A method, device, smart wearable device and storage medium for processing communication information

Abstract

The embodiments of the present application provide a method, apparatus, smart wearable device and storage medium for processing communication information, the method comprising: obtaining acceleration data collected by an acceleration sensor, wherein the acceleration data comprises an X-axis acceleration value, a Y-axis acceleration value and a Z-axis acceleration value of the acceleration sensor, wherein the X-axis is a number axis parallel to the arm, and the Y-axis and the Z-axis are perpendicular to each other and both perpendicular to the X-axis; determining the arm state according to the X-axis acceleration value of the acceleration sensor; when it is determined that the arm state matches the preset arm state, determining a rotation gesture feature according to the Y-axis acceleration value and / or the Z-axis acceleration value, wherein the rotation gesture feature comprises the number of rotations; and controlling the smart wearable device to process the communication information according to a control instruction corresponding to a target gesture matching the rotation gesture feature and the arm state, so that processing communication information through gestures becomes an urgent problem to be solved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of intelligent control, and specifically to a method, apparatus, intelligent wearable device and storage medium for processing communication information. Background Art

[0002] In the related technology, with the development of the smart wearable industry, people have put forward more and more requirements for the functions of smart wearable devices. At present, the way of smart wearable devices is to operate the screen or button to answer and hang up the call, remove the bracelet body from the wristband to answer the call, and put it back on the wristband to hang up the call. However, since it needs to be done manually, it will bring inconvenience in scenes such as running, cycling or driving.

[0003] Therefore, how to process communication information through gestures becomes an urgent problem to be solved. Summary of the invention

[0004] Embodiments of the present application provide a method, an apparatus, a smart wearable device, and a storage medium for processing communication information. Through some embodiments of the present application, at least the communication information of the smart wearable device can be processed through gestures.

[0005] In a first aspect, an embodiment of the present application provides a method for processing communication information, which is applied to a smart wearable device, which is used to be worn on a user's arm. The smart wearable device includes an acceleration sensor, and the method includes: obtaining acceleration data collected by the acceleration sensor, wherein the acceleration data includes an X-axis acceleration value, a Y-axis acceleration value, and a Z-axis acceleration value of the acceleration sensor, wherein the X-axis is a number axis parallel to the arm, and the Y-axis and the Z-axis are perpendicular to each other and both perpendicular to the X-axis; determining an arm state according to the X-axis acceleration value of the acceleration sensor; when it is determined that the arm state matches a preset arm state, determining a rotation gesture feature according to the Y-axis acceleration value and / or the Z-axis acceleration value, wherein the rotation gesture feature includes the number of rotations; and controlling the smart wearable device to process the communication information according to a control instruction corresponding to a target gesture matching the rotation gesture feature and the arm state.

[0006] Therefore, the embodiment of the present application can use an acceleration sensor including X, Y and Z axes to determine the arm state through a method of processing communication information, so as to determine the rotation gesture characteristics according to the arm state, thereby realizing the use of specific gesture actions to control the smart wearable device to process communication information, thereby enhancing the operability and practicality of incoming calls in scenarios such as walking, running, cycling, driving, etc., and using an acceleration sensor to collect data can reduce hardware costs, which is beneficial to controlling the power consumption of the overall smart wearable device.

[0007] In combination with the first aspect, in one embodiment, before determining the arm state according to the X-axis acceleration value, the method also includes: determining the motion state according to the X-axis acceleration value, the Y-axis acceleration value and the Z-axis acceleration value; wherein, determining the arm state according to the X-axis acceleration value includes: determining the arm state according to the X-axis acceleration value and the motion state.

[0008] Therefore, the embodiment of the present application determines the motion state before determining the arm state, and can determine the arm state according to different motion states, thereby enhancing the accuracy of recognition and reducing misjudgment.

[0009] In combination with the first aspect, in one implementation, the motion state is determined according to the X-axis acceleration value, the Y-axis acceleration value and the Z-axis acceleration value, including: obtaining the X-axis instantaneous momentum, the Y-axis instantaneous momentum and the Z-axis instantaneous momentum according to the X-axis acceleration value, the Y-axis acceleration value and the Z-axis acceleration value, respectively; and judging the motion state according to the X-axis instantaneous momentum, the Y-axis instantaneous momentum and the Z-axis instantaneous momentum.

[0010] In combination with the first aspect, in one embodiment, the motion state is judged according to the X-axis instantaneous momentum, the Y-axis instantaneous momentum and the Z-axis instantaneous momentum, including: calculating the maximum instantaneous momentum among the X-axis instantaneous momentum, the Y-axis instantaneous momentum and the Z-axis instantaneous momentum; comparing the maximum instantaneous momentum with the motion state threshold to obtain a comparison result; and judging the motion state according to the comparison result.

[0011] Therefore, the embodiments of the present application can perform rotation recognition through momentum changes. When the user rotates slowly, the momentum change is small, resulting in difficulty in recognition, thereby reducing the impact on gesture judgment during strenuous exercise (such as running) by the user.

[0012] In combination with the first aspect, in one embodiment, determining the arm state according to the X-axis acceleration value and the motion state includes: judging whether the X-axis acceleration value falls within a preset acceleration threshold range, wherein different motion states and different arm states correspond to different X-axis acceleration threshold ranges, respectively.

[0013] Therefore, the embodiment of the present application determines the arm state according to the motion state, and can take into account the arm state under different motion states, thereby reducing the impact on gesture judgment during strenuous exercise (such as running) of the user.

[0014] In combination with the first aspect, in one embodiment, when it is determined that the arm state matches the preset arm state, the rotation gesture characteristics are determined according to the Y-axis acceleration value and / or the Z-axis acceleration value, including: when the arm state is vertical or horizontal, the Y-axis acceleration value and the Z-axis acceleration value are calculated to obtain the Y-axis instantaneous momentum and the Z-axis instantaneous momentum; based on the Y-axis instantaneous momentum and / or the Z-axis instantaneous momentum, the rotation gesture characteristics are judged.

[0015] Therefore, the embodiment of the present application can accurately judge the rotation gesture characteristics of a person when performing a gesture by determining the rotation gesture characteristics according to the Y-axis acceleration value and / or the Z-axis acceleration value when determining that the arm state matches the preset arm state, thereby avoiding misjudgment.

