WO2022177132A1 - Method for checking wearing state by using gyro sensor, and wearable device - Google Patents

Abstract

Disclosed in various embodiments of the present invention are a method and a wearable device, the wearable device comprising: a wearing-detection sensor; a gyro sensor; a memory; and a processor operatively connected to the wearing-detection sensor, the gyro sensor and the memory, wherein the processor is configured to detect the proximity of an object from the wearing-detection sensor, collect gyro data during a predetermined time from the gyro sensor on the basis of the detection of the object proximity, select sampling data on the basis of the size of the collected gyro data, compare the selected sampling data with the reference value, and recognize the wearing state of the wearable device on the basis of the comparison result. Various embodiments are possible.

Description

A method for checking wearing state using a gyro sensor and a wearable device

Various embodiments of the present invention disclose a wearable state checking method and a wearable device using a gyro sensor.

With the development of digital technology, various types of electronic devices such as a mobile communication terminal, a personal digital assistant (PDA), an electronic notebook, a smart phone, a tablet PC (personal computer), or a wearable device are widely used. Such an electronic device may exchange information by connecting with an external device, such as a notebook computer, earphone, or headphone, using a short-range wireless technology such as Bluetooth. For example, the electronic device may connect the earphone with Bluetooth to output a sound of music or a video through the earphone.

In the earphone, a 'true wireless stereo (TWS) (or wireless output device)' type that can be inserted into both ears of a user is being released by reflecting the user's needs. Since the wireless earphone provides a function based on whether the user wears the earphone, it may be very important to detect whether the user is wearing the earphone. Since the wireless earphone detects whether it is worn using a wear sensor, one or more wear detection sensors may be installed.

When the wireless earphone is recognized as the proximity of the object by the wear detection sensor, it may be determined that the user is wearing the wireless earphone (eg, wearing state). The wear detection sensor may be configured as a combination of one or more proximity sensors or one or more contact (touch, grip) sensors. Alternatively, the wireless earphone may detect whether the user is wearing the wireless earphone using an acceleration sensor. The wear detection sensor may determine whether an object is close to the wireless earphone, or determine the amount of change in the amount of charge induced when the object is nearby. Accordingly, it may be less accurate to detect the wearing or non-wearing state of the wireless earphone only with the wear detection sensor mounted on the wireless earphone. The wear detection sensor may recognize that the wireless earphone is worn not only when the user wears the wireless earphone on the ear, but also as worn in various objects, hands, and pockets. The wireless earphone may automatically play music when the user erroneously recognizes that the wireless earphone is worn even though the user is not wearing it.

In various embodiments, when it is determined that an object is close to the wearable device using a wear detection sensor, the wearable device is determined based on sensing data obtained from the gyro sensor to determine whether the wearable device is worn, a method and apparatus for recognizing whether the wearable device is correctly worn can be disclosed about

A wearable device according to various embodiments of the present disclosure includes a wear detection sensor, a gyro sensor, a memory, and a processor operatively connected to the wear detection sensor, the gyro sensor, and the memory, wherein the processor is configured to detect the wear Detect object proximity from a sensor, collect gyro data from the gyro sensor for a certain period of time based on the object proximity detection, select sampling data based on the size of the collected gyro data, and use the selected sampling data as a reference value It may be set to compare with and recognize a wearing state of the wearable device based on the comparison result.

A method of operating a wearable device including a wear detection sensor and a gyro sensor according to various embodiments of the present disclosure includes the operation of detecting the proximity of an object from the wear detection sensor and the detection of the proximity of the object from the gyro sensor for a predetermined time The operation of collecting gyro data, the operation of selecting sampling data based on the size of the collected gyro data, the operation of comparing the selected sampling data with a reference value, and the recognition of the wearing state of the wearable device based on the comparison result It may include an action to

According to various embodiments, by determining whether the wearable device is worn using the gyro sensor, a malfunction according to the wearing state of the wearable device may be prevented.

According to various embodiments, when the wearing state of the wearable device is determined by the wear detection sensor, it may be difficult to distinguish whether the wearable device is actually worn by the user or the object is recognized, but the wearable device is more accurately worn using the gyro sensor. Wearing state can be recognized.

According to various embodiments, the wearing state of the wearable device is determined by making a primary wearing determination using a wear detection sensor, a secondary wearing determination using an acceleration sensor, and a tertiary wearing determination using a gyro sensor. can be judged more accurately.

1 is a block diagram of a wearable device according to various embodiments.

2 is a diagram illustrating a configuration of a wearable device according to various embodiments of the present disclosure;

3 is another block diagram of a wearable device according to various embodiments.

4 is a flowchart illustrating a method of operating a wearable device according to various embodiments of the present disclosure;

5 is a diagram illustrating an example of a wearing state of a wearable device according to various embodiments of the present disclosure;

6 is a diagram illustrating an example of a non-wearing state of a wearable device according to various embodiments of the present disclosure;

7 is a diagram illustrating an example of distinguishing a wearable device from a worn state from a non-wearing state according to various embodiments of the present disclosure;

8 is a diagram illustrating another example of distinguishing a wearable device from a worn state from a non-wearing state according to various embodiments of the present disclosure;

9 is a flowchart illustrating a method for checking a wearing state using a gyro sensor of a wearable device according to various embodiments of the present disclosure;

10 is another flowchart illustrating a method of checking a wearing state using a gyro sensor of a wearable device according to various embodiments of the present disclosure;

1 is a block diagram of a wearable device according to various embodiments.

Referring to FIG. 1 , the wearable device 101 includes a wear detection sensor 110 , an acceleration sensor 115 , a gyro sensor 120 , a touch sensor 125 , a memory 130 , a processor 140 , and a communication module ( 150 ), a microphone 160 , a speaker 165 , a charging module 170 , an interface 180 , or a battery 190 . In some embodiments, at least one of these components may be omitted or one or more other components may be added to the wearable device 101 . In some embodiments, some of these components may be integrated into one component. The wearable device according to various embodiments disclosed in this document may be a device of various types, for example, a wireless earphone.

The wear detection sensor 110 may be a sensor that detects an object proximate to the wearable device 101 . The wear detection sensor 110 is used to determine whether the wearable device 101 is worn, and may be disposed in an area of the wearable device 101 inserted into the user's ear. For example, the wear detection sensor 110 is a proximity sensor that determines whether an object is in proximity through the amount of reflection of infrared rays, or a grip sensor (or touch sensor) that determines whether an object is nearby, based on a change in the amount of electric charge induced when the object is nearby. ) can be The example of the wear detection sensor 110 is provided to help the understanding of the invention, and the present invention is not limited by the example.

The acceleration sensor 115 may be a sensor that measures a dynamic force such as acceleration, vibration, or impact of an object. The acceleration sensor 115 may detect a motion state of an object, and thus may be utilized for various purposes. The wearable device 101 may determine whether to wear the wearable device 101 based on acceleration data measured by the acceleration sensor 115 together with the wear detection sensor 110 .

The gyro sensor 120 may be a sensor that measures the angular velocity of an object. Unlike the acceleration sensor 115 that measures the acceleration of the object, the gyro sensor 120 may measure the angular velocity of the object. The angular velocity may mean a rotation speed (or angle) per hour. The gyro sensor 120 may be used to determine whether to wear the wearable device 101 based on the angular velocity of the wearable device 101 . The gyroscope sensor 120 may also be referred to as a gyroscope sensor.

