State monitoring method and device, wearable device and storage medium

Abstract

The application relates to the technical field of head posture detection, and discloses a state monitoring method and device, a wearable device and a storage medium, the method comprising the following steps: collecting head posture data of a to-be-detected object in real time; identifying a current head posture of the to-be-detected object according to the head posture data; and generating corresponding state notification information when the duration of the current head posture reaches a threshold value. The application improves the accuracy of user head posture monitoring, can accurately identify the bad posture of a user and timely remind the user.

Description

Technical Field

[0001] This application relates to the field of head posture detection technology, and in particular to state monitoring methods, devices, wearable devices and storage media. Background Technology

[0002] In modern society, with the rapid changes in work and study methods, it is increasingly common for people to spend long periods of time sitting, looking down, or in poor posture. Therefore, monitoring head posture and promptly reminding users to adjust their posture is particularly important. However, existing head posture monitoring technologies cannot accurately identify subtle changes in head posture, resulting in poor accuracy and an inability to provide timely status reminders.

[0003] Therefore, improving the accuracy of user head posture monitoring and providing timely status alerts is a problem that urgently needs to be solved.

[0004] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main purpose of this application is to provide a state monitoring method, device, wearable device and storage medium, which aims to solve the technical problem that existing head posture monitoring technologies cannot accurately identify subtle changes in head posture, resulting in poor head posture monitoring accuracy and inability to provide timely status reminders.

[0006] To achieve the above objectives, this application proposes a state monitoring method, the method comprising:

[0007] Real-time acquisition of head posture data of the object under test;

[0008] Identify the current head posture of the object under test based on the head posture data;

[0009] When the duration of the current head pose reaches a threshold, a corresponding status notification message is generated.

[0010] Furthermore, to achieve the above objectives, this application also proposes a condition monitoring device, which includes:

[0011] The acquisition module is used to acquire head posture data of the object under test in real time.

[0012] The recognition module is used to identify the current head posture of the object under test based on the head posture data;

[0013] The reminder module is used to generate corresponding status notification information when the duration of the current head posture reaches a threshold.

[0014] In addition, to achieve the above objectives, this application also proposes a wearable device that performs the steps of the state monitoring method described above.

[0015] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the state monitoring method described above.

[0016] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the state monitoring method described above.

[0017] This application provides a status monitoring method. The method first collects head posture data of the subject in real time; identifies the current head posture of the subject based on the head posture data; and generates corresponding status notification information when the duration of the current head posture reaches a threshold. This improves the accuracy of user head posture monitoring and can accurately identify the user's poor posture and provide timely reminders.

[0018] In summary, this application identifies the current head posture of the test subject by collecting real-time head posture data. It can monitor the user's head posture in real time, accurately identify poor postures of the test subject, and generate corresponding status notification information when the duration of the current head posture reaches the corresponding threshold, thus providing timely status reminders. This overcomes the technical shortcomings of existing head posture monitoring technologies, which cannot accurately identify subtle changes in head posture, resulting in poor head posture monitoring accuracy and the inability to provide timely status reminders. This application improves the accuracy of user head posture monitoring, accurately identifies poor postures of users, and provides timely reminders. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart illustrating an embodiment of the status monitoring method of this application.

[0022] Figure 2A schematic diagram of the coordinate system of an accelerometer provided in an embodiment of the state monitoring method of this application;

[0023] Figure 3 This is a flowchart illustrating Embodiment 2 of the status monitoring method of this application;

[0024] Figure 4 A schematic diagram illustrating the setting of angle threshold ranges for different head postures in an embodiment of the state monitoring method of this application;

[0025] Figure 5 This is a simplified flowchart of an embodiment of the status monitoring method of this application;

[0026] Figure 6 This is a schematic diagram of the module structure of the status monitoring device according to an embodiment of this application;

[0027] Figure 7 This is a schematic diagram of the device structure of the hardware operating environment involved in the status monitoring method of this application embodiment.

[0028] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0029] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0030] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0031] The main solution of this application embodiment is: to collect head posture data of the object under test in real time; to identify the current head posture of the object under test based on the head posture data; and to generate corresponding status notification information when the duration of the current head posture reaches a threshold.