[0016] In combination with the first aspect, in one embodiment, the characteristics of the rotation gesture are judged according to the instantaneous momentum of the Y-axis and / or the instantaneous momentum of the Z-axis, including: in response to the existence of at least two consecutive sensor sampling points in the positive direction of the Y-axis and the negative direction of the Y-axis with an absolute value of the instantaneous momentum greater than a momentum threshold, identifying it as a rotation; or in response to the existence of at least two consecutive sensor sampling points in the positive direction of the Z-axis and the negative direction of the Z-axis with an absolute value of the instantaneous momentum greater than a momentum threshold, identifying it as a rotation.

[0017] In combination with the first aspect, in one embodiment, the characteristics of the rotation gesture are judged according to the instantaneous momentum of the Y-axis and / or the instantaneous momentum of the Z-axis, including: calculating the momentum difference between the instantaneous momentum of the Y-axis and the instantaneous momentum of the Z-axis; in response to the existence of at least two consecutive sensor sampling points in both the positive and negative directions of the Y-axis or the Z-axis, the absolute value of the momentum difference is greater than the momentum difference threshold, identifying it as a rotation.

[0018] Therefore, the embodiment of the present application can use rotation recognition to calculate the instantaneous momentum difference between the Y-axis and the Z-axis when the force directions of the two are different during the rotation process, which can expand the change characteristics, make the change characteristics more obvious, and easier to identify, thereby increasing the recognition accuracy.

[0019] In combination with the first aspect, in one embodiment, according to the control instruction corresponding to the preset feature information matching the rotation gesture feature, the smart wearable device is controlled to process the communication information, including: within the preset time, when the number of rotations is greater than or equal to N times, judging whether the arm maintains the arm state during the rotation process according to the X-axis acceleration value or the X-axis acceleration average, where N is an integer greater than or equal to 2; when the arm state is maintained, matching the rotation gesture feature with the target gesture to obtain a recognition result; according to the recognition result, controlling the smart wearable device to process the communication information.

[0020] Therefore, the embodiment of the present application matches the rotation gesture feature with the target gesture while maintaining the arm state, and controls the smart wearable device to process the communication information. This can ensure that the arm always remains in a horizontal or vertical posture during the arm rotation action, avoid misjudgment, and thus accurately control the smart wearable device to process the communication information.

[0021] In a second aspect, a device for processing communication information is applied to a smart wearable device, which is used to be worn on a user's arm. The smart wearable device includes an acceleration sensor, and the device includes: an acquisition module, which is used to acquire acceleration data collected by the acceleration sensor, wherein the acceleration data includes an X-axis acceleration value, a Y-axis acceleration value and a Z-axis acceleration value of the acceleration sensor, wherein the X-axis is a number axis parallel to the arm, and the Y-axis and the Z-axis are perpendicular to each other and both perpendicular to the X-axis; a determination module, which is used to determine the arm state according to the X-axis acceleration value; a judgment module, which is used to determine the rotation gesture feature according to the Y-axis acceleration value and / or the Z-axis acceleration value when it is determined that the arm state matches the preset arm state, wherein the rotation gesture feature includes the number of rotations; a control module, which is used to control the smart wearable device to process the communication information according to the control instruction corresponding to the target gesture matching the rotation gesture feature and the arm state.

[0022] In combination with the second aspect, in one embodiment, the determination module is specifically used to: determine the motion state according to the X-axis acceleration value, the Y-axis acceleration value and the Z-axis acceleration value; wherein, determining the arm state according to the X-axis acceleration value includes: determining the arm state according to the X-axis acceleration value and the motion state.

[0023] In combination with the second aspect, in one embodiment, the determination module is also used to: obtain the X-axis instantaneous momentum, the Y-axis instantaneous momentum and the Z-axis instantaneous momentum according to the X-axis acceleration value, the Y-axis acceleration value and the Z-axis acceleration value respectively; and judge the motion state according to the X-axis instantaneous momentum, the Y-axis instantaneous momentum and the Z-axis instantaneous momentum.

[0024] In combination with the second aspect, in one embodiment, the determination module is also used to: calculate the maximum instantaneous momentum among the X-axis instantaneous momentum, the Y-axis instantaneous momentum and the Z-axis instantaneous momentum; compare the maximum instantaneous momentum with the motion state threshold to obtain a comparison result; and judge the motion state based on the comparison result.

[0025] In combination with the second aspect, in one embodiment, determining the arm state according to the X-axis acceleration value and the motion state includes: judging whether the X-axis acceleration value falls within a preset acceleration threshold interval, wherein different motion states and different arm states correspond to different X-axis acceleration threshold intervals, respectively.

[0026] In combination with the second aspect, in one embodiment, the judgment module is specifically used to: when it is determined that the arm state matches the preset arm state, determine the rotation gesture characteristics according to the Y-axis acceleration value and / or the Z-axis acceleration value, including: when the arm state is vertical or horizontal, calculate the Y-axis acceleration value and the Z-axis acceleration value to obtain the Y-axis instantaneous momentum and the Z-axis instantaneous momentum; judge the rotation gesture characteristics according to the Y-axis instantaneous momentum and / or the Z-axis instantaneous momentum.

[0027] In combination with the second aspect, in one embodiment, the judgment module is specifically used to: in response to the existence of at least two consecutive sensor sampling points in the positive direction of the Y-axis and the negative direction of the Y-axis with an absolute value of the instantaneous momentum greater than the momentum threshold, identify it as a rotation; or in response to the existence of at least two consecutive sensor sampling points in the positive direction of the Z-axis and the negative direction of the Z-axis with an absolute value of the instantaneous momentum greater than the momentum threshold, identify it as a rotation.

[0028] In combination with the second aspect, in one embodiment, the judgment module is specifically used to: judge the rotation gesture characteristics according to the Y-axis instantaneous momentum and / or the Z-axis instantaneous momentum, including: calculating the momentum difference between the Y-axis instantaneous momentum and the Z-axis instantaneous momentum; in response to the existence of at least two consecutive sensor sampling points in both the positive and negative directions of the Y-axis or Z-axis, the absolute value of the momentum difference is greater than the momentum difference threshold, identifying it as a rotation.

