Wearable device and method for identifying wearing state on basis of temperature, and non-transitory computer-readable recording medium

Abstract

A wearable device is disclosed. The wearable device may comprise: a temperature sensor arranged to face the skin of a user when the wearable device is worn on the user; at least one processor; and a memory for storing instructions. When executed by the at least one processor, the instructions can cause the wearable device to: identify that the wearable device is worn by the user; and identify, in response to identifying that the wearable device is worn by the user, one wearing state corresponding to temperature data indicating a temperature value measured through the temperature sensor from among a plurality of wearing states.

Description

Wearable device, method, and non-transitory computer-readable recording medium for identifying a wearing state based on temperature

[0001] The following descriptions relate to a wearable device, a method, and a non-transitory computer-readable recording medium for identifying a wearing state based on temperature.

[0002] Wearable devices have transformed the way users monitor their health. Typically worn on the wrist, wearable devices have gained popularity due to their ability to track various biometric parameters, such as heart rate, sleep patterns, and activity levels. However, there is a growing demand for alternative wearable form factors that can offer enhanced functionality, and ring-type wearable devices equipped with biometric sensors are being developed to address this need.

[0003] The above information may be provided as background art to aid in understanding the present disclosure. No claim or determination is made as to whether any of the above-described matters constitute prior art related to the present disclosure.

[0004] A wearable device is disclosed. The wearable device may include a temperature sensor arranged to face the skin of a user when the wearable device is worn on the user. The wearable device may include at least one processor. The wearable device may include a memory storing instructions. The instructions, when executed by the at least one processor, may be configured to cause the wearable device to identify that the wearable device is worn by the user. The instructions, when executed by the at least one processor, may be configured to cause the wearable device to identify, among a plurality of wearing states, one wearing state corresponding to temperature data representing a temperature value measured by the temperature sensor in response to identifying that the wearable device is worn by the user.

[0005] A method is disclosed. The method may be performed on a wearable device, the wearable device including a temperature sensor arranged to face the skin of a user when the wearable device is worn by the user. The method may include an operation of identifying that the wearable device is worn by the user. The method may include an operation of identifying, in response to identifying that the wearable device is worn by the user, one of a plurality of wearing states corresponding to temperature data representing a temperature value measured by the temperature sensor.

[0006] A non-transitory computer-readable storage medium is disclosed. The non-transitory computer-readable storage medium can store a program including instructions. The instructions, when executed by at least one processor of a wearable device including a temperature sensor arranged to face the skin of a user when the wearable device is worn on a user, can be configured to cause the wearable device to identify that the wearable device is worn on the user. The instructions, when executed by the at least one processor, can cause the wearable device to, in response to identifying that the wearable device is worn on the user, identify one of a plurality of wearing states corresponding to temperature data representing a temperature value measured by the temperature sensor.

[0007] FIG. 1 illustrates an exemplary wearable device according to one embodiment.

[0008] FIG. 2 illustrates a cross-section of an exemplary wearable device according to one embodiment.

[0009] FIG. 3 is a block diagram of a wearable device according to one embodiment.

[0010] FIG. 4 illustrates an example of a state diagram of a wearable device according to one embodiment.

[0011] FIG. 5 illustrates an example of a graph representing a temperature measured by a wearable device according to one embodiment.

[0012] FIG. 6A illustrates an example of wearing states of a wearable device according to one embodiment.

[0013] FIG. 6b illustrates an example of a graph representing temperatures in wearing states of a wearable device according to one embodiment.

[0014] FIG. 7 illustrates an example of a wearable device providing a notification to a user according to one embodiment.

[0015] FIG. 8A illustrates a position where a wearable device is worn, according to one embodiment.

[0016] FIG. 8b illustrates biometric data acquired by a wearable device according to one embodiment.

[0017] Figure 9 is a flowchart illustrating the operation of a wearable device according to one embodiment.

[0018] Figure 10 is a flowchart illustrating the operation of a wearable device according to one embodiment.

[0019] Figure 11 is a flowchart illustrating the operation of a wearable device according to one embodiment.

[0020] Figure 12 is a flowchart illustrating the operation of a wearable device according to one embodiment.

[0021] Figure 13 is a flowchart illustrating the operation of a wearable device according to one embodiment.

[0022] FIG. 14 is a block diagram of an electronic device within a network environment according to various embodiments.

[0023] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings so that those skilled in the art can easily implement the present disclosure. However, the present disclosure may be implemented in various different forms and is not limited to the embodiments described herein. In connection with the description of the drawings, the same or similar reference numerals may be used for identical or similar components. Furthermore, in the drawings and related descriptions, descriptions of well-known functions and configurations may be omitted for clarity and conciseness.

[0024] FIG. 1 illustrates an exemplary wearable device according to one embodiment.

[0025] Referring to FIGS. 1 and 2, a wearable device (101) (e.g., electronic device (1401) of FIG. 14) according to one embodiment may be configured to be wearable by a user. For example, the wearable device (101) may have a ring shape with a hole (15) provided so that a user can insert a body (or a part of the body) (100) (e.g., a finger) therein. However, the present invention is not limited thereto, and the wearable device (101) may have various shapes corresponding to the body in order to be worn on the body of a user.

[0026] In one embodiment, the wearable device (101) may include a housing (10).

[0027] Referring to FIG. 1, the housing (10) may form an exterior of the wearable device (101). For example, the housing (10) may form or define a first surface (10A), a second surface (10B), and a third surface (10C). When a user wears the wearable device (101), the first surface (10A) may surround the user's body so as to face the user's body (100). The first surface (10A) may at least partially contact the user's body (100). For example, the first region (31), the second region (32), and the third region (33) formed in the first surface (10A) may contact the user's body (100). The first region (31), the second region (32), and the third region (33) may be spaced apart from each other. The first region (31) may be positioned between the second region (32) and the third region (33). The second surface (10B) may be spaced apart from the first surface (10A) and may face in an opposite direction to the first surface (10A). The third surface (10C) may surround a space between the first surface (10A) and the second surface (10B). For example, the third surface (10C) may extend from an edge of the first surface (10A) to an edge of the second surface (10B). The housing (10) may be formed with a hole (15) defined by the first surface (10A) to accommodate a user's body (100). The first surface (10A) may be referred to as an inner surface and the second surface (10B) may be referred to as an outer surface.

[0028] In one embodiment, at least a portion of the first surface (10A) of the housing (10) may be formed by an insulating member. For example, the insulating member may form at least a first region (31), a second region (32), and a third region (33) of the first surface (10A). For example, the insulating member may form the first region (31), the second region (32), and the third region (33), and may also form a portion of the first surface (10A) extending from the first region (31), the second region (32), and the third region (33). The first to third regions (31, 32, 33) may be referred to as first to third sensing regions, first to third pattern regions, first to third Fresnel pattern regions, or first to third light-collecting regions, respectively.

[0029] In one embodiment, the second side (10B) and the third side (10C) of the housing (10) may be formed by a frame, but are not limited thereto. For example, the second side (10B) and / or the third side (10C) may be formed by a frame and an insulating member together.

[0030] In one embodiment, the frame of the housing (10) may be formed of metal and / or plastic. The frame and the insulating member may be coupled to each other. For example, the insulating member and the frame may be coupled through a process such as insert injection. For example, the insulating member coupled to the frame may be formed by injecting molten resin into a mold in which the frame is placed, but is not limited thereto. The insulating member may include, but is not limited to, a resin such as epoxy.

[0031] FIG. 2 illustrates a cross-section of an exemplary wearable device according to one embodiment.

[0032] Referring to FIG. 2, the wearable device (101) may include at least one light emitting unit (22, 24, 26) and at least one light receiving unit (23, 25, 27). In one embodiment, the wearable device (101) may include a substrate (28). In one embodiment, the wearable device (101) may include a processor (120), a controller (125), a memory (130), a temperature sensor (170), a motion sensor (173), a pressure sensor (175), an external temperature sensor (177), a lens (179), a battery (180), a power management module (183), a charging interface (185), a communication circuit (190), and an antenna (197).

[0033] In one embodiment, the substrate (28) may include a flexible printed circuit board or a rigid-flex printed circuit board. In one embodiment, the substrate (28) may be at least partially bendable. For example, the substrate (28) may include a bent portion to correspond to the curvature of the first surface (10A) having a ring shape.

[0034] In one embodiment, the processor (120) may correspond to the processor (1420) of FIG. 14. In one embodiment, the controller (125) may be included in the processor (1420) of FIG. 14. In one embodiment, the controller (125) may be included in the sensor module (1476) of FIG. 14. In one embodiment, the memory (130) may correspond to the memory (1430) of FIG. 14. In one embodiment, each of at least one light emitting unit (22, 24, 26), at least one light receiving unit (23, 25, 27), temperature sensor (170), motion sensor (173), pressure sensor (175), and external temperature sensor (177) may correspond to the sensor module (1476) of FIG. 14. In one embodiment, the battery (180) may correspond to the battery (1489) of FIG. 14. In one embodiment, the power management module (183) may correspond to the power management module (1488) of FIG. 14. In one embodiment, the communication circuit (190) may correspond to the communication module (1490) of FIG. 14. In one embodiment, the antenna (197) may correspond to the antenna module (1497) of FIG. 14. In one embodiment, the charging interface (185) may include a wired and / or wireless interface circuit for supplying power from an external power source for charging the battery (180).

[0035] In one embodiment, at least one light emitter (22, 24, 26) and at least one light receiver (23, 25, 27) may also be referred to as a photoplethysmography (PPG) sensor, but is not limited thereto. In one embodiment, at least one light emitter (22, 24, 26) and at least one light receiver (23, 25, 27) may also be referred to as a proximity sensor.

[0036] In one embodiment, at least one light emitting unit (22, 24, 26) and at least one light receiving unit (23, 25, 27) may be disposed on a substrate (28). For example, at least one light emitting unit (22, 24, 26) may be disposed on the substrate (28) so as to face the first surface (10A). For example, at least one light receiving unit (23, 25, 27) may be disposed on the substrate (28) so as to face the first surface (10A).

[0037] In one embodiment, the light emitting portion (22) and the light receiving portion (23) can face the first region (31) of the insulating member. The light emitting portion (22) and the light receiving portion (23) can be aligned with the first region (31) of the insulating member. The light emitting portion (22) and the light receiving portion (23) can overlap the first region (31). In one embodiment, the light emitting portion (24) and the light receiving portion (25) can face the second region (32) of the insulating member. The light emitting portion (24) and the light receiving portion (25) can be aligned with the second region (32) of the insulating member. The light emitting portion (24) and the light receiving portion (25) can overlap the second region (32). In one embodiment, the light emitting portion (26) and the light receiving portion (27) can face the third region (33) of the insulating member. The light emitting portion (26) and the light receiving portion (27) can be aligned to the third region (33) of the insulating member. The light emitting portion (26) and the light receiving portion (27) can overlap the third region (33).

