Physiological monitoring information measurement system and method

Abstract

To provide a measuring method of physiological monitoring information.SOLUTION: According to a user's operation a clinical physiological monitoring information management front-end interface programming module is activated on a mobile device, execution of the clinical physiological monitoring information management front-end interface programming module detects a first patient image, a second patient image, first patient audio of a patient, or second patient audio in real time to transmit a detected one to the clinical physiological monitoring information management back-end processing platform programming module, execution of the clinical physiological monitoring information management back-end processing platform programming module executes a non-contact / non-invasive physiological monitoring information sensoring programming module, and the patient's physiological monitoring information is acquired on the basis of one of the first patient image, the second patient image, the first patient audio and the second patient audio.SELECTED DRAWING: Figure 13

Description

[Technical Field]

[0001] The present invention relates to a physiological monitoring information measurement system and method, and in particular to a physiological monitoring information measurement system and method based on a non-contact, non-invasive physiological monitoring information measurement technology. [Background technology]

[0002] Vital signs refer to a set of external physiological characteristic parameters measured from the human body, usually including 4-6 indicators, such as body temperature, pulse or heart rate, respiratory rate, and blood pressure. These indicators not only indicate whether the human body is currently sustaining life or survival, but also provide a simple way to assess overall health and predict potential disease risks, which is particularly valuable for patients with chronic diseases. Furthermore, measuring vital signs can also indicate the progress of the human body's recovery.

[0003] In clinical practice, vital sign monitoring is very important for nursing staff. When patients require nursing care after hospitalization or surgery, nursing staff frequently measure the patient's vital signs, such as blood pressure and heart rate, to understand the patient's health status. Therefore, measuring vital signs accounts for a large proportion of nursing staff's daily work. Even simple vital sign measurement tasks can increase the workload of nursing staff.

[0004] However, with the advancement of science and technology, Internet of Things (IoT) devices are also beginning to be applied to measuring vital signs. By connecting smart sensors to a network, patients' vital sign information can be automatically monitored and collected, and the information can be transmitted in real time to processing platforms such as databases, cloud servers, or mobile devices, thereby reducing the workload of nursing staff.

[0005] Taking medical health management as an example, IoT devices can be attached to patients using wireless sensing technology to collect vital sign data such as blood pressure, heart rate, body temperature, and respiration in real time. The data can then be transmitted via communication protocols such as Wi-Fi and Bluetooth (registered trademark) to a network cloud server or a software platform on a mobile device for data analysis and monitoring.

[0006] In addition, in home care or long-term care settings, IoT technology can be used to measure vital signs, allowing medical professionals or family members to understand the patient's health condition in real time and take necessary measures.For example, if an abnormality in vital signs is discovered, medical professionals can be immediately notified and directed to treatment, thereby improving the efficiency and quality of medical care.

[0007] Although IoT devices can realize automated vital sign measurement, they also have many drawbacks. First, the cost of the devices is high, and many institutions cannot afford the expensive hardware costs. Furthermore, IoT devices require regular maintenance and updates to prevent potential breakdowns. Given the risk to human life, IoT devices must operate with extremely low fault tolerance. Furthermore, vital sign data collected by IoT devices involves sensitive personal information, and IoT devices easily generate large amounts of vital sign data, which must be processed and analyzed using complex algorithms, placing high demands on back-end servers and storage devices.

[0008] Therefore, the inventor has made efforts to develop the "physiological monitoring information measurement system and method" and succeeded in overcoming the above-mentioned drawbacks through diligent efforts and research. The following is a brief description of the present invention. Summary of the Invention

[0009] The present invention relates to a physiological monitoring information measurement system and method, and in particular to a physiological monitoring information measurement system and method based on non-contact and non-invasive physiological monitoring information measurement technology.

[0010] Accordingly, the present invention provides a physiological monitoring information measurement system, which includes a clinical physiological monitoring information management front end connected to each other via a network. Interface The clinical physiological monitoring information management back-end processing platform includes a mobile device including a programming module and a remote computing device including a programming module, and the clinical physiological monitoring information management front-end processing platform is operated by the mobile device in response to a user's operation. Interface and executing the clinical physiological monitoring information management back-end processing platform programming module to implement a non-contact, non-invasive physiological monitoring information detection and recognition integrated programming model, which includes a face recognition programming module, a physiological monitoring information image measurement programming module, a voiceprint recognition programming module, a natural language recognition programming module, a medication image recognition programming module, and a wound image recognition programming module, to automatically identify the patient's identity based on the first patient image, the second patient image, the first patient voice, and the second patient voice, and automatically detect and identify the patient's physiological monitoring information in an integrated manner, wherein the physiological monitoring information includes body temperature, blood pressure, heart rate, respiratory rate, blood oxygen saturation, wound records, medication records, and clinic conversation records, and is automatically entered into the patient's electronic medical record.

