Biological information measurement method

Abstract

According to an embodiment of the present disclosure, a method for measuring biological information performed by a measurement device is disclosed, in which the measurement device identifies a measurement attempt for the measurement device, and in response to the identified measurement attempt, performs both an operation of activating the measurement device and an operation of transmitting a wake-up signal to an external device, and transmits measurement information to the external device.

Description

[Technical Field]

[0001] The present disclosure relates to a method for measuring biological information, and more particularly to a method for identifying a measurement attempt using a measurement device, measuring biological information, and transmitting the measurement information to an external device. [Background technology]

[0002] Biometric information refers to information that can be used as an indicator of human physical activity, including bioelectricity, biomagnetism, pressure, sound, etc. Recently, many portable devices that operate in conjunction with external devices such as smartphones via communication technologies such as Bluetooth (registered trademark) have been developed as devices for measuring the above-mentioned biometric information.

[0003] However, currently, all of the above-mentioned biological information measuring devices that operate in conjunction with external devices (e.g., smart devices, etc.) require user input to the external device, i.e., input related to the start of measurement, input related to the end of measurement, input related to the start of analysis, etc. Depending on the user's condition or illness, biological information may need to be measured periodically, and operating the external device linked to the measuring device to prepare for measurement and obtain measurement results every time a measurement is performed causes great inconvenience to the user.

[0004] Furthermore, in an emergency situation, the need for such an operation may hinder the rapid acquisition of vital signs, which may result in a hindrance to prompt treatment of the patient.

[0005] Therefore, there is a need in the industry for a measurement device that can acquire biological information without separately operating an external device.

[0006] Patent Document 1 discloses "a method for correcting an electrocardiogram signal in a wearable device using an acceleration sensor and an electrocardiogram measurement wearable device to which the method is applied." [Prior art documents] [Patent documents]

[0007] [Patent Document 1] Korean Patent Registration No. 1995153 Summary of the Invention [Problem to be solved by the invention]

[0008] The present disclosure aims to utilize a measurement device that operates in conjunction with an external device, and enable the measurement device to quickly measure biometric information and provide the results without direct operation of the linked external device (e.g., a smart device, etc.).

[0009] However, the technical problems that this disclosure aims to solve are not limited to the above-mentioned technical problems, and may include a variety of technical problems within the scope that is obvious to an ordinary engineer based on the content described below. [Means for solving the problem]

[0010] According to an embodiment of the present disclosure for solving the above-mentioned problems, a method executed by a measurement device for measuring biological information is disclosed, which may include the steps of: identifying a measurement attempt for the measurement device; and, in response to the identified measurement attempt, performing both an operation of activating the measurement device and an operation of transmitting a wake-up signal to an external device, and a step of transmitting measurement information to the external device.

[0011] In an alternative embodiment, the step of transmitting measurement information to the external device can be performed without a measurement program for the measurement device running in the foreground of the external device.

[0012] In an alternative embodiment, the signal received from the external device may be: automatically generated based on analysis of the measurement information without user input to the external device.

[0013] In an alternative embodiment, the step of performing both the operation of activating the measurement device and the operation of sending a wake-up signal to an external device in response to the identified measurement attempt may further include: the step of generating an activation notification; and the step of identifying whether the measurement attempt satisfies a measurement start condition and generating a measurement start notification based on the result.

[0014] In an alternative embodiment, the method may further include performing at least one of the following operations if the identified measurement attempt is aborted: deactivating the measurement device; and transmitting an idle signal to the external device.

[0015] In an alternative embodiment, the method may further comprise performing an action of deactivating the measurement device.

[0016] In an alternative embodiment, the method further includes terminating the measurement operation based on a signal received from the external device, and the terminating the measurement operation based on the signal received from the external device may include: terminating the measurement operation if the signal is a measurement interrupt signal; or performing at least one of terminating the measurement operation, sending a standby signal to the external device, and deactivating the measurement device if the signal is a measurement completion signal, or terminating the measurement operation if a predetermined time has elapsed since the signal was received.

[0017] According to an embodiment of the present disclosure for solving the above-mentioned problems, a method executed by a computing device operating in conjunction with a measurement device is disclosed, which may include, when a wake-up signal is received from the measurement device, executing a program for the measurement device in the background, and analyzing measurement information received from the measurement device based on the program executed in the background.

[0018] In an alternative embodiment, the method may further include a step of transmitting, to the measurement device, feedback information relating to the measurement state being unstable, if the measurement state is determined to be unstable through the analysis.

[0019] In an alternative embodiment, the method may further include switching the program to a foreground state and outputting the analysis results once analysis of the measurement information is complete.

[0020] In an alternative embodiment, the unstable measurement situation described above can be determined based on at least one of the strength of the measurement information, the time interval between inputs of the measurement information, or the length of the measurement information.

[0021] According to one embodiment of the present disclosure, there is disclosed a computer program stored on a computer-readable storage medium, the computer program including instructions for causing a measurement device to perform operations for measuring biological information, the operations including: identifying a measurement attempt for the measurement device; activating the measurement device and transmitting a wake-up signal to an external device in response to the identified measurement attempt; and transmitting measurement information to the external device.

[0022] According to an embodiment of the present disclosure for achieving the above object, a measurement device for acquiring biological information is disclosed, the measurement device including at least one processor, a measurement unit for measuring biological information, a communication unit for communicating with an external device, and an output unit for providing a notification, wherein the processor is capable of identifying a measurement attempt for the measurement device, and performing both an operation of activating the measurement device and an operation of transmitting a wake-up signal to the external device in response to the identified measurement attempt, and transmitting measurement information to the external device. [Effects of the Invention]

[0023] The present disclosure utilizes a measurement device that operates in conjunction with an external device, and is capable of quickly measuring biometric information under the initiative of the measurement device and providing the results without direct operation of the linked external device (e.g., a smart device, etc.). [Brief explanation of the drawings]

