Chest compression assistance device, chest compression assistance system, chest compression assistance method, and chest compression assistance program
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Filing Date
- 2026-03-13
- Publication Date
- 2026-06-30
Abstract
Description
Chest compression support device, chest compression support system, chest compression support method, and chest compression support program
[0001] The present invention relates to a chest compression assist device, a chest compression assist system, a chest compression assist method, and a chest compression assist program, and in particular to a chest compression assist device, a chest compression assist system, a chest compression assist method, and a chest compression assist program that can determine the quality of chest compressions at emergency scenes and assist practitioners in improving their chest compressions.
[0002] In emergency situations, prompt CPR is required for patients in cardiac arrest. However, because only a small percentage of emergency patients in cardiac arrest return to normal life, ensuring the quality of CPR is crucial, in addition to ensuring reliable implementation. To ensure this quality, proper chest compressions are essential. However, only a limited number of people fully understand their importance and can perform them appropriately at emergency situations. In fact, it has been pointed out that the quality of CPR may be insufficient, even among emergency medical personnel.
[0003] Therefore, various support technologies for appropriately performing cardiopulmonary resuscitation have been proposed, such as a cardiopulmonary resuscitation training device, a cardiopulmonary resuscitation support system, and a vehicle (see Patent Document 1) that enable more practical cardiopulmonary resuscitation training tailored to the attributes of each patient.
[0004] The technology described in Patent Document 1 relates to a cardiopulmonary resuscitation training device that includes a simulated body provided with a display unit capable of displaying images, an attribute acquisition unit that acquires attributes of a patient, and a display control unit that displays the appearance and pressure points of the patient on the display unit of the simulated body based on the attributes acquired by the attribute acquisition unit.
[0005] Also proposed is a technology (see Patent Document 2) that provides real-time feedback on the quality of chest compressions and / or how to modify chest compressions to more effectively perform CPR (cardiopulmonary resuscitation) and assist rescuers or first responders, or multiple first responders.
[0006] The technology described in Patent Document 2 relates to a cardiopulmonary resuscitation monitoring device that is capable of measuring selected parameters (depth of chest compressions applied to a patient and frequency of chest compressions applied to a patient) when cardiopulmonary resuscitation is performed on a patient in need of cardiopulmonary resuscitation, providing values of the measurements in real time, and providing a method for evaluating the parameters and correcting any problems.
[0007] Japanese Patent Application Laid-Open No. 2023-124693 Japanese Patent Application Laid-Open No. 2023-540410
[0008] As previously mentioned, even among trained medical professionals, the quality of chest compressions varies widely. Therefore, to increase the chances of patient survival and rehabilitation, it is necessary to ensure the quality of chest compressions at emergency scenes. While prior art has suggested the concept of providing feedback on the quality of cardiopulmonary resuscitation, it is difficult to say that it is sufficiently effective in ensuring the quality of chest compressions. This is because the quality of chest compressions is not judged from the perspective of ensuring blood flow to vital organs (especially the brain), which is the primary purpose of chest compressions, but is limited to a superficial physical phenomenon, such as how far the practitioner's hands press down on the patient's sternum. Furthermore, it is difficult to accurately measure such physical phenomena at emergency scenes, which results in unstable assessments of the quality of chest compressions.
[0009] Therefore, the present invention has been made in consideration of the above-mentioned problems, and its purpose is to provide a chest compression assist device, a chest compression assist method, a chest compression assist system, and a chest compression assist program that can judge the quality of chest compressions at the scene of an emergency and assist practitioners in improving their chest compressions.
[0010] The above-mentioned problems are solved by the chest compression assist device of the present invention, which supports the optimization of chest compressions for a patient at the scene of an emergency, and includes a processor, an output unit, and a sensor that measures a biological phenomenon in the patient's artery or a physical phenomenon derived from the biological phenomenon, wherein the processor acquires measured values related to the artery from the sensor and estimates blood pressure or an index related to blood pressure in the artery by applying the measured values to a predetermined algorithm, and performs output control in the output unit according to the estimated blood pressure or the index. The chest compression assist device of the present invention has the above-mentioned configuration and executes a series of processes to determine the quality of chest compressions at the scene of an emergency and support the practitioner in improving the chest compressions.
[0011] In the chest compression assist device, the sensor preferably measures a pulse wave, which is a biological phenomenon occurring in the artery, or pressure, acceleration, or sound, which are physical phenomena resulting from the pulse wave. The processor preferably acquires a measurement value of the pulse wave, pressure, acceleration, or sound measured in the artery from the sensor, applies the measurement value to the algorithm, and estimates the blood pressure or a blood pressure-related index in the artery. The processor then controls the output of the output unit based on the estimated blood pressure or the index. This configuration enables estimation of a patient's blood pressure from various perspectives, not just the pulse wave. This allows, for example, selective application of a sensor that is technically and cost-effectively applicable depending on the situation, leading to efficient estimation of blood pressure, etc. This ultimately facilitates estimation of a patient's cerebral perfusion status under various environments.
[0012] In the chest compression assist device, the processor preferably acquires measurement values for different parts of the artery from the sensor, determines a time difference between the appearance of a specific value between the measurement values, and applies the time difference to the algorithm to estimate the blood pressure or a blood pressure-related index in the artery, and controls the output of the output unit in accordance with the estimated blood pressure or blood pressure-related index. This configuration enables measurements to be taken by the sensor at two locations on the artery, spaced a predetermined distance apart, and blood pressure and other parameters to be estimated based on the measurements. The estimation here is based on the correspondence between the so-called pulse transition time (PPT) and the blood pressure value in the artery.
[0013] In the chest compression assist device, the processor preferably controls the light emission of the output unit to a color or intensity determined according to the magnitude of the blood pressure or blood pressure-related indicator. This configuration allows emergency personnel at the scene of an emergency to easily visually recognize the real-time blood pressure level generated or increased in the patient's arteries due to chest compressions. The patient's blood pressure level fluctuates depending on the quality of the chest compressions and corresponds to the amount of blood flow from the arteries to the organs. This allows the personnel to quickly correct their own chest compressions based on the essential quality of their own chest compressions. This ultimately enables the quality of chest compressions at the scene of an emergency to be assessed, enabling more efficient support for appropriate improvement of the personnel's chest compressions.
[0014] In the chest compression assist device, the processor preferably displays the blood pressure or a blood pressure-related index value on the output unit. This configuration allows a medical practitioner at an emergency scene to visually recognize real-time values, such as blood pressure, generated or increased in the patient's arteries due to chest compressions. These values, such as the patient's blood pressure, fluctuate depending on the quality of the chest compressions and correspond to the amount of blood flow from the arteries to the organs. Therefore, a medical practitioner who can specifically recognize these values can more easily make prompt corrections based on the essential quality of their own chest compressions. This ultimately enables the quality of chest compressions at an emergency scene to be assessed, enabling more efficient support for medical practitioners in making appropriate improvements to their chest compressions.