[0038] In one embodiment, at least one light emitting unit (22, 24, 26) may be configured to emit light toward a user's body (100). In one embodiment, at least one light emitting unit (22, 24, 26) may be configured to emit light toward a user's body (100) under the control of a controller (125). Light emitted from at least one light emitting unit (22, 24, 26) may be transmitted to the user's body (100) through an insulating member. For example, light emitted from light emitting unit (22) may be transmitted to the user's body (100) through a first region (31). For example, light emitted from light emitting unit (24) may be transmitted to the user's body (100) through a second region (32). For example, light emitted from light emitting unit (26) may be transmitted to the user's body (100) through a third region (33). Light from at least one light emitting unit (22, 24, 26) may be reflected onto the user's body (100). The light reflected onto the user's body (100) may pass through an insulating member and reach at least one light-receiving unit (23, 25, 27). The light reflected onto the user's body (100) may reach at least one light-receiving unit (23, 25, 27) through at least one area (31, 32, 33). The at least one light-receiving unit (23, 25, 27) may receive light incident from the outside through the insulating member. In one embodiment, the at least one light-receiving unit (23, 25, 27) may be configured to receive light from the user's body (100) under the control of the controller (125). However, the present invention is not limited thereto. For example, light from at least one light-emitting element (22, 24, 26) can transmit (or pass through) the user's body (100). Light transmitted (or passed through) the user's body (100) can reach at least one light-receiving element (23, 25, 27) through at least one region (31, 32, 33).

[0039] In one embodiment, the motion sensor (173) may include an acceleration sensor and / or a gyro sensor. For example, the motion sensor (173) may be a three-axis sensor (e.g., an acceleration sensor). For example, the motion sensor (173) may be a six-axis sensor (e.g., an acceleration sensor and a gyro sensor).

[0040] In one embodiment, the pressure sensor (175) may be positioned on the substrate (28) so as to face the first surface (10A). In one embodiment, the pressure sensor (175) may measure a pressure value applied to at least a portion of the first surface (10A).

[0041] In one embodiment, an external temperature sensor (177) may be disposed on the substrate (28) so as to face the second surface (10B). The external temperature sensor (177) may measure the temperature of a temperature measurement target based on infrared rays emitted by the temperature measurement target. In one embodiment, a lens (179) may be provided to transmit infrared rays so that the infrared rays emitted by the temperature measurement target can be received by the external temperature sensor (177). The lens (179) may be disposed so as to face the second surface (10B).

[0042] In one embodiment, the processor (120) may acquire the user's biometric information using a sensor module. The processor (120) may detect the user's biometric information based on light emitted from at least one light emitting unit (22, 24, 26) and light received from at least one light receiving unit (23, 25, 27). For example, the biometric information may include, but is not limited to, information on heart rate and / or saturation of percutaneous oxygen (SpO2). For example, the biometric information may include information on arterial stiffness, blood pressure, or arterial age. Here, the heart rate may represent the number of heartbeats per unit time. The oxygen saturation may represent the ratio of the amount of hemoglobin combined with oxygen in the blood to the total amount of hemoglobin. The degree of arterial stiffness may represent the degree of hardening of the blood vessels. Blood pressure can indicate the pressure exerted on the blood vessel walls by blood pumped from the heart as it flows through them. Vascular age is a physiological indicator of vascular aging, and can be related to vascular stiffness. Biometric data can include information on stress, blood sugar, and / or irregular heart rhythm notification (IHRN).

[0043] Figure 3 is a block diagram of a wearable device (101).

[0044] Referring to FIG. 3, a wearable device (101) may include a processor (120), memory (130), a temperature sensor (170), a biosensor (171), a proximity sensor (172), a motion sensor (173), a pressure sensor (175), and a communication circuit (190).

[0045] The wearable device (101) may correspond to the electronic device (1401) of FIG. 14, but is not limited thereto. For example, the wearable device (101) may correspond to the electronic device (1402) of FIG. 14. The processor (120) of FIG. 3 may correspond to the processor (120) of FIG. 2. The memory (130) of FIG. 3 may correspond to the memory (130) of FIG. 2. The temperature sensor (170) of FIG. 3 may correspond to the temperature sensor (170) of FIG. 2. The biosensor (171) of FIG. 3 may correspond to at least one light-emitting unit (22, 24, 26) and at least one light-receiving unit (23, 25, 27) of FIG. 2. The motion sensor (173) of FIG. 3 may correspond to the motion sensor (173) of FIG. 2. The pressure sensor (175) of Fig. 3 may correspond to the pressure sensor (175) of Fig. 2. The communication circuit (190) of Fig. 3 may correspond to the communication circuit (190) of Fig. 2.

[0046] The proximity sensor (172) may be a sensor that emits infrared light and obtains the infrared light reflected from a finger. For example, the proximity sensor (172) may include at least one light-emitting unit (22, 24, 26) and at least one light-receiving unit (23, 25, 27). However, the present invention is not limited thereto. The proximity sensor (172) may be an electrode and / or a touch sensor. For example, the proximity sensor (172) may detect whether a body (100) is in contact with an electrode and / or a touch sensor.

[0047] In one embodiment, the processor (120) may establish a communication connection with an electronic device (102) via a communication circuit (190). Here, the electronic device (102) may be a device of various forms. For example, the electronic device (102) may be a portable communication device (e.g., a smartphone), a computer device, a portable multimedia device, a portable medical device, a camera, a wearable device (e.g., a watch), or a home appliance device. The electronic device (102) may correspond to the electronic device (1402) of FIG. 14, but is not limited thereto. For example, the electronic device (102) may correspond to the electronic device (1401) of FIG. 14.

[0048] Below, the operation of the wearable device (101) while it is not worn on the user's body (100) is described.

[0049] Fig. 4 illustrates an example of a state diagram of a wearable device (101). Referring to Fig. 4, the states of the wearable device (101) may transition between an unworn state (410), a worn state (420), and a worn state (430). Here, the unworn state (410) may refer to a state in which the wearable device (101) is unworn by the user. The worn state (420) may refer to a state in which the wearable device (101) is worn by the user. The worn state (430) may indicate how loosely (or tightly) the wearable device (101) is worn by the user.

[0050] The processor (120) may operate in a low power mode (or sleep mode) while the wearable device (101) is in an unworn state (410). Here, the low power mode (or sleep mode) may mean that functions other than a designated function are turned off. The low power mode (or sleep mode) may mean that functions other than a designated function are limited. The low power mode (or sleep mode) may mean that components other than a designated component are turned off. The low power mode (or sleep mode) may mean that power consumption of components other than a designated component is limited. For example, the operating frequency of the processor (120) may be reduced during the low power mode (or sleep mode). For example, during the low power mode (or sleep mode), sensors other than the motion sensor (173) (e.g., temperature sensor (170), biometric sensor (171), proximity sensor (172), and pressure sensor (175)) may be turned off. But it is not limited to this.

[0051] The processor (120) can obtain movement data indicating the movement of the wearable device (101) through the motion sensor (173). For example, the processor (120) can obtain movement data indicating three-axis movement (e.g., change in acceleration within space, or change in angular velocity within space). For example, the processor (120) can obtain movement data indicating six-axis movement (e.g., change in acceleration within space, and change in angular velocity within space).

[0052] The processor (120) can determine whether the wearable device (101) is moving based on the movement data. The processor (120) can determine whether the wearable device (101) is moving more than a specified distance (e.g., 50 centimeters) based on the movement data. If the wearable device (101) is moving more than the specified distance, the processor (120) can determine that the wearable device (101) is moving. If the wearable device (101) is moving less than the specified distance, the processor (120) can determine that the wearable device (101) is not moving.

[0053] The processor (120) can determine whether the wearable device (101) is worn by the user based on the movement data indicating movement of the wearable device (101). In response to the movement data indicating movement of the wearable device (101), the processor (120) can identify whether the wearable device (101) is worn. For example, the processor (120) can identify whether the wearable device (101) is worn if the wearable device (101) is identified as being moved more than a specified distance based on the movement data. Here, whether the wearable device (101) is worn can be identified by other sensors (e.g., a temperature sensor (170) and / or a proximity sensor (172)).

[0054] The processor (120) may release the low power mode (or sleep mode) based on whether the movement data indicates movement of the wearable device (101). The processor (120) may transition from the low power mode (or sleep mode) to the normal mode based on whether the movement data indicates movement of the wearable device (101). For example, the processor (120) may release the low power mode (or sleep mode) if it is determined that the wearable device (101) has moved more than a specified distance based on the movement data. Here, releasing the low power mode (or sleep mode) may mean that all functions are operating normally. Release of the low power mode (or sleep mode) may mean that all components are operating normally.

[0055] Below, an operation for identifying that a wearable device (101) is worn on a user's body (100) is described.

[0056] FIG. 5 illustrates an example of a graph showing the temperature measured by a wearable device (101) according to one embodiment.

[0057] In one embodiment, the processor (120) can identify that the wearable device (101) is worn by the user. In one embodiment, the processor (120) can identify that the wearable device (101) is worn by the user based on a temperature sensor (170) and / or a proximity sensor (172). The processor (120) can identify that the wearable device (101) is worn by the user while the state of the wearable device (101) is unworn (410).

[0058] In one embodiment, the processor (120) can identify that the wearable device (101) is worn by the user based on the temperature sensor (170). In one embodiment, the processor (120) can identify that the wearable device (101) is worn by the user based on the temperature value obtained through the temperature sensor (170). For example, the processor (120) can identify that the wearable device (101) is worn by the user based on whether the temperature value changes by more than a reference temperature value (e.g., 4 degrees). For example, the processor (120) can identify that the wearable device (101) is worn by the user based on whether the temperature value changes by more than a reference temperature value within a specified time (e.g., 10 seconds). For example, the processor (120) may identify that the wearable device (101) is worn by the user if the temperature value changes by more than a reference temperature value (e.g., 4 degrees) during a specific time period (e.g., a 10-second time period). However, 10 seconds and 4 degrees are merely examples and are not limited thereto.

[0059] For example, as shown in FIG. 5, if the difference between the temperature at point (T1) and the temperature at point (T2) about 10 seconds after point (T1) exceeds a reference temperature value (e.g., 4 degrees), the processor (120) can identify that the wearable device (101) has been worn by the user after point (T1).

[0060] In one embodiment, the processor (120) can identify that the wearable device (101) is worn by the user based on the proximity sensor (172). In one embodiment, the processor (120) can identify that the wearable device (101) is worn by the user based on an intensity value representing the intensity of light acquired through the proximity sensor (172). For example, the processor (120) can identify that the wearable device (101) is worn by the user based on whether the intensity value is greater than or equal to a reference intensity value. For example, when the intensity value is greater than or equal to the reference intensity value, the processor (120) can identify that the wearable device (101) is worn by the user.

[0061] In one embodiment, the processor (120) can identify that the wearable device (101) is worn by the user based on the temperature sensor (170) and the proximity sensor (172). The processor (120) can identify a first state of the wearable device (101) based on the temperature sensor (170). The processor (120) can identify a second state of the wearable device (101) based on the proximity sensor (172). The processor (120) can identify that the wearable device (101) is worn by the user when the first state indicates that the wearable device (101) is worn by the user and the second state indicates that the wearable device (101) is worn by the user. The processor (120) can identify that the wearable device (101) is not worn by the user if at least one of the first state or the second state indicates that the wearable device (101) is not worn by the user.