[0024] [Figure 1] FIG. 1 is a block diagram of a computing device included in a measurement device for measuring biological information according to an embodiment of the present disclosure. [Figure 2] 1 is a flowchart illustrating a process for measuring biological information in one embodiment of the present disclosure. [Figure 3] 1 is an exemplary diagram showing a 6-lead portable electrocardiogram measurement device among measurement devices according to an embodiment of the present disclosure. [Figure 4] 1 is an exemplary diagram showing a 2-lead portable electrocardiogram measurement device among measurement devices according to an embodiment of the present disclosure. [Figure 5] 1 is an exemplary graph of an electrocardiogram measured based on electrical signals received from electrodes, according to one embodiment of the present disclosure. [Figure 6] FIG. 1 is an exemplary diagram illustrating a blood pressure measurement device among measurement devices according to an embodiment of the present disclosure. [Figure 7] FIG. 1 is an exemplary diagram illustrating a weight measurement device among measurement devices according to an embodiment of the present disclosure. [Figure 8] FIG. 1 is a simplified general schematic diagram of an exemplary computing environment in which an embodiment of the present disclosure may be implemented. DETAILED DESCRIPTION OF THE INVENTION

[0025] The present disclosure relates to a method for quickly measuring biological information under the initiative of a measuring device without requiring a separate operation of an external device connected to the measuring device, and providing the results.

[0026] Various embodiments are described below with reference to the drawings. Various descriptions are provided herein to facilitate understanding of the present disclosure. However, it is apparent that such embodiments can be practiced without such specific descriptions.

[0027] As used herein, terms such as "component," "module," and "system" refer to computer-related entities, hardware, firmware, software, a combination of software and hardware, or the execution of software. For example, a component can be, but is not limited to, a procedure running on a processor, a processor, an object, a thread of execution, a program, and / or a computer. For example, both an application running on a computing device and the computing device can be a component. One or more components can reside within a processor and / or thread of execution. A component can be localized within one computer. A component can be distributed across two or more computers. Such components can also execute on various computer-readable media having various data structures stored therein. Components can communicate via local and / or remote processes, for example, using signals comprising one or more data packets (e.g., data and / or signals from one component interacting with other components in a local or distributed system, or data transmitted over a network such as the Internet with other systems).

[0028] It should be noted that the term "or" is intended to mean an inclusive "or" rather than an exclusive "or." That is, unless otherwise specified or clear from the context, "X utilizes A or B" is intended to mean one of the natural inclusive permutations. That is, if X utilizes A; X utilizes B; or X utilizes both A and B, then "X utilizes A or B" can apply to any of these. Additionally, the term "and / or" as used herein should be understood to refer to and include all possible combinations of one or more items among a list of associated items.

[0029] Additionally, the predicate "comprises" and / or the modifier "comprises" should be understood to mean the presence of the feature and / or component in question. However, the predicate "comprises" and / or the modifier "comprises" should be understood not to exclude the presence or addition of one or more other further features, components and / or groups thereof. Additionally, unless a specific number is specified or the context is clear that a singular form is indicated, the singular form in this specification and claims should generally be construed to mean "one or more."

[0030] Furthermore, the term "at least one of A or B" should be interpreted as meaning "when only A is included," "when only B is included," or "when a combination of A and B is included."

[0031] Those skilled in the art should further recognize that the various illustrative logical blocks, components, modules, circuits, means, logic, and algorithm steps described in accordance with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the various illustrative components, blocks, components, means, logic, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the particular application and design constraints of the overall system. Skilled artisans may implement the described functionality in various ways for each particular application. However, such implementation decisions should not be interpreted as departing from the scope of the present disclosure.

[0032] The description of the embodiments set forth herein is provided to enable one of ordinary skill in the art to utilize or practice the present disclosure. Various modifications to these embodiments will be apparent to those of ordinary skill in the art. The generic principles defined herein may be applied to other embodiments without departing from the scope of the present disclosure. Therefore, the present invention is not limited to the embodiments set forth herein. The present invention is to be accorded the broadest scope consistent with the principles and novel features disclosed herein.

[0033] FIG. 1 is a block diagram of a computing device included in a measurement device for measuring biological information according to an embodiment of the present disclosure.

[0034] The configuration of the computing device (100) shown in Figure 1 is merely a simplified example. In one embodiment of the present disclosure, the computing device (100) may include other components for implementing the computing environment of the computing device (100), and the computing device (100) may be configured with only some of the disclosed components.

[0035] The computer device (100) may include a processor (110), a memory (130), and a network unit (150).

[0036] In one embodiment of the present disclosure, the processor 110 may be configured with one or more cores and may include processors for data analysis and deep learning, such as a computing central processing unit (CPU), a general-purpose graphics processing unit (GPGPU), and a tensor processing unit (TPU). The processor 110 may read a computer program stored in the memory 130 and execute data processing for machine learning in one embodiment of the present disclosure. According to one embodiment of the present disclosure, the processor 110 may perform calculations for neural network training. In deep learning (DL), the processor 110 may execute calculations for neural network training, such as processing input data for training, extracting features from the input data, calculating errors, and updating neural network weights using backpropagation.

[0037] At least one of the CPU, GPGPU, and TPU of the processor 110 can process network function training. For example, the CPU and GPGPU can both train the network function or classify data using the network function. In one embodiment of the present disclosure, processors of multiple computing devices can be used together to train the network function or classify data using the network function. In one embodiment of the present disclosure, the computer program executed in the computing device can be a program executable by the CPU, GPGPU, or TPU.

[0038] According to one embodiment of the present disclosure, a processor 110 included in the measurement device can identify a measurement attempt for the measurement device. A detailed description of how the processor 110 identifies a measurement attempt will be provided below with reference to FIG. 2.

[0039] In one embodiment of the present disclosure, the processor 110 included in the measurement device can perform both an operation of activating the measurement device and an operation of sending a wake-up signal to the external device in response to the identified measurement attempt. Here, the wake-up signal can refer to a signal that changes the external device to a state where it can receive and record data transmitted by the measurement device. A detailed description of the operations of activating the measurement device and sending a wake-up signal to the external device will be provided below with reference to FIG. 2.

[0040] In one embodiment of the present disclosure, a processor 110 included in the measurement device can transmit measurement information to an external device. The measurement device and the external device can include communication modules for transmitting and receiving data, and the two devices can be linked via a wired connection or wireless pairing. Wireless pairing can be achieved using various technologies, including Bluetooth, Wi-Fi, etc.

[0041] In one embodiment of the present disclosure, the processor 110 included in the measurement device can terminate the measurement operation under a predetermined condition. A specific method for the processor to terminate the measurement operation will be described later with reference to FIG. 2.