The touch sensor 125 may be a sensor for controlling the wearable device 101 . When a touch is detected by the touch sensor 125 while the wearable device 101 outputs a sound, the wearable device 101 may stop playback. After playback is stopped, when a touch is detected by the touch sensor 125 , the wearable device 101 may start playback. The touch sensor 125 may be disposed in an external area of the wearable device 101 that is not inserted into the user's ear in order to receive a touch input while the user wears the wearable device 101 .

The memory 130 (or buffer) may store various data used by at least one component (eg, the processor 140 or the wear detection sensor 110 ) of the wearable device 101 . The data may include, for example, input data or output data for software (eg, a program) and instructions related thereto.

The processor 140 may execute software to control at least one other component (eg, a hardware or software component) of the wearable device 101 connected to the processor 140 , and perform various data processing or operations. can According to an embodiment, as at least part of data processing or operation, the processor 140 may store a command or data received from another component (eg, the wear detection sensor 110 or the communication module 150) into the memory 130 . may be stored in , process commands or data stored in the memory 130 , and store the result data in the memory 130 .

According to an embodiment, the processor 140 may include a main processor (eg, a central processing unit or an application processor) or an auxiliary processor (eg, a sensor hub processor or a communication processor) that can be operated independently or together. For example, when the wearable device 101 includes a main processor and an auxiliary processor, the auxiliary processor may be configured to use less power than the main processor or to be specialized for a specified function. The coprocessor may be implemented separately from or as part of the main processor.

According to various embodiments, when the proximity of an object is detected by the wear detection sensor 110 , the processor 140 collects gyro data from the gyro sensor 120 for a predetermined time, and based on the size of the collected gyro data, The wearing state of the wearable device 101 may be recognized based on the selection of sampling data, comparison of the selected sampling data with a reference value, and the comparison result. The processor 140 first determines the wearing state of the wearable device 101 using the wear detection sensor 110, and secondly determines the wearing state of the wearable device 101 using the gyro sensor 120. A wearing state of the wearable device 101 may be recognized more accurately.

According to various embodiments, the processor 140 first determines a wearing state of the wearable device 101 using the wear detection sensor 110 , and uses the acceleration sensor 115 to wear the wearable device 101 . The wearable state of the wearable device 101 may be more accurately recognized by secondary determination of the state and the third determination of the wearing state of the wearable device 101 using the gyro sensor 120 .

The communication module 150 may establish a wireless communication channel with an external electronic device (eg, a smart phone or a notebook computer) and support performing communication through the established communication channel. Communication module 150 is Bluetooth, low-power Bluetooth, Wi-Fi (Wi-Fi), ANT+ (adaptive network topology), LTE (long term evolution), 5G (5th generation mobile communication), NB-IoT (narrowband internet of things) It may be connected to an external electronic device through an access point or a network. The communication module 150 may receive an acoustic signal from an external electronic device or transmit sensing information (or a sensing signal) or an acoustic signal to the external electronic device.

The microphone 160 may convert a sound into an electric signal or, conversely, convert an electric signal into a sound. According to an embodiment, the microphone 160 may acquire sound (or audio) and convert it into an electrical signal.

The speaker 165 may output an audio (or sound) signal to the outside of the wearable device 101 . The speaker 165 may include a receiver. The speaker 165 may be used for general purposes such as multimedia playback or recording playback. The receiver can be used to receive incoming calls. According to one embodiment, the receiver may be implemented separately from or as part of the speaker 165 .

The charging module 170 may manage power supplied to the wearable device 101 . The charging module 170 may charge the battery 190 with power received through the interface 180 . The charging module 170 may be implemented as at least a part of a power management integrated circuit (PMIC).

The interface 180 may include a connector through which the wearable device 101 may be physically connected to an external device (eg, the case 250 of FIG. 2 ).

The battery 190 may supply power to at least one component of the wearable device 101 . According to one embodiment, battery 189 may include, for example, a non-rechargeable primary cell, a rechargeable secondary cell, or a fuel cell.

2 is a diagram illustrating a configuration of a wearable device according to various embodiments of the present disclosure;

Referring to FIG. 2 , a wearable device 200 (eg, the wearable device 101 of FIG. 1 ) according to various embodiments is wirelessly connected to an external electronic device (eg, a smart phone), and output from the external electronic device It receives an audio signal and outputs it through a speaker (eg, the speaker 165 of FIG. 1), or outputs an audio signal input from the outside (eg, a user) through a microphone (eg, the microphone 160 of FIG. 1) It may be a device that transmits to an electronic device. The wearable device 200 may include at least one of a first device 210 , a second device 230 , and a case 250 . Hereinafter, the wearable device 200 described in the present invention may refer to the first device 210 or the second device 230 .

The first device 210 and the second device 230 may be accommodated (or mounted) in the case 250 or may be separated (or detached) from the case 250 . The first device 210 and the second device 230 may be respectively worn on a part of the user's body (eg, the user's left ear or the user's right ear). Each of the first device 210 and the second device 230 may include a speaker or a microphone. Each of the first device 210 and the second device 230 may output an audio signal through a speaker or receive (or input) an audio signal from the outside through a microphone. When the first device 210 and the second device 230 are separated from the case 250 , power may be turned on. When the first device 210 and the second device 230 are mounted on the case 250 , the power of the first device 210 and the second device 230 may be turned off or charged.

According to various embodiments, the first device 210 may serve as a master, and the second device 230 may serve as a slave. Conversely, the first device 210 may act as a slave, and the second device 230 may act as a master. The first device 210 and the second device 230 may periodically transmit respective sensing information to an external electronic device.

The case 250 may include a housing having a receiving portion (or space) configured to receive (or store) the first device 210 or the second device 230 , and a cover attached to the housing. The receiving part may be configured to magnetically attract and hold the first device 210 or the second device 230 into the case 250 . The case 250 turns off the power of the first device 210 and the second device 230 when the first device 210 and the second device 230 are mounted in the receiving unit or the cover is closed. or it can be controlled to be charged. The case 250 turns on the power of the first device 210 and the second device 230 when the first device 210 and the second device 230 are separated from the receiving unit or the cover is opened. can do it

3 is another block diagram of a wearable device according to various embodiments.

Referring to FIG. 3 , a wearable device (eg, the wearable device 101 of FIG. 1 , or the wearable device 200 of FIG. 2 ) according to various embodiments is a first device (eg, the first device ( 210)), the first device (eg, the second device 230 of FIG. 2 ), and a case (eg, the case 250 of FIG. 2 ).

The first device 210 includes a first wear detection sensor 311 (eg, the wear detection sensor 110 of FIG. 1 ), a first acceleration sensor 313 (eg, the acceleration sensor 115 of FIG. 1 ), a second 1 gyro sensor 315 (eg, gyro sensor 120 of FIG. 1 , first touch sensor 317 (eg, touch sensor 125 of FIG. 1 )), first charging module 319 (eg, FIG. 1 ) of the charging module 170), the first communication module 320 (eg, the communication module 150 of FIG. 1), the first processor 325 (eg, the processor 140 of FIG. 1), the first microphone ( 330) (eg, microphone 160 of FIG. 1 ), first speaker 331 (eg, speaker 165 of FIG. 1 ), first battery 333 (eg, battery 190 of FIG. 1 ) or At least one of the first interfaces 335 (eg, the interface 180 of FIG. 1 ) may be included.