[0029] In combination with the second aspect, in one embodiment, the control module is specifically used to: control the smart wearable device to process communication information according to the control instruction corresponding to the preset feature information matching the rotation gesture feature, including: within the preset time, when the number of rotations is greater than or equal to N times, judging whether the arm maintains the arm state during the rotation process according to the X-axis acceleration value or the X-axis acceleration average, where N is an integer greater than or equal to 2; when the arm state is maintained, matching the rotation gesture feature with the target gesture to obtain a recognition result; and according to the recognition result, controlling the smart wearable device to process the communication information.

[0030] In the third aspect, a smart wearable device includes: an acceleration sensor, a processor, a memory and a bus; the acceleration sensor is used to collect acceleration data; the memory stores computer-readable instructions; the processor is connected to the memory and the acceleration sensor through the bus, and is used to execute the computer-readable instructions in the memory to implement the method for processing communication information as in the first aspect and all embodiments thereof.

[0031] In a fourth aspect, a computer-readable storage medium stores a computer program, which, when executed by a server, implements the method for processing communication information as in the first aspect and all embodiments thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 is a flow chart of a method for processing communication information shown in an embodiment of the present application;

[0033] Figure 2 is a schematic diagram of coordinate axes of a smart wearable device shown in an embodiment of the present application;

[0034] Figure 3 is a flow chart of processing incoming calls shown in an embodiment of the present application;

[0035] Figure 4 is an internal structure diagram of a device for processing communication information shown in an embodiment of the present application;

[0036] Figure 5 It is a diagram of the internal structure of a smart wearable device shown in an embodiment of the present application. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0038] The method steps in the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0039] The implementation of this application can be applied to a variety of scenarios for processing communication information, for example, these scenarios include scenarios for controlling smart wearable devices to process information during the process of answering and hanging up calls. In the case where people have higher and higher requirements for the functions of smart wearable devices, there are still many inconveniences in the process of people manually operating smart wearable devices to answer and hang up calls. Therefore, the inventor of this application found that the method for processing communication information provided by some embodiments of this application can realize the use of specific gestures to control smart wearable devices to process communication information, thereby enhancing the operability and practicality of incoming calls in scenes such as walking, running, cycling, and driving, and using acceleration sensors to collect data can reduce hardware costs, which is beneficial to controlling the power consumption of the overall smart wearable device. It can be understood that the application scenarios of the embodiments of this application are not limited to controlling smart wearable devices to answer and hang up calls, but can also answer voice, video, etc.

[0040] In the related technology, with the development of the smart wearable industry, people have put forward more and more requirements for the functions of smart wearable devices. At present, the way of smart wearable devices is to operate the screen or button to answer and hang up the phone, remove the bracelet body from the wristband to answer the call, and put it back on the wristband to hang up the call. However, since it needs to be done manually, it will bring inconvenience in scenes such as running, cycling or driving. Therefore, how to process communication information through gestures has become an urgent problem to be solved.

[0041] In view of the above problems, the embodiments of the present application provide a method, apparatus, smart wearable device and storage medium for processing communication information, the method comprising: obtaining acceleration data collected by an acceleration sensor, wherein the acceleration data comprises an X-axis acceleration value, a Y-axis acceleration value and a Z-axis acceleration value of the acceleration sensor, wherein the X-axis is a number axis parallel to the arm, and the Y-axis and the Z-axis are perpendicular to each other and both perpendicular to the X-axis; determining the arm state according to the X-axis acceleration value of the acceleration sensor; when it is determined that the arm state matches the preset arm state, determining a rotation gesture feature according to the Y-axis acceleration value and / or the Z-axis acceleration value, wherein the rotation gesture feature comprises the number of rotations; controlling the smart wearable device to process the communication information according to a control instruction corresponding to a target gesture matching the rotation gesture feature and the arm state, so that processing communication information through gestures becomes an urgent problem to be solved.

[0042] The following will be combined Figure 1 A method for processing communication information is described in detail, such as Figure 1 The steps shown include:

[0043] S110, acquiring acceleration data collected by an acceleration sensor.

[0044] Target gestures corresponding to different rotation gesture features and arm states are pre-stored in the memory of the smart wearable device, and an association relationship between a call answering instruction and a call hang-up instruction corresponding to the target gesture is set. For example, when the target gesture for answering a call is to rotate the arm horizontally twice, the call answering instruction is triggered when this target gesture is met.

[0045] It should be noted that the smart wearable device may be a smart watch, a smart bracelet, etc., but the implementation of this application is not limited thereto.

[0046] In one embodiment, acceleration data collected by an acceleration sensor is obtained, wherein the acceleration data includes an X-axis acceleration value, a Y-axis acceleration value, and a Z-axis acceleration value of the acceleration sensor, wherein the X-axis is a numerical axis parallel to the arm, and the Y-axis and the Z-axis are perpendicular to each other and are both perpendicular to the X-axis.

[0047] During an incoming call, the acceleration sensor collects the acceleration data of the user's gesture in real time and transmits it to the processor of the smart wearable device. The processor obtains the acceleration data collected by the acceleration sensor. The acquired acceleration data includes the acceleration values ​​of the X-axis, the Y-axis and the Z-axis. Figure 2 As shown, the Z axis of the acceleration sensor is perpendicular to the touch screen of the smart wearable device, the X axis and Y axis of the acceleration sensor are perpendicular to each other and parallel to the touch screen, and the X axis is parallel to the arm.

[0048] The above describes that the processor of the smart wearable device obtains the acceleration data collected by the acceleration sensor, and the following will describe that the processor determines the arm state according to the X-axis acceleration value of the acceleration sensor.

[0049] S120, determining the arm state according to the X-axis acceleration value of the acceleration sensor.

[0050] In one embodiment, before determining the arm state according to the X-axis acceleration value, the method further includes: determining the motion state according to the X-axis acceleration value, the Y-axis acceleration value and the Z-axis acceleration value; and determining the arm state according to the X-axis acceleration value and the motion state. Figure 2 As shown, a three-dimensional coordinate system based on the smart wearable device can be established, and the coordinate system includes an X-axis, a Y-axis, and a Z-axis. Based on the coordinate system, the moving directions of the smart wearable device include the positive direction of the X-axis, the negative direction of the X-axis, the positive direction of the Y-axis, the negative direction of the Y-axis, the positive direction of the Z-axis, and the negative direction of the Z-axis.