[0062] In one embodiment, when the wearable device (101) is identified as being worn by the user, the state of the wearable device (101) may transition from unworn (410) to worn (420).

[0063] Below, the operation of the wearable device (101) to identify the wearing state is described.

[0064] FIG. 6A illustrates examples of wearing states of a wearable device according to one embodiment. FIG. 6B illustrates examples of graphs representing temperatures in wearing states of a wearable device according to one embodiment.

[0065] In one embodiment, the processor (120) can identify a wearing state of the wearable device (101). In response to identifying that the wearable device (101) is worn by a user, the processor (120) can identify the wearing state of the wearable device (101). Here, the wearing state may be composed of a plurality of wearing states. The plurality of wearing states may indicate different degrees of looseness (or tightness) between the wearable device (101) and the body (100). The processor (120) can identify the wearing state of the wearable device (101) while the state of the wearable device (101) is wearing (420).

[0066] For example, the plurality of wearing states (601, 603, 605) may correspond to a plurality of finger circumferences. For example, the plurality of wearing states (601, 603, 605) may correspond to a state worn by each of fingers having a finger circumference within a specified range (e.g., 44 millimeters to 69 millimeters). For example, the plurality of wearing states (601, 603, 605) may be set to have a 1 millimeter interval within a range between about 44 millimeters and about 69 millimeters. For example, the first wearing state may correspond to a state worn by a finger of about 44 millimeters. For example, the second wearing state may correspond to a state worn by a finger of about 45 millimeters. For example, the 24th, 25th, and 26th wearing states may each correspond to a state worn by fingers of 67, 68, and 69 millimeters, respectively, but is not limited thereto.

[0067] For example, the plurality of wearing states (601, 603, 605) can be divided into N wearing states. For example, the plurality of wearing states (601, 603, 605) can include N-2 wearing states between the tight state (605) and the loose state (601). For example, when N is 3, the plurality of wearing states (601, 603, 605) can be divided into three wearing states. For example, the plurality of wearing states (601, 603, 605) can be divided into the tight state (605), the normal state (603), or the loose state (601). In this case, when a finger having a finger circumference of a portion (e.g., about 44 to about 49 millimeters) among the finger circumferences in a specified range (e.g., about 44 to about 69 millimeters) is worn, the processor (120) may determine the wearing state of the wearable device (101) as a loose state (601). When a finger having a finger circumference of a portion (e.g., about 50 to about 59 millimeters) among the finger circumferences in a specified range (e.g., about 44 to 69 millimeters) is worn, the processor (120) may determine the wearing state of the wearable device (101) as a normal state (603). When a finger having a finger circumference within a portion (e.g., about 60 to about 69 millimeters) of a specified range (e.g., about 44 millimeters to about 69 millimeters) of finger circumferences is worn, the processor (120) may determine the wearing state of the wearable device (101) as a tight state (605). However, this is not limited thereto. Hereinafter, a plurality of wearing states may be described as three wearing states.

[0068] The processor (120) can identify the wearing state of the wearable device (101) based on the temperature sensor (170). The processor (120) can identify one wearing state corresponding to temperature data indicating a temperature value measured by the temperature sensor (170) among a plurality of wearing states. For example, the processor (120) can identify one wearing state corresponding to a change in a temperature value indicated by the temperature data among a plurality of wearing states (601, 603, 605). For example, the processor (120) can identify one wearing state corresponding to a change in a temperature value indicated by temperature data acquired over a specified period of time. For example, the processor (120) can identify one wearing state corresponding to a variance, deviation, and / or standard deviation of a temperature value indicated by temperature data acquired over a specified period of time. For example, when a range is set for each of a plurality of wearing states, the processor (120) can identify a wearing state to which a value indicating a change in a temperature value (e.g., variance, deviation, and / or standard deviation) belongs as a wearing state of the wearable device (101).

[0069] For example, referring to FIG. 6B, the temperature change range in the loose state (601) may be greater than the temperature change range in the tight state (605). The temperature change range in the normal state (603) may be located between the temperature change range in the loose state (601) and the temperature change range in the tight state (605). In addition, the standard deviation of the temperature in the loose state (601) may be greater than the standard deviation of the temperature in the tight state (605). The standard deviation of the temperature in the normal state (603) may be located between the temperature standard deviation in the loose state (601) and the temperature standard deviation in the tight state (605). For example, if the standard deviations of the loose state (601), the normal state (603), and the tight state (605) are about 0.032, about 0.051, and about 0.084, respectively, the standard deviation of the temperature for distinguishing the loose state (601), the normal state (603), or the tight state (605) can be determined by a value between about 0.032 and about 0.051 (e.g., about 0.042) and a value between about 0.051 and about 0.084 (e.g., about 0.068). For example, the processor (120) may determine the state of the wearable device (101) as one of a loose state (601), a normal state (603), or a tight state (605) depending on which of three sections, where the standard deviation of the temperature values ​​represented by the temperature data acquired during a specified period of time is approximately 0.042 and approximately 0.068, falls.

[0070] In one embodiment, when the wearing state of the wearable device (101) is identified, the state of the wearable device (101) may transition from wearing (420) to wearing state (430).

[0071] Below, an operation of a wearable device (101) providing a notification to a user based on a wearing state is described.

[0072] FIG. 7 illustrates an example of a wearable device providing a notification to a user according to one embodiment.

[0073] In one embodiment, the processor (120) can identify a wearing state. The processor (120) can identify a wearing state based on temperature data representing a temperature value measured by a temperature sensor (170). For example, the processor (120) can identify a wearing state based on a change in a temperature value represented by temperature data acquired over a specified period of time. For example, the processor (120) can identify a wearing state based on a variance, deviation, and / or standard deviation of a temperature value represented by temperature data acquired over a specified period of time.

[0074] In one embodiment, the processor (120) may output a notification indicating the identified wearing state. The processor (120) may cause the electronic device (102) to output a notification indicating the wearing state. For example, the processor (120) may transmit data indicating the identified wearing state to the electronic device (102) based on a communication connection with the electronic device (102). The electronic device (102) may output a notification indicating the wearing state based on data indicating the identified wearing state received from the wearable device (101). However, the present invention is not limited thereto. The processor (120) may output a notification indicating the wearing state through the wearable device (101). For example, the processor (120) may output a notification indicating the wearing state through a user-interactive component included in the wearable device (101) (e.g., the sound output module (1455), the display module (1460), and / or the haptic module (1479) of FIG. 14). Here, the notification indicating the wearing state may include information indicating whether the wearing state is appropriate (e.g., “Change the wearing finger”, “This is a wearing that fits your finger”). However, the present invention is not limited thereto.

[0075] For example, referring to FIG. 7, in a loose wearing state (701), the wearable device (101) may provide a user with a notification (e.g., “loose wearing” and / or “change the wearing finger”) to inform the user of a loose wearing state through the electronic device (102). In a normal wearing state (703), the wearable device (101) may provide a user with a notification (e.g., “normal wearing” and / or “fitting the finger”) to inform the user of a normal wearing state through the electronic device (102). In a tight wearing state (705), the wearable device (101) may provide a user with a notification (e.g., “tight wearing” and / or “change the wearing finger”) to inform the user of a tight wearing state through the electronic device (102).

[0076] Below, an operation of a wearable device (101) providing a notification to a user based on a change in the wearing state is described.

[0077] In one embodiment, the processor (120) can identify a change in the wearing state. For example, the processor (120) can identify a change in the wearing state while the wearable device (101) is worn by the user. The processor (120) can identify a change in the wearing state based on temperature data representing a temperature value measured by the temperature sensor (170). For example, the processor (120) can identify a change in the wearing state based on a change in a temperature value represented by temperature data acquired over a specified period of time. For example, the processor (120) can identify a change in the wearing state based on a variance, deviation, and / or standard deviation of the temperature values ​​represented by the temperature data acquired over a specified period of time.

[0078] In one embodiment, the processor (120) can identify whether the changed wearing state is a designated wearing state. Here, the designated wearing state may be a tight wearing state.

[0079] In one embodiment, the processor (120) may output a notification guiding a change in the wearing state based on the identification that the changed wearing state is a designated wearing state.

[0080] In one embodiment, the processor (120) may output the notification based on the changed wearing state being maintained in the designated wearing state for a designated period of time or longer. For example, the processor (120) may output the notification based on the wearing state of the wearable device (101) being maintained in the designated wearing state for a designated period of time or longer after the changed wearing state is identified as the designated wearing state. Here, the designated period of time may be set to be shorter than the period of time during which the user feels discomfort due to wearing the wearable device (101). The period of time during which the user feels discomfort due to wearing the wearable device (101) may be experimentally measured.

[0081] In one embodiment, the processor (120) may determine whether to output a notification guiding a change in the wearing state through the pressure sensor (175) based on the identification that the changed wearing state is a designated wearing state. For example, the processor (120) may output the notification based on a pressure value indicated by a pressure signal acquired through the pressure sensor (175) in response to the identification that the changed wearing state is a designated wearing state. For example, the processor (120) may output the notification based on a pressure value indicated by a pressure signal acquired through the pressure sensor (175) exceeding a designated pressure value in response to the identification that the changed wearing state is a designated wearing state.

[0082] In one embodiment, the processor (120) may output a notification guiding a change in the wearing state through the electronic device (102). The processor (120) may cause the electronic device (102) to output a notification guiding a change in the wearing state. For example, the processor (120) may transmit data indicating an identified wearing state to the electronic device (102) based on a communication connection with the electronic device (102). The electronic device (102) may output a notification guiding a change in the wearing state based on data indicating an identified wearing state received from the wearable device (101). However, the present invention is not limited thereto. The processor (120) may output a notification guiding a change in the wearing state through the wearable device (101). For example, the processor (120) may output a notification guiding a change in the wearing state through a user-interactive component included in the wearable device (101) (e.g., the sound output module (1455), the display module (1460), and / or the haptic module (1479) of FIG. 14). Here, the notification guiding a change in the wearing state may include information indicating a suitable finger position for the user (e.g., “Change to the fourth finger”). However, the present invention is not limited thereto.

[0083] Below, the operation of the wearable device (101) to obtain the user's biometric information based on the wearing state is described.

[0084] FIG. 8A illustrates a position where a wearable device is worn, according to one embodiment. FIG. 8B illustrates biometric data acquired by a wearable device, according to one embodiment.

[0085] In one embodiment, the processor (120) may obtain an input requesting acquisition of biometric information. Here, the input requesting acquisition of biometric information may be a trigger that instructs acquisition of biometric information. The input requesting acquisition of biometric information may be generated by the processor (120) based on the satisfaction of a specified condition. For example, when acquisition of biometric information is required periodically or aperiodically, the processor (120) may generate an input requesting acquisition of biometric information periodically or aperiodically. The input requesting acquisition of biometric information may be obtained from a user. For example, the processor (120) may obtain a user input requesting acquisition of biometric information based on an input module (e.g., input module (1450) of FIG. 14) provided in the wearable device (101). The input requesting acquisition of biometric information may be obtained from the electronic device (102).