[0015] In the chest compression assist device, it is also preferable that the processor controls the output of sound at regular time intervals from the output unit. This configuration allows a practitioner performing chest compressions at an emergency scene to recognize the appropriate timing and pace of chest compressions without shifting their gaze to the output unit, etc. This allows the practitioner to more easily and reliably optimize the timing and pace of chest compressions. This ultimately makes it possible to assess the quality of chest compressions at an emergency scene and more efficiently support the practitioner in making appropriate improvements to their chest compressions.
[0016] In addition, in the chest compression assist device, the processor preferably has an estimation model that learns the relationship between the measurement values of the artery and the arterial blood pressure or a blood pressure-related index, and estimates the arterial blood pressure or a blood pressure-related index of the patient by applying the measurement values of the patient to the estimation model. This configuration makes it possible to adopt and use an estimation model for blood pressure, etc., based on deep learning or the like, which uses as training data the correspondence between blood pressure, etc., observed for many people or on many measurement occasions and the measurement values. This leads to efficient estimation of each patient's blood pressure, etc., based on appropriate universal trends and standards. Ultimately, it is possible to assess the quality of chest compressions at emergency scenes and support practitioners in improving their chest compressions.
[0017] In addition, in the chest compression assist device, the processor preferably has an estimation model that learns the relationship between the time difference between the measurement values for different parts of the artery and the arterial blood pressure or a blood pressure-related index, and estimates the arterial blood pressure or a blood pressure-related index of the patient by applying the time difference identified for the patient to the estimation model. This configuration makes it possible to adopt and use a blood pressure estimation model based on deep learning or the like, using as training data the correspondence between blood pressure, etc., observed for many people or on many measurement occasions and the time difference. This leads to efficient estimation of each patient's blood pressure, etc., based on appropriate universal trends and standards. Ultimately, it is possible to assess the quality of chest compressions at emergency scenes and support practitioners in improving their chest compressions.
[0018] Furthermore, in the above-mentioned chest compression assist device, it is preferable that the device is communicably connected to another sensor, which is one of an electrocardiogram sensor that measures an electrical potential derived from the heart of the patient, a pressure sensor that measures pressure associated with chest compressions on the patient, an acceleration sensor that measures acceleration associated with chest compressions on the patient, and a sound sensor that measures blood flow sounds associated with chest compressions on the patient, and that the device estimates blood pressure in the artery by identifying the time difference between the waveform indicated by the measurement value of the other sensor and the pulse wave, based on the measurement value obtained from the other sensor and the measurement value obtained from a pulse wave sensor that measures the pulse wave in the artery, and applying the time difference to the algorithm. According to the above configuration, when estimating the arterial blood pressure of a patient, for example, a blood pressure estimation based on the time lag between the pulse wave and electrocardiogram data (measured values by an electrocardiogram sensor), between the pulse wave and the pressure value (measured values by a pressure sensor) or acceleration value (measured values by an acceleration sensor) of chest compressions, or between the pulse wave and the volume of blood flow sounds (measured values by a sound sensor) can be additionally performed, thereby correcting the blood pressure estimation result based solely on the pulse wave. This correction can be performed, for example, by averaging the blood pressure estimation result based solely on the pulse wave with the blood pressure estimation result based on the pulse wave and the electrocardiogram data, or by averaging the blood pressure estimation result based solely on the pulse wave with the pulse wave and the pressure, acceleration, or volume. Alternatively, the blood pressure estimation result based on the time lag between the pulse wave and the electrocardiogram data or the pressure, acceleration, or volume of chest compressions can be used as the patient's blood pressure. By adopting this method of estimating blood pressure based on measurements from multiple types of sensors, it is possible to determine the quality of chest compressions at emergency scenes and more efficiently support practitioners in improving their chest compressions.
[0019] In the chest compression assist device, the sensor is preferably attached to an artery between the patient's specific organ and the heart to measure the biological or physical phenomenon in the artery. This configuration enables immediate observation of how blood flow to an important organ (e.g., the brain) is restored by chest compressions at an emergency scene. Blood pressure affects vascular stiffness, which in turn affects the magnitude of blood flow velocity (the smaller the time difference between the appearance of characteristic values between pulse waves, the greater the blood flow velocity). Therefore, if blood pressure estimation reveals that the blood pressure in the artery is at an appropriate level, it can be estimated that blood flow in the artery is reaching the target organ appropriately. This can lead to improvements in chest compressions that take into account the maintenance of the target organ's function. Ultimately, the quality of chest compressions at an emergency scene can be assessed, enabling support for improving chest compressions by practitioners.
[0020] The chest compression assist device preferably includes a circuit board mounting the processor, the output unit, and the sensor, and an adhesive sheet integral with one surface of the circuit board for attaching the circuit board to the patient's skin, the sensor being an element on the circuit board that performs measurements on the artery. This configuration allows the chest compression assist device to be easily and non-invasively attached to the skin in accordance with the location of the patient's artery. Attaching the chest compression assist device to a patient requires difficult installation conditions, such as an emergency scene and an immobile patient. However, the chest compression assist device configured as described above allows for quick attachment to the appropriate position desired by the operator via the adhesive sheet. This facilitates rapid initiation of appropriate blood pressure estimation. This ultimately allows for more rapid assessment of the quality of chest compressions at the emergency scene, enabling more efficient support for improving chest compressions by the operator. The circuit board is made of a resin or elastic material with appropriate flexibility and plasticity, and includes the processor, output unit (display and speaker), and a battery and various wiring necessary for operating and processing data from the sensors. Furthermore, if the sensor is a pulse wave sensor and the elements constituting it emit light to the skin (e.g., near-infrared light with a wavelength of 660 to 940 nm) and receive light reflected from the blood flow in the subcutaneous artery in response to the emitted light, excessive strain on the patient's body can be avoided during attachment and measurement.
[0021] In the chest compression assist device, it is also preferable that the circuit board and the adhesive sheet have a tactile opening that penetrates the center of each and exposes the patient's skin. This configuration allows emergency personnel to palpate the throat of a patient wearing the chest compression assist device to check for the presence or absence of a heartbeat and whether it has resumed. This allows emergency personnel performing chest compressions to check the patient's blood pressure and other information, as well as the heartbeat by touch.
[0022] The above-mentioned problem can be solved by a chest compression assist system of the present invention, which supports the optimization of chest compressions for a patient at the scene of an emergency, and includes a processor, an output unit, and a sensor that measures a biological phenomenon in the patient's artery or a physical phenomenon derived from the biological phenomenon, wherein the processor acquires a measurement value of the artery from the sensor and estimates blood pressure or an index related to blood pressure in the artery by applying the measurement value to a predetermined algorithm, and controls the output unit in accordance with the estimated blood pressure or the index. The above-mentioned chest compression assist system can assess the quality of chest compressions at the scene of an emergency and support the practitioner in improving their chest compressions.