[0042] In one embodiment of the present disclosure, the processor 110 included in the measurement device can identify that a measurement attempt has been interrupted and perform both an operation to deactivate the measurement device and an operation to send an idle signal to the external device, without relying on an interruption signal received from an external device. For example, if the measurement device is a 6-lead portable electrocardiogram measurement device for measuring an electrocardiogram, a part of the body must be in contact with each of the three electrodes to measure the electrocardiogram. The processor 110 can identify that a measurement attempt has been interrupted if some of the electrodes are not in contact with the body, if the connection with the external device is lost, if acceleration above a certain level is detected, or if another abnormal condition occurs. In this case, the processor 110 of the portable electrocardiogram measurement device can perform an operation to deactivate the measurement device and an operation to send an idle signal to the linked external device, thereby switching to a state in which a measurement attempt can be identified again. The example of deactivating the measuring device and switching the external device to the idle state is not limited to an electrocardiogram measuring device, but other measuring devices such as blood pressure measuring device, weight measuring device, and body temperature measuring device can also perform the above-mentioned operation.

[0043] In the present disclosure, the measurement device identifies that a measurement attempt has been interrupted, thereby eliminating the need to interrupt the measurement based on user input to an external device, while also reducing the time required to measure biometric information.

[0044] In addition, the processor 110 included in the measurement device may perform an operation to deactivate the measurement device after transmitting the measurement information to the external device. For example, if the measurement device is a 6-lead portable measurement device for measuring an electrocardiogram, the processor 110 may obtain electrocardiogram data as measurement information, transmit the same to the external device, and then immediately deactivate the measurement device. As another example, the processor 110 may perform an operation to deactivate the measurement device after a predetermined time (e.g., 3 seconds) has elapsed after transmitting the measurement information to the external device.

[0045] In one embodiment of the present disclosure, the memory 130 may include at least one type of storage medium selected from the group consisting of flash memory, hard disk, micro multimedia card, card-type memory (e.g., SD or XD memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, and optical disk. The computing device 100 may also operate in conjunction with web storage that performs storage functions of the memory 130 over the Internet. The above descriptions of memory are merely examples, and the present disclosure is not limited thereto.

[0046] The network unit 150 in one embodiment of the present disclosure can use various wired communication systems such as a Public Switched Telephone Network (PSTN), x Digital Subscriber Line (xDSL), Rate Adaptive DSL (RADSL), Multi Rate DSL (MDSL), Very High Speed ​​DSL (VDSL), Universal Asymmetric DSL (UADSL), High Bit Rate DSL (HDSL), and a Local Area Network (LAN).

[0047] In addition, the network unit (150) in this specification can use various wireless communication systems such as CDMA (Code Division Multi Access), TDMA (Time Division Multi Access), FDMA (Frequency Division Multi Access), OFDMA (Orthogonal Frequency Division Multi Access), SC-FDMA (Single Carrier-FDMA), and other systems.

[0048] In the present disclosure, the network unit 150 can use any type of wired or wireless communication system.

[0049] The techniques described herein can be used in the above networks as well as other networks.

[0050] In one embodiment of the present disclosure, a method is disclosed that is performed by an external device (e.g., a smart device) that operates in conjunction with a measurement device. Here, the external device can be implemented in a form that includes a computing device, similar to the measurement device described above. The external device can also include a processor, memory, a network unit, etc.

[0051] Meanwhile, the method executed by the external device described above can be embodied in the form of a program, an application, or the like.

[0052] In one embodiment of the present disclosure, when an external device receives a wake-up signal from the measurement device, the external device can execute a program for the measurement device in the background. The external device can also analyze measurement information received from the measurement device based on the program executed in the background. Then, when a measurement completion condition is met as a result of analyzing the measurement information, the external device can transmit a measurement end signal to the measurement device. Furthermore, when the external device determines that the measurement status is unstable as a result of analyzing the measurement information, the external device can transmit feedback information related to the unstable measurement status to the measurement device. In this case, the measurement status being unstable can be determined based on at least one of the strength of the measurement information, the input time interval of the measurement information, and the length of the measurement information.

[0053] FIG. 2 is a flowchart illustrating a process for measuring biological information in one embodiment of the present disclosure.

[0054] According to FIG. 2, the process of measuring biometric information in the present disclosure may include a step of identifying a measurement attempt for the measurement device (S210), a step of activating the measurement device and sending a wake-up signal to an external device in response to the identified measurement attempt (S220), and a step of sending measurement information to the external device (S230).

[0055] In step S210, the processor 110 included in the measurement device can identify a measurement attempt for the measurement device. A measurement attempt in this disclosure includes various attempts by a user to operate the measurement device to measure biometric information. For example, the measurement device can include a gyroscope or acceleration sensor, and the sensor can detect changes such as the user moving or lifting the measurement device, and the processor 110 can identify the sensor's response as a measurement attempt. As another example, the measurement device can include a contact sensor, and the sensor can detect the user's skin contacting the electrodes of the measurement device, and the processor 110 can identify the sensor's response as a measurement attempt. However, the measurement attempt in this disclosure is not limited to the methods provided as examples.

[0056] In step S220, the processor 110 included in the measurement device may perform both an operation of activating the measurement device and an operation of transmitting a wake-up signal to the external device in response to the identified measurement attempt. Here, "activation" may refer to an operation of changing the state of the measurement device so that the measurement device can receive user input and record a biosignal. Furthermore, the "wake-up signal" may refer to an operation of waking the external device from an idle state and changing the state of the external device so that the external device can receive, record, and analyze measurement information transmitted by the measurement device. Upon receiving the wake-up signal, the external device can receive, record, and analyze the measurement information transmitted from the measurement device without any additional input from the user.

[0057] Step S220 may include generating an activation notification. The activation notification may refer to an operation of notifying a user that the measurement device has been activated and is ready to receive input of the user's biological information, such as by starting the measurement device, contacting an electrode included in the measurement device, or moving the portable measurement device. Step S220 may also identify whether the measurement attempt satisfies a measurement start condition and generate a measurement start notification based on the result. In this case, the measurement start condition refers to a condition related to whether the input from the user is suitable for measuring biological information. For example, if the measurement device is a 6-lead electrocardiogram measurement device having three electrodes, the measurement start condition may be a condition in which the user's fingers on both hands touch the first and second electrodes of the measurement device, the user's foot touches the third electrode, and a potential difference is measured between the electrodes. As another example, if the measurement device is a blood pressure monitor, the measurement start condition may be a condition in which a sensor included in a blood pressure measurement cuff detects the user's arm.