[0086] In one embodiment, the processor (120) can identify whether the wearing state is a wearing state designated for acquiring biometric data. In one embodiment, in response to receiving an input requesting acquisition of biometric information, the processor (120) can identify whether the wearing state is a wearing state designated for acquiring biometric data. In one embodiment, the processor (120) can identify whether the wearing state corresponds to a type of biometric information requested for acquisition among a plurality of wearing states. Here, the corresponding wearing state may vary depending on the type of biometric information requested for acquisition. The number of wearing states corresponding to heart rate may be greater than the number of wearing states corresponding to oxygen saturation. For example, heart rate may be acquired in all of the tight state, normal state, and loose state. For example, oxygen saturation may be acquired in the tight state or normal state.

[0087] For example, if the biometric information requested for acquisition is oxygen saturation and the wearing state is loose, the processor (120) can identify that the wearing state is a different wearing state from the designated wearing state. For example, if the biometric information requested for acquisition is oxygen saturation and the wearing state is tight or normal, the processor (120) can identify that the wearing state is a designated wearing state.

[0088] For example, referring to FIG. 8a, the fingers (811, 813, 815, 817, 819) of the user's hand (810) may have different thicknesses (or circumferences). For example, the thickness (or circumference) may become smaller from the thumb (811) to the little finger (819). For example, when the wearable device (101) is worn on the ring finger (817) or the little finger (819), the processor (120) may identify that the wearable device (101) is worn in a loose state. For example, when the wearable device (101) is worn on the middle finger (815), the processor (120) may identify that the wearable device (101) is worn in a normal state. For example, when the wearable device (101) is worn on the thumb (811) or the index finger (813), the processor (120) may identify that the wearable device (101) is worn in a tight state.

[0089] In one embodiment, the processor (120) may output a notification guiding a change in the wearing state in response to identifying that the wearing state is a different wearing state from a designated wearing state. The processor (120) may cause the electronic device (102) to output a notification guiding a change in the wearing state. For example, the processor (120) may transmit data indicating the identified wearing state to the electronic device (102) based on a communication connection with the electronic device (102). The electronic device (102) may output a notification guiding a change in the wearing state based on data indicating the identified wearing state received from the wearable device (101). However, the present invention is not limited thereto. The processor (120) may output a notification guiding a change in the wearing state through the wearable device (101). For example, the processor (120) may output a notification guiding a change in the wearing state through a user-interactive component included in the wearable device (101) (e.g., an audio output module (1455), a display module (1460), and / or a haptic module (1479) of FIG. 14).

[0090] In one embodiment, the processor (120) may acquire biometric data through the biometric sensor (171) in response to identifying that the wearing state is a designated wearing state. For example, the processor (120) may acquire biometric data by acquiring the reflected light of light emitted through at least one light emitting unit (22, 24, 26) through at least one light receiving unit (23, 25, 27). Here, the biometric data may include pulse wave information according to changes in blood flow of the body (100) on which the wearable device (101) is worn. The biometric data may include information related to the waveform of the pulse wave in which the blood flow in the blood vessel changes over time as the heart repeats contraction and relaxation. For example, the processor (120) may acquire biometric data including the waveform (820) of the pulse wave illustrated in FIG. 8B through the biometric sensor (171).

[0091] In one embodiment, the processor (120) can obtain biometric information based on the acquired biometric data. In one embodiment, the processor (120) can obtain biometric information based on the waveform of the pulse wave indicated by the acquired biometric data. For example, the processor (120) can obtain heartbeat information (or heart rate) based on the number of peak values ​​of the waveform of the pulse wave. For example, the processor (120) can obtain oxygen saturation information based on the ratio between the intensity of the pulse wave indicated by the reflected light of infrared light and the intensity of the pulse wave indicated by the reflected light of red light.

[0092] In one embodiment, the processor (120) may select a coefficient corresponding to the identified wearing state from among a plurality of coefficients. For example, the processor (120) may select a coefficient corresponding to a wearing state for correcting a value indicated by biometric information. Here, a plurality of coefficients for a plurality of wearing states may be preset for at least one of heart rate, oxygen saturation, vascular stiffness, blood pressure, vascular age, stress, blood sugar, or IHRN. For example, for heart rate, coefficients corresponding to a tight state, a normal state, or a loose state may be preset. Here, the coefficient may be a value to compensate for the fact that the pulse wave is not measured accurately as it goes from a tight state to a loose state. For example, referring to FIG. 8B, the processor (120) can identify all peaks (821, 822, 823, 824, 825, 826, 827) indicated by the waveform (820) of the pulse wave through the biometric data acquired in a tight state or a normal state. For example, referring to FIG. 8B, at least some waveforms of the waveform (820) of the pulse wave may not be lost in the biometric data acquired through the biometric sensor (171) in a tight state or a normal state. The processor (120) can identify only some of all peaks (821, 822, 823, 824, 825, 826, 827) indicated by the waveform (820) of the pulse wave through the biometric data acquired in a loose state. For example, in the loose state, at least some of the pulse wave waveforms (820) may be lost in the biometric data acquired through the biometric sensor (171). Accordingly, in the loose state, some of the peaks (821, 822, 823, 824, 825, 826, 827) may not be identified.

[0093] In one embodiment, the processor (120) may adjust the acquired biometric information based on the selected coefficient. The processor (120) may adjust biometric information regarding at least one of heart rate, oxygen saturation, vascular stiffness, blood pressure, vascular age, stress, blood sugar, or IHRN based on the selected coefficient. For example, the processor (120) may increase the heart rate based on the coefficient corresponding to the relaxed state. For example, the processor (120) may adjust the heart rate by multiplying the heart rate acquired in the relaxed state by the coefficient corresponding to the relaxed state.

[0094] Below, the operation of obtaining information on the finger of a user wearing a wearable device (101) is described.

[0095] In one embodiment, the processor (120) can identify the wearing state of the wearable device (101). For example, the processor (120) can identify which finger of the user the wearable device (101) is worn on. For example, when the wearable device (101) is worn in an unworn state, the processor (120) can identify which finger of the user the wearable device (101) is worn on. For example, the processor (120) can identify which finger of the user the wearable device (101) is worn on based on the wearing state identified when the wearable device (101) is worn in an unworn state.

[0096] In one embodiment, the processor (120) may identify on which finger of the user the wearable device (101) is worn based on information related to the user's body (100). For example, the processor (120) may identify on which finger of the user the wearable device (101) is worn based on information about the thickness (or circumference) of the user's finger. For example, the processor (120) may compare the finger thickness (or circumference) indicated by the wearing state with information about the thickness (or circumference) of the user's finger to identify on which finger of the user the wearable device (101) is worn. For example, if the circumference of the user's index finger is about 57 millimeters, the circumference of the middle finger is about 56 millimeters, and the circumference of the ring finger is about 55 millimeters, the processor (120) may identify that the wearable device (101) is worn on a finger corresponding to a change in a temperature value indicated by the temperature data. For example, the processor (120) can determine that the wearing state of the wearable device (101) is tight when the wearable device (101) is worn on a finger having a circumference of about 57 millimeters. The processor (120) can determine that the wearing state of the wearable device (101) is normal when the wearable device (101) is worn on a finger having a circumference of about 56 millimeters. The processor (120) can determine that the wearing state of the wearable device (101) is loose when the wearable device (101) is worn on a finger having a circumference of about 55 millimeters.

[0097] According to an embodiment, when the processor (120) detects that the wearable device (101) is worn after guiding the user to wear it with a designated finger, the processor (120) may obtain information about the thickness (or circumference) of the user's designated finger. In addition, when the processor (120) detects that the wearable device (101) is worn after guiding the user to wear it with a designated finger, the processor (120) may obtain information about the thickness (or circumference) of the user's designated finger and / or changes in the thickness (or circumference) of the finger during the user's sleep.

[0098] Below, an operation of providing a notification based on the finger of a user wearing a wearable device (101) is described.

[0099] In one embodiment, the processor (120) may obtain user input based on an interaction between the wearable device (101) and the user. For example, when the wearable device (101) is worn on the user's body (100) and the user points to a point using the body (100) or moves along a designated path, the processor (120) may obtain the motion using the body (100) as the user's input. However, if the wearable device (101) is not worn on an appropriate location (e.g., the index finger) on the body (100), the user's input may not be properly obtained. Accordingly, in order for the user to smoothly perform a gesture operation, it is necessary to guide the wearable device (101) so that it is worn on an appropriate finger of the user. An operation for this purpose may be described below.

[0100] In one embodiment, the processor (120) can identify the wearing state of the wearable device (101). For example, the processor (120) can identify which finger of the user the wearable device (101) is worn on. For example, when the wearable device (101) is worn in an unworn state, the processor (120) can identify which finger of the user the wearable device (101) is worn on. For example, the processor (120) can identify which finger of the user the wearable device (101) is worn on based on the wearing state identified when the wearable device (101) is worn in an unworn state.

[0101] In one embodiment, the processor (120) can determine whether the wearable device (101) is worn on a designated finger of the user. Here, the designated finger may be a finger designated for gesture input (e.g., an index finger).

[0102] In one embodiment, the processor (120) may output a notification guiding a change in the wearing state in response to the wearable device (101) being identified as being worn on a finger other than the user's designated finger. The processor (120) may cause the electronic device (102) to output a notification guiding a change in the wearing state. For example, the processor (120) may transmit data indicating the identified wearing state to the electronic device (102) based on a communication connection with the electronic device (102). The electronic device (102) may output a notification guiding a change in the wearing state based on the data indicating the identified wearing state received from the wearable device (101). However, the present invention is not limited thereto. The processor (120) may output a notification guiding a change in the wearing state through the wearable device (101). For example, the processor (120) may output a notification guiding a change in the wearing state through a user-interactive component included in the wearable device (101) (e.g., an audio output module (1455), a display module (1460), and / or a haptic module (1479) of FIG. 14).

[0103] In one embodiment, the processor (120) may obtain motion data representing movement of the wearable device (101) through the motion sensor (173) in response to the wearable device (101) being identified as being worn on a user's designated finger. For example, the processor (120) may obtain motion data representing three-axis motion (e.g., change in acceleration in space, or change in angular velocity in space). For example, the processor (120) may obtain motion data representing six-axis motion (e.g., change in acceleration in space, and change in angular velocity in space).

[0104] In one embodiment, the processor (120) can identify a gesture corresponding to a movement path of the wearable device (101) indicated by the movement data. In one embodiment, the processor (120) can obtain a gesture corresponding to a movement path of the wearable device (101) indicated by the movement data as a user input.

[0105] Below, an operation of providing a notification based on the position of the hand on which the wearable device (101) is worn is described.

[0106] In one embodiment, the processor (120) may acquire a movement trajectory of the body (100) while the wearable device (101) is worn on the user's body (100). The movement trajectory of the body (100) may be fed back to the user. For example, to inform the user whether a golf swing, a tennis stroke, and / or a baseball pitching motion have been properly performed, the processor (120) may feed back the movement trajectory of the body (100) to the user. To this end, the wearable device (101) needs to be worn on a finger of the user's designated dominant hand. Accordingly, it is necessary to guide the wearable device (101) so that it can be worn on an appropriate hand of the user so that the movement trajectory can be properly collected during the user's exercise. An operation for this purpose may be described below.

[0107] In one embodiment, the processor (120) can identify the wearing state of the wearable device (101).