[0023] Furthermore, the above-mentioned problem is solved by a chest compression assist method of the present invention, in which a chest compression assist device that supports the optimization of chest compressions for a patient at the scene of an emergency comprises a processor, an output unit, and a sensor that measures a biological phenomenon in the patient's artery or a physical phenomenon derived from the biological phenomenon, and the processor executes the following processes: acquiring a measurement value of the artery from the sensor, estimating blood pressure or an index related to blood pressure in the artery by applying the measurement value to a predetermined algorithm, and controlling the output of the output unit in accordance with the estimated blood pressure or the index. The above chest compression assist method makes it possible to determine the quality of chest compressions at the scene of an emergency and to assist a practitioner in improving their chest compressions.
[0024] The above-mentioned problems can be solved by the chest compression assist program of the present invention, which executes the processes included in the chest compression assist method on a computer, and by executing the program on a computer, it is possible to assess the quality of chest compressions at the scene of an emergency and assist the practitioner in improving the chest compressions.
[0025] The chest compression assist device, chest compression assist system, chest compression assist method, and chest compression assist method of the present invention make it possible to judge the quality of chest compressions at emergency scenes and assist practitioners in improving their chest compressions.
[0026] 1 is a conceptual diagram showing an example of an implementation status of chest compression operation. FIG. 2 is a graph showing the concept of the automatic cerebral blood flow adjustment function in the relationship between blood pressure and blood flow velocity. FIG. 3 is a diagram showing an example of an application of the chest compression assist device in this embodiment. FIG. 4 is a diagram showing an example of an attachment form of the chest compression assist device in this embodiment. FIG. 5 is a diagram showing an example of an output control form of the chest compression assist device in this embodiment. FIG. 6 is a diagram showing an example of an outline structure of the chest compression assist device in this embodiment. FIG. 7 is a diagram showing an example of a hardware configuration of the chest compression assist device in this embodiment. FIG. 8 is a diagram showing an example of a control rule in this embodiment. FIG. 9 is a diagram showing an example of a procedure of the chest compression assist method in this embodiment. FIG. 10 is a diagram showing the configuration and operation concept of a pulse wave sensor (optical sensor) in this embodiment. FIG. 11 is a diagram showing an example of a configuration of a chest compression assist system in this embodiment. FIG. 12 is a diagram showing an application example of the chest compression assist device in this embodiment. FIG. 13 is a graph (part 1) showing a conceptual example of pulse wave propagation time in this embodiment. FIG. 14 is a diagram showing another application example of the chest compression assist device in this embodiment. FIG. 15 is a graph (part 2) showing a conceptual example of pulse wave propagation time in this embodiment. FIG. 16 is a diagram showing an example of an output control form in this embodiment. FIG. 17 is a diagram showing an example of a hardware configuration of the chest compression assist device in another embodiment. FIG. 18 is a diagram showing an application example of the chest compression assist device in another embodiment. 10 is a graph (part 3) showing an example of a pulse wave waveform in another embodiment. FIG. 11 is a diagram showing an example of a procedure of a chest compression assist method in another embodiment.
[0027] <<Regarding a Chest Compression Assist Device According to One Embodiment of the Present Invention>> A chest compression assist device, a chest compression assist system, a chest compression assist method, and a chest compression assist program according to one embodiment of the present invention (hereinafter referred to as the present embodiment) will be described below with reference to the accompanying drawings. However, the embodiment described below is merely an example provided to facilitate understanding of the present invention and does not limit the present invention. In other words, the present invention may be modified or improved from the embodiment described below without departing from the spirit of the present invention. Naturally, the present invention also includes equivalents thereof.
[0028] Furthermore, the output examples shown in the drawings referenced in the following description are merely examples, and the configuration example of the output content, the content of the output information, and the GUI (Graphical User Interface), etc., can be freely designed according to the system design specifications and user preferences, and can also be changed as appropriate.
[0029] In addition, in this specification, the term "device" refers not only to a single device that performs a specified function on its own, but also to a combination of multiple devices that are separate from each other but work together to perform a specified function.
[0030] Alternatively, a processor may be used that realizes the entire chest compression assist device including each function on a single IC (Integrated Circuit) chip, such as a SoC (System on Chip), etc. The hardware configuration of the various processors described above may be an electric circuit (circuitry) that combines circuit elements such as semiconductor elements.
[0031] In the following explanation, we will assume a situation in which chest compressions, a type of cardiopulmonary resuscitation, are performed on an emergency patient who has gone into cardiac arrest outside a hospital. The practitioners performing chest compressions on the patient may include doctors, nurses, emergency medical personnel, and general non-medical personnel such as the patient's family. Furthermore, the location where the patient went into cardiac arrest is not limited to outside a hospital, but may also include cases within a hospital. Figure 1 shows the situation in which the practitioner performs chest compressions on the patient.
[0032] <Concept of Chest Compression Quality> As shown in Figure 1, assume that an emergency patient 1 is lying face up on the ground, a bed, a stretcher, or the like, with a therapist 10 kneeling next to the patient's chest 4. The therapist 10 places his or her hands 11 on top of each other and presses them against the patient's 1 chest 4 (around the lower half of the sternum). With his or her arms straight, the therapist 10 repeatedly compresses the chest 4 with his or her hands 11 on top of each other so that his or her weight is applied vertically from above to below the patient's 1 chest 4. This repeated compression causes the patient's 1 chest 4 to continuously sink and release (return to its original position).
[0033] Current guidelines recommend that such compressions be performed continuously (e.g., without a break of 10 seconds or more) at a predetermined speed (e.g., 100-120 compressions per minute) and depth (e.g., 5-6 cm). Performing appropriate chest compressions like these may ultimately lead to the patient's 1 returning to normal heartbeat. However, to further increase this possibility, it is necessary to check whether the blood pressure in the patient's 1 arteries is recovering to an appropriate level through chest compressions, i.e., to confirm the degree of recovery of blood flow, and then immediately modify the chest compressions based on the results of this check.
[0034] In this embodiment, good quality chest compressions are defined as those that lead to the recovery of blood pressure and blood flow, regardless of superficial phenomena such as the depth to which the chest 4 sinks. Note that the "condition of blood flow recovery" refers to whether or not the blood flow rate has recovered to a reference value along with the recovery of blood pressure, or to what extent.
[0035] The relationship between blood pressure and blood flow velocity in the human body is shown in Figure 2. Figure 2 is graph G1 (K. Spengos, G. Tsivgoulis, and N. Zakopoulos, "Blood Pressure Management in Acute Stroke: A Long-Standing Debate," European Neurology, vol. 55, no. 3, pp. 123-135, June 2006, doi: 10.1159 / 000093212.) that illustrates the concept of cerebral blood flow autoregulation in relation to blood pressure and blood flow velocity. As shown in graph G1, when blood pressure reaches a certain range (approximately 60 mmHg to 160 mmHg), cerebral blood flow velocity is also maintained at a constant appropriate level (approximately 50 ml / 100 g / min). In other words, if blood pressure can be increased to an appropriate level by chest compression, the blood flow in the patient's brain is more likely to recover to a satisfactory level. The inventors of the present application have focused on the essence of chest compression and have been researching and developing a chest compression assist device that is not available in the prior art. The following describes the specific configuration of the chest compression assist device in this embodiment.