The second device 230 includes a second wear detection sensor 341 (eg, the wear detection sensor 110 of FIG. 1 ), a second acceleration sensor 343 (eg, the acceleration sensor 115 of FIG. 1 ), a first 2 gyro sensor 345 (eg, gyro sensor 120 of FIG. 1 , second touch sensor 347 (eg, touch sensor 125 of FIG. 1 )), second charging module 349 (eg, FIG. 1 ) of the charging module 170), the second communication module 350 (eg, the communication module 150 of FIG. 1), the second processor 355 (eg, the processor 140 of FIG. 1), the second microphone ( 360) (eg, microphone 160 in FIG. 1 ), second speaker 361 (eg, speaker 165 in FIG. 1 ), second battery 363 (eg, battery 190 in FIG. 1 ) or At least one of the second interfaces 365 (eg, the interface 180 of FIG. 1 ) may be included.

Since the components included in the first device 210 and the components included in the second device 230 are the same or similar, “first” and “second” may be indicated in front of the components to distinguish them. Components included in the first device 210 and the second device 230 are the same as or similar to those described with reference to FIG. 1 , and thus a detailed description thereof will be omitted.

Case 250 includes first device interface 371 , second device interface 373 , detection module 375 , power interface 377 , case processor 380 , battery 385 , or charging module 390 . may include at least one of The first device interface 371 or the second device interface 373 may be physically connected to the first device 210 or the second device 230 . For example, the first device interface 371 may be connected to the first interface 335 of the first device 210 . The second device interface 373 may be connected to the second interface 356 of the second device 230 .

The case processor 380 may control the operation of the case 250 . The case processor 380 may control other components (eg, the charging module 390 and the detection module 375 ) included in the case 250 and perform various data processing or operations. For example, when the first device 210 is connected, the case processor 380 controls the first device 210 to be charged, and when the second device 230 is connected, the second device 230 is charged. can be controlled as much as possible.

The charging module 390 may manage power supplied to the first device 210 , the second device 230 , or the case 250 . The charging module 390 may supply power to the first device 210 through the first device interface 371 and supply power to the second device 230 through the second device interface 373 . The charging module 390 may charge the battery 385 with power received through the power interface 377 . The charging module 390 may be the same as or similar to the charging module 170 of FIG. 1 .

The detection module 375 may detect whether the first device 210 or the second device 230 is mounted (or accommodated) in the case 250 . The detection module 375 may transmit the first device 210 or the second device 230 to the case processor 380 when the first device 210 or the second device 230 is mounted in the receiving part of the case 250 . The detection module 375 may include at least one sensor that detects whether at least one of the first device 210 or the second device 230 is located in the case 250 . The detection module 375 periodically detects contact portions (eg, the first device interface 371 or the second device interface 373 ) that are in contact with (or connected to) the first device 210 or the second device 230 . It could be a circuit that "pings". The detection module 375 may be a magnetic sensor, an optical sensor, a switch, a Hall effect sensor, a magnetic flux sensor, a capacitive sensor, a photodetector, a proximity detector, a momentary switch, a mechanical sensor, or an electrical sensor. The battery 385 may supply power to at least one component of the case 250 . Battery 385 may be the same as or similar to battery 190 of FIG. 1 . The power interface 377 may be physically connected to an external power supply.

A wearable device (eg, the wearable device 101 of FIG. 1 ) according to various embodiments of the present disclosure includes a wear detection sensor (eg, the wear detection sensor 110 of FIG. 1 ) and a gyro sensor (eg, the gyro of FIG. 1 ). sensor 120), a memory (eg, memory 130 of FIG. 1 ), and a processor (eg, processor 140 of FIG. 1 ) operatively coupled to the wear detection sensor, the gyro sensor, and the memory. and, the processor detects object proximity from the wear detection sensor, collects gyro data from the gyro sensor for a predetermined time based on the object proximity detection, and collects sampling data based on the size of the collected gyro data selection, comparing the selected sampling data with a reference value, and recognizing a wearing state of the wearable device based on the comparison result.

The processor may be configured to collect the gyro data from the gyro sensor after detecting the proximity of the object.

The processor may be configured to select some gyro data having a maximum value among the collected gyro data as the sampling data.

The processor may be configured to select x-axis gyro data, y-axis gyro data, and z-axis gyro data as the sampling data, respectively.

The processor may be configured to determine the wearable device as a worn state when the selected sampling data is less than a reference value, and to determine the wearable device as a non-wear state when the selected sampling data is greater than or equal to a reference value.

When the selected sampling data is less than a reference value, the processor determines the wearable device as a worn state, identifies an interval between maximum values of the sampling data, and detects a pattern from the sampling data based on the interval between the maximum values It can be set to determine whether or not

The processor may be configured to recognize the wearable device as a worn state when a pattern is detected from the sampling data, and to determine the wearable device as a non-wear state when no pattern is detected from the sampling data.

The processor is configured to set an interval between the maximum values of the sampling data, a similar tendency between the sampling data of the x-axis, the y-axis, and the z-axis, whether a pattern is detected from the sampling data, or an interval reference value in which the interval between the maximum values of the sampling data is set. It may be configured to determine whether to wear the wearable device based on at least one of whether the wearable device is exceeded.

The wearable device further includes an acceleration sensor (eg, the acceleration sensor 115 of FIG. 1 ), and the processor obtains acceleration data from the acceleration sensor based on the object proximity detection, and adds It may be configured to determine whether to collect gyro data from the gyro sensor based on the gyro sensor.

When the amount of change of the acceleration data corresponds to a set amount of change, the processor drives the gyro sensor to collect gyro data for a certain period of time, and when the amount of change of the acceleration data does not correspond to the set amount of change, the gyro sensor It can be set to remain idle.

4 is a flowchart 400 illustrating a method of operating a wearable device according to various embodiments of the present disclosure.

Referring to FIG. 4 , in operation 401, a processor (eg, the processor 140 of FIG. 1 ) of the wearable device (eg, the wearable device 101 of FIG. 1 ) according to various embodiments is configured as a wear detection sensor (eg: The proximity of the object may be detected from the wear detection sensor 110 of FIG. 1 . The wear detection sensor 110 may be a sensor that detects an object proximate to the wearable device 101 . For example, the wear detection sensor 110 may detect the proximity of an object when the wearable device 101 approaches or is inserted into the user's ear. Alternatively, the wear detection sensor 110 may detect proximity when the wearable device 101 approaches various objects or a user's hand, or when the wearable device 101 is put in a bag or a clothes pocket worn by the user. When the wear detection sensor 110 detects the proximity of the object, the wear detection sensor 110 may transmit the object proximity detection to the processor 140 . The processor 140 may acquire object proximity detection from the wear detection sensor 110 .

In operation 403 , the processor 140 may collect (or acquire) gyro data for a predetermined period of time. The gyro data may be a sensor value obtained from a gyro sensor (eg, the gyro sensor 120 of FIG. 1 ). When the proximity of the object is detected by the wear detection sensor 110 , the processor 140 may acquire gyro data from the gyro sensor 120 . The predetermined time may be set by the wearable device 101 or set by a user. The predetermined time may include a set time after the object proximity is sensed. The processor 140 may acquire gyro data from the gyro sensor 120 for a predetermined time (eg, 3 seconds or 5 seconds).