[0108] In one embodiment, the processor (120) may obtain motion data representing movement of the wearable device (101) through the motion sensor (173) in response to the wearable device (101) being identified as being worn by the user. For example, the processor (120) may obtain motion data representing three-axis motion (e.g., change in acceleration in space, or change in angular velocity in space). For example, the processor (120) may obtain motion data representing six-axis motion (e.g., change in acceleration in space, and change in angular velocity in space).

[0109] In one embodiment, the processor (120) may obtain a tracking input for tracking a movement path of the wearable device (101) (or a movement path of the user's hand (or arm)). In one embodiment, the processor (120) may obtain movement data representing the movement of the wearable device (101) through the motion sensor (173) in response to the tracking input.

[0110] In one embodiment, the processor (120) can identify a movement path of the wearable device (101) indicated by the movement data.

[0111] In one embodiment, the processor (120) may identify the position of the hand on which the wearable device (101) is worn based on the movement path of the wearable device (101) indicated by the movement data. For example, the processor (120) may identify the hand that can move along the movement path of the wearable device (101) among both hands as the hand on which the wearable device (101) is worn. For example, if at least a portion of the movement path of the wearable device (101) is outside the range of motion of either the left or right arm, the processor (120) may identify that the wearable device (101) is worn on the hand of the other arm. However, the present invention is not limited thereto.

[0112] In one embodiment, the processor (120) can determine whether the wearable device (101) is worn on a designated hand of the user. Here, the designated hand may be the user's primary hand. The primary hand may be the hand designated for the user's exercise (e.g., golf, tennis, baseball).

[0113] In one embodiment, the processor (120) may output a notification guiding a change in the wearing state in response to the wearable device (101) being identified as being worn on a hand other than the user's designated hand. The processor (120) may cause the electronic device (102) to output a notification guiding a change in the wearing state. For example, the processor (120) may transmit data indicating the identified wearing state to the electronic device (102) based on a communication connection with the electronic device (102). The electronic device (102) may output a notification guiding a change in the wearing state based on the data indicating the identified wearing state received from the wearable device (101). However, the present invention is not limited thereto. The processor (120) may output a notification guiding a change in the wearing state through the wearable device (101). For example, the processor (120) may output a notification guiding a change in the wearing state through a user-interactive component included in the wearable device (101) (e.g., an audio output module (1455), a display module (1460), and / or a haptic module (1479) of FIG. 14).

[0114] In one embodiment, the processor (120) may provide movement data to the user in response to the wearable device (101) being identified as being worn on the user's designated hand. For example, the processor (120) may cause the electronic device (102) to display a movement trajectory based on the movement data. For example, the processor (120) may transmit the movement data to the electronic device (102) based on a communication connection with the electronic device (102). The electronic device (102) may display the movement trajectory based on the movement data received from the wearable device (101). However, the present invention is not limited thereto.

[0115] Figure 9 is a flowchart illustrating the operation of a wearable device according to one embodiment.

[0116] In the following examples, the operations may be performed sequentially, but are not necessarily sequential. For example, the order of the operations may be changed, and at least two operations may be performed in parallel.

[0117] Figure 9 can be explained with reference to Figures 1 to 6b.

[0118] Referring to FIG. 9, in operation 910, the processor (120) may identify wearing. In one embodiment, the processor (120) may identify that the wearable device (101) is worn by the user based on a temperature sensor (170) and / or a proximity sensor (172). The processor (120) may identify that the wearable device (101) is worn by the user while the state of the wearable device (101) is unworn (410).

[0119] In one embodiment, the processor (120) can identify that the wearable device (101) is worn by the user based on the temperature sensor (170). In one embodiment, the processor (120) can identify that the wearable device (101) is worn by the user based on the temperature value obtained through the temperature sensor (170). For example, the processor (120) can identify that the wearable device (101) is worn by the user based on whether the temperature value changes by more than a reference temperature value. For example, the processor (120) can identify that the wearable device (101) is worn by the user based on whether the temperature value changes by more than a reference temperature value within a specified time period.

[0120] In one embodiment, the processor (120) can identify that the wearable device (101) is worn by the user based on the proximity sensor (172). In one embodiment, the processor (120) can identify that the wearable device (101) is worn by the user based on an intensity value representing the intensity of light acquired through the proximity sensor (172). For example, the processor (120) can identify that the wearable device (101) is worn by the user based on whether the intensity value is greater than or equal to a reference intensity value. For example, when the intensity value is greater than or equal to the reference intensity value, the processor (120) can identify that the wearable device (101) is worn by the user.

[0121] In one embodiment, the processor (120) can identify that the wearable device (101) is worn by the user based on the temperature sensor (170) and the proximity sensor (172). The processor (120) can identify a first state of the wearable device (101) based on the temperature sensor (170). The processor (120) can identify a second state of the wearable device (101) based on the proximity sensor (172). The processor (120) can identify that the wearable device (101) is worn by the user when the first state indicates that the wearable device (101) is worn by the user and the second state indicates that the wearable device (101) is worn by the user. The processor (120) can identify that the wearable device (101) is not worn by the user if at least one of the first state or the second state indicates that the wearable device (101) is not worn by the user.

[0122] In operation 920, the processor (120) may identify a wearing state. In one embodiment, the processor (120) may identify a wearing state of the wearable device (101). In response to identifying that the wearable device (101) is worn by the user, the processor (120) may identify the wearing state of the wearable device (101). Here, the wearing state may be composed of multiple wearing states. The multiple wearing states may indicate different degrees of looseness (or tightness) between the wearable device (101) and the body (100). The processor (120) may identify the wearing state of the wearable device (101) while the state of the wearable device (101) is wearing (420).

[0123] For example, the plurality of wearing states (601, 603, 605) may correspond to a plurality of finger circumferences. For example, the plurality of wearing states (601, 603, 605) may correspond to a state worn by each of the fingers having a finger circumference within a specified range. For example, the plurality of wearing states (601, 603, 605) may be set to have a 1 millimeter interval within the specified range. However, the present invention is not limited thereto.

[0124] For example, the plurality of wearing states (601, 603, 605) can be divided into N wearing states. For example, the plurality of wearing states (601, 603, 605) can include N-2 wearing states between the tight state (605) and the loose state (601). For example, when N is 3, the plurality of wearing states (601, 603, 605) can be divided into 3 wearing states.

[0125] The processor (120) can identify the wearing state of the wearable device (101) based on the temperature sensor (170). The processor (120) can identify one wearing state corresponding to temperature data indicating a temperature value measured by the temperature sensor (170) among a plurality of wearing states. For example, the processor (120) can identify one wearing state corresponding to a change in a temperature value indicated by the temperature data among a plurality of wearing states (601, 603, 605). For example, the processor (120) can identify one wearing state corresponding to a change in a temperature value indicated by temperature data acquired over a specified period of time. For example, the processor (120) can identify one wearing state corresponding to a variance, deviation, and / or standard deviation of a temperature value indicated by temperature data acquired over a specified period of time. For example, when a range is set for each of a plurality of wearing states, the processor (120) can identify a wearing state to which a value indicating a change in a temperature value (e.g., variance, deviation, and / or standard deviation) belongs as a wearing state of the wearable device (101).

[0126] Figure 10 is a flowchart illustrating the operation of a wearable device according to one embodiment.

[0127] In the following examples, the operations may be performed sequentially, but are not necessarily sequential. For example, the order of the operations may be changed, and at least two operations may be performed in parallel.

[0128] Figure 10 can be explained with reference to Figures 1 to 6b.

[0129] Referring to FIG. 10, in operation 1010, the processor (120) can identify a first state based on the temperature sensor (170). The processor (120) can identify a first state of the wearable device (101) based on the temperature sensor (170). Here, the first state of the wearable device (101) can indicate one of the wearing of the wearable device (101) (410) or the wearing of the wearable device (101) (420).

[0130] In one embodiment, the processor (120) may identify the first state of the wearable device (101) based on a temperature value obtained through the temperature sensor (170). For example, the processor (120) may identify the first state of the wearable device (101) based on whether the temperature value changes by more than a reference temperature value (e.g., 4 degrees). For example, the processor (120) may identify the first state of the wearable device (101) based on whether the temperature value changes by more than a reference temperature value within a specified time (e.g., 10 seconds).

[0131] In operation 1020, the processor (120) can identify a second state based on the proximity sensor (172). The processor (120) can identify a second state of the wearable device (101) based on the proximity sensor (172). Here, the second state of the wearable device (101) can indicate one of the wearable device (101) being unworn (410) or the wearable device (101) being worn (420).

[0132] In one embodiment, the processor (120) may identify the second state of the wearable device (101) based on an intensity value representing the intensity of light acquired through the proximity sensor (172). For example, the processor (120) may identify the second state of the wearable device (101) based on whether the intensity value is greater than or equal to a reference intensity value.

[0133] In operation 1030, the processor (120) can identify wearing based on the first state and the second state.

[0134] The processor (120) can identify that the wearable device (101) is worn by the user when the first state indicates that the wearable device (101) is worn by the user and the second state indicates that the wearable device (101) is worn by the user. The processor (120) can identify that the wearable device (101) is not worn by the user when at least one of the first state or the second state indicates that the wearable device (101) is not worn by the user.

[0135] Figure 11 is a flowchart illustrating the operation of a wearable device according to one embodiment.

[0136] In the following examples, the operations may be performed sequentially, but are not necessarily sequential. For example, the order of the operations may be changed, and at least two operations may be performed in parallel.

[0137] Figure 11 can be explained with reference to Figures 1 to 6b.

[0138] Referring to FIG. 11, in operation 1110, the processor (120) may obtain movement data of the wearable device (101) based on the motion sensor (173). In one embodiment, the processor (120) may obtain movement data indicating the movement of the wearable device (101) through the motion sensor (173) while the state of the wearable device (101) is unworn (410). In one embodiment, the processor (120) may obtain movement data indicating the movement of the wearable device (101) through the motion sensor (173) while operating in a low power mode (or sleep mode). For example, the processor (120) may obtain movement data indicating a three-axis movement (e.g., a change in acceleration in space, or a change in angular velocity in space). For example, the processor (120) can obtain motion data representing six-axis motion (e.g., changes in acceleration within space, and changes in angular velocity within space).

[0139] In operation 1120, the processor (120) can determine whether the wearable device (101) is moving. Based on the movement data, the processor (120) can determine whether the wearable device (101) moves more than a specified distance (e.g., 50 centimeters). If the wearable device (101) moves more than the specified distance, the processor (120) can determine that the wearable device (101) has moved. If the wearable device (101) moves less than the specified distance, the processor (120) can determine that the wearable device (101) has not moved.

[0140] In operation 1120, if it is determined that the wearable device (101) has moved, the processor (120) may perform operation 1130. In operation 1120, if it is determined that the wearable device (101) has not moved, the processor (120) may perform operation 1110 again.