[0058] The activation notification and the measurement start notification can be generated in various ways, such as visually or audibly, or two or more ways can be used simultaneously. For example, the activation notification and the measurement start notification can be generated by an LED included in the measurement device turning on, by a display included in the measurement device showing video, images, or text information, or by a speaker included in the measurement device generating a specific audio signal.

[0059] In step S230, the processor (110) included in the measurement device can transmit the measurement information to an external device.

[0060] In one embodiment of the present disclosure, the processor 110 included in the measurement device can terminate the measurement operation based on a signal received from an external device. In this case, the signal received from the external device can include a measurement interrupt signal or a measurement completion signal. Furthermore, the measurement interrupt signal and measurement completion signal received from the external device can be generated without direct input from a user (i.e., without direct operation of the external device).

[0061] The measurement interruption signal may be feedback information transmitted from the external device to the measurement device when the external device analyzes the measurement information and determines that the measurement state is unstable. The measurement state being unstable may be determined based on at least one of the strength of the measurement information, the time interval between inputs of the measurement information, or the length of the measurement information. For example, the measurement state may be determined to be unstable when it is determined that the conditions for analyzing the measurement information are not met, such as when the measurement information is weak, the time interval between inputs of the measurement information is long, or the measurement information is short. Meanwhile, the measurement completion signal may be feedback information transmitted from the external device to the measurement device when the measurement completion condition is met when the external device analyzes the measurement information.

[0062] When the measurement device receives a measurement interruption signal, the processor 110 included in the measurement device can execute an operation to terminate the measurement operation. In this case, since the measurement was not performed normally, the operation to deactivate the measurement device can be omitted, and the measurement device can remain activated and wait for the next input.

[0063] When the measurement device receives the measurement completion signal, the processor 110 included in the measurement device can perform at least one of the following operations: terminating the measurement operation, sending a standby signal to the external device, and deactivating the measurement device. If the measurement information is successfully transmitted, the measurement device and the external device may not be used until the next measurement. Therefore, the processor 110 can save power used to operate the measurement device by terminating the measurement operation or deactivating the measurement device.

[0064] In the present disclosure, the measurement termination operation can be performed independently of a signal received from an external device. For example, the measurement device can automatically terminate the measurement after a predetermined time has elapsed. In this case, the predetermined time can vary depending on the type of measurement device, and the length of the predetermined time can be changed by user settings.

[0065] In step S230, the measurement program for the measurement device may be executed without being executed in the foreground of the external device. That is, the measurement program may be executed in the background. A foreground process may refer to a process that requires user-initiated input or interaction, or that the user can recognize or perceive in real time. Therefore, in the present disclosure, the external device may receive measurement information from the measurement device without user input to the external device. Similarly, the external device may generate and send measurement interruption signals and measurement completion signals to the measurement device based on an analysis of the measurement information without user input.

[0066] In the present disclosure, a measurement program running in the background of an external device can be switched to the foreground state when analysis of measurement information is completed. The measurement program can generate a separate alarm to notify the user that analysis of the measurement information is completed, and then be switched to the foreground state by user input. Alternatively, the measurement program can automatically switch to the foreground state when analysis of the measurement information is completed without generating a separate alarm. The processor 110 included in the external device can then output analysis results included in the analysis of the measurement information. For example, the processor 110 can display the analysis results on a display included in the external device.

[0067] The present disclosure makes it possible to measure biological information without user input to an external device, which significantly reduces the time and effort required to operate the device when measuring biological information, enables more appropriate responses to emergencies, and improves user convenience.

[0068] FIG. 3 is an exemplary diagram showing a 6-lead portable electrocardiogram measurement device among measurement devices according to an embodiment of the present disclosure.

[0069] A 6-lead portable electrocardiogram measuring device according to one embodiment of the present disclosure may include a main measuring unit (300). The main measuring unit (300) may include a first electrode (310), a second electrode (320), and a third electrode (330). The first electrode (310), the second electrode (320), and the third electrode (330) may be categorized by their positions. The first electrode (310), the second electrode (320), and the third electrode (330) may be categorized by the target body part of the user to which they need to be closely attached. Each electrode may form part of the housing of the main measuring unit. If each electrode forms part of the housing of the main measuring unit, the user can simultaneously hold or use three electrodes without using a separate cable. As shown in FIG. 3, in one embodiment, the main measuring unit (300) may have a pad shape. If the main measuring unit (300) has a pad shape, the first electrode (310) and the second electrode (320) are located on both sides of the front part of the pad, and the third electrode is located on the rear part of the pad, the user can measure the electrocardiogram by touching the first electrode (310) and the second electrode (320) with the thumbs of both hands, respectively, and touching a part of the foot with the rear electrode. The above-mentioned examples of the shape of the main measuring unit are merely examples and do not limit the present disclosure.

[0070] FIG. 4 is an exemplary diagram showing a 2-lead portable electrocardiogram measurement device among measurement devices according to an embodiment of the present disclosure.

[0071] The main measuring unit 400 of the two-lead portable electrocardiogram measuring device may include a first electrode 410 and a second electrode 420. The first electrode 410 and the second electrode 420 may be distinguished by their positions. The first electrode 410 and the second electrode 420 may be distinguished by the target body part of the user to which they need to be closely attached. Each electrode may form part of the housing of the main measuring unit. If each electrode forms part of the housing of the main measuring unit, the user can simultaneously hold and use three electrodes without using a separate cable. As shown in FIG. 4, in one embodiment, the main measuring unit 400 may have a pad shape. If the main measuring unit 400 has a pad shape and the first electrode 410 and the second electrode 420 are located on either side of the front surface of the pad, the user can measure an electrocardiogram by touching the first electrode 410 and the second electrode 420 with the thumbs of both hands, respectively. The above-mentioned examples regarding the shape of the main measuring portion are merely examples and are not intended to limit the present disclosure.