[0011] Such a physiological monitoring information measurement system is the physiological monitoring information measurement system described above, further comprising a light source module and a nursing smart cart or a mobile nurse station, wherein the light source module includes a light emitting diode light source and is attached to the nursing smart cart or the mobile nurse station to provide additional illumination to the first patient image and the second patient image, the nursing smart cart includes a first support pole, the first support pole having a first support first end and a first support second end, the first support second end being connected to the mobile device, and the The nursing smart cart further includes a second support, the second support including a second support first end and a second support second end, the second support second end being connected to the light source module; the nursing smart cart further includes a first flexible support, the first flexible support including a first flexible support first end and a first flexible support second end, the first flexible support second end being connected to the mobile device, the mobile device being capable of instantly adapting to any positioning requirement of the user and being held at a first position within a hemispherical range centered on the first flexible support first end; The mobile nurse station includes a second flexible support, the second flexible support including a second flexible support first end and a second flexible support second end, the second flexible support second end being connected to the light source module, so that the light source module can be held at a second position within a hemispherical range centered on the second flexible support first end, instantly adapting to any positioning requirement of the user; the mobile nurse station includes a first support, the first support including a first support first end and a first support second end, the first support second end being connected to the mobile device; and the mobile nurse station further includes a second support. the second support includes a second support first end and a second support second end, the second support second end being connected to the light source module; the mobile nurse station includes a first flexible support, the first flexible support includes a first flexible support first end and a first flexible support second end, the first flexible support second end being connected to the mobile device, so that the mobile device can be held at a first position within a hemispherical range centered on the first flexible support first end, instantaneously adapting to any positioning requirement of the user; the mobile nurse station further includes a second flexible support;The second flexible support includes a second flexible support first end and a second flexible support second end, and the second flexible support second end is connected to the light source module, so that the light source module can be held at a second position within a hemispherical range centered on the second flexible support first end, instantly adapting to any positioning requirement of the user.

[0012] The present invention further provides a physiological monitoring information measurement method, which includes connecting a clinical physiological monitoring information management front end to a clinical physiological monitoring information management front end via a network communication. Interface connecting a mobile device including a programming module and a remote computing device including a clinical physiological monitoring information management back-end processing platform programming module; and Interface and executing the clinical physiological monitoring information management back-end processing platform programming module to implement a non-contact, non-invasive physiological monitoring information detection and recognition integrated programming model, which includes a face recognition programming module, a physiological monitoring information image measurement programming module, a voiceprint recognition programming module, a natural language recognition programming module, a medication image recognition programming module, and a wound image recognition programming module, to automatically identify the patient's identity based on the first patient image, the second patient image, the first patient voice, and the second patient voice, and automatically detect and identify the patient's physiological monitoring information in an integrated manner, wherein the physiological monitoring information includes body temperature, blood pressure, heart rate, respiratory rate, blood oxygen saturation, wound records, medication records, and clinic conversation records, and is automatically entered into the patient's electronic medical record.

[0013] The above Summary of the Invention is intended to provide a simplified summary of the disclosure so that the reader can have a basic understanding of the disclosure. This Summary of the Invention is not intended to disclose a complete description of the invention, and is not intended to point out important / key elements of embodiments of the invention or to delineate the scope of the invention. [Brief explanation of the drawings]

[0014] [Figure 1] 1 discloses a schematic diagram of the system architecture of the physiological monitoring information measurement system of the present invention. [Figure 2] 1 shows a schematic diagram of a first hardware architecture of a mobile device of the present invention; [Figure 3] 1 discloses a schematic diagram of the hardware architecture of the remote computing device of the present invention. [Figure 4] 1 discloses a schematic diagram of a second hardware architecture of the mobile device of the present invention. [Figure 5] A block diagram of programming modules executable by multiple processor units included in the present invention is disclosed. [Figure 6] 1 is a block diagram of a clinical physiological monitoring information management front-end interface programming module of the present invention, the user interface of the medical practitioner side. [Figure 7] 1 is a perspective view showing the structure of a smart nursing cart included in the present invention; [Figure 8] 1 is a schematic side view of the structure of a nursing smart cart included in the present invention; [Figure 9] 1 is a structural diagram of the mobile device connection member of the present invention in a connected state with a mobile device; [Figure 10(A)] 1 discloses a schematic diagram of an application situation of a first embodiment included in the present invention. [Figure 10(B)] 1 discloses a schematic diagram of an application situation of a first embodiment included in the present invention. [Figure 10(C)]1 discloses a schematic diagram of an application situation of a first embodiment included in the present invention. [Figure 11(A)] 10 is a schematic diagram of an application situation of the second embodiment included in the present invention; [Figure 11(B)] 10 is a schematic diagram of an application situation of the second embodiment included in the present invention; [Figure 11(C)] 10 is a schematic diagram of an application situation of the second embodiment included in the present invention; [Figure 12(A)] 10 shows a schematic diagram of an application scenario of the third embodiment included in the present invention. [Figure 12(B)] 10 shows a schematic diagram of an application scenario of the third embodiment included in the present invention. [Figure 12(C)] 10 shows a schematic diagram of an application scenario of the third embodiment included in the present invention. [Figure 13] 1 is a flowchart illustrating the steps of a physiological monitoring information measurement method according to the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0015] The physiological monitoring information described herein includes basic vital sign information of a patient, including, but not limited to, information such as body temperature, blood pressure, heart rate, respiratory rate, and blood oxygen saturation, as well as various information recorded in medical records, including, but not limited to, wound records and medication records. Physiological monitoring information is an important basis for doctors to assess a patient's condition and formulate a medical plan.