[0036] <Chest Compression Assist Device and Its Usage> Next, an overview of the chest compression assist device 20 according to this embodiment and its usage will be described. FIG. 3 is a diagram showing an application example of the chest compression assist device 20 according to this embodiment, and FIG. 4 is a diagram showing an example of how the chest compression assist device 20 according to this embodiment is attached. The chest compression assist device 20 is attached by a practitioner 10, such as a paramedic, to a patient 1 lying down at the scene of an emergency. A typical example of the attachment position is assumed to be the neck 2. As shown in FIG. 4, the neck 2 is home to a pair of carotid arteries 3, one on the left and one on the right, which extend from the heart in the chest 4 toward the head of the patient 1. Therefore, by estimating the blood pressure in the carotid arteries 3, the state of blood flow resumed to the brain by chest compression can be interpreted as the quality of the chest compression.
[0037] In this embodiment, the carotid artery 3 is used as an example of the attachment position of the chest compression assist device 20, but other arteries may also be used as appropriate. Such arteries include the forehead and earlobes of the patient 1, where attachment of the chest compression assist device 20 is not obstructed by hair or other factors.
[0038] Therefore, the practitioner 10 presses his / her hand 11 against the chest 4 of the patient 1 and presses downward to perform chest compressions. By continuing this chest compression, as is known from the so-called thoracic pump theory (the theory that chest compressions increase intrathoracic pressure, resulting in cardiac output) and the cardiac pump theory (the theory that chest compressions physically compress the heart between the sternum and spine, resulting in cardiac output), it is believed that cardiac output gradually increases and one-third to one-quarter of the normal amount of blood is supplied to the brain.
[0039] The chest compression assist device 20 continuously estimates the blood pressure associated with the blood supply from the carotid artery 3 to the brain. Based on the estimation results, the chest compression assist device 20 controls the light emission, audio output, or numerical display of the output unit 23. Details of the control of the output unit 23 will be described later. The surface of the chest compression assist device 20, excluding the output unit 23, is covered with a cover body 21, and is structured to have a tactile window 22 in the center. The tactile window 22 is an opening that allows a practitioner 10 performing chest compressions, such as a doctor or emergency medical technician, to palpate the pulse of the emergency patient 1 near the carotid bifurcation.
[0040] The control of light emission and the like in the output unit 23 may employ, for example, control content such as emitting light in a color corresponding to the magnitude of the estimated blood pressure value. For this purpose, the chest compression assist device 20 stores a control rule 263 (described later with reference to Figures 7 and 8 ) that defines the light emission color for each range of blood pressure values. In this case, the chest compression assist device 20 checks the estimated blood pressure value against this control rule 263 to determine the light emission color and instructs the output unit 23 to emit light in that color. Since this control of the light emission color is performed each time blood pressure is estimated, as shown in Figure 5, the output form is such that different colors (or the same color) are displayed on the output unit 23 at each blood pressure estimation timing, and various colors appear to flash repeatedly over time.
[0041] The light emission control may be performed not only on color but also on light intensity. In this case, the chest compression assist device 20 determines the light emission intensity of the output unit 23 by comparing the waveform of the pulse wave, i.e., the magnitude of the potential, observed by the pulse wave sensor 29 (see Figures 6 and 7, etc.), rather than the estimated blood pressure, with the control rule 263, and emits light at that intensity. The practitioner 10 can clearly recognize the blood pressure from the color and can learn the fluctuations of the pulse wave from changes in the intensity of the light. The chest compression assist device 20 also periodically determines whether the pulse wave observation results satisfy the return of spontaneous circulation criteria. If it determines that the patient 1 has returned spontaneous circulation, it displays a message indicating return of spontaneous circulation on the display 23A (described below with reference to Figure 7) of the output unit 23 or outputs a sound from the speaker 23B (described below with reference to Figure 7).
[0042] The chest compression assist device 20 can not only control the light emission but also control the sound output from the output unit 23. In this case, the chest compression assist device 20 outputs a buzzer sound from the output unit 23 once every 0.5 to 0.6 seconds, which is considered to be an appropriate tempo for chest compressions.
[0043] The chest compression assist device 20 can also control the display of the estimated blood pressure value on the output unit 23, which is composed of a display 23A. In this case, the chest compression assist device 20 displays the blood pressure value at each blood pressure estimation timing on the output unit 23. Of course, in addition to displaying such a numerical value, the output of the light emission and buzzer sound may also be controlled.
[0044] <Structure of Chest Compression Assist Device> Next, the specific structure of the chest compression assist device 20 in this embodiment will be described. Fig. 6 is a diagram showing an example of the outline structure of the chest compression assist device 20 in this embodiment. The chest compression assist device 20 shown in Fig. 6 is mainly composed of a cover body 21, a circuit board 25, and an adhesive sheet material 31. The cover body 21 is a member that covers the upper surface of the circuit board 25, and can be made of a rubber material or a resin material that has the same flexibility and plasticity as the circuit board 25. The cover body 21 has two openings: an opening 24 that exposes the output unit 23 provided on the circuit board 25, and a tactile window 22 that allows the practitioner 10 to palpate the pulsation of the carotid artery 3.
[0045] The circuit board 25 is a board on which the output unit 23 is mounted on the upper surface and the pulse wave sensor 29 is mounted on the lower surface. In addition, a memory unit 26, a processor 27, and a communication unit 28 are mounted, for example, in the form of chips on the upper surface and are covered with the cover body 21. The circuit board 25 also has a board opening 30 for the tactile window 22.
[0046] Here, a pulse wave sensor 29 is used as an example of a sensor. The pulse wave sensor 29 is located on the lower surface of the circuit board 25 and is composed of pulse wave sensors 29A and 29B, which are a pair of elements 29X and 29Y that respectively emit and receive light for the pair of carotid arteries 3. When observing a pulse wave in either the left or right carotid artery 3 in the neck region 2, only one of the pulse wave sensors 29A and 29B illustrated in FIG. 7 may be used. Similarly to the cover body 21, the circuit board 25 is composed of a rubber or resin material with appropriate flexibility and plasticity. In addition to the pulse wave sensor 29, various sensors (e.g., pressure sensors, acceleration sensors, sound-collecting microphones) may be used to measure physical phenomena resulting from pulse waves in various arteries, such as the carotid artery 3, such as pressure and acceleration generated on the skin of the patient 1 due to pulsation in a subcutaneous artery, or blood flow sounds generated by blood flow in the artery.
[0047] The adhesive sheet material 31 is a sheet material that is integrated with the lower surface of the circuit board 25 and adheres the circuit board 25 to the skin of the patient 1. Like the circuit board 25 and the cover body 21, the adhesive sheet material 31 is made of a material with appropriate flexibility and plasticity, and its surface is coated with an adhesive. If a pulse wave sensor 29 is used as the sensor, the adhesive sheet material 31 is made of an appropriate optically transparent resin material so as not to interfere with the light-emitting and light-receiving operations of the light-emitting and light-receiving elements 29X, 29Y. Alternatively, the adhesive sheet material 31 may have openings for exposing the light-emitting and light-receiving elements 29X, 29Y of the pulse wave sensor 29.