[0051] In this embodiment, the X-axis is a digital axis parallel to the arm, and the Y-axis and the Z-axis are perpendicular to each other and perpendicular to the X-axis. The acceleration data of the smart wearable device includes the X-axis acceleration value, the Y-axis acceleration value, and the Z-axis acceleration value. When the acceleration sensor detects the acceleration in the positive direction of the X-axis, it outputs a positive X-axis acceleration value. When the acceleration sensor detects the acceleration in the negative direction of the X-axis, it outputs a negative X-axis acceleration value. Similarly, when the acceleration sensor detects the acceleration in different directions of the Y-axis and the Z-axis, the output Y-axis acceleration value and the Z-axis acceleration value are positive or negative.

[0052] Since the smart wearable device is worn on the user's arm, the accelerometer can be used to detect the movement and state of the user's arm. Specifically, for example, if the user's arm is in a horizontal state (such as Figure 2), the X-axis direction of the smart wearable device is not subjected to force, and the X-axis acceleration data is basically 0; when the user's arm is perpendicular to the ground and facing the ground, the positive direction of the X-axis of the smart wearable device is subject to gravity, then the X-axis acceleration value is equal to the gravity acceleration value of 1G, if the user's arm is perpendicular to the ground and facing the opposite direction of the ground, the negative direction of the X-axis of the smart wearable device is subject to gravity, then the X-axis acceleration value is -1G. Therefore, the user's arm state can be determined by the X-axis acceleration value. In addition, the same posture of the user in a static state and in a moving state will be affected by the movement. For example, when the user's arm is kept horizontal in a static state, the X-axis acceleration value of the acceleration sensor is basically 0; when the user keeps his arm horizontal during walking, running or other sports, the X-axis direction of the smart wearable device may be subjected to force (including the force of the user's arm and / or gravity) due to movement, geographical location or other factors, then the X-axis acceleration value of the acceleration sensor will increase (subject to the force in the positive direction of the X-axis) or decrease (subject to the force in the negative direction of the X-axis), and the absolute value of the X-axis acceleration value will increase. Therefore, when judging the state of the user's arm, the user's movement state also needs to be considered.

[0053] In one embodiment, the instantaneous momentum of the X-axis, the instantaneous momentum of the Y-axis, and the instantaneous momentum of the Z-axis are obtained according to the acceleration value of the X-axis, the acceleration value of the Y-axis, and the acceleration value of the Z-axis, respectively; the motion state is determined according to the instantaneous momentum of the X-axis, the instantaneous momentum of the Y-axis, and the instantaneous momentum of the Z-axis. Specifically, the maximum instantaneous momentum among the instantaneous momentum of the X-axis, the instantaneous momentum of the Y-axis, and the instantaneous momentum of the Z-axis can be calculated; the maximum instantaneous momentum can be compared with the motion state threshold to obtain a comparison result; and the motion state can be determined according to the comparison result.

[0054] It should be noted that the motion state may include strenuous motion and non-strenuous motion, and may also include complete stillness, slight activity, normal activity, etc., but the embodiments of the present application are not limited thereto.

[0055] Therefore, the embodiments of the present application can determine the arm state according to different motion states by determining the motion state before determining the arm state, thereby enhancing the accuracy of recognition and reducing misjudgment. Rotation recognition is performed through momentum change. When the user rotates slowly, the momentum change is small, resulting in difficulty in recognition, thereby reducing the impact of gesture judgment during strenuous exercise (such as running) by the user.

[0056] The following describes in detail the process of determining the exercise state by taking the exercise states of strenuous exercise and non-strenuous exercise as examples.

[0057] After obtaining the X-axis acceleration value, the Y-axis acceleration value and the Z-axis acceleration value, the X-axis instantaneous momentum corresponding to the X-axis acceleration value, the Y-axis instantaneous momentum corresponding to the Y-axis acceleration value and the Z-axis instantaneous momentum corresponding to the Z-axis acceleration value are calculated, and then the maximum instantaneous momentum of the three axes is calculated according to the instantaneous momentum of the three axes, that is, the motion state is determined according to the maximum instantaneous momentum of the instantaneous momentum of the three axes of X, Y, and Z, and the maximum instantaneous momentum is compared with the preset motion state threshold. If the maximum instantaneous momentum falls within the violent motion state threshold interval, it is judged as a violent motion state, and if the maximum instantaneous momentum falls within the non-violent motion state threshold interval, it is judged as a non-violent motion state. Since momentum and acceleration are positively correlated, in practical applications, the difference between the readings of the previous sampling point and the next sampling point of the acceleration sensor can be equated with the momentum of the user's arm, so the threshold of the difference between the previous sampling point and the next sampling point of the acceleration sensor can be set as the motion state threshold, and the calculation method of instantaneous momentum can also refer to other existing technologies.

[0058] It should be noted that the motion state threshold can be determined according to actual conditions, and in some embodiments, the motion state threshold corresponding to different motion states includes multiple values. For example, the motion state threshold can be set under motion states such as complete stillness, slight activity, and normal activity.

[0059] In one embodiment, the arm state is determined according to the X-axis acceleration value and the motion state, including: judging whether the X-axis acceleration value falls within a preset acceleration threshold interval, wherein different motion states and different arm states correspond to different X-axis acceleration threshold intervals. For example, it can be predefined that in a violent motion state, when the user's arm is in a horizontal state, the X-axis acceleration corresponds to a first threshold interval, and when the user's arm is in a vertical state, the X-axis acceleration corresponds to a second threshold interval; in a non-violent motion state, when the user's arm is in a horizontal state, the X-axis acceleration corresponds to a third threshold interval, and when the user's arm is in a vertical state, the X-axis acceleration corresponds to a fourth threshold interval. If the smart wearable device recognizes that the current user's motion state is a violent motion state, and the X-axis acceleration value of the acceleration sensor falls within the second threshold interval, the user's arm state is recognized as a vertical state.

