the patient's activity level.

[0074] [1.5 Effects] Thus, according to this embodiment, it is possible to easily evaluate a patient's RASS score based on their activity level. While a patient's RASS score was previously evaluated subjectively by the evaluator, using activity levels makes it possible to evaluate it objectively.

[0075] Furthermore, since the patient's activity level can be continuously acquired using the measuring device, it becomes possible to continuously evaluate the RASS score. This allows staff, for example, to continuously monitor activity levels to quickly detect increases (or decreases) in activity that indicate the onset of symptoms of hyperactive delirium, such as restlessness (or oversedation), which are easily overlooked in normal clinical practice.

[0076] Furthermore, by quantifying the restlessness and sedation levels associated with delirium in terminally ill patients, it can provide a good indicator for patient care.

[0077] [2. Second Embodiment] A second embodiment will now be described. The second embodiment is an embodiment that utilizes the RASS evaluation of the first embodiment to display information regarding treatment and medication for patients.

[0078] First, when a patient is selected, the control unit 100 performs the RASS evaluation process described in the first embodiment and evaluates the patient's RASS score (or RASS group) (S202 → S204).

[0079] The control unit 100 then acquires treatment information, which is information about the treatment performed on the patient (S206). The control unit 100 can acquire the treatment information from any source; for example, it may acquire the treatment information by querying the electronic medical record server. For example, the disease information acquisition unit 150 may acquire the treatment information. The treatment information includes, for example, information about the medications (sleeping pills, sedatives) administered to the patient.

[0080] The control unit 100 outputs the action to be taken based on the acquired treatment information and the RASS evaluation (S208). Then, if the control unit 100 determines that a doctor call is necessary, it issues a doctor call (S210; Yes → S212). The control unit 100 then returns to S204 and repeats the process, thereby continuously monitoring the patient's condition.

[0081] Here, we will explain in detail the actions output by the control unit 100. For example, the memory unit 200 may have information regarding actions (action information) depending on the administered drug. For example, the following describes the case where mitarazom, a benzodiazepine-based anesthetic induction agent and sedative, or propofol, a general anesthetic and sedative, is used in the ICU (Intensive Care Unit).

[0082] For example, the control unit 100 displays a message indicating a dose reduction of 1 mL / hr when the patient's RASS score is evaluated from "-5" to "-3". The control unit also displays a message indicating that the current dose should be maintained when the patient's RASS score is evaluated from "-2" to "0". Furthermore, if the RASS score remains the same after 2 hours, the control unit displays a message indicating a dose reduction of 1 mL / hr.

[0083] The control unit 100 indicates that if the patient's RASS score is evaluated from "+1" to "+3", a 2 mL bolus dose should be administered. The control unit 100 may also indicate that two doses should be administered with a 15-minute interval between doses. If there is no change in the RASS score after the two doses, the control unit 100 indicates that the dose should be increased by 1 mL / hr if the patient is receiving continuous infusion. The control unit 100 also indicates that if the patient has interrupted medication, medication should be resumed at the initial dose.

[0084] Furthermore, the control unit 100 displays a message indicating that a 2ML bolus should be administered when the RASS score is "+4". In addition, the control unit 100 determines that a doctor call is necessary and issues a doctor call.

[0085] In the case of other medications, a doctor call may be issued even if the patient's RASS score is assessed as "+1" to "+3". For example, in the case of dexmedetomidine, an α2 agonist sedative, if the RASS score is assessed as "+1" to "+3" and the patient has been interrupted from taking the medication, a doctor call should be issued.

[0086] Thus, according to this embodiment, it is possible to output the appropriate course of action or issue a doctor call based on the patient's RASS score.

[0087] [3. Third Embodiment] A third embodiment will now be described. The third embodiment is an embodiment that stores a patient's RASS score and RASS group, and for example, displays or prints them. The control unit 100 stores the user's RASS score and RASS group in the storage unit 200 in chronological order.

[0088] The control unit 100 displays the RASS scores and RASS groups stored in chronological order, allowing staff, for example, to easily understand the user's past condition.

[0089] In this case, the control unit 100 may display the RASS score together with other information, for example. For example, Figure 8 is an example of a sleep diary displayed in the third embodiment. The sleep diary displays the patient's sleep status, and for example, the periods of being out of bed and in bed (awake or asleep) are displayed in a graph in a band shape for each day.

[0090] In this embodiment, the control unit 100 displays information related to RASS along with the sleep state. For example, in Figure 8, the sleep state is displayed in the upper row and the RASS group is displayed in the lower row for each date. In this way, the control unit 100 can display multiple past conditions related to the patient (biological information values, sleep state, RASS score, RASS group). Staff can then perform appropriate actions such as administering medication or conducting rounds, as the RASS information is displayed in conjunction with previous biological information values ​​and sleep state.