[0016] 1 shows a schematic diagram of the system architecture of a physiological monitoring information measurement system according to the present invention. The physiological monitoring information measurement system 10 provided by the present invention includes a mobile device 100 and a remote computing device 200 that are communicatively connected to each other via a network 20, which preferably includes the Internet, a wide area network (WAN), a local area network (LAN), a wired network, a wireless network, a telecommunications network, or any combination thereof, and the physiological monitoring information measurement system 10 preferably implements the non-contact physiological monitoring information measurement method provided by the present invention.

[0017] 2 shows a schematic diagram of a first hardware architecture of a mobile device of the present invention. The mobile device 100 included in the present invention is preferably a user device operated by a user, such as, but not limited to, a smartphone or a tablet device. Regardless of the type of user device, its hardware architecture includes at least one first processor unit 101 and at least one first storage medium 102, which is preferably a local storage medium installed inside the mobile device 100 or an external storage device connected to the outside, as shown in FIG. 2.

[0018] The first processor unit 101 can load and execute a plurality of processor-executable programming modules, which are pre-stored in the first storage medium 102 and are executed by the first processor unit 101 after being loaded into the first processor unit 101, and these programming modules are used as a clinical physiological monitoring information management front end. Interface This includes, but is not limited to, a programming module 103 .

[0019] 3 discloses a schematic diagram of the hardware architecture of the remote computing device of the present invention. The remote computing device 200 included in the present invention is preferably composed of a single remote server or multiple remote servers, and the remote computing device 200 is preferably, for example, but not limited to, an application server or a computation server. Regardless of the type of server, its hardware architecture includes at least one second processor unit 201 and at least one second storage medium 202, and the second storage medium 202 is preferably a local storage medium within the remote computing device 200 or an external storage device connected to the outside, as shown in FIG. 3.

[0020] The second processor unit 201 can load and execute multiple processor-executable programming modules, which are pre-stored in the second storage medium 202 and executed by the second processor unit 201 after being loaded into the second processor unit 201, including but not limited to a clinical physiological monitoring information management backend processing platform programming module 203.

[0021] 4 discloses a schematic diagram of a second hardware architecture of the mobile device of the present invention. The mobile device 100 includes a clinical physiological monitoring information management front-end (CMD) stored in a first storage medium 102. Interface In addition to including a first processor unit 101 that executes a programming module 103, it also includes hardware components such as an image sensor 104, a sound sensor 105, an infrared sensor 106, and a communication transmission module 107.

[0022] Clinical physiological monitoring information management front-end InterfaceAfter being started and executed, the programming module 103 responds to a user's operation by activating the image sensor 104 and the audio sensor 105, thereby detecting the first and second patient images and the first and second patient voices of a certain patient, respectively, and further activating the infrared sensor 106 to detect the patient's temperature. The detected information, such as the first and second patient images, the first and second patient voices, and the patient's temperature, is then transmitted to the clinical physiological monitoring information management back-end processing platform programming module 203 via the communication transmission module 107. Clinical physiological monitoring information management front-end as a front-end Interface The programming module 103 and the clinical physiological monitoring information management backend processing platform programming module 203 together form a clinical physiological monitoring information management platform 210 .

[0023] 5 shows a block diagram of programming modules executable by multiple processor units included in the present invention. The clinical physiological monitoring information management backend processing platform programming module 203 executed by the second processor unit 201 of the remote computing device 200 further includes a face recognition programming module 204, a physiological monitoring information image measurement programming module 205, a voiceprint recognition programming module 206, a natural language recognition programming module 207, a drug image recognition programming module 208, and a wound image recognition programming module 209, all of which are pre-stored in the second storage medium 202 and are executed by the second processor unit 201 after being loaded into the second processor unit 201.