[0141] In operation 1130, the processor (120) can identify whether the wearable device (101) is worn. The processor (120) can determine whether the wearable device (101) is worn by the user based on the movement data indicating movement of the wearable device (101). The processor (120) can identify whether the wearable device (101) is worn in response to the movement data indicating movement of the wearable device (101). For example, the processor (120) can identify whether the wearable device (101) is worn if the wearable device (101) is identified as being moved by a specified distance or more based on the movement data. For example, the processor (120) can identify whether the wearable device (101) is worn by the user based on the temperature sensor (170) and / or the proximity sensor (172). The processor (120) can identify that the wearable device (101) is worn by the user while the state of the wearable device (101) is unworn (410).

[0142] Figure 12 is a flowchart illustrating the operation of a wearable device according to one embodiment.

[0143] In the following examples, the operations may be performed sequentially, but are not necessarily sequential. For example, the order of the operations may be changed, and at least two operations may be performed in parallel.

[0144] Figure 12 can be explained with reference to Figures 1 to 6b.

[0145] Referring to FIG. 12, in operation 1210, the processor (120) may identify a request for acquisition of biometric information. Here, the input requesting acquisition of biometric information may be a trigger that instructs acquisition of biometric information. The input requesting acquisition of biometric information may be generated from the processor (120) based on the satisfaction of a specified condition. For example, when acquisition of biometric information is required periodically or aperiodically, the processor (120) may generate an input requesting acquisition of biometric information periodically or aperiodically. The input requesting acquisition of biometric information may be obtained from a user. For example, the processor (120) may obtain a user input requesting acquisition of biometric information based on an input module (e.g., input module (1450) of FIG. 14) provided in the wearable device (101). The input requesting acquisition of biometric information may be obtained from the electronic device (102).

[0146] In operation 1220, the processor (120) may determine whether the wearing state is a wearing state for acquiring biometric data. In one embodiment, the processor (120) may identify whether the wearing state of the wearable device (101) is a wearing state designated for acquiring biometric data. In one embodiment, in response to receiving an input requesting acquisition of biometric information, the processor (120) may identify whether the wearing state is a wearing state designated for acquiring biometric data. In one embodiment, the processor (120) may identify whether the wearing state corresponds to a type of biometric information requested for acquisition among a plurality of wearing states. Here, the corresponding wearing state may vary depending on the type of biometric information requested for acquisition. The number of wearing states corresponding to heart rate may be greater than the number of wearing states corresponding to oxygen saturation. For example, heart rate may be acquired in all of a tight state, a normal state, and a loose state. For example, oxygen saturation may be acquired in a tight state or a normal state.

[0147] In operation 1220, if it is determined that the wearing state of the wearable device (101) is a wearing state for acquiring biometric data, the processor (120) may perform operation 1230. In operation 1220, if it is determined that the wearing state of the wearable device (101) is not a wearing state for acquiring biometric data, the processor (120) may perform operation 1240.

[0148] In operation 1230, the processor (120) can obtain biometric information.

[0149] In one embodiment, the processor (120) may acquire biometric data through the biometric sensor (171) in response to identifying that the wearing state is a designated wearing state. Here, the biometric data may include pulse wave information according to changes in blood flow of the body (100) on which the wearable device (101) is worn.

[0150] In one embodiment, the processor (120) can obtain biometric information based on the acquired biometric data. In one embodiment, the processor (120) can obtain biometric information based on the waveform of the pulse wave indicated by the acquired biometric data. For example, the processor (120) can obtain heartbeat information (or heart rate) based on the number of peak values ​​of the waveform of the pulse wave. For example, the processor (120) can obtain oxygen saturation information based on the ratio between the intensity of the pulse wave indicated by the reflected light of infrared light and the intensity of the pulse wave indicated by the reflected light of red light.

[0151] In operation 1240, the processor (120) may guide a change in the wearing state. In one embodiment, the processor (120) may output a notification guiding a change in the wearing state in response to identifying the wearing state as being different from the wearing state for acquiring biometric data. The processor (120) may cause the electronic device (102) to output a notification guiding a change in the wearing state. For example, the processor (120) may transmit data indicating the identified wearing state to the electronic device (102) based on a communication connection with the electronic device (102). The electronic device (102) may output a notification guiding a change in the wearing state based on the data indicating the identified wearing state received from the wearable device (101). However, the present invention is not limited thereto.

[0152] Figure 13 is a flowchart illustrating the operation of a wearable device according to one embodiment.

[0153] In the following examples, the operations may be performed sequentially, but are not necessarily sequential. For example, the order of the operations may be changed, and at least two operations may be performed in parallel.

[0154] Figure 13 can be explained with reference to Figures 1 to 6b.

[0155] Referring to FIG. 13, in operation 1310, the processor (120) may obtain biometric data. In one embodiment, the processor (120) may obtain biometric data through the biometric sensor (171). In one embodiment, in response to identifying that the wearing state is a designated wearing state, the processor (120) may obtain biometric data through the biometric sensor (171). Here, the biometric data may include pulse wave information according to changes in blood flow of the body (100) on which the wearable device (101) is worn.

[0156] In operation 1320, the processor (120) may obtain biometric information based on the biometric data. In one embodiment, the processor (120) may obtain biometric information based on the waveform of the pulse wave indicated by the obtained biometric data. For example, the processor (120) may obtain heartbeat information (or heart rate) based on the number of peak values ​​of the waveform of the pulse wave. For example, the processor (120) may obtain oxygen saturation information based on the ratio between the intensity of the pulse wave indicated by the reflected light of infrared light and the intensity of the pulse wave indicated by the reflected light of red light.

[0157] In operation 1330, the processor (120) may select a correction factor corresponding to the wearing state. In one embodiment, the processor (120) may select a correction factor corresponding to the identified wearing state from among a plurality of correction factors. For example, the processor (120) may select a coefficient corresponding to the wearing state for correcting a value indicated by the biometric information. Here, a plurality of correction factors for a plurality of wearing states may be preset for at least one of heart rate, oxygen saturation, vascular stiffness, blood pressure, vascular age, stress, blood sugar, or IHRN. For example, for heart rate, correction factors corresponding to a tight state, a normal state, or a loose state may be preset. Here, the correction factor may be a value to compensate for the fact that the pulse wave is not measured accurately as it goes from a tight state to a loose state.

[0158] In operation 1340, the processor (120) may adjust biometric information based on a correction factor. The processor (120) may adjust biometric information for at least one of heart rate, oxygen saturation, vascular stiffness, blood pressure, vascular age, stress, blood sugar, or IHRN based on the selected correction factor. For example, the processor (120) may increase the heart rate based on a coefficient corresponding to a relaxed state. For example, the processor (120) may adjust the heart rate by multiplying the heart rate obtained in a relaxed state by a coefficient corresponding to the relaxed state.

[0159] FIG. 14 is a block diagram of an electronic device (1401) within a network environment (1400) according to various embodiments.

[0160] Referring to FIG. 14, in a network environment (1400), an electronic device (1401) may communicate with an electronic device (1402) via a first network (1498) (e.g., a short-range wireless communication network), or may communicate with at least one of an electronic device (1404) or a server (1408) via a second network (1499) (e.g., a long-range wireless communication network). In one embodiment, the electronic device (1401) may communicate with the electronic device (1404) via the server (1408). According to one embodiment, the electronic device (1401) may include a processor (1420), a memory (1430), an input module (1450), an audio output module (1455), a display module (1460), an audio module (1470), a sensor module (1476), an interface (1477), a connection terminal (1478), a haptic module (1479), a camera module (1480), a power management module (1488), a battery (1489), a communication module (1490), a subscriber identification module (1496), or an antenna module (1497). In some embodiments, the electronic device (1401) may omit at least one of these components (e.g., the connection terminal (1478)), or may have one or more other components added. In some embodiments, some of these components (e.g., sensor module (1476), camera module (1480), or antenna module (1497)) may be integrated into a single component (e.g., display module (1460)).

[0161] The processor (1420) may, for example, execute software (e.g., a program (1440)) to control at least one other component (e.g., a hardware or software component) of the electronic device (1401) connected to the processor (1420) and perform various data processing or operations. According to one embodiment, as at least a part of the data processing or operations, the processor (1420) may store commands or data received from other components (e.g., a sensor module (1476) or a communication module (1490)) in a volatile memory (1432), process the commands or data stored in the volatile memory (1432), and store result data in a non-volatile memory (1434). According to one embodiment, the processor (1420) may include a main processor (1421) (e.g., a central processing unit or an application processor) or an auxiliary processor (1423) (e.g., a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor) that can operate independently or together with the main processor (1421). For example, when the electronic device (1401) includes the main processor (1421) and the auxiliary processor (1423), the auxiliary processor (1423) may be configured to use less power than the main processor (1421) or to be specialized for a given function. The auxiliary processor (1423) may be implemented separately from the main processor (1421) or as a part thereof.

[0162] The auxiliary processor (1423) may control at least a portion of functions or states associated with at least one component (e.g., the display module (1460), the sensor module (1476), or the communication module (1490)) of the electronic device (1401), for example, on behalf of the main processor (1421) while the main processor (1421) is in an inactive (e.g., sleep) state, or together with the main processor (1421) while the main processor (1421) is in an active (e.g., application execution) state. In one embodiment, the auxiliary processor (1423) (e.g., an image signal processor or a communication processor) may be implemented as a part of another functionally related component (e.g., a camera module (1480) or a communication module (1490)). In one embodiment, the auxiliary processor (1423) (e.g., a neural network processing unit) may include a hardware structure specialized for processing artificial intelligence models. The artificial intelligence models may be generated through machine learning. This learning can be performed, for example, on the electronic device (1401) where the artificial intelligence model is executed, or can be performed through a separate server (e.g., server (1408)). The learning algorithm can include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but is not limited to the examples described above. The artificial intelligence model can include multiple artificial neural network layers.The artificial neural network may be one of a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a deep Q-network, or a combination of two or more of the above, but is not limited to the examples described above. In addition to, or alternatively to, a hardware structure, an artificial intelligence model may include a software structure.

[0163] The memory (1430) can store various data used by at least one component (e.g., the processor (1420) or the sensor module (1476)) of the electronic device (1401). The data can include, for example, software (e.g., the program (1440)) and input data or output data for commands related thereto. The memory (1430) can include volatile memory (1432) or non-volatile memory (1434).

[0164] The program (1440) may be stored as software in memory (1430) and may include, for example, an operating system (1442), middleware (1444), or an application (1446).

[0165] The input module (1450) can receive commands or data to be used in a component of the electronic device (1401) (e.g., a processor (1420)) from an external source (e.g., a user) of the electronic device (1401). The input module (1450) can include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen).

[0166] The audio output module (1455) can output audio signals to the outside of the electronic device (1401). The audio output module (1455) can include, for example, a speaker or a receiver. The speaker can be used for general purposes, such as multimedia playback or recording playback. The receiver can be used to receive incoming calls. In one embodiment, the receiver can be implemented separately from the speaker or as part of the speaker.

[0167] The display module (1460) can visually provide information to an external party (e.g., a user) of the electronic device (1401). The display module (1460) may include, for example, a display, a holographic device, or a projector, and a control circuit for controlling the device. In one embodiment, the display module (1460) may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of a force generated by the touch.

[0168] The audio module (1470) can convert sound into an electrical signal, or vice versa. According to one embodiment, the audio module (1470) can acquire sound through the input module (1450), output sound through the sound output module (1455), or an external electronic device (e.g., electronic device (1402)) (e.g., speaker or headphone) directly or wirelessly connected to the electronic device (1401).