[0091] [4. Fourth Embodiment] The fourth embodiment is an embodiment in which the judgment threshold is changed. For example, the control unit 100 can change the first judgment threshold and the second judgment threshold.

[0092] Figure 9(a) shows an example of the display screen W400 when the judgment threshold is changed to an arbitrary value by staff or other personnel. For example, the display screen W400 has an area R402 in which a first judgment threshold can be entered and an area R404 in which a second judgment threshold can be entered. The control unit 100 stores the values ​​entered in areas R402 and R404 as the first judgment threshold and the second judgment threshold, respectively. The first judgment threshold and the second judgment threshold may also be set for each patient. In this case, the judgment threshold is stored in association with, for example, the patient ID.

[0093] Furthermore, the judgment threshold may be automatically set by the control unit 100 using machine learning. In other words, the memory unit 200 may further store a trained model that outputs the patient's RASS score.

[0094] A trained model, for example, takes the patient's biometric data (activity level) as an explanatory variable and outputs the RASS score as the target variable. Here, the explanatory variables must at least include patient information (e.g., age, sex, disease information) and activity level. The explanatory variables may also include additional patient biometric data (heart rate, respiratory rate) and disease information (medication information). Staff members then evaluate the patient's condition using the RASS score and input it as training data. The control unit 100 uses these parameters to perform machine learning to generate or retrain a trained model that outputs the RASS score as the target variable.

[0095] Figure 9(b) shows an example of a display screen W410 that allows staff to input a new RASS scale when the control unit 100 retrains a previously learned model. For example, the display screen W410 shows the RASS scale of the patient currently evaluated by the control unit 100.

[0096] Therefore, domain R410 is the RASS scale evaluated by the staff. This allows the trained model to be retrained based on the new RASS scale provided by the staff.

[0097] The trained model may be applied to each patient individually or to each facility. Alternatively, the service provider may collect the data centrally. By adjusting the trained model based on a large amount of data, the service provider can generate a more accurate model.

[0098] [5. Fifth Embodiment] The fifth embodiment is an embodiment in which the control unit 100 cooperates with other devices using the RASS scale evaluated in the first embodiment.

[0099] The operation of the fifth embodiment will be described with reference to Figure 10. The control unit 100 first selects the device to be controlled (S502). Next, the control unit 100 executes the RASS evaluation process of the first embodiment to evaluate the patient's RASS scale and the RASS scale group (S504).

[0100] As an example, the control unit 100 evaluates the patient's RASS scale group, and if the RASS scale group is evaluated as the high RASS group, it switches the device to restricted mode (S508). On the other hand, if the patient's RASS scale group is not the high RASS group, it switches the device to normal mode. The following embodiments are possible as examples of the selected device.

[0101] (1) Bed device 3 The operation modes of the bed device 3, such as back elevation and knee elevation. For example, if the control unit 100 evaluates that the patient is in the high RASS group, it may restrict the back elevation angle to a range that is more limited than usual (for example, while the back elevation can normally be performed from 0 to 75 degrees, the range in which the back elevation can be performed is restricted to 0 to 20 degrees).

[0102] Furthermore, when in limiting mode, the control unit 100 may deform the bottom of the bed device 3 into a flat state.

[0103] Furthermore, the control unit 100 may control the height of the bed device 3. For example, the height of the bed device 3 may be controlled to be lower in restricted mode compared to normal mode. For instance, the control unit 100 can lower the height of the bed device 3 when the patient's RASS scale group is evaluated as high RASS. The control unit 100 may also lower the height of the bed device based on the patient's activity level.

[0104] (2) Changing the threshold of the bed exit sensor For example, the control unit 100 may change the threshold at which a sensor capable of detecting when a patient has left bed (bed exit sensor) determines that the patient has left bed. For example, in restriction mode, the control unit 100 may lower the threshold to notify that even slight movements of the patient may result in them leaving bed.

[0105] (3) Range of abnormal value notification from vital sensors For example, the control unit 100 can output an alarm or call staff when a patient's biometric values ​​exceed (or fall below) a predetermined threshold. Normally, the control unit 100 notifies by outputting an alarm (for example, by displaying a warning on the screen or emitting an alarm sound), but in restricted mode, it may also send emails or push notifications via applications to staff.

[0106] Thus, this embodiment makes it possible to appropriately control other devices based on the patient's condition (RASS).

[0107] [6. Variant] This disclosure is not limited to the embodiments described above, and various modifications are possible. In other words, embodiments obtained by combining technical means that are appropriately modified within the scope of this disclosure are also included in the technical scope. Furthermore, although the embodiments described above were explained with the application to RASS for palliative care as preferred examples, they may also be applied to RASS for ICU patients, for example.

[0108] Furthermore, although the embodiments described above are explained separately for the sake of explanation, they can be combined and implemented to the extent possible. In addition, we intend to obtain rights to any of the technologies described in this specification through amendments or divisional applications.