[0024] 6 shows a block diagram of the clinical physiological monitoring information management front-end interface programming module of the present invention. The clinical physiological monitoring information management back-end processing platform programming module 203 includes six functional modules, namely, a face recognition programming module 204, a physiological monitoring information image measurement programming module 205, a voiceprint recognition programming module 206, a natural language recognition programming module 207, a drug image recognition programming module 208, and a wound image recognition programming module 209. Interface The programming module 103 includes a medical professional user interface 120, which includes a face recognition button 124, a physiological monitoring information image measurement button 125, and a medical professional user interface 126. 5, a dialogue recognition button 126, a drug recognition medication record button 127, and a wound image recognition button 1 28 included.

[0025] When the user presses the face recognition button 124, the physiological monitoring information image measurement button 125, or the dialogue recognition button 126, the execution of the face recognition programming module 204, the physiological monitoring information image measurement programming module 205, the voiceprint recognition programming module 206, and the natural language recognition programming module 207 is initiated remotely, respectively.

[0026] The facial recognition programming module 204 included in the present invention extracts facial feature points from the first and second patient images and compares and analyzes them with a pre-built model to identify the patient's identity. The facial recognition programming module 204 integrates a feature point extraction method, a neural network method, and a statistical model method, which can be selected and configured by the user. The feature point extraction method extracts feature points (e.g., but not limited to, the positions of the eyes, nose, and mouth) from the patient image and calculates parameters such as the distance and angle between these feature points to determine the patient's identity. The neural network method uses deep learning technology to train a facial recognition model and learns and memorizes patient images using a multi-layer neural network, achieving high-precision facial recognition. The statistical model method performs facial recognition by representing patient images as statistical models through statistical analysis and comparing the differences between statistical models for different faces.

[0027] The physiological monitoring information image measurement programming module 205 is based on photoplethysmography (PPG) technology, image-based photoplethysmography (image-based PPG) technology, or video-based PPG technology, and detects slight changes in brightness, such as slight changes in color on the skin surface, between an image of a first patient and an image of a second patient to form a waveform diagram. By analyzing this waveform diagram, it is possible to calculate changes in the patient's heart rate, blood oxygen saturation (SpO2), respiratory rate, blood pressure, etc., and further calculate the patient's heart rate, blood oxygen saturation, respiratory rate, and blood pressure. Therefore, the physiological monitoring information image measurement programming module 205 can be implemented using only a general lens, does not require any additional sensors or detection devices, and belongs to a non-contact and non-invasive physiological monitoring information measurement method.

[0028] The voiceprint recognition programming module 206 extracts and compares the characteristics of the spectrum, waveform, frequency, etc. of the doctor's and patient's voices to distinguish between different voiceprints and further distinguish between the doctor's and patient's voices. The natural language recognition programming module 207 integrates automatic speech recognition (ASR) technology, natural language understanding (NLU) technology, and text-to-speech (TTS) technology, and can automatically convert speech into text. When the natural language recognition programming module 207 cooperates with the voiceprint recognition programming module 206, it can automatically record the conversation between the nurse and the patient as text content, in particular, record the patient's voice, and then automatically generate text to add to the patient's chief complaint in the medical chart or nursing record.

[0029] The drug image recognition programming module 208 can use computer vision technology to extract drug features, such as, but not limited to, shape, color, texture, etc., from images containing drugs, and then train a supervised machine learning algorithm model to learn these drug features, and after training is complete, the model can automatically recognize the name, dosage, use, etc. of the drug in an image. The drug image recognition programming module 208 helps medical professionals identify drugs more quickly and accurately, effectively reducing possible errors and risks in drug use, improving the safety of drug use for patients, and can automatically identify drug dosages and detect whether a patient is experiencing drug interactions, etc.

[0030] The wound image recognition programming module 209 uses supervised learning algorithms, including object detection algorithms and classification algorithms, to automatically analyze and interpret the size, shape, depth, color, texture, etc. of the wound in the wound image, and further automatically determine the type, severity, treatment method, etc. of the wound, and record it in the medical or nursing record.

[0031] FIG. 7 shows a schematic perspective view of the structure of a smart nursing cart according to the present invention. FIG. 8 shows a schematic side view of the structure of a smart nursing cart according to the present invention. The physiological monitoring information measurement system 10 of the present invention can also be used in combination with a smart nursing cart to form a mobile nursing station. The smart nursing cart 300 disclosed in the present invention includes a mobile base 310, an intermediate support column assembly 320, a first support column 330, a mobile device connection member 340, an optional first component connection member 350, an optional second component connection member 360, an optional third component connection member (component connection member) 370, a second support column 380, and a light source module 390. The first component connection member 350, the second component connection member 360, and the third component connection member 370 are optional members. That is, the smart nursing cart 300 can be configured with all three types of connection members listed, only one type of connection member, or more connection members. For example, in the embodiment shown in Figure 7, the nursing smart cart 300 includes only the first component connection member 350 and the third component connection member 370. In the embodiment shown in Figure 8, the nursing smart cart 300 includes the first component connection member 350, the second component connection member 360, and the third component connection member 370.