According to various embodiments, the gyro sensor 120 may always operate (eg, 24 hours) or may operate selectively. For example, when the gyro sensor 120 is always operated, the processor 140 may collect gyro data obtained after the proximity of an object is sensed to detect a wearing state of the wearable device 101 . Alternatively, the gyro sensor 120 maintains an off state (eg, not driven), and when an object proximity is detected, the processor 140 turns the gyro sensor 120 on (eg, drives). state) can be switched (or changed). The processor 140 may acquire gyro data from the gyro sensor 120 for a predetermined time after the object proximity is sensed. After obtaining gyro data from the gyro sensor 120 , the processor 140 may switch the gyro sensor 120 to an off state.

According to various embodiments, the current consumption of the gyro sensor 120 may be greater than that of the wear detection sensor 110 or the acceleration sensor (eg, the acceleration sensor 115 of FIG. 1 ). If the size of the wearable device 101 is small, the capacity of the battery (eg, the battery 190 of FIG. 1 ) may also be small. If the gyro sensor 120 is always operated, the current consumed by the gyro sensor 120 increases. This may reduce the use time of the wearable device 101. In order to prevent the consumption current from increasing, the gyro sensor 120 maintains an off state and detects proximity of an object by the wear detection sensor 110, the gyro The sensor 120 may be switched to an on state. The processor 140 may obtain gyro data from the gyro sensor 120 for a predetermined period of time, and then may switch the gyro sensor 120 to an off state again. The driving of the sensor 120 is only an implementation issue and does not limit the present invention.

In operation 405 , the processor 140 may select sampling data based on the size of the collected gyro data. Since the gyro sensor 120 measures angular velocity, which is a rotational speed (or angle) per time, the gyro data may represent angular velocity, that is, a change in velocity (or change in position) per unit time of the wearable device 101 . The processor 140 may store the gyro data collected for a predetermined time in a memory (eg, the memory 130 ). The processor 140 may select some gyro data having a maximum value among the gyro data stored in the memory 130 as sampling data. For example, the gyro sensor 120 may sense 20 times per second, and the processor 140 may collect (or acquire) 60 gyro data from the gyro sensor 120 for 3 seconds. For example, since the gyro sensor 120 senses the x-axis, y-axis, and z-axis, respectively, the processor 140 generates 60 x-axis gyro data, 60 y-axis gyro data, and 60 z-axis gyro data for 3 seconds. can be collected. The processor 140 selects five x-axis gyro data having a maximum value from among 60 x-axis gyro data as the sampling data, and samples five y-axis gyro data having a maximum value among 60 pieces of y-axis gyro data. It may be selected as data, and 5 z-axis gyro data having a maximum value among 60 z-axis gyro data may be selected as the sampling data. Numerical examples are provided only to help the understanding of the invention, and do not limit the content of the invention.

In operation 407 , the processor 140 may compare the selected sampling data with a reference value. The reference value may refer to a reference value for determining whether the wearable device 101 is worn. The reference value may be determined based on gyro data detected when the user wears the wearable device 101 . The processor 140 may determine whether there is sampling data exceeding the reference value among the selected sampling data.

In operation 409 , the processor 140 may recognize a wearing state of the wearable device 101 based on the comparison result. When the user wears the wearable device 101 , the selected sampling data may be less than a reference value. Alternatively, when the wearable device 101 is put in a bag or a clothes pocket worn by the user, the selected sampling data may be greater than or equal to a reference value. When the selected sampling data is less than a reference value, the processor 140 may determine (or determine) the wearable device 101 as a worn state. When it is determined that the wearable device 101 is worn, the processor 140 may turn on an active noise cancelation (ANC) function or an ambient sound listening function. Alternatively, when a call comes to the external electronic device connected to the wearable device 101 , the processor 140 may control the speaker 165 to output a ring-back sound. Alternatively, when the processor 140 determines that the wearable device 101 is in a worn state, the processor 140 may perform the flowchart 900 of FIG. 9 . When the selected sampling data is equal to or greater than a reference value, the processor 140 may determine (or determine) the wearable device 101 as a non-wearing state. When determining that the wearable device 101 is not worn, the processor 140 may return to operation 401 .

According to various embodiments, the processor 140 may detect whether the wearable device 101 is worn based on the acceleration data obtained from the acceleration sensor 115 before obtaining the gyro data from the gyro sensor 120 . have. When the processor 140 detects an object in operation 401 , the processor 140 may acquire acceleration data from the acceleration sensor 115 for a predetermined period of time. Similar to the wear detection sensor 110 , the value sensed in the acceleration data may be inaccurate. When it is determined whether the wearable device 101 is worn only by the acceleration data, it may be determined that the wearable device 101 is worn even though it is not worn on the user's ear. When it is determined that the wearable device 101 is in a worn state by the wear detection sensor 110 and the acceleration sensor 115 , the processor 140 may use the gyro sensor 120 for more accurate determination.

For example, when the amount of change of the acceleration data corresponds to a set amount of change, the processor 140 may perform operation 403, and when the amount of change of the acceleration data does not correspond to the set amount of change, the processor 140 may determine that it is not worn. The set amount of change may be determined based on acceleration data detected when the user wears the wearable device 101 . When the amount of change of the acceleration data corresponds to the set amount of change, the processor 140 may determine that the wearable device 101 is worn, and may collect the gyro data by driving the gyro sensor 120 . When the amount of change of the acceleration data does not correspond to the set amount of change, the processor 140 may determine that the wearable device 101 is not worn, and may maintain the gyro sensor 120 in a non-driven state. The gyro sensor 120 is maintained in a non-driven state, and when it is determined that the wearable device 101 is in a worn state by the wear detection sensor 110 and the acceleration sensor 115, according to the control of the processor 140 The gyro sensor 120 may be driven.

5 is a diagram illustrating an example of a wearing state of a wearable device according to various embodiments of the present disclosure;

Referring to FIG. 5 , a wearable device (eg, the wearable device 101 of FIG. 1 ) according to various embodiments is worn on the user's ear using a gyro sensor (eg, the gyro sensor 120 of FIG. 1 ) ( 510) can be recognized. In the wearing state 510 , the wearable device 101 may be located within a predetermined distance 513 from the user's body axis 511 . For example, the body axis 511 may be a central axis of the user's body, such as a spine, a vertical central (or middle) axis of a face, or a central axis of a shoulder. In the wearing state 510 , the wearable device 101 may be rotated 515 about the body axis 511 while being fixed to the user's ear to some extent. Here, the rotation 515 may be in a horizontal (eg, left, right) direction or a vertical direction (eg, up or down).

According to various embodiments, the wearing state graph 550 may indicate gyro data (or gyro data value) sensed over time when the wearable device 101 is in the wearing state 510 . Since the gyro sensor 120 measures angular velocity, which is a rotational speed (or angle) per time, the gyro data may represent angular velocity, that is, a change in velocity (or change in position) per unit time of the wearable device 101 . The angular velocity may increase as the measured time is shorter. For example, the angular velocity of a situation in which the user rotates his head a lot slowly and a situation in which the user rotates his head a little quickly may have a large instantaneous value, but the accumulated rotation amount may be smaller. The wearing state graph 550 includes x-axis gyro data 551 and y-axis gyro data 553 collected for a certain period of time after detecting the proximity of an object from a wear detection sensor (eg, the wear detection sensor 110 of FIG. 1 ). , and z-axis gyro data 555 may be represented.