[0072] In the 6-lead portable electrocardiogram measuring device and the 2-lead portable electrocardiogram measuring device according to an embodiment of the present disclosure, the main measuring unit (300 or 400) can include a network unit for wireless data communication. The main measuring unit can transmit and receive data by interacting with an external device via wired or wireless communication. Data communication by the network unit can be performed by short-range wireless communication. The short-range wireless communication method can include, for example, wireless LAN (WLAN), Bluetooth (registered trademark), etc.

[0073] A portable electrocardiogram measurement device according to an embodiment of the present disclosure may further include an output unit. The output unit may output at least one of information related to electrical signal measurement of each electrode, information related to an electrocardiogram measurement method of a processor included in the portable electrocardiogram measurement device, and notification information. The output unit may include at least one of a configuration for audio output and a configuration for video, image, or text output. The output unit may also be included in an external device linked to the portable electrocardiogram measurement device. For example, the output unit may be included in a user's PC, smartphone, tablet, etc.

[0074] A program for a portable electrocardiogram measurement device according to an embodiment of the present disclosure can be executed in the background of an external device, and the external device can receive electrocardiogram information from the portable electrocardiogram measurement device, analyze the information, and display it to the user without any additional input from the user.

[0075] Figure 5 is an example of an electrocardiogram measured based on electrical signals received from the electrodes. As shown in Figure 5, the waveform of an electrocardiogram is classified into P waves, Q waves, R waves, S waves, and T waves. First, the P wave is a waveform that appears during atrial depolarization and progresses across the atrium from right to left. Therefore, the portion before the P wave indicates depolarization of the right atrium, and the portion after the P wave indicates depolarization of the left atrium.

[0076] The QRS complex, which includes the Q, R, and S waves, is caused by ventricular depolarization. The Q wave represents depolarization of the interventricular septum, and the remainder of the QRS complex represents simultaneous depolarization of the left and right ventricles.

[0077] The T wave occurs due to the repolarization of the ventricles. It occurs at the end of ventricular systole. Repolarization proceeds more slowly than depolarization and has a longer wavelength and lower amplitude than the QRS complex. In this way, an electrocardiogram measured based on the electrical signals received from the electrodes can be used to determine the movement of the ventricles and atria inside the heart.

[0078] There are a total of 12 electrocardiogram leads included in electrocardiogram data. These electrocardiogram leads are classified into limb leads and precordial leads. Limb leads can be further classified into standard limb leads, including leads I, II, and III, and augmented limb leads, including leads aVR, aVL, and aVF. Standard limb leads can be used interchangeably with standard leads. Augmented limb leads can be used interchangeably with limb leads. Of the 12 leads, the standard limb leads, including three leads, are bipolar leads that record the potential difference between two electrodes. Of the 12 leads, the remaining leads, excluding the standard limb leads, are unipolar leads that are measured by a single electrode.

[0079] Throughout this specification, the terms lead, lead, and lead may be used interchangeably and all refer to leads contained in electrocardiogram data as described above.

[0080] FIG. 6 is an exemplary diagram illustrating a blood pressure measurement device among measurement devices according to an embodiment of the present disclosure.

[0081] The blood pressure measurement device 600 can include a blood pressure measurement cuff 610, a start blood pressure measurement button 620, and a stop blood pressure measurement button 630. Touching the start blood pressure measurement button, or a separate input that activates the blood pressure measurement device, can cause a processor in the blood pressure measurement device to identify a measurement attempt to be applied to the blood pressure measurement device.

[0082] When a sensor included in the blood pressure cuff 610 identifies that the user's arm is inside the blood pressure cuff, the processor of the blood pressure measurement device can begin measuring blood pressure. If the user's arm moves beyond a certain range during measurement, if a certain external force is applied to the blood pressure measurement device, or if an interrupt signal is received from an external device linked to the blood pressure measurement device, the processor of the blood pressure measurement device can perform all of the following actions: abort the measurement attempt, deactivate the measurement device, and send an idle signal to the external device.

[0083] The blood pressure measurement device according to an embodiment of the present disclosure may further include an output unit. The output unit may output at least one of information related to the user's measured blood pressure and information related to notification of measurement status. The output unit may include at least one of a configuration for audio output, and a configuration for video, image, or text output. The output unit may also be included in an external device linked to the blood pressure measurement device. For example, the output unit may be included in the user's PC, smartphone, tablet, or the like.

[0084] A program for a blood pressure measurement device according to an embodiment of the present disclosure can be executed in the background of an external device, which can receive information related to a user's blood pressure from the blood pressure measurement device without any separate input from the user, analyze the information, and display it to the user.

[0085] FIG. 7 is an exemplary diagram showing a weight scale as a measuring device according to an embodiment of the present disclosure.

[0086] The scale 700 can include a pressure sensing element 710. By applying pressure to the pressure sensing element 710 or by providing a separate input to activate the scale, the scale's processor can identify a measurement attempt on the scale.

[0087] When the sensor included in the pressure sensing unit 710 identifies that the pressure applied to the sensor is equal to or greater than a certain level, the scale's processor can begin measuring the weight. If the pressure sensed by the pressure sensor changes suddenly during measurement, or if an interrupt signal is received from an external device linked to the scale, the scale's processor can perform the following actions: abort the measurement attempt, deactivate the measuring device, and send an idle signal to the external device.

[0088] A weight scale according to an embodiment of the present disclosure may further include an output unit. The output unit may output at least one of information related to the measured weight of the user and information related to notification of information related to the measurement status. The output unit may include at least one of a configuration for audio output and a configuration for video, image, or text output. The output unit may also be included in an external device linked to the weight scale. For example, the output unit may be included in the user's PC, smartphone, tablet, etc.

[0089] A program for a weight scale according to an embodiment of the present disclosure can be executed in the background of an external device, and the external device can receive information related to a user's weight from the weight scale without any separate input from the user, analyze the information, and display it to the user.

[0090] As shown in Figures 3, 4, 6, and 7, the measurement device in the present disclosure can be a device that measures biological information including an electrocardiogram, blood pressure, and weight. However, the measurement device in the present disclosure is not limited to the measurement device shown in the drawings, and a method similar to that of the present disclosure can also be used for a measurement device that measures other biological information such as an electromyogram or an electroencephalogram.

[0091] In accordance with one embodiment of the present disclosure, a computer-readable storage medium having a data structure stored thereon is disclosed.