[0032] The movable base 310 includes components such as a base 311 and movable wheels 313, and the base 311 is preferably, but not limited to, made of stainless steel, aluminum alloy, or plastic. In one embodiment, an insertion opening is formed in the center of the base 311, into which a portion of the insertion sleeve 312 is inserted and connected to the base 311, or into which the intermediate support assembly 320 is directly inserted and connected to the base 311. In one embodiment, the base 311 itself and the insertion sleeve 312 are manufactured by integral molding or forging, and the insertion sleeve 312 and the base 311 or the intermediate support assembly 320 and the base 311 may be fixed by means of screws, nuts, welding, or the like. The base 311 generally includes a plurality of support legs of different lengths extending outward, which provide the smart nursing cart 300 with good horizontal stability and make the smart nursing cart 300 less likely to shake. At the outer end of each support leg, a pair of movable wheels 313 are mounted, which may preferably be movable plastic wheels, or omni-wheels or the like.

[0033] The intermediate support assembly 320 is preferably a single or multiple upright, fixed-height, non-retractable hollow circular tubes, or a set of telescopic rods composed of multiple stages of hollow sleeves and solid vertical rods, or a multi-connected rod structure composed of multiple hollow or solid connecting rods. The fixed-height intermediate support assembly 320 preferably has a length ranging from 70 to 100 centimeters (cm), and the adjustable-height intermediate support assembly 320 has a length ranging from 50 to 120 centimeters. The shape of the intermediate support assembly 320 is preferably, but not limited to, circular, and may be rectangular or other suitable shape. The intermediate support assembly 320 may be made of, but is not limited to, stainless steel, aluminum alloy, or plastic material, or may be made of a composite material. When the intermediate support assembly 320 is a hollow tube, the space contained therein can accommodate various wires, tubes, or element modules, for example, but not limited to, electrical wires, network cables, data cables, power modules, etc., which can be arranged, aligned, or distributed therein. Here, in the embodiment disclosed in FIG. 7, the intermediate support assembly 320 is connected to the insertion sleeve 312 on the movable base 310, tightly assembled with the movable base 310, and stands upright above the ground from the movable base 310; in the embodiment disclosed in FIG. 8, the intermediate support assembly 320 is directly inserted into the insertion opening on the movable base 310 and fixed to the movable base 310 by screws and nuts.

[0034] In some embodiments, the first support pole 330 is preferably a non-flexible structure, such as, but not limited to, a straight solid support pole or a straight hollow tube. In some embodiments, the first support pole 330 is preferably a flexible structure (first flexible support pole) configured using a hollow metallic or non-metallic hose with a gooseneck or coil mechanism, such as, but not limited to, a combination of stainless steel wire and copper alloy wire, which can bend or curve in response to an external force. The inner space of the hollow hose can accommodate various wires, tubes, or device modules, such as, but not limited to, electrical cables, network cables, data cables, power modules, etc., which can be arranged, aligned, or distributed therein. Here, a first end 331 of the first support pole 330 is connected to the intermediate support pole assembly 320 by a method such as a screw, nut, or welding, and is fixed to the intermediate support pole assembly 320. A mobile device connection member 340 is installed at a second end 332 to connect the mobile device 100.

[0035] Therefore, after the mobile device 100 is fixed to the second end 332, the first support 330 itself has the property of bending and curving in response to external forces, so that the mobile device 100 can immediately adapt to any positioning needs of the user and be held at any position within a three-dimensional hemispherical range 335 centered on the first end 331, thereby allowing the user to manually adjust the mobile device 100 to the optimal height and position.

[0036] The multi-purpose platform 351 is connected to the intermediate support column assembly 320 and the nursing smart cart 300 by the first component connecting member 350, the set of push handles 361 by the second component connecting member 360, and the set of device carrying members 371 by the third component connecting member 370 in a movable manner. The first component connecting member 350, the second component connecting member 360, and the third component connecting member 370 enable the height of the intermediate support column assembly 320 from the ground to be adjusted, so that the user can freely adjust it according to the usage situation. Therefore, through the cooperative operation of the movable base 310, the intermediate support column assembly 320, the first support column 330, etc., the intermediate support column assembly 320 and the first support column 330 of the nursing smart cart 300 can have a total extended height of up to 160 cm or 170 cm after fully extended, and preferably the user can freely extend and retract the height from the ground to a range of 50 cm to 170 cm, or 60 cm to 160 cm.