In the wearing state 510, as the rotation of the wearable device 101 has a radius from the body axis 511, the rotation amount (distance) of each axis (eg, x-axis, y-axis, z-axis) is limited. At the same time, the physical rotation time may be increased, and thus the maximum value of the angular velocity may be limited to less than the standard. For example, in the wearing state 510 , values of the gyro data may be measured to be smaller than or equal to a reference value (eg, 280 degrees per second (DPS)). The reference value may be changed according to the design of the wearable device 101 or the position of the gyro sensor 120 mounted on the wearable device 101 . Depending on the state in which the user wears the wearable device 101, the x-axis, y-axis, and z-axis may be the dominant axes, so the maximum value among the x-axis, y-axis, and z-axis is referred to because of the variable for wearing. can do. For example, the processor (eg, the processor 140 of FIG. 1 ) selects a value having the largest data size in the x-axis gyro data 551 , the y-axis gyro data 553 , and the z-axis gyro data 555 . The sampling data 571 and 573 can be selected. When the size of the selected sampling data 571 and 573 is equal to or less than the reference value, the processor 140 may determine the wearable device 101 as the worn state 510 .

6 is a diagram illustrating an example of a non-wearing state of a wearable device according to various embodiments of the present disclosure;

Referring to FIG. 6 , a wearable device (eg, the wearable device 101 of FIG. 1 ) according to various embodiments of the present disclosure is moved to a non-wearing state 610 using a gyro sensor (eg, the gyro sensor 120 of FIG. 1 ). can recognize In the non-wear state 610 , gyro data different from the worn state 510 may be measured. For example, a user may hold the wearable device 101 by hand and put the wearable device 101 in a clothes pocket. When the wearable device 101 enters the clothes pocket, the wearable device 101 may detect the proximity of an object by a wear detection sensor (eg, the wear detection sensor 110 of FIG. 1 ). Since the wearable device 101 acquires gyro data after object proximity (eg, the user's hand), the wearable device 101 can be fixed by the user's hand when the user is holding the wearable device 101 by hand. , a small amount of rotation of the gyro data may be measured.

After the user puts the wearable device 101 in the clothes pocket, the wearable device 101 may rotate while falling into the clothes pocket. When the wearable device 101 rotates in the clothes pocket, as in the wearing state 510 , there is no external fixed axis (eg, the user's body axis 511 ), and based on the own axis 611 of the wearable device 101 . may be rotated in the horizontal direction 613 or the vertical direction 615 . In the non-wear state 610 , since the wearable device 101 rotates about its own axis 611 , even if a rotation amount similar to that of the worn state 510 occurs, the magnitude of the rotation amount may be larger.

According to various embodiments, the wearable state graph 650 may indicate gyro data (or gyro data value) sensed over time when the wearable device 101 is in the not worn state 610 . The non-wear state graph 650 includes x-axis gyro data 651 and y-axis gyro data 653 collected for a certain period of time after detecting the proximity of an object from a wear detection sensor (eg, the wear detection sensor 110 of FIG. 1 ). , and z-axis gyro data 655 may be represented. In the non-wearing state 610 , as in the wearing state 510 , there is no position at which the wearable device 101 is fixed, such as the user's pinna or an ear hole, so that the amount of rotation of the wearable device 101 is measured or large angular velocity. can be measured. For example, in the non-wear state 610 , values of the gyro data may be measured to be greater than a reference value. The processor (eg, the processor 140 of FIG. 1 ) samples the data 671 having the largest size in the x-axis gyro data 651 , the y-axis gyro data 653 , and the z-axis gyro data 655 . , 673) can be selected. When the size (eg, 2000 DPS) of the selected sampling data 671 and 673 exceeds a reference value, the processor 140 may determine the wearable device 101 as the non-wearing state 610 .

7 is a diagram illustrating an example of distinguishing a wearable device from a worn state from a non-wearing state according to various embodiments of the present disclosure;

Referring to FIG. 7 , a wearable device (eg, the wearable device 101 of FIG. 1 ) according to various embodiments is worn on the user's ear using a gyro sensor (eg, the gyro sensor 120 of FIG. 1 ) ( 710) can be recognized. The processor (eg, the processor 140 of FIG. 1 ) may determine whether a pattern is detected from the gyro data in the worn state 710 to distinguish it from the non-wearing state (eg, the non-wearing state 610 of FIG. 6 ). have. When the user shakes the head in a state 710 wearing the wearable device 101 , the range of rotation by the user's body axis 711 (eg, the body axis 511 of FIG. 5 ) may be limited. Also, the rotation range may be in a horizontal direction 713 or a vertical direction 715 with respect to the user's body.

According to various embodiments, the wearing state graph 750 may indicate gyro data (or gyro data value) sensed over time when the head is shaken in the wearing state 710 of the wearable device 101 . The wearing state graph 750 includes x-axis gyro data 751 and y-axis gyro data 753 collected for a certain period of time after detecting the proximity of an object from a wear detection sensor (eg, the wear detection sensor 110 of FIG. 1 ). , and z-axis gyro data 755 . In order for the user to continue shaking the head at a certain speed or more while wearing the wearable device 101 in the state 710 , an action of shaking the head to the side must occur, and thus a repetitive pattern may occur.

The processor (eg, the processor 140 of FIG. 1 ) samples the data 771 having the largest size in the x-axis gyro data 751 , the y-axis gyro data 753 , and the z-axis gyro data 755 . , 773) can be selected. The processor 140 may determine whether the sampling data 771 and 773 have a pattern by identifying an interval between the maximum values of the selected sampling data 771 and 773 . When the user shakes his/her head while wearing the wearable device 101 , it can be seen that a cycle in which the maximum values of the sampling data 771 and 773 are similar is repeated. Even if the maximum value of the sampling data exceeds the reference value in the wearing state 710 , the processor 140 may determine the wearing state when the sampling data has a pattern.

8 is a diagram illustrating another example of distinguishing a wearable device from a worn state from a non-wearing state according to various embodiments of the present disclosure;

Referring to FIG. 8 , a wearable device (eg, the wearable device 101 of FIG. 1 ) according to various embodiments is worn on the user's ear using a gyro sensor (eg, the gyro sensor 120 of FIG. 1 ) ( 810) can be recognized. The user may move the wearable device 101 in a state 810 while wearing the wearable device 101 to put the wearable device 101 well on the ear.

According to various embodiments, the wearing state graph 850 may include gyro data (or gyro data value) sensed over time when the position of the wearable device 101 is adjusted in the wearing state 810 of the wearable device 101 . ) can be represented. The wearing state graph 850 includes x-axis gyro data 851 and y-axis gyro data 853 collected for a certain time after detecting the proximity of an object from a wear detection sensor (eg, the wear detection sensor 110 of FIG. 1 ). , and z-axis gyro data 855 may be represented. When the user moves the wearable device 101 with the user's hand in the state 810 while wearing the wearable device 101, since the wearable device 101 is fixed to the user's ear, it is not fixed such as a bag or a clothes pocket. The range of rotation may be more limited than rotation in position.