[0060] In a specific embodiment, when the motion state is strenuous motion, the first threshold interval corresponding to the horizontal state of the arm is [-0.2G, 0.2G], and the second threshold interval corresponding to the vertical state of the arm is [0.8G, 1.2G] and [-1.2, -0.8G,]. The positive threshold interval represents that the arm is facing downward, and the negative threshold interval represents that the arm is facing upward; when the motion state is non-strenuous motion, the third threshold interval corresponding to the horizontal state of the arm is [-0.1G, 0.1G], and the fourth threshold interval corresponding to the vertical state of the arm is [0.9G, 1.1G] and [-1.1G, -0.9G]. It can be seen that the X-axis acceleration threshold interval in the strenuous motion state is greater than the arm state threshold interval in the non-strenuous motion state. In fact, the reading of the acceleration sensor is a specific value, and the threshold interval based on the acceleration sensor reading can be set according to the correspondence between the acceleration sensor reading and the gravity value. For example, the correspondence between the acceleration sensor reading and the gravity value is such that the acceleration count value 4 is 1g, and the acceleration count value 4 is 0g, so the threshold interval of the acceleration sensor reading is set based on the correspondence. The conversion relationship between the acceleration sensor reading and the gravity value can refer to the prior art and will not be described in detail here.

[0061] Therefore, the embodiment of the present application judges the arm state in combination with the user's movement state, and then determines the rotation gesture characteristics according to the Y-axis acceleration value and / or the Z-axis acceleration value, which can accurately judge the rotation gesture characteristics of a person when performing a gesture, thereby avoiding misjudgment.

[0062] It should be noted that the arm state can be any pre-set state related to control information communication, which can be a vertical state and a horizontal state, or a forward extending state or a backward extending state. The embodiments of the present application are not limited to this.

[0063] The above describes in detail the detailed process of determining the arm state according to the X-axis acceleration value, and the following will describe the detailed process of determining the rotation gesture feature according to the Y-axis acceleration value and / or the Z-axis acceleration value.

[0064] S130: Determine a rotation gesture feature according to the Y-axis acceleration value and / or the Z-axis acceleration value.

[0065] It should be noted that the step of identifying the rotation gesture feature is performed only when the arm state is determined to be the specified arm state capable of realizing control information communication, otherwise no identification is performed. For example: when the arm state is determined to be a vertical state or a horizontal state, steps 130 and 140 are performed, otherwise no identification is performed. When it is determined that the arm state matches the preset arm state, the rotation gesture feature is determined according to the Y-axis acceleration value and / or the Z-axis acceleration value, wherein the rotation gesture feature includes the number of rotations.

[0066] In one embodiment, when the arm is in a vertical or horizontal state, the Y-axis acceleration value and the Z-axis acceleration value are calculated to obtain the Y-axis instantaneous momentum and the Z-axis instantaneous momentum; the rotation gesture feature is determined based on the Y-axis instantaneous momentum and / or the Z-axis instantaneous momentum.

[0067] In the embodiment of the present invention, the user's rotation gesture feature can be determined by the Y-axis instantaneous momentum or the Z-axis instantaneous momentum, or the user's rotation gesture feature can be determined according to the difference between the Y-axis and Z-axis instantaneous momentums. The following will describe the two different methods in detail.

[0068] In one embodiment, in response to the existence of at least two consecutive sensor sampling points in the positive direction of the Y axis and the negative direction of the Y axis with an absolute value of the instantaneous momentum greater than the momentum threshold, it is recognized as a rotation; or in response to the existence of at least two consecutive sensor sampling points in the positive direction of the Z axis and the negative direction of the Z axis with an absolute value of the instantaneous momentum greater than the momentum threshold, it is recognized as a rotation. When the user rotates his arm, the wrist rotates once in both the instantaneous clockwise and counterclockwise directions and returns to the original state before it is recognized as a complete rotation. Therefore, it is necessary to consider the momentum changes in both the positive and negative directions of the Y axis or the Z axis. If only the momentum change in the positive direction or the negative direction is recognized, it is not recognized as a complete rotation.

[0069] Specifically, when the arm state is judged to be vertical or horizontal, the Y-axis acceleration value and the Z-axis acceleration value obtained from the acceleration sensor are used to calculate the Y-axis instantaneous momentum and the Z-axis instantaneous momentum. If they are greater than the momentum threshold, it is judged as suspected rotation. Then, it is judged that the Y-axis instantaneous momentum or the Z-axis instantaneous momentum has at least two consecutive sensor sampling points in both the positive and negative directions within a preset time, and the absolute values ​​of the instantaneous momentum are greater than the momentum threshold. If so, it is judged as a rotation. For example, the instantaneous momentum of the Y-axis within the preset time is (0, 10, 30, 50, 80, 70, 40, 0, -5, -20, -40, -50, -70, -100, -50, -40, -20, -5, 0, 0), and the momentum threshold is set to 40. Then, if there are 3 consecutive sampling points in the instantaneous momentum in the positive direction of the Y-axis exceeding 40 (i.e., 50, 80, 70), it is recorded as exceeding the momentum threshold once in the positive direction; and if there are 4 consecutive sampling points in the negative direction whose absolute value of the instantaneous momentum exceeds 40 (i.e., -50, -70, -100, -50), it is recognized as one rotation. In this embodiment, the momentum threshold is set to the momentum absolute value threshold.

[0070] In one embodiment, the momentum difference between the Y-axis instantaneous momentum and the Z-axis instantaneous momentum is calculated, and in response to the absolute value of the momentum difference of at least two consecutive sensor sampling points in the positive and negative directions of the Y-axis or Z-axis being greater than the momentum difference threshold, it is identified as a rotation. It should be noted that the process of calculating the momentum difference is to obtain the difference between each instantaneous momentum of the Y-axis instantaneous momentum and the Z-axis instantaneous momentum within the same preset time. Specifically, when the arm state is judged to be a vertical state or a horizontal state, the Y-axis acceleration value and the Z-axis acceleration value obtained from the acceleration sensor are calculated to obtain the Y-axis instantaneous momentum and the Z-axis instantaneous momentum, and the momentum difference between the Y-axis instantaneous momentum and the Z-axis instantaneous momentum is obtained. If it is greater than the momentum difference threshold, it is judged as a suspected rotation, and then it is judged whether the absolute value of the momentum difference exceeds the preset threshold at least once within the preset time. If so, it is identified as a rotation. Whether there are multiple consecutive momentum differences greater than or equal to the momentum difference threshold in the same direction (same positive direction or same negative direction), if so, it will be judged as a rotation. For example: the instantaneous momentum of the Y axis within the preset time is (0, 10, 30, 50, 80, 70, 40, 0, -5, -20, -40, -50, -70, -100, -50, -40, -20, -5, 0, 0); the instantaneous momentum of the Z axis within the preset time is (0, -5, -10, -30, -40, -30, -10, 0, 5, 10, 30, 40, 50, 60, 30, 20, 10, 10, 5, 0), then the Y axis and the Z axis are The instantaneous momentum difference is (0, 15, 40, 80, 120, 100, 50, 0, -10, -30, -70, -90, -120, -160, -80, -60, -30, -15, -5, 0), and the preset momentum difference absolute value threshold is 80. If there are 2 consecutive sampling points exceeding 80 (i.e. 120, 100) in the positive direction of the Y axis, and the instantaneous momentum absolute value exceeds 80 3 times in the negative direction (i.e. -90, -120, -160), it is recognized as a rotation. If the above rotation is not recognized, continue to judge.