[0037] The light source module 390 includes a light emitting diode (LED) light source and is attached to the second end 382 of the second support 380, and the first end 381 of the second support 380 is attached to the intermediate support assembly 320, and the light source module 390 can provide additional illumination to the lens, helping the face recognition programming module 204, the physiological monitoring information image measurement programming module 205, the drug image recognition programming module 208, and the wound image recognition programming module 209 to capture clear first and second patient images.

[0038] In one embodiment, the second support 380 is preferably a non-flexible structure, such as, but not limited to, a straight solid support or a straight hollow tube. In another embodiment, the second support 380 is preferably a flexible structure (second flexible support) formed using a hollow metal or non-metal hose with a gooseneck mechanism or a coiled tube mechanism. Therefore, after the light source module 390 is fixed to the second end 382, ​​the second support 380 itself has the property of bending and curving in response to external forces. Therefore, the light source module 390 can instantly adapt to the user's arbitrary positioning requirements and be held at any position within a three-dimensional hemispherical range 385 centered on the first end 381, allowing the user to manually adjust the light source module 390 to the optimal height and position.

[0039] In actual use, the user can adjust the first support 330 to hold the mobile device 100 at an appropriate height according to the on-site usage situation, and can adjust the multi-purpose platform 351, push handle 361, and device carrying member 371 to different heights above the ground by adjusting the first component connecting member 350, the second component connecting member 360, and the third component connecting member 370, respectively, to provide convenience for operation. The nursing smart cart 300 of the present invention can provide users with various devices and components to operate at different heights above the ground, providing users with multiple adjustment freedom and optimal flexibility, and is suitable for use in fields such as medical care and nursing, and can meet the usage needs of various emergency, special, and sudden situations.

[0040] The outer surfaces of components included in the smart nursing cart 300, such as the movable base 310, the intermediate support column assembly 320, the first support column 330, the mobile device connecting member 340, the first component connecting member 350, the second component connecting member 360, and the third component connecting member 370, can be further surface-treated to impart special functions to the surfaces, such as hydrophobicity, hydrophilicity, scratch resistance, abrasion resistance, slip resistance, dust resistance, antibacterial properties, or disinfecting properties, making them suitable for use in fields such as medical care and nursing.

[0041] FIG. 9 shows a structural diagram of the mobile device connection member of the present invention and the mobile device in a connected state. In one embodiment, the mobile device connecting member 340 is mounted on the second end 332 of the first support 330 and includes a set of universal joints 341 and a set of vacuum suction cups 342 or a magnetic suction locking tenon. The vacuum suction cups 342 are attached to the flat part on the back of the mobile device 100, tightly but movably connecting and fixing the mobile device 100 to the first support 330 and the smart nursing cart 300. The first support 330 allows the height of the mobile device 100 to be adjusted at any time, making it height adjustable. The universal joint 341 allows the mobile device 100 to be rotated in any direction and at any angle, making it multiple degrees of freedom adjustable. During the use of the smart nursing cart 300, the user can freely adjust the mobile device 100 at any time, allowing the mobile device 100 to be operated from any direction and angle, providing the user with great flexibility and convenience.

[0042] 10(A), 10(B) and 10(C) show a schematic diagram of the application of the first embodiment of the present invention. In this embodiment, the physiological monitoring information measurement system of the present invention is used to measure vital signs, and the mobile device 100 is preferably a tablet device such as an iPad (registered trademark), and has already been equipped with a clinical physiological monitoring information management front end. Interface With the programming module 103 installed, the mobile device 100 is preferably attached to the second end 332 of the first support 330 included in the nursing smart cart 300. The mobile device 100 preferably establishes a communication connection with the remote computing device 200 via the network 20, thereby providing a clinical physiological monitoring information management front end. Interface A corresponding communication connection is established between the programming module 103 and the clinical physiological monitoring information management backend processing platform programming module 203 .

[0043] As shown in FIG. 10(A), when a nurse 401 measures the vital signs of a patient 403, the nurse 401 first moves the nursing smart cart 300 to the bedside where the patient 300 is located, and then attaches the mobile device 100 to the second end 332 of the first support 330 included in the nursing smart cart 300, for example, but not limited to, by a suction cup or a quick release mechanism, so that the mobile device 100 can be held in any position according to the user's request. Next, the user starts the execution of the clinical physiological monitoring information management front-end programming module 103 on the mobile device 100, for example, by a click operation. After the clinical physiological monitoring information management front-end programming module 103 is executed, a communication connection is established between the clinical physiological monitoring information management back-end processing platform programming module 203 and the clinical physiological monitoring information management front-end programming module 103 via the network.