The processor (eg, the processor 140 of FIG. 1 ) may select a value having the largest size of the gyro data as the sampling data 871 , 873 , and 875 . The processor 140 identifies an interval between the maximum values of the selected sampling data 871 , 873 , and 875 , and whether the interval between the maximum values of the sampling data 871 , 873 , 875 is longer (or larger) than the set interval reference value. can determine whether In the non-wearing state (eg, FIG. 6 ), the period (or interval) of the maximum value of the sampling data is short, and in actual wearing, the period of the maximum value of the sampling data is long, so that the period may be determined. For example, when the user moves the wearable device 101 by hand while wearing the wearable device 101 , the interval between the maximum values of the sampling data 871 , 873 , and 875 exceeds the set interval reference value. (eg, long case), it may be determined by the actual worn state. Even if the maximum value of the sampling data exceeds the reference value in the wearing state 810 , the processor 140 may determine the wearing state when the interval between the maximum values of the sampling data exceeds the set interval reference value.

9 is a flowchart 900 illustrating a method of checking a wearing state using a gyro sensor of a wearable device according to various embodiments of the present disclosure.

Referring to FIG. 9 , in operation 901 , the processor (eg, the processor 140 of FIG. 1 ) of the wearable device (eg, the wearable device 101 of FIG. 1 ) according to various embodiments operates the wearable device 101 . It may be determined by the wearing state (eg, the wearing state 510 of FIG. 5 ). For example, as in operation 409 of FIG. 4 , the processor 140 detects the proximity of an object by a wear detection sensor (eg, the wear detection sensor 110 of FIG. 1 ), and a gyro sensor (eg, FIG. 1 ) for a predetermined time. When the sampling data selected from among the gyro data acquired from the gyro sensor 120 of No. 1) is equal to or less than the reference value, the wearable device 101 may be determined as the wearing state 510 .

According to various embodiments, the gyro data represents the angular velocity of the wearable device 101 , that is, it may represent a change in velocity (or change in position) per unit time of the wearable device 101 . A large size of the gyro data may mean that the wearable device 101 rotates a lot or that a large angular velocity is measured. In the wearing state 510 , values of the gyro data may be measured to be less than or equal to a reference value. Even in the wearing state 510 , a large size of the gyro data may be detected exceptionally in a specific situation. Even after determining that the wearable device 101 is in the wearing state 510 , the processor 140 determines whether the wearable device 101 is in a specific situation, and in the wearing state 510 , the non-wearing state (eg, the non-wearing state in FIG. 6 ). (610)), it is possible to detect whether it is changed. Hereinafter, operations 903 to 907 may be for determining whether a specific situation exists.

In operation 903 , the processor 140 may identify a maximum value of the sampling data. The sampling data may mean some gyro data having a maximum value among gyro data acquired from the gyro sensor 120 for a predetermined time. The maximum value of the sampling data may mean all sampling data or some sampling data selected based on the size of the collected gyro data. The maximum value corresponds to a vertex (eg, decreasing while increasing, or increasing while decreasing) of the sampling data, and may mean a value having the largest absolute value of the sampling data.

In operation 905 , the processor 140 may identify an interval between the maximum values. For example, when the user shakes the head while wearing the wearable device 101, the range of rotation by the user's body axis (eg, the body axis 511 of FIG. 5 ) may be limited. Alternatively, when the user moves the wearable device 101 with the user's hand in the state 810 while wearing the wearable device 101, since the wearable device 101 is fixed to the user's ear, it is fixed like a bag or a clothes pocket. The rotation range may be more limited than rotating in a non-wearing position (eg, not worn state 610). Referring to the wearing state graph 750 of FIG. 7 and the wearing state graph 850 of FIG. 8 , in the wearing state, the intervals between the maximum values (771 to 773, 871 to 875) of the sampling data have a constant interval and appear periodically. , the interval between the maximum values (771 to 773, 871 to 875) may be measured to be long. Referring to the non-wear state graph 650 of FIG. 6 , in the non-wear state, the interval between the maximum values 671 and 673 of the sampling data does not appear periodically, and the interval between the maximum values 671 and 673 may be measured to be short.

In operation 907, the processor 140 may determine whether a pattern is detected from the sampling data based on the interval between the maximum values. Rotation of an object may occur based on a rotation axis. The rotating axis may be inside or outside the wearable device 101 . When the user shakes the user's body, for example, the neck or body while wearing the wearable device 101 , the wearable device 101 may be rotated by an external rotation axis. When rotating by an external rotation axis, as in the wearing state graph 750 of FIG. 7 , the x-axis gyro data 751 , the y-axis gyro data 753 , and the z-axis gyro data 755 move in a similar tendency. that can be checked Also, it can be seen that a period in which the maximum values of the sampling data 771 and 773 are similar is repeated.

In addition, when the user moves the wearable device 101 while wearing the wearable device 101 , looking at the wearing state graph 850 of FIG. 8 , the interval between the maximum values of the sampling data 871 , 873 , and 875 is If it is longer than the set interval reference value, it may be determined as a wearing state. However, in a state in which the user does not wear the wearable device 101 , the maximum values of the sampling data 671 and 673 may not show a constant pattern as shown in the non-wear state graph 650 of FIG. 6 . The processor 140 may perform operation 909 when a pattern (or period) is detected from the sampling data, and may perform operation 911 when no pattern is detected from the sampling data. In addition, the processor 140 may perform operation 909 when the interval between the maximum values of the sampling data exceeds the set interval reference value, and perform operation 911 when the interval between the maximum values of the sampling data is less than or equal to the set interval reference value. .

When a pattern is detected from the sampling data, in operation 909 , the processor 140 may recognize the wearable device 101 as a worn state. Even if the maximum value of the sampling data exceeds the reference value, the processor 140 may determine the wearing state when the sampling data has a pattern. Referring to the graphs of FIGS. 6 to 8 , in a worn state (eg, FIGS. 7 and 8 ), sampling data (or gyro data) of the x-axis, y-axis, and z-axis shows a similar trend, but in an unworn state In (eg, FIG. 6 ), sampling data (or gyro data) of the x-axis, y-axis, and z-axis may not exhibit a similar tendency. The processor 140 may determine the wearing state when the sampling data of each axis shows a similar tendency. In addition, in an unworn state (eg, FIG. 6 ), the period (or interval) of the maximum value is short, and in a worn state (eg, FIGS. 7 and 8 ), the period of the maximum value is long, so that the period may be determined.

When a pattern is not detected from the sampling data, in operation 911 , the processor 140 may recognize the wearable device 101 as a non-wearing state. When the sampling data exceeds the reference value and the sampling data does not have a pattern, the processor 140 may determine the non-wearing state. When it is determined that the processor 140 is not worn, the processor 140 may return to operation 401 of FIG. 4 to detect the proximity of the object using a wear detection sensor (eg, the wear detection sensor 110 of FIG. 1 ).