[0169] The sensor module (1476) can detect the operating status (e.g., power or temperature) of the electronic device (1401) or the external environmental status (e.g., user status) and generate an electrical signal or data value corresponding to the detected status. According to one embodiment, the sensor module (1476) can include, for example, a gesture sensor, a gyro sensor, a barometric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biometric sensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0170] The interface (1477) may support one or more designated protocols that may be used to directly or wirelessly connect the electronic device (1401) with an external electronic device (e.g., the electronic device (1402)). In one embodiment, the interface (1477) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0171] The connection terminal (1478) may include a connector through which the electronic device (1401) may be physically connected to an external electronic device (e.g., the electronic device (1402)). In one embodiment, the connection terminal (1478) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0172] The haptic module (1479) can convert electrical signals into mechanical stimuli (e.g., vibration or movement) or electrical stimuli that a user can perceive through tactile or kinesthetic sensations. In one embodiment, the haptic module (1479) may include, for example, a motor, a piezoelectric element, or an electrical stimulation device.

[0173] The camera module (1480) can capture still images and videos. In one embodiment, the camera module (1480) may include one or more lenses, image sensors, image signal processors, or flashes.

[0174] The power management module (1488) can manage the power supplied to the electronic device (1401). According to one embodiment, the power management module (1488) can be implemented as, for example, at least a part of a power management integrated circuit (PMIC).

[0175] A battery (1489) may power at least one component of the electronic device (1401). In one embodiment, the battery (1489) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0176] The communication module (1490) may support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between the electronic device (1401) and an external electronic device (e.g., electronic device (1402), electronic device (1404), or server (1408)), and the performance of communication through the established communication channel. The communication module (1490) may operate independently from the processor (1420) (e.g., application processor) and may include one or more communication processors that support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (1490) may include a wireless communication module (1492) (e.g., a cellular communication module, a short-range wireless communication module, or a global navigation satellite system (GNSS) communication module) or a wired communication module (1494) (e.g., a local area network (LAN) communication module, or a power line communication module). Among these communication modules, a corresponding communication module can communicate with an external electronic device (1404) via a first network (1498) (e.g., a short-range communication network such as Bluetooth, wireless fidelity (WiFi) direct, or infrared data association (IrDA)) or a second network (1499) (e.g., a long-range communication network such as a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (e.g., a local area network or a wide area network)). These various types of communication modules can be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module (1492) can verify or authenticate the electronic device (1401) within a communication network such as the first network (1498) or the second network (1499) by using subscriber information (e.g., an international mobile subscriber identity (IMSI)) stored in the subscriber identification module (1496).

[0177] The wireless communication module (1492) can support 5G networks and next-generation communication technologies following the 4G network, such as NR access technology (new radio access technology). NR access technology can support high-speed transmission of high-capacity data (eMBB (enhanced mobile broadband)), minimizing terminal power and connecting multiple terminals (mMTC (massive machine type communications)), or high reliability and low latency communications (URLLC (ultra-reliable and low-latency communications)). The wireless communication module (1492) can support, for example, a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate. The wireless communication module (1492) may support various technologies for securing performance in high-frequency bands, such as beamforming, massive multiple-input and multiple-output (MIMO), full dimensional MIMO (FD-MIMO), array antenna, analog beam-forming, or large scale antenna. The wireless communication module (1492) may support various requirements specified in the electronic device (1401), an external electronic device (e.g., the electronic device (1404)), or a network system (e.g., the second network (1499)). According to one embodiment, the wireless communication module (1492) can support a peak data rate (e.g., 20 Gbps or more) for eMBB implementation, a loss coverage (e.g., 664 dB or less) for mMTC implementation, or a U-plane latency (e.g., 0.5 ms or less for downlink (DL) and uplink (UL), or 6 ms or less for round trip) for URLLC implementation.

[0178] The antenna module (1497) can transmit or receive signals or power to or from an external device (e.g., an external electronic device). In one embodiment, the antenna module (1497) may include an antenna including a radiator formed of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). In one embodiment, the antenna module (1497) may include a plurality of antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network, such as the first network (1498) or the second network (1499), may be selected from the plurality of antennas by, for example, the communication module (1490). A signal or power may be transmitted or received between the communication module (1490) and the external electronic device via the at least one selected antenna. In some embodiments, in addition to the radiator, another component (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as a part of the antenna module (1497).

[0179] According to various embodiments, the antenna module (1497) may form a mmWave antenna module. In one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent a first side (e.g., a bottom side) of the printed circuit board and capable of supporting a designated high frequency band (e.g., a mmWave band), and a plurality of antennas (e.g., an array antenna) disposed on or adjacent a second side (e.g., a top side or a side side) of the printed circuit board and capable of transmitting or receiving signals in the designated high frequency band.

[0180] At least some of the above components can be interconnected and exchange signals (e.g., commands or data) with each other via a communication method between peripheral devices (e.g., a bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)).

[0181] According to one embodiment, commands or data may be transmitted or received between the electronic device (1401) and an external electronic device (1404) via a server (1408) connected to a second network (1499). Each of the external electronic devices (1402 or 1404) may be the same or a different type of device as the electronic device (1401). According to one embodiment, all or part of the operations executed in the electronic device (1401) may be executed in one or more of the external electronic devices (1402, 1404, or 1408). For example, when the electronic device (1401) is to perform a certain function or service automatically or in response to a request from a user or another device, the electronic device (1401) may, instead of or in addition to executing the function or service itself, request one or more external electronic devices to perform the function or at least a part of the service. One or more external electronic devices that receive the request may execute at least a portion of the requested function or service, or an additional function or service related to the request, and transmit the result of the execution to the electronic device (1401). The electronic device (1401) may process the result as is or additionally and provide it as at least a portion of a response to the request. For this purpose, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used, for example. The electronic device (1401) may provide an ultra-low latency service using, for example, distributed computing or mobile edge computing. In another embodiment, the external electronic device (1404) may include an Internet of Things (IoT) device. The server (1408) may be an intelligent server utilizing machine learning and / or a neural network.According to one embodiment, an external electronic device (1404) or server (1408) may be included within the second network (1499). The electronic device (1401) may be applied to intelligent services (e.g., smart homes, smart cities, smart cars, or healthcare) based on 5G communication technology and IoT-related technology.

[0182] As described above, the wearable device (101) may include a temperature sensor (170) arranged to face the skin of the user when the wearable device (101) is worn by the user. The wearable device (101) may include at least one processor (120). The wearable device (101) may include a memory (130) that stores instructions. The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to identify that the wearable device (101) is worn by the user. The instructions may be configured to cause the wearable device (101) to, when executed by the at least one processor (120), identify one wearing state corresponding to temperature data representing a temperature value measured by the temperature sensor (170) among a plurality of wearing states (601, 603, 605) in response to identifying that the wearable device (101) is worn by the user.

[0183] The wearable device (101) may further include a biometric sensor (171) for acquiring biometric data related to the user. The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to identify, in response to an input requesting acquisition of biometric information, whether the identified wearing state is a first wearing state for acquiring the biometric data. The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to output a notification guiding a change in the identified wearing state in response to identifying that the identified wearing state is a wearing state different from the first wearing state. The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to acquire biometric data through the biometric sensor (171) in response to the identified wearing state being identified as the first wearing state. The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to acquire biometric information based on the acquired biometric data.

[0184] The wearable device (101) may further include a biometric sensor (171) for acquiring biometric data related to the user. The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to acquire biometric data through the biometric sensor (171) in response to an input requesting acquisition of biometric information. The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to acquire biometric information based on the biometric data. The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to select a coefficient corresponding to the identified wearing state from among a plurality of coefficients. The above instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to adjust the biometric information based on the selected coefficient.

[0185] The above instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to identify that the wearable device (101) is worn by the user based on the temperature value changing by more than a reference temperature value within a specified time period.

[0186] The wearable device (101) may further include a proximity sensor (172). The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to identify a first state of the wearable device (101) based on a proximity sensing value obtained from the proximity sensor (172). The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to identify a second state of the wearable device (101) based on the temperature value changing by a reference temperature value or more within a specified time period. The above instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to identify that the wearable device (101) is worn by the user based on the first state and the second state both indicating that the wearable device (101) is worn by the user.

[0187] The wearable device (101) may further include a motion sensor (173). The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to obtain, through the motion sensor (173), movement data indicating movement of the wearable device (101). The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to determine, in response to the movement data indicating that the wearable device (101) is moving, whether the wearable device (101) is worn by the user.

[0188] The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to identify a change in the wearing state while the wearable device (101) is worn by the user. The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to identify that the changed wearing state is a second wearing state among the plurality of wearing states (601, 603, 605). The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to output a notification guiding a change in the wearing state based on the identification of the changed wearing state as the second wearing state.

[0189] The above instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to output the notification based on the second wearing state being maintained for a specified period of time or longer after the changed wearing state is identified as the second wearing state.

[0190] The wearable device (101) may further include a pressure sensor (175) arranged to face the user's skin. The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to obtain a pressure signal through the pressure sensor (175) based on the changed wearing state being identified as the second wearing state. The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to output the notification based on the pressure value indicated by the pressure signal exceeding a specified pressure value.

[0191] The wearable device (101) may further include a communication circuit (190). The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to establish a communication connection with an external electronic device (102) through the communication circuit (190). The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to transmit data representing the identified wearing state to the external electronic device (102) based on the communication connection, such that the external electronic device (102) outputs a notification guiding the user to the identified wearing state.

[0192] The above instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to identify that the wearable device (101) is worn on one of the user's fingers corresponding to the temperature data.

[0193] The wearable device (101) may be configured to further include a motion sensor (173). The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to obtain, through the motion sensor (173), motion data representing a movement of the wearable device (101), based on the wearable device (101) being worn on a first finger among the fingers. The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to identify, based on the wearable device (101) being worn on a first finger among the fingers, a gesture corresponding to a movement path of the wearable device (101) represented by the motion data. The above instructions, when executed by the at least one processor (120), may be configured to output a notification guiding a change in the identified wearing state based on the wearable device (101) being identified as being worn on a finger other than the first finger among the fingers.

[0194] The wearable device (101) may further include a motion sensor (173). The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to obtain movement data representing movement of the wearable device (101) through the motion sensor (173). The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to identify a hand on which a finger on which the wearable device (101) is worn is located, among the user's two hands, based on a movement path of the wearable device (101) represented by the movement data.

[0195] The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to obtain a tracking input for tracking a movement path. The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to determine, in response to the tracking input, whether the identified hand is a designated hand. The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to obtain movement data for tracking the movement path in response to identifying the identified hand as the designated hand. The instructions, when executed by the at least one processor (120), may be configured to cause the wearable device (101) to output a notification guiding a change in the identified wearing state in response to identifying the identified hand as being different from the designated hand.

[0196] As described above, the method may be performed in a wearable device (101) including a temperature sensor (170) arranged to face the skin of a user when the wearable device (101) is worn by the user. The method may include an operation of identifying that the wearable device (101) is worn by the user. In response to identifying that the wearable device (101) is worn by the user, the method may include an operation of identifying one wearing state corresponding to temperature data representing a temperature value measured by the temperature sensor (170) among a plurality of wearing states (601, 603, 605).