[0092] A data structure can refer to the organization, management, and storage of data that allows efficient access and modification. A data structure can refer to the organization of data to solve a specific problem (e.g., data retrieval, data storage, data modification) in the shortest possible time. A data structure can also be defined as the physical or logical relationships between data elements designed to support a specific data processing function. Logical relationships between data elements can include the interconnections between data elements as perceived by a user. Physical relationships between data elements can include the actual relationships between data elements physically stored on a computer-readable storage medium (e.g., a hard disk). A data structure can specifically include a collection of data, the relationships between the data, and functions or commands that can be applied to the data. An effectively designed data structure allows a computing device to perform calculations while minimizing the use of computing device resources. Specifically, an effectively designed data structure can increase the efficiency of operations, reading, inserting, deleting, comparing, exchanging, and searching.

[0093] Data structures can be divided into linear and non-linear data structures depending on their type. A linear data structure can be a structure in which only one piece of data is linked to another. Linear data structures can include lists, stacks, queues, and deques. A list can refer to a series of data sets that have an internal order. Lists can also include linked lists. A linked list can be a data structure in which data is linked in a row with a pointer to each piece of data. In a linked list, the pointer can contain information about the connection to the next or previous piece of data. Depending on the type, linked lists can be expressed as singly linked lists, doubly linked lists, or circularly linked lists. A stack can be a data list structure that allows limited data access. A stack can be a linear data structure in which data can only be accessed (e.g., inserted or deleted) at one end of the data structure. Data stored in a stack can be a LIFO (Last in First Out) data structure. A queue is a data structure that allows limited access to data, and unlike a stack, it can be a data structure (FIFO - First in First out) where the slowest data stored is the slowest data available. A deck can be a data structure that allows data to be processed at both ends of the data structure.

[0094] A non-linear data structure may be a structure in which multiple pieces of data are concatenated after one piece of data. A non-linear data structure may include a graph data structure. A graph data structure may be defined by vertices and edges, and a backbone may include a line connecting two different vertices. A graph data structure may include a tree data structure. A tree data structure may be a data structure in which a path connecting two different vertices among multiple vertices included in a tree is a single data structure. In other words, a graph data structure may be a data structure that does not form loops.

[0095] Throughout this specification, the terms computational model, neural network, network function, and neural network are used interchangeably (hereinafter, they will be referred to as neural network). A data structure may include a neural network. The data structure including a neural network may be stored on a computer-readable storage medium. The data structure including a neural network may also include data input to the neural network, neural network weights, neural network hyperparameters, data acquired from the neural network, activation functions associated with each node or layer of the neural network, and a loss function for training the neural network. The data structure including a neural network may include any of the components disclosed above. That is, the data structure including a neural network may include all or any combination of data input to the neural network, neural network weights, neural network hyperparameters, data acquired from the neural network, activation functions associated with each node or layer of the neural network, and a loss function for training the neural network. In addition to the above-mentioned components, the data structure including a neural network may include any other information that determines the characteristics of the neural network. Furthermore, the data structure may include any form of data used or generated in the computational process of a neural network, and is not limited to the foregoing. The computer-readable storage medium may include a computer-readable recording medium and / or a computer-readable transmission medium. A neural network may be composed of a collection of interconnected computational units generally called nodes. Such nodes may be called neurons. A neural network is composed of at least one or more nodes.

[0096] The data structure may include data to be input to the neural network. The data structure including the data to be input to the neural network may be stored in a computer-readable storage medium. The data to be input to the neural network may include training data input during the training process of the neural network and / or input data to be input to the neural network after training has been completed. The data to be input to the neural network may include data that has undergone pre-processing and / or data to be pre-processed. Pre-processing may include a data processing process for inputting data to the neural network. Therefore, the data structure may include data to be pre-processed and data generated by pre-processing. The above-described data structures are merely examples, and the present disclosure is not limited thereto.

[0097] The data structure may include weights of the neural network. (In this specification, the terms "weights" and "parameters" may be used interchangeably.) The data structure including the weights of the neural network may be stored in a computer-readable storage medium. The neural network may include multiple weights. The weights are variable and may be changed by a user or an algorithm to enable the neural network to perform a desired function. For example, if one or more input nodes are interconnected to an output node by respective links, the output node may determine its output node value based on the values ​​input to the input nodes connected to the output node and the parameters set for the links corresponding to each input node. The above data structure is merely exemplary, and the present disclosure is not limited thereto.

[0098] By way of example and not limitation, the weights may include weights that change during neural network training and / or weights at which neural network training has been completed. The weights that change during neural network training may include weights at the start of a training cycle and / or weights that change during a training cycle. The weights at which neural network training has been completed may include weights at which a training cycle has been completed. Therefore, a data structure including neural network weights may include a data structure including weights that change during neural network training and / or weights at which neural network training has been completed. Therefore, the above-mentioned weights and / or combinations of each weight are included in a data structure including neural network weights. The above-mentioned data structures are merely examples, and the present disclosure is not limited thereto.

[0099] The data structure including the neural network weights may be stored in a computer-readable storage medium (e.g., memory, hard disk) after undergoing a serialization process. Serialization may be a process of converting a data structure into a form that can be stored on the same or another computing device and later reconstructed for use. A computing device may serialize the data structure and transmit or receive the data over a network. The serialized data structure including the neural network weights may be reconstructed on the same or another computing device through deserialization. The data structure including the neural network weights is not limited to serialization. Furthermore, the data structure including the neural network weights may include a data structure (e.g., a nonlinear data structure such as a B-tree, a Trie, an m-way search tree, an AVL tree, or a Red-Black tree) that increases computational efficiency while minimizing the use of computing device resources. The foregoing is merely exemplary, and the present disclosure is not limited thereto.

[0100] The data structure may include hyperparameters of the neural network. The data structure including the hyperparameters of the neural network may be stored in a computer-readable storage medium. The hyperparameters may be variables that can be changed by a user. The hyperparameters may include, for example, a learning rate, a cost function, the number of learning cycle iterations, weight initialization (e.g., setting a range of weights to be initialized), and the number of hidden units (e.g., the number of hidden layers, the number of nodes in the hidden layers). The above-described data structure is merely exemplary, and the present disclosure is not limited thereto.