According to various embodiments, the processor 140 determines whether the interval between the maximum values of the sampling data, the similarity between the sampling data of each axis, whether a pattern is detected from the sampling data, or the interval between the maximum values of the sampling data is the interval reference value. Whether to wear the wearable device 101 may be determined based on at least one of whether or not it exceeds. When the interval between the maximum values of the sampling data exceeds the interval reference value, the processor 140 may determine the worn state, and when the interval between the maximum values of the sampling data is less than or equal to the interval reference value, the processor 140 may determine the non-wear state. When the sampling data of each axis shows a similar tendency, the processor 140 may determine the wearing state, and when the sampling data of each axis does not show a similar tendency, the processor 140 may determine the non-wearing state.

When the interval between the maximum values of the sampling data is long, the sampling data of each axis shows a similar tendency, and the sampling data shows a periodic pattern, the processor 140 may determine the wearing state. Alternatively, when the interval between the maximum values of the sampling data is short, the sampling data of each axis does not show a similar tendency, and the sampling data does not show a periodic pattern, the processor 140 may determine the non-wearing state.

10 is another flowchart 1000 illustrating a method for checking a wearing state using a gyro sensor of a wearable device according to various embodiments of the present disclosure.

Referring to FIG. 10 , in operation 1001 , a processor (eg, the processor 140 of FIG. 1 ) of the wearable device (eg, the wearable device 101 of FIG. 1 ) according to various embodiments is a wear detection sensor (eg: The proximity of the object may be detected from the wear detection sensor 110 of FIG. 1 . The wear detection sensor 110 may be a sensor that detects an object proximate to the wearable device 101 . When the wear detection sensor 110 detects the proximity of the object, the wear detection sensor 110 may transmit the object proximity detection to the processor 140 . The processor 140 may acquire object proximity detection from the wear detection sensor 110 . Since operation 1001 is the same as or similar to operation 401 of FIG. 4 , a detailed description thereof may be omitted.

In operation 1003 , the processor 140 may obtain acceleration data from an acceleration sensor (eg, the acceleration sensor 115 of FIG. 1 ). When the proximity of the object is sensed by the wear detection sensor 110 , the processor 140 may acquire acceleration data from the acceleration sensor 115 .

In operation 1005 , the processor 140 may detect whether the wearable device 101 is worn based on the acceleration data. The processor 140 may determine whether to collect gyro data from the gyro sensor (eg, the gyro sensor 120 of FIG. 1 ) based on the acquired acceleration data. The processor 140 may perform operation 1007 when the amount of change in the acceleration data corresponds to the set amount of change, and perform operation 1004 when the amount of change in the acceleration data does not correspond to the set amount of change. The set amount of change may be determined based on acceleration data detected when the user wears the wearable device 101 .

When the amount of change of the acceleration data corresponds to the set amount of change, in operation 1007 , the processor 140 may collect (or acquire) the gyro data from the gyro sensor 120 . When the wearable device 101 is determined to be in a worn state by the wear detection sensor 110 and the acceleration sensor 115 , the processor 140 may acquire gyro data for a predetermined time. The predetermined time may be set by the wearable device 101 or set by a user. According to various embodiments, the gyro sensor 120 may always operate (eg, 24 hours) or may operate selectively. When the amount of change of the acceleration data corresponds to the set amount of change, the processor 140 may collect the gyro data for a predetermined time by driving the gyro sensor 120 . The gyro sensor 120 maintains an off state, and when the amount of change in the acceleration data corresponds to a set amount of change, the processor 140 may drive the gyro sensor 120 . Since operation 1007 is the same as or similar to operation 403 of FIG. 4 , a detailed description thereof may be omitted.

In operation 1009 , the processor 140 may select sampling data based on the size of the acquired gyro data. Since the gyro sensor 120 measures angular velocity, which is a rotation speed (or angle) per hour, the gyro data may mean angular velocity. The processor 140 may store the gyro data collected for a predetermined time in a memory (eg, the memory 130 ). The processor 140 may select some gyro data having a maximum value among the gyro data stored in the memory 130 as sampling data. Since operation 1009 is the same as or similar to operation 405 of FIG. 4 , a detailed description thereof may be omitted.

In operation 1011 , the processor 140 may determine whether the selected sampling data is less than a reference value. The reference value may refer to a reference value for determining whether the wearable device 101 is worn. The reference value may be determined based on gyro data detected when the user wears the wearable device 101 . The processor 140 may determine whether there is sampling data exceeding the reference value among the selected sampling data. The processor 140 may perform operation 1013 when the selected sampling data is less than the reference value, and perform operation 1004 if the selected sampling data is greater than or equal to the reference value.

When the selected sampling data is less than the reference value, in operation 1013 , the processor 140 may recognize the wearable device 101 as a worn state. When the processor 140 determines that the wearable device 101 is worn, the ANC function or the ambient sound listening function is turned on, or an audio signal received from an external electronic device connected to the wearable device 101 is transmitted to a speaker (eg, a 1 through the speaker 165). Alternatively, when a call comes to the external electronic device, the processor 140 may control the speaker 165 to output a ring-back sound. Alternatively, when the processor 140 determines that the wearable device 101 is in a worn state, the processor 140 may perform the flowchart 900 of FIG. 9 .

When the amount of change of the acceleration data does not correspond to the set amount of change, or when the selected sampling data is equal to or greater than a reference value, in operation 1004 , the processor 140 may determine that the wearable device 101 is not worn. When the amount of change of the acceleration data does not correspond to the set amount of change, the processor 140 may maintain the gyro sensor 120 in an off state (eg, not driven). If it is determined that the wearable device 101 is not worn, the processor 140 may return to operation 1001 to detect the proximity of the object using the wear detection sensor 110 .

A wearable device (eg, FIG. 1 ) including a wear detection sensor (eg, the wear detection sensor 110 of FIG. 1 ) and a gyro sensor (eg, the gyro sensor 120 of FIG. 1 ) according to various embodiments of the present disclosure The operation method of the wearable device 101) of 1 includes an operation of detecting proximity of an object from the wear detection sensor, an operation of collecting gyro data from the gyro sensor for a certain period of time based on the object proximity detection, and the collected gyro data The method may include selecting sampling data based on the size of , comparing the selected sampling data with a reference value, and recognizing a wearing state of the wearable device based on the comparison result.

The collecting may include collecting the gyro data from the gyro sensor after detecting the proximity of the object.

The selecting may include selecting some gyro data having a maximum value among the collected gyro data as the sampling data.

The selecting operation may include selecting each of x-axis gyro data, y-axis gyro data, and z-axis gyro data as the sampling data.

The operation of recognizing the wearing state includes an operation of determining the wearable device as a worn state when the selected sampling data is less than a reference value, or an operation of determining the wearable device as a non-wearing state when the selected sampling data is greater than or equal to a reference value. may include

The operation of recognizing the wearing state may include an operation of determining the wearable device as a wearing state when the selected sampling data is less than a reference value, an operation of identifying an interval between maximum values of the sampling data, and an interval between the maximum values based on and determining whether a pattern is detected from the sampling data.

The operation of recognizing the wearing state may include, when a pattern is detected from the sampling data, an operation of recognizing the wearable device as a worn state, or when a pattern is not detected from the sampling data, determining the wearable device as a non-wearing state It may include an action to

The operation of recognizing the wearing state may include an interval between the maximum values of the sampling data, a similar tendency between sampling data of the x-axis, y-axis, and z-axis, whether a pattern is detected from the sampling data, or between the maximum values of the sampling data. and determining whether to wear the wearable device based on at least one of whether the interval exceeds a set interval reference value.