[0109] Furthermore, in each embodiment, the program that operates in each device is a program that controls the CPU and other components (a program that makes the computer function) in order to realize the functions of the embodiments described above. The information handled by these devices is temporarily stored in a temporary storage device (for example, RAM) during processing, and then stored in various ROMs or HDDs, and read, modified, and written by the CPU as needed.

[0110] Here, the recording medium for storing the program may be any of the following: semiconductor media (e.g., ROM or non-volatile memory card), optical recording medium or magneto-optical recording medium (e.g., DVD (Digital Versatile Disc), CD (Compact Disc), BD (Blu-ray® Disc)), magnetic recording medium (e.g., magnetic tape, flexible disk), etc.

[0111] Furthermore, when distributing the program to the market, it can be stored on a portable recording medium and distributed, or transferred to a server computer connected via a network such as the Internet. In this case, the storage device of the server device is, of course, also included in this disclosure.

[0112] Furthermore, the data mentioned above may not be stored within the device itself, but rather stored on an external device and retrieved as needed. For example, the data may be stored on a NAS (Network Attached Storage) or on the cloud.

[0113] Furthermore, the scope of this disclosure is not limited to the configurations explicitly described in the specification, but also includes combinations of the technologies disclosed herein. While the configurations for which patent protection is sought are described in the attached claims, there is no intention to exclude them from the technical scope simply because they are not described in the claims.

[0114] Furthermore, the phrases "in the case of..." and "when..." in the above-mentioned specification are explained as examples only, and do not represent a configuration limited to those described. Even for configurations other than those described, we disclose information that would be obvious to a person skilled in the art, and we intend to acquire rights to such information.

[0115] Furthermore, the descriptions of the processes and data flows described in the specification are not limited to the order in which they are described. For example, configurations in which parts of the process are deleted or the order is rearranged are also disclosed, and the company intends to acquire rights to them.

[0116] Furthermore, although the functions described in the embodiments are explained as being performed by each device, they may also be implemented by a single device or by utilizing an external server.

[0117] Furthermore, each functional block or feature of the apparatus used in the embodiments described above may be implemented or executed by an electrical circuit, such as an integrated circuit or a plurality of integrated circuits. An electrical circuit designed to perform the functions described herein may include a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic device, discrete gates or transistor logic, discrete hardware components, or a combination thereof. The general-purpose processor may be a microprocessor, a conventional processor, controller, microcontroller, or state machine. The aforementioned electrical circuit may consist of digital circuits or analog circuits. Also, if advances in semiconductor technology lead to the emergence of integrated circuit technologies that replace current integrated circuits, one or more aspects of this disclosure may use new integrated circuits based on such technologies.

[0118] Furthermore, in this embodiment, the processing unit 14 outputs biological information based on the results output by the detection device 12, but the detection device 12 may calculate everything itself. Also, this can be implemented not only by installing an application on a terminal device (e.g., a smartphone, tablet, or computer), but also by, for example, processing on the server side and returning the processing results to the terminal device.

[0119] For example, the detection device 12 may upload biometric information to the server, thereby enabling the server to perform the processing described above. This detection device 12 may be implemented as a device such as a smartphone with a built-in acceleration sensor and vibration sensor. [Explanation of Symbols]

[0120] 1 System 10 Evaluation device 12 Detection device 14 Processing Unit 100 Control Unit 200 Storage section 210 storage 220 ROM 230 RAM 400 Biosignal Acquisition Unit 600 Input Section 700 Output section 800 News Department 900 Communications Department 3 beds 5 Mattresses 40 Server Devices 50 Terminal devices

Claims

1. An evaluation device comprising a biosignal acquisition unit for acquiring the patient's biosignals and a control unit, The control unit, Based on the biosignals acquired from the biosignal acquisition unit, the patient's activity level is calculated. Based on the calculated activity level, evaluate the patient's sedation scale (RASS: Richmond Agitation-Sedation Scale). Evaluation device.

2. The control unit, By comparing the activity level with the threshold, the patient's sedation scale is evaluated into a low RASS group, a medium RASS group, and a high RASS group. The evaluation apparatus according to claim 1.

3. The control unit, Based on the sedation scale, output the appropriate course of action for the patient. The evaluation apparatus according to claim 1.

4. The control unit, The sleep state of the aforementioned patient is obtained, Output a sleep diary including the patient's sleep state and the sedation scale. The evaluation apparatus according to claim 1.

5. A sheet-like detection device placed beneath the patient to detect the patient's body movements, A calculation device that calculates the patient's activity level from the aforementioned body movements, An evaluation device that evaluates the patient's sedation scale (RASS: Richmond Agitation-Sedation Scale) based on the activity level, An evaluation system that includes this.

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