[0071] The embodiment of the present application uses the difference in instantaneous momentum of the Y-axis and the Z-axis for calculation based on the different force directions of the two during the rotation process, which can amplify the change characteristics, make the rotation change characteristics more significant, and make it easier to identify the rotation, thereby increasing the recognition accuracy.

[0072] It should be noted that the rotation gesture feature in the embodiment of the present application is the number of rotations, and may also be turning the wrist, raising the hand, etc. The embodiment of the present application is not limited to this.

[0073] The above describes in detail the process of determining the rotation gesture characteristics based on the Y-axis acceleration value and / or the Z-axis acceleration value. The following will describe in detail the control instructions corresponding to the target gesture matching the rotation gesture characteristics and the arm state to control the smart wearable device to process the communication information.

[0074] S140, controlling the smart wearable device to process the communication information according to the control instruction corresponding to the target gesture matching the rotation gesture feature and the arm state.

[0075] In one embodiment, within a preset time, when the number of rotations is greater than or equal to N times, it is determined whether the arm maintains the arm state during the rotation process according to the X-axis acceleration value or the X-axis acceleration average, wherein N is an integer greater than or equal to 2; when the arm state is maintained, the rotation gesture feature is matched with the target gesture to obtain a recognition result; according to the recognition result, the smart wearable device is controlled to process the communication information. It can be determined whether the X-axis acceleration value of each acceleration sensor sampling point during the rotation process is less than a threshold value to determine whether the user's arm always maintains a certain arm state (such as vertical or horizontal); it can also be determined whether the X-axis acceleration average of the corresponding multiple acceleration sensor sampling points during the rotation process is less than a threshold value to determine whether the user's arm always maintains a certain arm state.

[0076] Specifically, after the processor of the smart wearable device recognizes the above-mentioned single rotation process, it determines whether it is a continuous rotation that meets the conditions (i.e., continuous rotation N times within the preset time, N is greater than or equal to 2) according to the preset time and the number of rotations. For example: it rotates twice within 1 second. If continuous rotation is performed within the preset time period (the number of rotations is greater than or equal to 2), it is determined whether the arm maintains the arm state during the rotation process in the time period from the start of rotation to the end of rotation, that is, whether the acceleration value of the X-axis or the mean value of the acceleration of the X-axis falls within the corresponding threshold interval. The continuous rotation feature is recognized, and in the case of maintaining the arm state, the rotation gesture feature and the arm state are matched with the target gesture (i.e., the target gesture corresponding to answering, hanging up or rejecting the call), and the target gesture is output, and the target gesture may include vertical rotation and horizontal rotation. Finally, the processor feeds back the communication control instruction corresponding to the target gesture to the communication module of the smart wearable device, controls the smart wearable device to process the communication information, including answering the call, hanging up the call, rejecting the call, connecting the voice, etc., and the processor feeds back the above recognition result to the communication module of the smart wearable device, and controls the smart wearable device to process the communication information.

[0077] Since the user's arm maintains a certain state and rotates in motion, the X-axis acceleration value is greatly affected by the motion state. Judging whether the mean X-axis acceleration falls within the corresponding threshold range to judge the user's arm state will reduce the impact of the motion state and improve the arm state recognition rate.

[0078] Therefore, the embodiment of the present application, through the method of processing communication information, can determine the arm state and rotation gesture characteristics using only an acceleration sensor including X, Y and Z axes, thereby identifying the target gesture based on the arm state and rotation gesture characteristics, thereby realizing the use of specific gesture actions to control the smart wearable device to process communication information, thereby enhancing the operability and practicality of incoming calls in scenarios such as walking, running, cycling, driving, etc., and using an acceleration sensor to collect data can reduce hardware costs, which is beneficial to controlling the power consumption of the overall smart wearable device.

[0079] The above describes in detail the implementation steps of a method for processing communication information. The following describes in detail a specific embodiment of processing incoming call information in the method for processing communication information.

[0080] like Figure 3 As shown, when a call comes in at S501 on the smart wearable device, the user wearing the smart wearable device determines whether to answer the call at S502. If not, the user executes S505 to rotate the arm vertically twice, and the smart wearable device executes S506 to refuse to answer the call and executes S511 to end the process. If answered, the user executes S503 to rotate the arm horizontally twice, and the smart wearable device executes S504 to answer the call. During the call at S507, the user executes S508 to determine whether to continue the call. If so, continue to execute S507. If not, the user executes S509 to rotate the arm vertically twice, and the smart wearable device executes S510 to hang up the call and executes S511 to end the process.

[0081] The above describes in detail the specific embodiment of processing incoming call information. Figure 4 and Figure 5 A device for processing communication information and a smart wearable device are described in detail.

[0082] like Figure 4 As shown, a device for processing communication information includes: an acquisition module 310, a determination module 320, a judgment module 330 and a control module 340.

[0083] In one embodiment, a device for processing communication information is applied to a smart wearable device, which is used to be worn on a user's arm. The smart wearable device includes an acceleration sensor, and the device includes: an acquisition module, which is used to acquire acceleration data collected by the acceleration sensor, wherein the acceleration data includes an X-axis acceleration value, a Y-axis acceleration value, and a Z-axis acceleration value of the acceleration sensor, wherein the X-axis is a number axis parallel to the arm, and the Y-axis and the Z-axis are perpendicular to each other and both perpendicular to the X-axis; a determination module, which is used to determine the arm state according to the X-axis acceleration value; a judgment module, which is used to determine the rotation gesture feature according to the Y-axis acceleration value and / or the Z-axis acceleration value when it is determined that the arm state matches the preset arm state, wherein the rotation gesture feature includes the number of rotations; and a control module, which is used to control the smart wearable device to process the communication information according to the control instruction corresponding to the target gesture matching the rotation gesture feature and the arm state.