The method may further include acquiring acceleration data from an acceleration sensor based on the object proximity detection, and determining whether to collect gyro data from the gyro sensor based on the acquired acceleration data. have.

In the collecting operation, when the amount of change of the acceleration data corresponds to a set amount of change, driving the gyro sensor to collect the gyro data for a predetermined time, or when the amount of change of the acceleration data does not correspond to the set amount of change, It may include an operation of maintaining the gyro sensor in a non-driving state.

The various embodiments of this document and terms used therein are not intended to limit the technical features described in this document to specific embodiments, but it should be understood to include various modifications, equivalents, or substitutions of the embodiments. In connection with the description of the drawings, like reference numerals may be used for similar or related components. The singular form of the noun corresponding to the item may include one or more of the item, unless the relevant context clearly dictates otherwise. As used herein, "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 "A , B, or C," each of which may include any one of the items listed together in the corresponding one of the phrases, or all possible combinations thereof. Terms such as “first”, “second”, or “first” or “second” may simply be used to distinguish the component from other such components, and refer to those components in other aspects (e.g., importance or order) is not limited. It is said that one (eg, first) component is “coupled” or “connected” to another (eg, second) component, with or without the terms “functionally” or “communicatively”. When referenced, it means that one component can be connected to the other component directly (eg by wire), wirelessly, or through a third component.

The term “module” used in various embodiments of this document may include a unit implemented in hardware, software, or firmware, and is interchangeable with terms such as, for example, logic, logic block, component, or circuit. can be used as A module may be an integrally formed part or a minimum unit or a part of the part that performs one or more functions. For example, according to an embodiment, the module may be implemented in the form of an application-specific integrated circuit (ASIC).

Various embodiments of the present document may be implemented as software including one or more instructions stored in a storage medium (eg, memory 130) readable by a machine (eg, wearable device 101). can For example, the processor (eg, the processor 140 ) of the device (eg, the wearable device 101 ) may call at least one of the one or more instructions stored from the storage medium and execute it. This makes it possible for the device to be operated to perform at least one function according to the called at least one command. The one or more instructions may include code generated by a compiler or code executable by an interpreter. The device-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-transitory' only means that the storage medium is a tangible device and does not contain a signal (eg, electromagnetic wave), and this term refers to the case where data is semi-permanently stored in the storage medium and It does not distinguish between temporary storage cases.

According to one embodiment, the method according to various embodiments disclosed in this document may be provided in a computer program product (computer program product). Computer program products may be traded between sellers and buyers as commodities. The computer program product is distributed in the form of a machine-readable storage medium (eg compact disc read only memory (CD-ROM)), or via an application store (eg Play Store ^TM ) or on two user devices ( It can be distributed (eg downloaded or uploaded) directly, online between smartphones (eg: smartphones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created in a machine-readable storage medium such as a memory of a server of a manufacturer, a server of an application store, or a relay server.

According to various embodiments, each component (eg, a module or a program) of the above-described components may include a singular or a plurality of entities, and some of the plurality of entities may be separately disposed in other components. have. According to various embodiments, one or more components or operations among the above-described corresponding components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (eg, a module or a program) may be integrated into one component. In this case, the integrated component may perform one or more functions of each component 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, operations performed by a module, program, or other component are executed sequentially, in parallel, repeatedly, or heuristically, or one or more of the operations are executed in a different order, or omitted. , or one or more other operations may be added.

Various embodiments of the present invention disclosed in the present specification and drawings are merely provided for specific examples in order to easily explain the technical contents of the present invention and help the understanding of the present invention, and are not intended to limit the scope of the present invention. Therefore, the scope of the present invention should be construed as including all changes or modifications derived based on the technical spirit of the present invention in addition to the embodiments disclosed herein are included in the scope of the present invention.

Claims (15)

In a wearable device, wear detection sensor; gyro sensor; Memory; and a processor operatively connected to the wear detection sensor, the gyro sensor, and the memory; The processor is Detect the proximity of the object from the wear detection sensor, Collecting gyro data from the gyro sensor for a certain period of time based on the object proximity detection, selecting sampling data based on the size of the collected gyro data; comparing the selected sampling data with a reference value; A wearable device configured to recognize a wearing state of the wearable device based on the comparison result. The method of claim 1, wherein the processor comprises: A wearable device configured to collect the gyro data from the gyro sensor after detecting the proximity of the object. The method of claim 1, wherein the processor comprises: A wearable device configured to select some gyro data having a maximum value among the collected gyro data as the sampling data. The method of claim 3, wherein the processor comprises: A wearable device configured to select x-axis gyro data, y-axis gyro data, and z-axis gyro data as the sampling data, respectively. The method of claim 1, wherein the processor comprises: When the selected sampling data is less than the reference value, it is determined that the wearable device is worn, A wearable device configured to determine that the wearable device is not worn when the selected sampling data is equal to or greater than a reference value. The method of claim 1, wherein the processor comprises: When the selected sampling data is less than the reference value, it is determined that the wearable device is worn, identifying an interval between the maximum values of the sampling data; A wearable device configured to determine whether a pattern is detected from the sampling data based on an interval between the maximum values. The method of claim 6, wherein the processor comprises: When a pattern is detected from the sampling data, the wearable device is recognized as a worn state, A wearable device configured to determine that the wearable device is not worn when a pattern is not detected from the sampling data. The method of claim 6, wherein the processor comprises: The interval between the maximum values of the sampling data, the similarity between the sampling data of the x-axis, the y-axis, and the z-axis, whether a pattern is detected from the sampling data, and whether the interval between the maximum values of the sampling data exceeds a set interval reference value A wearable device configured to determine whether to wear the wearable device based on at least one. According to claim 1, further comprising an accelerometer; The processor is Acceleration data is obtained from the acceleration sensor based on the object proximity detection, A wearable device configured to determine whether to collect gyro data from the gyro sensor based on the acquired acceleration data. 10. The method of claim 9, wherein the processor, When the amount of change of the acceleration data corresponds to the set amount of change, the gyro sensor is driven to collect the gyro data for a certain period of time; A wearable device configured to maintain the gyro sensor in a non-driving state when the amount of change of the acceleration data does not correspond to the set amount of change. A method of operating a wearable device including a wear detection sensor and a gyro sensor, the method comprising: detecting proximity of an object from the wear detection sensor; collecting gyro data from the gyro sensor for a predetermined time based on the object proximity detection; selecting sampling data based on the size of the collected gyro data; comparing the selected sampling data with a reference value; and and recognizing a wearing state of the wearable device based on the comparison result. The method of claim 11, wherein the selecting operation comprises: and selecting some gyro data having a maximum value among the collected gyro data as the sampling data. The method of claim 12, wherein the selecting operation comprises: and selecting each of x-axis gyro data, y-axis gyro data, and z-axis gyro data as the sampling data. The method of claim 11, wherein the operation of recognizing the wearing state comprises: determining that the wearable device is in a worn state when the selected sampling data is less than a reference value; or and determining that the wearable device is not worn when the selected sampling data is equal to or greater than a reference value. The method of claim 11, wherein the operation of recognizing the wearing state comprises: determining that the wearable device is in a worn state when the selected sampling data is less than a reference value; identifying an interval between the maximum values of the sampled data; and and determining whether a pattern is detected from the sampling data based on an interval between the maximum values.

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