[0048] <Hardware configuration of circuit board> Next, the hardware configuration of the circuit board 25 in the chest compression assist device 20 will be described. Fig. 7 is a diagram showing an example of the hardware configuration of the circuit board 25 in this embodiment. Note that the circuit board 25 in this embodiment may be configured as a single computer as shown in the figure, or may be configured as multiple computers distributed in parallel. Alternatively, the chest compression assist device 20 may be configured as a computer for an ASP (Application Service Provider), SaaS (Software as a Service), PaaS (Platform as a Service), or IaaS (Infrastructure as a Service).
[0049] Here, assuming that the circuit board 25 in this embodiment is configured as a stand-alone computer, Figure 7 shows a configuration in which the circuit board 25 has an output unit 23, a memory unit 26, a processor 27, a communication unit 28, and a pulse wave sensor 29 connected by a bus within the circuit.
[0050] Of the above components, the output unit 23 is implemented by a display 23A and a speaker 23B. The display 23A is a display device that displays estimated blood pressure values and emits light or displays messages corresponding to those values. This display 23A is assumed to be, for example, a small liquid crystal display unit. The speaker 23B is an audio output device that outputs a buzzer sound at regular intervals and an audio message indicating return of spontaneous circulation. The display control on the display 23A and the audio output control on the speaker 23B are executed by the processor 27.
[0051] The storage unit 26 may be configured with volatile semiconductor memory such as a read-only memory (ROM) and a random access memory (RAM). The storage unit 26 in this embodiment stores a program 261 including an operating system (OS), a blood pressure estimation model 262, and a control rule 263. The OS controls the circuit board 25 itself and implements basic functions. Under its control, the processor 27 calls and executes each part of the program 261, thereby implementing each function corresponding to the chest compression assist method.
[0052] Depending on the size and configuration of the chest compression assist device 20, it is possible to use a storage device or storage medium such as a hard disk drive (HDD), solid state drive (SSD), flash memory, flexible disk (FD), magneto-optical disk (MO disk), compact disk (CD), digital versatile disk (DVD), secure digital card (SD card), or universal serial bus memory (USB memory) as the storage unit 26. The storage unit 26 may be mounted on the surface of the circuit board 25 or may be externally connected to the circuit board 25.
[0053] The processor 27 may be configured by a CPU (Central Processing Unit), an MPU (Micro-Processing Unit), an MCU (Micro Controller Unit), a GPU (Graphics Processing Unit), a DSP (Digital Signal Processor), a TPU (Tensor Processing Unit), an ASIC (Application Specific Integrated Circuit), etc. The processor 27 calls up and executes the program 261 from the storage unit 26, thereby implementing the functions required for the chest compression assist device 20.
[0054] The program 261 includes a blood pressure estimation model 262 for estimating blood pressure. This blood pressure estimation model 262 is, for example, a model generated by a deep learning engine or the like in a separate management PC (personal computer). In generating such a model, the deep learning engine uses as training data the correspondence between actual blood pressures (e.g., actual values measured with a sphygmomanometer) observed for many people or on many measurement occasions and pulse waves, pressures, accelerations, and sound waveforms observed for the person's arteries. Alternatively, the blood pressure estimation model is trained using as training data the correspondence between the time differences between peak values of pulse waves observed at multiple locations in the person's arteries.
[0055] By inputting pulse wave waveforms or differences in the times at which peak values of each pulse wave appear, obtained for example by the pulse wave sensor 29, at one or more locations on a person to the learned blood pressure estimation model 262, an estimated blood pressure value for that person is output. The PC sets the blood pressure estimation model 262 generated as described above in the chest compression assist device 20 via an appropriate network N, for example, and implements the blood pressure estimation function in the chest compression assist device 20.
[0056] In this embodiment, the blood pressure transition is measured using the blood pressure estimation model 262 as described above, but the blood pressure estimation method is not limited to this. For example, a blood pressure estimation formula can be assumed in which the blood pressure value in the carotid artery 3 is used as the output and the time difference between the peak values observed in the carotid artery 3 of the patient 1 is used as a variable. Such a formula can be, for example, a regression formula obtained by performing a regression analysis on the correspondence between the actual blood pressures (e.g., actual values measured with a sphygmomanometer) observed for many people or on many measurement occasions and the time difference between the peak values observed at each location in the artery of the person. In this case, the chest compression assist device 20 stores the regression formula in the memory unit 26 instead of the blood pressure estimation model 262 and performs blood pressure estimation using this formula.
[0057] Furthermore, for example, when the network N connecting the PC and other external sensors (sensors other than the pulse wave sensor 29) is configured with a wireless LAN, the communication unit 28 is assumed to be a network interface card compatible with a wireless AN protocol based on Wi-Fi (registered trademark). However, as another implementation form, when the network N is a 3G to 5G or later generation mobile communication network, the communication unit 28 can also be assumed to be a communication chipset compatible with such a mobile communication protocol or the LTE (Long Term Evolution) protocol.
[0058] As already mentioned, the pulse wave sensor 29 is provided on the lower surface of the circuit board 25 and is composed of pulse wave sensors 29A, 29B, which are a pair of elements 29X, 29Y that emit and receive light for one or both of the pair of carotid arteries 3. While an optical sensor is used as the pulse wave sensor 29, the present invention is not limited to this, and a sensor that monitors pulse waves by observing other events may also be used. The pulse wave sensor 29 is merely one example of a sensor, and the pressure, acceleration, and sound sensors already mentioned may be used instead of or in combination with the pulse wave sensor 29.
[0059] <Output Control Rules> Next, the output control rules held by the chest compression assist device 20 in this embodiment will be described with reference to Fig. 8. Fig. 8 is a diagram showing an example of a control rule 263 in this embodiment. The control rule 263 in this embodiment is a table that stores various criteria for the chest compression assist device 20 to control light emission and audio output in the output unit 23. The information stored here is set by a predetermined administrator (for example, a person who manages the chest compression assist device 20 in a medical institution, etc.).
[0060] The data structure is a collection of records containing information such as events and rules, with a rule ID as a key. Among these, the rule ID is an ID that can uniquely identify the rule. The event is an event that serves as the basis for control of the output unit 23, and is assumed to be blood pressure or pulse wave. The rule specifies the control content of the output unit 23 that should be performed depending on the situation (case) of the event.
[0061] 8, the rule specifies, for example, the following content for the event "blood pressure": "light color: red" for case 1 "blood pressure value: ** mmHg or less," "light color: yellow" for case 2 "blood pressure value: ** mmHg to ** mmHg," and "light color: green" for case 3 "blood pressure value: ** mmHg or more." Also, for the event "pulse wave," the rule specifies, for case 1 "electric potential: **," "light intensity: weak," for case 2 "electric potential: ***," "light intensity: medium," and for case 3 "electric potential: **," "light intensity: strong."