[0044] The nurse 401 aligns the lens of the mobile device 100 with the patient 403, then presses the face recognition button 124 to activate the face recognition function included in the clinical physiological monitoring information management platform 210, and the clinical physiological monitoring information management front-end interface programming module 103 returns the first patient image and the second patient image including the patient 403 captured by the lens to the clinical physiological monitoring information management back-end processing platform programming module 203, and the clinical physiological monitoring information management back-end processing platform programming module 203 first executes the face recognition programming module 204 to identify the identity of the patient 403, and retrieves the relevant information of the patient 403 from the database and returns it to the clinical physiological monitoring information management front-end interface programming module 103, for display on the medical professional side user interface 120 of the clinical physiological monitoring information management front-end interface programming module 103.

[0045] As shown in FIG. 10(B), the nurse 401 presses the physiological monitoring information image measurement button 125 included in the medical professional user interface 120 to activate the physiological monitoring information image measurement function, and the clinical physiological monitoring information management front end Interface The programming module 103 returns the first patient image and the second patient image including the patient 403 captured by the lens to the clinical physiological monitoring information management back-end processing platform programming module 203. The clinical physiological monitoring information management back-end processing platform programming module 203 executes the physiological monitoring information image measurement programming module 205 to measure the blood pressure, heart rate, blood oxygen saturation, respiratory rate, etc. of the patient 403, and measures the body temperature of the patient 403 by the infrared sensor 106. The measured vital sign data is sent to the clinical physiological monitoring information management front-end processing platform 203. Interface The programming module 103 immediately responds, and the clinical physiological monitoring information management front end Interface The display is on the medical professional user interface 120 of the programming module 103.

[0046] As shown in FIG. 10(C), after the image measurement of the physiological monitoring information is completed, the nurse 401 then presses the speech recognition button 126 included in the medical staff user interface 120 to activate the speech recognition and recording function, and the clinical physiological monitoring information management front end InterfaceThe programming module 103 sends the voice including the conversation between the nurse 401 and the patient 403 captured by the audio sensor 105, for example, a microphone, back to the clinical physiological monitoring information management backend processing platform programming module 203. The clinical physiological monitoring information management backend processing platform programming module 203 starts to execute the voiceprint recognition programming module 206 and the natural language recognition programming module 207. By executing the voiceprint recognition programming module 206, it distinguishes the voices of the patient 403 and the nurse 401 from the voice, and by executing the natural language recognition programming module 207, it identifies the natural language contained in the voice, and these can be recorded respectively as a self-reported record of the patient's 403's condition and a medical interview record of the nurse 401, and further recorded as a medical conversation record, and the self-reported record of the patient 403 can be the patient's 403's main complaint.

[0047] 11(A), 11(B), and 11(C) show schematic diagrams of an application of a second embodiment of the present invention. The second embodiment is based on the first embodiment and includes the first implementation. In this embodiment, the physiological monitoring information measurement system of the present invention is used for drug identification and medication recording. As shown in FIG. 11(B), a nurse 401 aligns the lens of the mobile device 100 with a drug 405 and then presses the drug recognition and medication recording button 127 to activate the drug image recognition function. The clinical physiological monitoring information management front-end interface programming module 103 returns the image containing the drug 405 captured by the lens to the clinical physiological monitoring information management back-end processing platform programming module 203. The clinical physiological monitoring information management back-end processing platform programming module 203 executes the drug image recognition programming module 208 to identify medication information such as the name and dosage of the drug 405, and returns the identified medication information to the medical professional user interface 120 of the clinical physiological monitoring information management front-end interface programming module 103 for display. The related medication information is then stored in a database.

[0048] 12(A), 12(B) and 12(C) show a schematic diagram of the application of the third embodiment of the present invention. The third embodiment is based on the first embodiment and includes the first implementation. In this embodiment, the physiological monitoring information measurement system of the present invention is used for wound identification and recording. As shown in FIG. 12(B), a nurse 401 aligns the lens of the mobile device 100 with the wound 407 of the patient 403, and then presses the wound image recognition button 128 to activate the wound image recognition function, and the clinical physiological monitoring information management front end Interface The programming module 103 returns the image including the wound 407 captured by the lens to the clinical physiological monitoring information management back-end processing platform programming module 203, which executes the wound image recognition programming module 209 to identify wound information of the wound 407, including, but not limited to, the geometric shape, wound level, color, and size, and transmits the wound information to the clinical physiological monitoring information management front-end processing module 203. Interface The data is returned to the medical practitioner user interface 120 of the programming module 103 and displayed.