[0101] FIG. 8 is a simplified general schematic diagram of an exemplary computing environment in which embodiments of the present disclosure can be implemented.

[0102] While the present disclosure has been described above as generally being embodied in a computing device, those skilled in the art will appreciate that the present disclosure can also be embodied in combination with computer-executable instructions and / or other program modules that can be executed on one or more computers and / or as a combination of hardware and software.

[0103] Generally, modules herein include routines, programs, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Those skilled in the art will also appreciate that the methods of the present disclosure can be practiced with other computer system configurations, including single-processor or multi-processor computer systems, minicomputers, mainframe computers, as well as personal computers, handheld computing devices, microprocessor-based or programmable consumer electronics, etc., each of which can operate in conjunction with one or more associated devices.

[0104] The embodiments described in this disclosure may also be practiced in distributed computing environments where certain tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

[0105] A computer includes a variety of computer-readable media. Any medium accessible by a computer can be computer-readable, including volatile and nonvolatile media, transitory and non-transitory media, and portable and non-portable media. By way of example and not limitation, computer-readable media can include computer-readable storage media and computer-readable transmission media. Computer-readable storage media include volatile and non-volatile media, transitory and non-transitory media, portable and non-portable media implemented in any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer-readable storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital video disk (DVD) or other optical disk storage devices, magnetic cassettes, magnetic tape, magnetic disk storage devices or other magnetic storage devices, or any other medium that can be accessed by a computer and used to store information.

[0106] Computer-readable transmission media typically embodies computer-readable instructions, data structures, program modules or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and includes all information delivery media. The term modulated data signal means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, computer-readable transmission media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media. Any combination of any of the foregoing media should also be included within the scope of computer-readable transmission media.

[0107] An exemplary environment (1100) for implementing various aspects of the present disclosure is shown, including a computer (1102) including a processing unit (1104), a system memory (1106), and a system bus (1108). The system bus (1108) couples system components, including but not limited to the system memory (1106), to the processing unit (1104). The processing unit (1104) can be any of a variety of commercially available processors. Dual processors and other multi-processor architectures can also be utilized as the processing unit (1104).

[0108] The system bus (1108) can be any of several types of bus structures that can be further interconnected to a memory bus, a peripheral bus, and a local bus using any of a variety of commercially available bus architectures. The system memory (1106) includes read-only memory (ROM) (1110) and random access memory (RAM) (1112). The basic input / output system (BIOS) is stored in non-volatile memory (1110), such as ROM, EPROM, or EEPROM. The BIOS contains the basic routines that support the exchange of information between the various components within the computer (1102), such as during startup. The RAM (1112) can also include high-speed RAM, such as static RAM, for caching data.

[0109] The computer 1102 also includes an internal hard disk drive (HDD) 1114 (e.g., EIDE, SATA)—the internal hard disk drive 1114 can also be configured for external use in a suitable chassis (not shown)—a magnetic floppy disk drive (FDD) 1116 (e.g., for reading from and writing to a removable diskette 1118), and an optical disk drive 1120 (e.g., for reading from a CD-ROM disk 1122 or for reading from and writing to other high-capacity optical media such as DVDs). The hard disk drive 1114, magnetic disk drive 1116, and optical disk drive 1120 can be connected to the system bus 1108 by a hard disk drive interface 1124, a magnetic disk drive interface 1126, and an optical drive interface 1128, respectively. The interface (1124) for implementing an external drive includes, for example, at least one or both of USB (Universal Serial Bus) and IEEE 1394 interface technologies.

[0110] These drives and their associated computer-readable media provide non-volatile storage of data, data structures, computer-executable instructions, etc. In the case of computer 1102, the drives and media accommodate storing any data in a suitable digital format. While the foregoing description of computer-readable storage media refers to hard disk drives, removable magnetic disks, and removable optical media such as CDs or DVDs, those skilled in the art will appreciate that other types of computer-readable storage media, such as zip drives, magnetic cassettes, flash memory cards, cartridges, etc., can also be used in the exemplary operating environment, and that any such media can contain computer-executable instructions for performing the methods of the present disclosure.

[0111] A number of program modules, including an operating system 1130, one or more application programs 1132, other program modules 1134, and program data 1136, may be stored on the drives and in RAM 1112. All or portions of the operating system, applications, modules, and / or data may also be cached in RAM 1112. It will be appreciated that the present disclosure may be implemented with various commercially available operating systems or combinations of operating systems.

[0112] A user can enter commands and information into the computer 1102 through one or more wired or wireless input devices, such as a keyboard 1138 and a pointing device such as a mouse 1140. Other input devices (not shown) may include a microphone, an IR remote control, a joystick, a game pad, a stylus pen, a touch screen, and the like. These and other input devices are often connected to the processing unit 1104 through an input device interface 1142 connected to the system bus 1108, but may also be connected through other interfaces such as a parallel port, an IEEE 1394 serial port, a game port, a USB port, an IR interface, and the like.

[0113] A monitor 1144 or other type of display device is also connected to the system bus 1108 through an interface, such as a video adapter 1146. In addition to the monitor 1144, computers typically include other peripheral output devices (not shown), such as speakers, printers, etc.

[0114] The computer 1102 can operate in a networked environment using logical connections to one or more remote computers, such as remote computer(s) 1148, via wired and / or wireless communications. The remote computer(s) 1148 can be a workstation, a server computer, a router, a personal computer, a handheld computer, a microprocessor-based entertainment device, a peer device, or other conventional network node, and typically includes many or all of the components described for the computer 1102, although for simplicity, only a memory storage device 1150 is shown. The logical connections shown include wired and wireless connections in a local area network (LAN) 1152 and / or larger networks, e.g., a long-range network (WAN) 1154. Such LAN and WAN networking environments are commonplace in offices and companies and facilitate enterprise-wide computer networks, such as intranets, all of which may connect to a global computer network, e.g., the Internet.

[0115] When used in a LAN networking environment, the computer 1102 connects to the local network 1152 through a wired and / or wireless communication network interface or adapter 1156. The adapter 1156 can facilitate wired or wireless communication to the LAN 1152, which may also include a wireless access point attached thereto for communicating with the wireless adapter 1156. When used in a WAN networking environment, the computer 1102 can include a modem 1158 or other means for establishing communications over the WAN 1154, such as connecting to a communications server on the WAN 1154 or through the Internet. The modem 1158, which can be internal or external and can be a wired or wireless device, connects to the system bus 1108 through the serial port interface 1142. In a networked environment, program modules described for computer 1102, or portions thereof, may be stored in remote memory / storage device 1150. It will be readily appreciated that the network connections shown are exemplary and other means of establishing a communications link between two or more computers may be used.