[0197] The method may include, in response to an input requesting acquisition of biometric information, an operation of identifying whether the identified wearing state is a first wearing state for acquiring the biometric data. The method may include, in response to identifying the identified wearing state as being a wearing state different from the first wearing state, an operation of outputting a notification guiding a change of the identified wearing state. The method may include, in response to identifying the identified wearing state as being the first wearing state, an operation of acquiring biometric data through a biometric sensor (171) of the wearable device (101). The method may include an operation of acquiring the biometric information based on the acquired biometric data.

[0198] The method may include an operation of acquiring biometric data through a biometric sensor (171) of the wearable device (101) in response to an input requesting acquisition of biometric information. The method may include an operation of acquiring the biometric information based on the biometric data. The method may include an operation of selecting a coefficient corresponding to the identified wearing state among a plurality of coefficients. The method may include an operation of adjusting the biometric information based on the selected coefficient.

[0199] The method may include an action of identifying that the wearable device (101) is worn by the user based on the temperature value changing by more than a reference temperature value within a specified time period.

[0200] The method may include an operation of obtaining movement data indicating movement of the wearable device (101) through a motion sensor (173) of the wearable device (101). The method may include an operation of determining whether the wearable device (101) is worn by the user in response to the movement data indicating that the wearable device (101) is moving.

[0201] The method may include an operation of identifying a change in the wearing state while the wearable device (101) is worn by the user. The method may include an operation of identifying that the changed wearing state is a second wearing state among the plurality of wearing states (601, 603, 605). The method may include an operation of outputting a notification guiding a change in the wearing state based on the identification of the changed wearing state as the second wearing state.

[0202] As described above, a non-transitory computer-readable recording medium can store a program including instructions. The instructions, when executed by at least one processor (120) of the wearable device (101) including a temperature sensor (170) arranged to face the skin of a user when the wearable device (101) is worn by the user, can be configured to cause the wearable device (101) to identify that the wearable device (101) is worn by the user. The instructions, when executed by the at least one processor (120), can cause the wearable device (101) to, in response to identifying that the wearable device (101) is worn by the user, identify one wearing state corresponding to temperature data representing a temperature value measured by the temperature sensor (170) among a plurality of wearing states (601, 603, 605).

[0203] Electronic devices according to the various embodiments disclosed in this document may take various forms. Electronic devices may include, for example, portable communication devices (e.g., smartphones), computer devices, portable multimedia devices, portable medical devices, cameras, wearable devices, or home appliances. Electronic devices according to the embodiments of this document are not limited to the aforementioned devices.

[0204] The various embodiments of this document and the terminology used therein are not intended to limit the technical features described in this document to specific embodiments, but should be understood to include various modifications, equivalents, or substitutes of the embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of the items, unless the context clearly indicates otherwise. In this document, each of the phrases "A or B", "at least one of A and B", "at least one of A or B", "A, B, or C", "at least one of A, B, and C", and "at least one of A, B, or C" can include any one of the items listed together in the corresponding phrase among those phrases, or all possible combinations thereof. Terms such as "first," "second," or "first" or "second" may be used merely to distinguish one component from another, and do not limit the components in any other respect (e.g., importance or order). When a component (e.g., a first component) is referred to as "coupled" or "connected" to another component (e.g., a second component), with or without the terms "functionally" or "communicatively," it means that the component can be connected to the other component directly (e.g., wired), wirelessly, or through a third component.

[0205] The term "module" used in various embodiments of this document may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit. A module may be an integral component, or a minimum unit or part of such a component that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0206] Various embodiments of the present document may be implemented as software (e.g., a program (1440)) including one or more instructions stored in a storage medium (e.g., an internal memory (1436) or an external memory (1438)) readable by a machine (e.g., an electronic device (1401)). For example, a processor (e.g., a processor (1420)) of the machine (e.g., an electronic device (1401)) may call at least one instruction among the one or more instructions stored from the storage medium and execute it. This enables the machine to operate to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code executable by an interpreter. The machine-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-transitory' simply means that the storage medium is a tangible device and does not contain signals (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently or temporarily on the storage medium.

[0207] According to one embodiment, the method according to various embodiments disclosed in this document may be provided as included in a computer program product. The computer program product may be traded as a product between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., a compact disc read-only memory (CD-ROM)), or may be distributed online (e.g., by download or upload) through an application store (e.g., Play Store™) or directly between two user devices (e.g., smart phones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily generated in a machine-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or an intermediary server.

[0208] According to various embodiments, each component (e.g., a module or a program) of the above-described components may include one or more entities, and some of the entities may be separately arranged in other components. According to various embodiments, one or more components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (e.g., a module or a program) may be integrated into a single component. In such a case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by the corresponding component among the plurality of components prior to the integration. According to various embodiments, the operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

Claims

1. In a wearable device (101), When the wearable device (101) is worn by a user, a temperature sensor (170) arranged to face the user's skin; at least one processor (120), and A wearable device (101) comprises a memory (130) storing instructions, wherein the instructions, when individually or collectively executed by the at least one processor (120), Identifying that the wearable device (101) is worn by the user, In response to identifying that the wearable device (101) is worn by the user, causing one of the plurality of wearing states (601, 603, 605) to be identified, which corresponds to temperature data indicating a temperature value measured by the temperature sensor (170). Wearable devices.

2. In claim 1, It further includes a biometric sensor (171) that obtains biometric data related to the user, The above instructions, when executed individually or collectively by the at least one processor (120), cause the wearable device (101) to: In response to an input requesting acquisition of biometric information, identifying whether the identified wearing state is a first wearing state for acquisition of the biometric data; In response to identifying that the identified wearing state is a different wearing state from the first wearing state, output a notification guiding a change in the identified wearing state, In response to the above-mentioned identified wearing state being identified as the first wearing state, biometric data is acquired through the biometric sensor (171), Based on the above acquired biometric data, causing the biometric information to be acquired, Wearable devices.

3. In any one of claims 1 to 2, It further includes a biometric sensor (171) that obtains biometric data related to the user, The above instructions, when executed individually or collectively by the at least one processor (120), cause the wearable device (101) to: In response to an input requesting acquisition of biometric information, biometric data is acquired through the biometric sensor (171), Based on the above biometric data, the biometric information is acquired, Select a coefficient corresponding to the identified wearing state among multiple coefficients, and Based on the above selected coefficients, causing the biometric information to be adjusted, Wearable devices.

4. In any one of claims 1 to 3, The above instructions, when executed individually or collectively by the at least one processor (120), cause the wearable device (101) to: Based on the temperature value changing more than the reference temperature value within a specified time, the wearable device (101) causes the user to identify that it is worn. Wearable devices.

5. In claim 4, Further comprising a proximity sensor (172), The above instructions, when executed individually or collectively by the at least one processor (120), cause the wearable device (101) to: Based on the proximity sensing value obtained from the proximity sensor (172), the first state of the wearable device (101) is identified, Based on the temperature value changing by more than the reference temperature value within a specified time, the second state of the wearable device (101) is identified, Based on the above first state and the above second state both indicating that the wearable device (101) is worn by the user, causing the wearable device (101) to identify that it is worn by the user. Wearable devices.

6. In any one of claims 1 to 5, Further comprising a motion sensor (173), The above instructions, when executed individually or collectively by the at least one processor (120), cause the wearable device (101) to: Through the above motion sensor (173), movement data indicating the movement of the wearable device (101) is acquired, In response to the above movement data indicating that the wearable device (101) is moving, causing the wearable device (101) to determine whether it is worn by the user. Wearable devices.

7. In any one of claims 1 to 6, The above instructions, when executed individually or collectively by the at least one processor (120), cause the wearable device (101) to: While the wearable device (101) is worn by the user, changes in the wearing status are identified, Identifying that the above-mentioned changed wearing state is the second wearing state among the plurality of wearing states (601, 603, 605), Causing a notification to be output to guide a change in the wearing state based on the above-mentioned changed wearing state being identified as the second wearing state, Wearable devices.

8. In claim 7, The above instructions, when executed individually or collectively by the at least one processor (120), cause the wearable device (101) to: Causing the notification to be output based on the second wearing state being maintained for a specified period of time or longer after the changed wearing state is identified as the second wearing state. Wearable devices.

9. In claim 7, It further includes a pressure sensor (175) arranged to face the user's skin, The above instructions, when executed individually or collectively by the at least one processor (120), cause the wearable device (101) to: Based on the above-mentioned changed wearing state being identified as the second wearing state, a pressure signal is acquired through the pressure sensor (175), Causing the notification to be output based on the pressure value indicated by the above pressure signal exceeding a specified pressure value; Wearable devices.

10. In any one of claims 1 to 9, Further comprising a communication circuit (190), The above instructions, when executed individually or collectively by the at least one processor (120), cause the wearable device (101) to: Through the above communication circuit (190), a communication connection is established with an external electronic device (102), Based on the above communication connection, causing the external electronic device (102) to transmit data representing the identified wearing state to the external electronic device (102) so as to output a notification guiding the user to the identified wearing state. Wearable devices.

11. In any one of claims 1 to 10, The above instructions, when executed individually or collectively by the at least one processor (120), cause the wearable device (101) to: Causing to identify that the wearable device (101) is worn on one of the user's fingers corresponding to the temperature data; Wearable devices.

12. In claim 11, Further comprising a motion sensor (173), The above instructions, when executed individually or collectively by the at least one processor (120), cause the wearable device (101) to: Based on the above wearable device (101) being worn on the first finger among the above fingers: Through the above motion sensor (173), movement data indicating the movement of the wearable device (101) is acquired, Identifying a gesture corresponding to the movement path of the wearable device (101) indicated by the above movement data, Based on the identification that the finger other than the first finger among the above fingers is worn, a notification is output to guide a change in the identified wearing state. Wearable devices.

13. In any one of claims 1 to 12, Further comprising a motion sensor (173), The above instructions, when executed individually or collectively by the at least one processor (120), cause the wearable device (101) to: Through the above motion sensor (173), movement data indicating the movement of the wearable device (101) is acquired, Based on the movement path of the wearable device (101) indicated by the above movement data, causing identification of the hand on which the finger on which the wearable device (101) is worn is located among the user's two hands. Wearable devices.

14. In claim 13, The above instructions, when executed individually or collectively by the at least one processor (120), cause the wearable device (101) to: Obtain tracking input to track the movement path, In response to the above tracking input, determine whether the identified hand is the designated hand; In response to identifying the identified hand as being the designated hand, obtaining movement data for tracking the movement path; In response to the identification that the identified hand is a different hand from the designated hand, causing a notification to be output that guides a change in the identified wearing state. Wearable devices.

15. A method performed in a wearable device (101), comprising a temperature sensor (170) arranged to face the skin of a user when the wearable device (101) is worn by the user, An action for identifying that the wearable device (101) is worn by the user, and In response to identifying that the wearable device (101) is worn by the user, an operation of identifying one wearing state corresponding to temperature data representing a temperature value measured by the temperature sensor (170) among a plurality of wearing states (601, 603, 605) is included. method.

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