[0049] The physiological monitoring information measurement system 10 of the present invention includes a clinical physiological monitoring information management platform 210, which, when used in combination with a nursing smart cart 300, can form a small, multi-purpose mobile nurse station. The technologies of face recognition, physiological monitoring information measurement, voiceprint recognition, natural language recognition, drug image recognition, and wound image recognition can help nursing staff care for patients more quickly and accurately, and can automate the entire measurement process of physiological monitoring information, including vital signs.

[0050] When using the physiological monitoring information measurement system 10 of the present invention, nursing staff only need to carry a single tablet device, and the entire physiological monitoring information measurement program can be executed using the tablet device's built-in hardware devices, such as a video camera, microphone, and display. The nursing staff points the cart to the bedside, activates the system, and then uses the tablet device's video camera to perform operations such as facial recognition, medication image recognition, and wound image recognition on the patient. They then activate the microphone to record voiceprint and natural language recognition technology. Finally, all recognition and measurement results, including the patient's identity, physiological monitoring information, medication information, and wound information, are displayed on the tablet device's screen.

[0051] 13 discloses a flowchart showing the implementation steps of the physiological monitoring information measurement method according to the present invention. The physiological monitoring information measurement method 500 according to the present invention is implemented by a clinical physiological monitoring information management front end. Interface Step 501: Connecting a mobile device including a programming module and a remote computing device including a clinical physiological monitoring information management back-end processing platform programming module via network communication; Interface activating a programming module (step 502); InterfacePreferably, but not limited to, the method includes: executing a programming module to instantly sense a first patient image, a second patient image, a first patient voice, or a second patient voice of a patient, and transmitting the sensed first patient image, second patient image, first patient voice, or second patient voice to the clinical physiological monitoring information management backend processing platform programming module (step 503); and executing the clinical physiological monitoring information management backend processing platform programming module to implement a non-contact non-invasive physiological monitoring information sensing programming module, and acquiring physiological monitoring information of the patient based on the first patient image, second patient image, first patient voice, or second patient voice (step 504).

Claims

[Claim 1] A physiological monitoring information measurement method, comprising: connecting a mobile device including a clinical physiological monitoring information management front-end interface programming module and a remote computing device including a clinical physiological monitoring information management back-end processing platform programming module via network communication; launching the clinical physiological monitoring information management front-end interface programming module on the mobile device in response to a user's operation; Executing the clinical physiological monitoring information management front-end interface programming module to instantly sense a first patient image and a second patient image of a patient having slight brightness variations with each other, for obtaining a waveform diagram used for calculating physiological monitoring information, and transmitting the first patient image and the second patient image to the clinical physiological monitoring information management back-end processing platform programming module; Implementing a non-contact, non-invasive physiological monitoring information detection and recognition integrated programming model by executing the clinical physiological monitoring information management backend processing platform programming module, and executing a face recognition programming module and a physiological monitoring information image measurement programming module included therein, to automatically identify the patient's identity based on the first patient image and the second patient image, and automatically detect and identify the patient's physiological monitoring information in an integrated manner, the physiological monitoring information including blood pressure, heart rate, respiratory rate, and blood oxygen saturation, and automatically write the physiological monitoring information into the patient's electronic medical record; After the patient's identity is automatically identified, executing the clinical physiological monitoring information management front-end interface programming module to transmit at least one of a user-patient conversation voice, a medication image, and a patient wound image to the clinical physiological monitoring information management back-end processing platform programming module; the clinical physiological monitoring information management back-end processing platform programming module is executed to execute a voiceprint recognition programming module and a natural language recognition programming module to generate a clinic conversation record when a voice consisting of a conversation between a user and a patient is transmitted, to execute a drug image recognition programming module to generate a medication record when a drug image is transmitted, to execute a wound image recognition programming module to generate a wound record when a wound image of the patient is transmitted, and to add the generated clinic conversation record, medication record, and wound record to the physiological monitoring information, and automatically write them into the patient's electronic medical record; Including, the voiceprint recognition programming module is configured to extract and compare spectral, waveform, and frequency features of the voice data to distinguish between the user's voice and the patient's voice; The natural language recognition programming module is configured to integrate automatic speech recognition (ASR) technology, natural language understanding (NLU) technology, and text-to-speech (TTS) technology, automatically convert and record the conversational speech between the user and the patient into text, and then write the text into a conversation record at the clinic; the medication image recognition programming module is configured to implement a trained supervised machine learning algorithm model for automatically recognizing medication names, dosages, and uses contained in medication images and recording the recognition results in a medication record; The wound image recognition programming module is configured to implement a supervised learning algorithm model for automatically analyzing and interpreting wound size, shape, depth, color, and texture in the wound image, and is configured to automatically determine wound type, severity, and treatment, and record the results in a wound record. Physiological monitoring information measurement method.

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