[0084] In one embodiment, the determination module is specifically used to: determine the motion state according to the X-axis acceleration value, the Y-axis acceleration value and the Z-axis acceleration value; wherein, determining the arm state according to the X-axis acceleration value includes: determining the arm state according to the X-axis acceleration value and the motion state.

[0085] In one embodiment, the determination module is also used to: obtain the X-axis instantaneous momentum, the Y-axis instantaneous momentum and the Z-axis instantaneous momentum according to the X-axis acceleration value, the Y-axis acceleration value and the Z-axis acceleration value respectively; and judge the motion state according to the X-axis instantaneous momentum, the Y-axis instantaneous momentum and the Z-axis instantaneous momentum.

[0086] In one embodiment, the determination module is also used to: calculate the maximum instantaneous momentum among the X-axis instantaneous momentum, the Y-axis instantaneous momentum and the Z-axis instantaneous momentum; compare the maximum instantaneous momentum with the motion state threshold to obtain a comparison result; and judge the motion state based on the comparison result.

[0087] In one embodiment, determining the arm state according to the X-axis acceleration value and the motion state includes: determining whether the X-axis acceleration value falls within a preset acceleration threshold range, wherein different motion states and different arm states correspond to different X-axis acceleration threshold ranges.

[0088] In one embodiment, the judgment module is specifically used to: when it is determined that the arm state matches the preset arm state, determine the rotation gesture characteristics according to the Y-axis acceleration value and / or the Z-axis acceleration value, including: when the arm state is vertical or horizontal, calculate the Y-axis acceleration value and the Z-axis acceleration value to obtain the Y-axis instantaneous momentum and the Z-axis instantaneous momentum; judge the rotation gesture characteristics according to the Y-axis instantaneous momentum and / or the Z-axis instantaneous momentum.

[0089] In one embodiment, the judgment module is specifically used to: in response to the existence of at least two consecutive sensor sampling points in the positive direction of the Y axis and the negative direction of the Y axis with an absolute value of the instantaneous momentum greater than the momentum threshold, identify it as a rotation; or in response to the existence of at least two consecutive sensor sampling points in the positive direction of the Z axis and the negative direction of the Z axis with an absolute value of the instantaneous momentum greater than the momentum threshold, identify it as a rotation.

[0090] In one embodiment, the judgment module is specifically used to: judge the rotation gesture characteristics according to the Y-axis instantaneous momentum and / or the Z-axis instantaneous momentum, including: calculating the momentum difference between the Y-axis instantaneous momentum and the Z-axis instantaneous momentum; in response to the existence of at least two consecutive sensor sampling points in both the positive and negative directions of the Y-axis or Z-axis with an absolute value of the momentum difference greater than a momentum difference threshold, identifying it as a rotation.

[0091] In one embodiment, the control module is specifically used to: control the smart wearable device to process communication information according to the control instruction corresponding to the preset feature information matching the rotation gesture feature, including: within the preset time, when the number of rotations is greater than or equal to N times, judging whether the arm maintains the arm state during the rotation process according to the X-axis acceleration value or the X-axis acceleration average, where N is an integer greater than or equal to 2; when the arm state is maintained, matching the rotation gesture feature with the target gesture to obtain a recognition result; and according to the recognition result, controlling the smart wearable device to process the communication information.

[0092] In the embodiments of the present application, Figure 4 The modules shown can achieve Figure 1 , Figure 2 and Figure 3 Each process in the method embodiment. Figure 4 The operations and / or functions of each module in Figure 1 , Figure 2 and Figure 3 For details, please refer to the description in the above method embodiment. To avoid repetition, detailed description is appropriately omitted here.

[0093] like Figure 5 As shown, an embodiment of the present application also provides a smart wearable device, including: an acceleration sensor 410, a processor 420, a memory 430 and a bus 440; the acceleration sensor is used to collect acceleration data; the memory stores computer-readable instructions; the processor is connected to the memory and the acceleration sensor through the bus, and is used to execute the computer-readable instructions in the memory to implement the method of processing communication information as in all the above embodiments. For details, please refer to the description in the above method embodiments. To avoid repetition, the detailed description is appropriately omitted here.

[0094] Among them, the bus is used to realize the direct connection and communication of these components. Among them, the processor in the embodiment of the present application can be an integrated circuit chip with signal processing capabilities. The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The disclosed methods, steps and logic block diagrams in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0095] The memory may be, but is not limited to, a random access memory (RAM), a read only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable read-only memory (EEPROM), etc. The memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the method in the above embodiment may be executed.

[0096] Understandably, Figure 5 The structure shown is for illustration only and may also include Figure 5 More or fewer components as shown, or with Figure 5 Different configurations shown. Figure 5 Each component shown in the figure can be implemented by hardware, software or a combination thereof.

[0097] An embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method for processing communication information in all the above embodiments is implemented. For details, please refer to the description in the above method embodiments. To avoid repetition, the detailed description is appropriately omitted here.

[0098] The above are only preferred embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application. It should be noted that similar numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings.

[0099] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for processing communication information, characterized in that: The method is applied to a smart wearable device, the smart wearable device is used to be worn on a user's arm, the smart wearable device includes an acceleration sensor, and the method includes: Acquire acceleration data collected by the acceleration sensor, wherein the acceleration data includes an X-axis acceleration value, a Y-axis acceleration value, and a Z-axis acceleration value of the acceleration sensor, wherein the X-axis is a numerical axis parallel to the arm, and the Y-axis and the Z-axis are perpendicular to each other and both perpendicular to the X-axis; Determining the arm state according to the X-axis acceleration value of the acceleration sensor; In a case where it is determined that the arm state matches the preset arm state, determining a rotation gesture feature according to the Y-axis acceleration value and / or the Z-axis acceleration value, wherein the rotation gesture feature includes a number of rotations; Controlling the smart wearable device to process the communication information according to a control instruction corresponding to a target gesture matching the rotation gesture feature and the arm state; The determining the arm state according to the X-axis acceleration value of the acceleration sensor comprises: determining the arm state by judging whether the X-axis acceleration value falls within a preset acceleration threshold interval; Wherein, in a state of intense exercise, when the user's arm is in a horizontal state, the preset acceleration threshold interval is a first threshold interval, and when the user's arm is in a vertical state, the preset acceleration threshold interval is a second threshold interval; In a non-violent exercise state, when the user's arm is in a horizontal state, the preset acceleration threshold interval is the third threshold interval, and when the user's arm is in a vertical state, the preset acceleration threshold interval is the fourth threshold interval; When it is determined that the arm state matches the preset arm state, determining the rotation gesture feature according to the Y-axis acceleration value and / or the Z-axis acceleration value, including: when the arm state is a vertical state or a horizontal state, calculating the Y-axis acceleration value and the Z-axis acceleration value to obtain the Y-axis instantaneous momentum and the Z-axis instantaneous momentum; judging the rotation gesture feature according to the Y-axis instantaneous momentum and / or the Z-axis instantaneous momentum.