[0062] Of course, these definitions are merely examples, and the present invention can also be applied to other events and control contents. For example, with respect to the event "blood pressure," it is possible to assume the following definitions: Case 1: "blood pressure value: ** mmHg or less," "output audio frequency: low," Case 2: "blood pressure value: ** mmHg to ** mmHg," "output audio frequency: medium," and Case 3: "blood pressure value: ** mmHg or more," "output audio frequency: high." Or, with respect to the event "pulse wave," it is possible to assume the following definitions: Case 1: "electric potential: **," "light emission frequency: low," Case 2: "electric potential: ***," "light emission frequency: medium," and Case 3: "electric potential: **," "light emission frequency: high."
[0063] <Chest Compression Assist Flow> Next, an example of the flow of the chest compression assist method according to this embodiment will be described. In the following description, for the purpose of making the explanation easier to understand, an example of chest compression assist according to this embodiment will be assumed in which a certain patient 1, as already mentioned, is the target of chest compression treatment, and blood pressure is estimated by observing pulse waves at multiple locations on the carotid artery 3 of this patient 1. The chest compression assist method according to this embodiment proceeds, for example, according to the flow shown in Fig. 9. Fig. 9 is an example of the procedure of the chest compression assist method according to this embodiment, and is a flow chart sequentially showing the processing contents in the chest compression assist device 20, starting from the action of a practitioner 10, such as a paramedic.
[0064] In this flow, first, the practitioner 10 attaches the chest compression assist device 20 to the neck 2 of the patient 1 (S1). This attachment is performed by the practitioner 10 by attaching the adhesive sheet material 31 of the chest compression assist device 20 to the skin of the neck 2 of the patient 1. This attachment is performed so that the pulse wave sensor 29 abuts the carotid artery 3 of the neck 2. More specifically, for example, the pulse wave sensor 29A can be placed on the upstream side of the carotid artery 3 (closer to the heart) and the pulse wave sensor 29B can be placed on the downstream side (closer to the brain) of the carotid artery 3. At this time, the angle and position of attachment must be adjusted so that the pharyngeal region of the neck 2 (the so-called Adam's apple) is exposed through the tactile window 22 of the chest compression assist device 20.
[0065] Once the chest compression assist device 20 has been attached to the emergency patient 1 as described above, the practitioner 10 begins chest compressions on the chest 4 of the patient 1 (S2). This action involves the practitioner 10 repeatedly compressing the chest 4 of the patient 1 from top to bottom with the hands 11 of the practitioner 10 overlapping each other. Each time this compression is repeated, blood flows from the heart inside the chest 4 for a short period of time. In other words, blood pulsation occurs. The chest compression assist device 20 observes pulse waves corresponding to this blood pulsation with the pulse wave sensor 29 (S3) and performs blood pressure estimation based on the observation results (S4).
[0066] FIG. 10 shows the configuration and operation concept of the pulse wave sensor 29 (optical sensor) of this embodiment. As described above, the blood flow generated with each chest compression (see FIG. 10 ) becomes a short-duration pulse wave corresponding to the compression and propagates from the heart to the carotid artery 3 and further to the brain. Meanwhile, the light-emitting element 29X in the pulse wave sensor 29 continuously emits near-infrared light that passes through the body tissue 3A (i.e., the skin) of the patient 1 and the underlying intravenous blood flow 3B to reach the carotid artery 3. Meanwhile, the light-receiving element 29Y continuously receives the near-infrared light reflected by the intraarterial blood flow 3C in the carotid artery 3, thereby obtaining an observation value related to the pulse wave of the blood flow 3C in the patient 1. As shown in FIG. 12 , these observation values are obtained from the upstream pulse wave sensor 29A near the heart and the downstream pulse wave sensor 29B near the brain.
[0067] In the blood pressure estimation process (S4), the processor 27 of the chest compression assist device 20 acquires pulse wave observation values from each of the pulse wave sensors 29A and 29B and calculates the time difference between the peak values of the two pulse wave observation values, for example. Graph G2 in Fig. 13 shows the time difference between the peak values of the two pulse waves as "Pulse Transit Time." Graph G2 in Fig. 13 is a two-dimensional graph with the horizontal axis representing time and the vertical axis representing potential, and depicts pulse waves obtained from the pulse wave sensors 29 at two locations on the carotid artery 3.
[0068] Of the two pulse waves in graph G2, pulse wave PW1 is obtained from the upstream pulse wave sensor 29A, and pulse wave PW2 is obtained from the downstream pulse wave sensor 29B. Their peak values differ in appearance time, i.e., there is a time difference, due to differences in the propagation timing of the blood flow 3C at the upstream and downstream pulse wave sensors 29. This difference in appearance time becomes smaller as the flow velocity of the blood flow 3C increases. As previously mentioned, blood pressure affects vascular stiffness, which in turn affects the magnitude of the blood flow velocity. In other words, the smaller the time difference between the appearance times of the peak values, the higher the blood pressure in the carotid artery 3. In light of this, a blood flow velocity estimation model, which serves as an index related to blood pressure, may be adopted instead of the blood pressure estimation model 262 in this embodiment. In this case, output control in the output unit 23 is performed for blood flow velocity using the same algorithm as for blood pressure. The blood flow velocity estimation model is a model that is trained using as training data the correspondence between the blood flow velocity actually measured for a predetermined number of people and the waveform of the pulse wave and the time difference between the appearance of peak values for the people at that time. Note that the blood flow velocity is an example of an index related to blood pressure, and any index related to any phenomenon may be used as long as it has a fixed correlation with blood pressure, and the model is generated and used according to the index.
[0069] The processor 27, having calculated the time difference between the appearance times of the peak values, inputs the value of this time difference into the blood pressure estimation model 262 to estimate the blood pressure of the carotid artery 3. At this time, the processor 27 determines at regular intervals whether the pulse wave observation results satisfy the ROSC criteria, and identifies whether the patient 1 has achieved ROSC. An example of the ROSC criteria is that the average value of the pulse wave (electric potential) of the carotid artery or the like remains above a certain standard. When it is determined that the ROSC has been achieved, the processor 27 displays a message indicating that the ROSC has been achieved on the display 23A of the output unit 23, or outputs it as an audio message from the speaker 23B.
[0070] Next, processor 27 compares the blood pressure value estimated in S4 with the record of the "blood" event in control rule 263 to identify the corresponding output control content and instructs output unit 23 on the control content (S5). If the blood pressure value estimated in S4 corresponds to, for example, "Case 1" specified in the record of control rule 263, processor 27 issues a red light emission instruction to display 23A of output unit 23. In response to this instruction, display 23A of output unit 23 causes its own LED (Light Emitting Diode) light-emitting unit, which has a color adjustment function, to emit red light. In addition to the cases where the light emission instruction is issued as described above, processor 27 may also control display of the blood pressure value on display 23A (see FIG. 16).
[0071] The processor 27 may also compare the pulse wave observation results obtained in S3 with the record of the "pulse wave" event in the control rule 263 to identify the corresponding output control content and instruct the output unit 23 on the control content. In this case, if the peak value level indicated by the pulse wave observation results corresponds to, for example, "Case 1" defined in the record of the control rule 263, the processor 27 notifies the display 23A of the output unit 23 of an instruction to emit light at a "weak" light intensity. In response to this instruction, the display 23A of the output unit 23 causes its own LED (Light Emitting Diode) light-emitting unit, which has an illuminance adjustment function, to emit light in a "weak" mode.