[0116] The computer 1102 is operable to communicate with any wireless device or unit configured and operating in a wireless manner, such as printers, scanners, desktop and / or handheld computers, portable data assistants (PDAs), communications satellites, any equipment or location associated with a radio-detectable tag, and telephones. This includes at least Wi-Fi and Bluetooth® wireless technologies. Thus, communication can be in a predefined structure, such as a traditional network, or simply ad hoc communication between at least two devices.

[0117] Wi-Fi (Wireless Fidelity) allows devices to connect to the Internet without being wired. Wi-Fi is a wireless technology similar to cell phones, allowing such devices, such as computers, to send and receive data indoors and outdoors—anywhere within the coverage area of ​​a base station. Wi-Fi networks use IEEE 802.11 (a, b, g, etc.) radio technology to provide secure, reliable, and fast wireless connections. Wi-Fi can be used to connect computers to each other, the Internet, and wired networks (using IEEE 802.3 or Ethernet). Wi-Fi networks can operate in the unlicensed 2.4 or 5 GHz radio bands, at data rates of, for example, 11 Mbps (802.11a) or 54 Mbps (802.11b), or in products that include both bands (dual bands).

[0118] Those skilled in the art will appreciate that information and signals may be represented using any of a variety of different technologies and techniques. For example, the data, instructions, commands, information, signals, bits, symbols, and chips referred to in the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields, etc. or particles, optical fields, etc. or particles, or any combination thereof.

[0119] Those skilled in the art will appreciate that the various illustrative logic blocks, modules, processors, means, circuits, and algorithm steps described in the description of the embodiments disclosed herein can be implemented with electronic hardware, various forms of program or design code (for convenience, referred to herein as "software"), or a combination of all of these. To clearly illustrate this interoperability of hardware and software, the various illustrative components, blocks, modules, circuits, and steps have been described above generally by focusing on their functionality. Whether such functionality is implemented in hardware or software depends on the particular application and design constraints imposed on the overall system. Those skilled in the art will appreciate that the described functionality can be implemented in various ways for each particular application, and such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

[0120] Various embodiments described herein may be implemented as a method, apparatus, or article of manufacture using standard programming and / or engineering techniques. The term "article of manufacture" includes any computer program, carrier, or media accessible by a computer-readable device. For example, computer-readable storage media include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, magnetic strips, etc.), optical disks (e.g., CDs, DVDs, etc.), smart cards, and flash memory devices (e.g., EEPROMs, cards, sticks, key drives, etc.). Additionally, various storage media described herein include one or more devices and / or other machine-readable media for storing information.

[0121] It should be understood that the specific order or hierarchy of steps in the processes depicted is an example of an exemplary approach. Based on design priorities, it should be understood that the specific order or hierarchy of steps in the processes may be rearranged within the scope of this disclosure. The accompanying method claims present elements of the various steps in a sample order, but are not meant to be limited to the specific order or hierarchy depicted.

[0122] The description of the illustrated embodiments is provided to enable any person skilled in the art to which the disclosure pertains to use or practice the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited by the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0123] As described above, the related content has been described based on the best mode for carrying out the invention.

Claims

1. 1. A method performed by a measurement device for measuring biological information, comprising: identifying a measurement attempt for the measurement device; In response to the identified measurement attempt, performing both the operations of activating the measurement device and sending a wake-up signal to an external device; and transmitting measurement information to the external device; Including, method.

2. In claim 1, The step of transmitting the measurement information to the external device includes: A measurement program for the measurement device is It runs without being running in the foreground, method.

3. In claim 1, In response to the identified measurement attempt, performing both an operation of activating the measurement device and an operation of sending a wake-up signal to an external device; generating an activation notification; identifying whether the measurement attempt satisfies a measurement initiation condition and generating a measurement initiation notification based on the result; further comprising: method.

4. In claim 1, performing at least one of the following operations if the identified measurement attempt is aborted: deactivating the measurement device; and transmitting an idle signal to the external device; further comprising: method.

5. In claim 1, performing an operation to deactivate the measurement device; further comprising: method.

6. In claim 1, terminating a measurement operation based on a signal received from the external device; further comprising The step of terminating a measurement operation based on a signal received from the external device comprises: if the signal is a measurement interrupt signal, terminating the measurement operation; If the signal is a measurement completion signal, performing at least one of the following operations: terminating the measurement operation; sending a standby signal to an external device; and deactivating the measurement device; or terminating the measurement operation when a predetermined time has elapsed since the signal was received; Including, method.

7. 1. A method performed by a computing device operating in conjunction with a measurement device, comprising: When a wake-up signal is received from the measurement device, executing a program for the measurement device in the background; and analyzing measurement information received from the measurement device based on the program running in the background; Including, method.

8. In claim 7, transmitting feedback information relating to the unstable measurement state to the measurement device when it is determined through the analysis that the measurement state is unstable; further comprising: method.

9. In claim 8, and, when the analysis of the measurement information is completed, switching the program to a foreground state and outputting the analysis result. method.

10. In claim 8, The unstable measurement conditions mentioned above mean that The determination is based on at least one of the strength of the measurement information, the input time interval of the measurement information, or the length of the measurement information. method.

11. 1. A computer program stored on a computer-readable storage medium, the computer program comprising instructions for causing a measurement device to perform operations for measuring biological information, the operations comprising: identifying a measurement attempt for said measurement device; activating the measurement device and sending a wake-up signal to an external device in response to the identified measurement attempt; and transmitting measurement information to the external device; Including, A computer program stored on a computer-readable storage medium.

12. A measurement device for acquiring biological information, at least one processor; a measurement unit for receiving biometric information input; and a communication unit for communicating with an external device; The at least one processor Identifying a measurement attempt for the measurement device; In response to the identified measurement attempt, perform both the actions of activating the measurement device and sending a wake-up signal to an external device; and transmitting measurement information to the external device; A measuring device for acquiring biological information.

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