2. The method according to claim 1, characterized in that Before determining the arm state according to the X-axis acceleration value, the method further includes: Determine a motion state according to the X-axis acceleration value, the Y-axis acceleration value, and the Z-axis acceleration value; Wherein, determining the arm state according to the X-axis acceleration value includes: The arm state is determined according to the X-axis acceleration value and the motion state.

3. The method according to claim 2, characterized in that Determining the motion state according to the X-axis acceleration value, the Y-axis acceleration value, and the Z-axis acceleration value includes: Obtaining an X-axis instantaneous momentum, a Y-axis instantaneous momentum, and a Z-axis instantaneous momentum according to the X-axis acceleration value, the Y-axis acceleration value, and the Z-axis acceleration value, respectively; The motion state is determined according to the X-axis instantaneous momentum, the Y-axis instantaneous momentum, and the Z-axis instantaneous momentum.

4. The method according to claim 3, characterized in that The determining the motion state according to the X-axis instantaneous momentum, the Y-axis instantaneous momentum and the Z-axis instantaneous momentum includes: Calculating the maximum instantaneous momentum among the X-axis instantaneous momentum, the Y-axis instantaneous momentum, and the Z-axis instantaneous momentum; Comparing the maximum instantaneous momentum with the motion state threshold to obtain a comparison result; The motion state is determined according to the comparison result.

5. The method according to claim 2, characterized in that: Determining the arm state according to the X-axis acceleration value and the motion state includes: It is determined whether the X-axis acceleration value falls within a preset acceleration threshold range, wherein different motion states and different arm states correspond to different X-axis acceleration threshold ranges.

6. The method according to claim 1, characterized in that The determining the rotation gesture feature according to the Y-axis instantaneous momentum and / or the Z-axis instantaneous momentum includes: In response to the existence of at least two consecutive sensor sampling points in the positive direction of the Y axis and the negative direction of the Y axis with an absolute value of the instantaneous momentum greater than a momentum threshold, identifying it as one rotation; Or in response to the existence of at least two consecutive sensor sampling points in both the positive direction of the Z axis and the negative direction of the Z axis with instantaneous momentum absolute values ​​greater than the momentum threshold, it is identified as one rotation.

7. The method according to claim 1, characterized in that The determining the rotation gesture feature according to the Y-axis instantaneous momentum and / or the Z-axis instantaneous momentum includes: Calculating the momentum difference between the Y-axis instantaneous momentum and the Z-axis instantaneous momentum; In response to the absolute values ​​of the momentum differences of at least two consecutive sensor sampling points in both the positive direction and the negative direction of the Y-axis or the Z-axis being greater than a momentum difference threshold, one rotation is identified.

8. The method according to claim 1, characterized in that The controlling the smart wearable device to process the communication information according to the control instruction corresponding to the target gesture matching the rotation gesture feature and the arm state comprises: Within a preset time, when the number of rotations is greater than or equal to N times, judging whether the arm maintains the arm state during the rotation process according to the X-axis acceleration value or the X-axis acceleration average, wherein N is an integer greater than or equal to 2; While maintaining the arm state, matching the rotation gesture feature with the target gesture to obtain a recognition result; According to the recognition result, the smart wearable device is controlled to process the communication information.

9. A device for processing communication information, characterized in that: The device is applied to a smart wearable device, the smart wearable device is used to be worn on a user's arm, the smart wearable device includes an acceleration sensor, and the device includes: An acquisition module, used to acquire acceleration data collected by the acceleration sensor, wherein the acceleration data includes an X-axis acceleration value, a Y-axis acceleration value, and a Z-axis acceleration value of the acceleration sensor, wherein the X-axis is a numerical axis parallel to the arm, and the Y-axis and the Z-axis are perpendicular to each other and are both perpendicular to the X-axis; A determination module, used to determine the arm state according to the X-axis acceleration value; A judgment module, configured to determine a rotation gesture feature according to the Y-axis acceleration value and / or the Z-axis acceleration value when it is determined that the arm state matches a preset arm state, wherein the rotation gesture feature includes a number of rotations; A control module, used to control the smart wearable device to process communication information according to a control instruction corresponding to a target gesture matching the rotation gesture feature and the arm state; The determination module is further configured to: determine the arm state by determining whether the X-axis acceleration value falls within a preset acceleration threshold interval; Wherein, in a state of intense exercise, when the user's arm is in a horizontal state, the preset acceleration threshold interval is a first threshold interval, and when the user's arm is in a vertical state, the preset acceleration threshold interval is a second threshold interval; In a non-violent exercise state, when the user's arm is in a horizontal state, the preset acceleration threshold interval is the third threshold interval, and when the user's arm is in a vertical state, the preset acceleration threshold interval is the fourth threshold interval; The judgment module is specifically used for: when the arm state is vertical or horizontal, calculating the Y-axis acceleration value and the Z-axis acceleration value to obtain the Y-axis instantaneous momentum and the Z-axis instantaneous momentum; judging the rotation gesture feature according to the Y-axis instantaneous momentum and / or the Z-axis instantaneous momentum.

10. A smart wearable device, characterized in that: include: Accelerometer, processor, memory and bus; The acceleration sensor is used to collect acceleration data; The memory stores computer-readable instructions; The processor is connected to the memory and the acceleration sensor through the bus, and is used to execute the computer-readable instructions in the memory to implement the method for processing communication information according to any one of claims 1-8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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