[0072] In addition, the processor 27 controls the output of sounds in parallel with the control of the display 23A. In this case, the processor 27 outputs a buzzer sound from the speaker 23B of the output unit 23 once every 0.5 to 0.6 seconds, which is considered to be the appropriate tempo for chest compressions (S6). Note that the processor 27 controls the output of this buzzer sound to immediately stop once the return of spontaneous cardiac beat is confirmed.
[0073] <Regarding Alternative Embodiment 1> In addition to the above-described configuration in which blood pressure estimation is performed using only the pulse wave sensor 29, a configuration in which a sensor that observes a different event is used in combination with the pulse wave sensor 29 can also be employed. Figure 11 shows an example of the configuration of a chest compression support system S in this embodiment. In the chest compression support system S shown here, a chest compression support device 20 is connected to a PC (Personal Computer) 60 via a network N, to which an ECG (Electrocardiogram) 40 and a pressure sensor 50 are connected. The PC 60 is an information processing device that generates a blood pressure estimation model 262 and installs it in the chest compression support device 20. The ECG 40 is an electrocardiogram sensor that obtains electrocardiogram data of the patient 1. The pressure sensor 50 measures the pressure applied to the chest 4 during chest compressions by the therapist 10 and can be assumed to be installed on the surface of the chest 4 where the therapist 10 places his / her hand 11.
[0074] For example, as shown in Fig. 14 , assume that a pressure sensor 50 is attached to the chest 4 of the patient 1. In this case, the processor 27 acquires a waveform of the pressure value acting on the chest 4, i.e., a pressure waveform, from the pressure sensor 50. Graph G3 in Fig. 15 shows the time difference between the appearance times of the peak values of the pressure waveform PW3 and the pulse wave PW4 as "Pulse Transit Time." Graph G3 shown in Fig. 15 is a two-dimensional graph with the horizontal axis representing time and the vertical axis representing potential, and depicts the pressure waveform PW3 generated by chest compressions on the chest 4 and the pulse wave PW4 measured at the carotid artery 3 in the neck 2.
[0075] The peak values of the two waveforms in graph G3, the pressure waveform PW3 observed on the upstream side and the pulse wave PW4 observed on the downstream side, differ in appearance time, i.e., there is a time difference. The faster the flow velocity of the blood flow 3C, the smaller this difference in appearance time becomes. Therefore, it can be determined that the smaller the time difference in the appearance time of the peak values, the higher the blood pressure in the carotid artery 3.
[0076] The processor 27, having calculated the time difference between the appearance times of the peak values, inputs the value of this time difference into the blood pressure estimation model 262 to estimate the blood pressure of the carotid artery 3. The blood pressure estimation model 262 used here is a model obtained by learning using training data in which the time difference between the peak values of the pressure waveform and the pulse wave is input and the actual measured value of blood pressure under the circumstances in which this time difference occurs is output. The generation of this model is also performed by the PC 60. The generation of this model and the various processes for blood pressure estimation using this model are also performed in the case in which the time difference between the peak values of the pulse wave and the electrocardiogram obtained from the ECG 40 is input.
[0077] By adopting and implementing such a configuration, when estimating blood pressure in the carotid artery 3 of the patient 1, it is possible to additionally perform blood pressure estimation based on the time difference in the appearance time of peak values between the pulse wave and electrocardiogram data, or between the pulse wave and pressure waveform, and correct the blood pressure estimation result based solely on the pulse wave. This correction can be performed, for example, by averaging the blood pressure estimation result based solely on the pulse wave and the blood pressure estimation result based on the pulse wave and electrocardiogram data, or the blood pressure estimation result based solely on the pulse wave and the blood pressure estimation result based on the pulse wave and the pressure value. By adopting such a blood pressure estimation method based on measurements from multiple types of sensors, it is possible to average out the differences in measurement accuracy between sensors and to expect an overall improvement in blood pressure estimation accuracy.
[0078] <Regarding Alternative Embodiment 2> In the above example, a configuration in which pulse waves and the like are measured at multiple locations on the carotid artery 3 has been shown. However, a configuration in which pulse waves and the like are measured at only one location on the carotid artery 3, i.e., by one pulse wave sensor 29A, and blood pressure and the like are estimated based on the measurement results can also be employed. In this case, as illustrated in Fig. 17 , the program 261 used by the chest compression assist device 20 has a blood pressure estimation model 2621 that estimates blood pressure or a blood pressure-related index from a measurement value at only one location on the carotid artery 3, or the program 261 can be externally called and used. The blood pressure estimation model 2621 is obtained by deep learning using as training data the correspondence between actual blood pressures (e.g., actual values measured with a sphygmomanometer) observed for many people or on many measurement occasions and any one of the waveforms of pulse waves, pressure, acceleration, and sound observed for that artery at the time of observation.
[0079] By providing as input to the blood pressure estimation model 2621 generated through such deep learning at one location of a person's artery (see FIG. 18 ), for example, a waveform of a pulse wave obtained by a pulse wave sensor 29A, a pressure measured by a pressure sensor, an acceleration measured by an acceleration sensor, or a sound measured by a sound-collecting microphone (see FIG. 19 ), an estimated value of the person's blood pressure is output.
[0080] Here, an example of the procedure of the chest compression assist method in this embodiment will be described with reference to Fig. 20. Fig. 20 is a diagram showing an example of the procedure of the chest compression assist method in another embodiment. Note that, among the procedures shown in Fig. 9, the processes of attaching the chest compression assist device 20 to the neck 2 of the patient 1 (S1) and starting the chest compression operation by the practitioner 10 (S2) are also performed in the same way, so descriptions of those processes will be omitted.
[0081] When the chest compression operation (S2) is repeated, blood flows from the heart inside the chest 4 for a short period of time. In other words, blood flow pulsation occurs. The chest compression assist device 20 monitors a pulse wave corresponding to this blood flow pulsation with the pulse wave sensor 29 (S3). Through this monitoring, the chest compression assist device 20 obtains the waveform of the pulse wave of the blood flow 3C in the patient 1 as an observed value. Unlike in FIG. 13, this observed value is data of a single waveform, as shown in graph G4 in FIG. 19.
[0082] Next, the processor 27 of the chest compression assist device 20 estimates the blood pressure of the carotid artery 3 by inputting the waveform data of the pulse wave into the blood pressure estimation model 2621 (S4). The waveform data input into the blood pressure estimation model 2621 may be the waveform data itself or a feature value of the waveform data. For example, the feature value may correspond to the sharpness of the rise of the peak value Pv of the waveform shown in graph G4.
[0083] Specifically, the kurtosis calculated from the magnitude of the peak value Pv among the values (electric potentials) indicated by graph G4 and the extent of the spread of values before and after the appearance of the peak value Pv can be used as an index of the sharpness of the rising edge. Note that the method for calculating the kurtosis itself may be any known method as appropriate. Of course, the kurtosis is only one example of an index indicating a feature value, and any other index may be used. The feature value relating to the sharpness of the rising edge increases as the flow velocity of the blood flow 3C increases. As already mentioned, the level of blood pressure affects the stiffness of blood vessels, and the stiffness of blood vessels affects the magnitude of the blood flow velocity. In other words, the greater the feature value of the sharpness of the rising edge, the higher the blood pressure in the carotid artery 3 can be determined to be.
[0084] Thereafter, similar to the procedure shown in Fig. 9, processor 27 identifies the content of output control according to control rule 263 based on the blood pressure value estimated in S4 and instructs output unit 23 on the content (S5). Also, similar to the procedure shown in Fig. 9, processor 27 outputs a buzzer sound once every 0.5 to 0.6 seconds, which is considered to be an appropriate tempo for chest compressions, from speaker 23B of output unit 23 (S6).
[0085] Although specific embodiments of the present invention have been described above, the above embodiments are merely examples given to facilitate understanding of the present invention and are not intended to limit the present invention. That is, the present invention may be modified or improved from the embodiments described below without departing from the spirit of the present invention. The present invention also includes equivalents thereof. Furthermore, embodiments of the present invention may include a combination of the above embodiments with one or more of the following modifications.
[0086] N Network S Chest compression support system 1 Patient (emergency patient) 2 Neck 3 Carotid artery 3C Blood flow 4 Chest 10 Practitioner 11 Hand 20 Chest compression support device 21 Cover body 22 Tactile window (tactile opening) 23 Output unit 23A Display 23B Speaker 24 Opening 25 Circuit board 26 Memory unit 261 Program 262 Blood pressure estimation model 2621 Blood pressure estimation model 263 Control rule 27 Processor 28 Communication unit 29 Pulse wave sensor 29A Pulse wave sensor 29B Pulse wave sensor 29X Light-emitting element 29Y Light-receiving element 30 Board opening 31 Adhesive sheet material 32 Sheet opening 40 ECG (Electrocardiogram) sensor 50 Pressure sensor 60 PC (Personal Computer) 65 Machine Learning Engine
Claims
1. A chest compression support device that assists in optimizing chest compressions for patients in emergency situations, A processor, an output unit, and a sensor for measuring the pulse wave in the patient's carotid artery or physical phenomena originating from the pulse wave are integrated into one unit. The sensor is composed of an element that performs measurement operations on the carotid artery, The aforementioned processor, A chest compression support device that acquires measured values related to the carotid artery from the sensor, estimates blood pressure or a blood pressure-related indicator in the carotid artery by applying the measured values to a predetermined algorithm, and performs output control in the output unit according to the estimated blood pressure or the indicator.
2. The sensor is a sensor that measures either a pulse wave, which is a biological phenomenon in the carotid artery, or pressure, acceleration, and sound, which are physical phenomena derived from the pulse wave. The aforementioned processor, The sensor acquires a measured value of pulse wave, pressure, acceleration, or sound related to the carotid artery, and by applying the measured value to the algorithm, the blood pressure or a blood pressure-related indicator in the carotid artery is estimated, and output control in the output unit is performed according to the estimated blood pressure or the indicator. The chest compression support device according to claim 1.
3. The aforementioned processor, The system obtains measurement values from the sensor for each different part of the carotid artery, identifies the time difference in the appearance of a specific value between the measurement values, applies the time difference to the algorithm to estimate blood pressure or a blood pressure-related indicator in the carotid artery, and performs output control in the output unit according to the estimated blood pressure or blood pressure-related indicator. The chest compression support device according to claim 1.
4. The aforementioned processor, The chest compression support device according to claim 1, wherein the output unit controls the emission of light of a color or intensity determined according to the magnitude of the blood pressure or an indicator related to blood pressure.
5. The aforementioned processor, The chest compression support device according to claim 1, wherein the output unit displays the value of the blood pressure or an index related to the blood pressure.
6. The aforementioned processor, The chest compression support device according to claim 1, wherein the output unit controls the output of sound at regular time intervals.
7. The aforementioned processor, The chest compression support device according to claim 1, having an estimation model that has learned the relationship between measured values relating to the carotid artery and the blood pressure or blood pressure-related indicators of the carotid artery, and estimating the blood pressure or blood pressure-related indicators of the patient by applying the measured values relating to the patient to the estimation model.
8. The aforementioned processor, The chest compression support device according to claim 3, having an estimation model that has learned the relationship between the time difference in the appearance of a specific value among the measured values for each different part of the carotid artery and the blood pressure or blood pressure-related indicator of the carotid artery, and estimating the blood pressure or blood pressure-related indicator of the patient by applying the time difference identified for the patient to the estimation model.
9. The aforementioned processor, A chest compression support device according to claim 1, which is connected in a communicable manner to one of the following other sensors: an electrocardiogram sensor for measuring cardiac potential in the patient; a pressure sensor for measuring pressure associated with chest compressions on the patient; an acceleration sensor for measuring acceleration associated with chest compressions on the patient; and a sound sensor for measuring blood flow sounds associated with chest compressions on the patient; and which estimates the blood pressure in the carotid artery by identifying the time difference between the waveform shown by the measurement from the other sensor and the pulse wave sensor for measuring the pulse wave in the carotid artery, and applying the time difference to the algorithm.
10. A circuit board on which the processor, the output unit, and the sensor are mounted, It consists of one surface of the circuit board and an adhesive sheet material that is integrated with the surface of the circuit board and attaches the circuit board to the patient's skin, The sensor is located on the circuit board and consists of an element that performs measurement operations on the carotid artery. The chest compression support device according to claim 1.
11. The circuit board and the adhesive sheet material are each provided with a tactile opening that penetrates the center of each and exposes the patient's skin. The chest compression support device according to claim 10.
12. A chest compression support system that assists in optimizing chest compression techniques for patients in emergency situations, A chest compression support device comprising a processor, an output unit, and a sensor for measuring pulse waves or physical phenomena originating from the pulse waves in the patient's carotid artery, wherein the sensor is composed of elements that perform measurement operations on the carotid artery, the processor acquires measured values of the carotid artery from the sensor, applies the measured values to a predetermined algorithm to estimate blood pressure or blood pressure-related indicators in the carotid artery, and performs output control in the output unit according to the estimated blood pressure or indicators, A chest compression support system including...
13. A chest compression support device that helps optimize chest compressions for patients in emergency situations, The system comprises a processor, an output unit, and a sensor for measuring the pulse wave in the patient's carotid artery or physical phenomena originating from the pulse wave, with the sensor being composed of elements that perform measurement operations on the carotid artery. In the aforementioned processor, The process includes: acquiring measured values of the carotid artery from the sensor; estimating blood pressure or a blood pressure-related indicator in the carotid artery by applying the measured values to a predetermined algorithm; and performing output control in the output unit according to the estimated blood pressure or indicator. A method of assisting with chest compressions.
14. A program for causing a computer to perform each of the processes included in the chest compression support method described in claim 13.