[0032] In modern society, with the rapid changes in work and study methods, it is increasingly common for people to spend long periods of time sitting, looking down, or in poor posture. Therefore, monitoring head posture and promptly reminding users to adjust their posture is particularly important. However, existing head posture monitoring technologies cannot accurately identify subtle changes in head posture, resulting in poor accuracy and an inability to provide timely status alerts. Therefore, improving the accuracy of user head posture monitoring and providing timely status alerts is a problem that urgently needs to be solved.

[0033] This application identifies the current head posture of the subject by collecting head posture data in real time. It can monitor the user's head posture in real time, accurately identify the user's poor posture, and generate corresponding status notification information when the duration of the current head posture reaches a corresponding threshold, so as to provide timely status reminders. This overcomes the technical defects of existing head posture monitoring technologies, which cannot accurately identify subtle changes in head posture, resulting in poor head posture monitoring accuracy and failure to provide timely status reminders. This application improves the accuracy of user head posture monitoring and can accurately identify the user's poor posture and provide timely reminders.

[0034] Based on this, embodiments of this application provide a status monitoring method, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the status monitoring method of this application.

[0035] In this embodiment, the status monitoring method includes steps S10 to S30:

[0036] Step S10: Collect head posture data of the object under test in real time.

[0037] It should be noted that the execution subject of this embodiment is a wearable device, which refers to an electronic device that can be worn by a user, such as a headset. This embodiment does not impose specific limitations on this; the example used is a headset. This device has built-in sensors, such as accelerometers and gyroscopes, used to monitor the user's head movements and posture changes in real time.

[0038] It is understood that head posture data refers to acceleration data in different directions collected by the accelerometer within the wearable device, which may include acceleration data along the X, Y, and Z axes. This embodiment does not impose specific limitations on this. Figure 2 As shown, Figure 2 This is a schematic diagram of the coordinate system of the accelerometer. The installation coordinates of the accelerometer on the headphones consist of the X-axis, Y-axis, and Z-axis, which are perpendicular to each other. The X-axis represents the horizontal direction, the Y-axis represents the vertical direction, and the Z-axis represents the depth direction.

[0039] Specifically, when a user wears headphones, the three-axis data of the accelerometer are collected in real time: acc_x (X-axis), acc_y (Y-axis), and acc_z (Z-axis), which are used as the user's head posture data.

[0040] Step S20: Identify the current head posture of the object to be tested based on the head posture data.

[0041] It should be noted that by using the accelerometer sensor integrated into the headphones, the user's head posture can be accurately monitored and analyzed. That is, by using the acceleration data in the X, Y and Z axes of the accelerometer, the user's head posture can be identified in real time and accurately in different wearing scenarios.

[0042] Understandably, head posture data is acquired through an accelerometer sensor in the headset, which detects the user's head movements in three-dimensional space. This sensor continuously monitors the subject's head movements and converts them into corresponding acceleration data. This data is then used to analyze the subject's head posture, such as determining whether the user is looking down, up, turning left, or turning right. In this way, the subject's cervical spine status can be assessed in real time, and reminders can be given when necessary to help the user maintain correct sitting or standing posture.

[0043] Step S30: When the duration of the current head pose reaches a threshold, generate corresponding status notification information.

[0044] It should be noted that status notification information is used to inform users of their head posture status. This information can be a visual, auditory, or tactile reminder. Status notification information can issue warnings or provide suggested posture adjustment guidance. For example, when it is detected that the user has been looking down for too long, it can emit a sound or vibration to remind the user to look up, or provide some simple neck stretching exercise guidance.

[0045] Understandably, this implementation employs a tiered warning mechanism based on different head postures to differentiate the degree of impact of different postures on the cervical spine. For example, an excessively forward-leaning head posture may have a significant impact on the cervical spine; therefore, when this posture is detected, a lower threshold is set, and a more urgent reminder is issued. Conversely, slight head rotation may have a smaller impact on the cervical spine, so the threshold can be increased accordingly, and the reminder can be more gentle. This tiered warning mechanism can more effectively guide users to adjust their posture.

[0046] Specifically, wearable devices can intelligently record and analyze the duration of various head postures maintained by the wearer. Once it is detected that the wearer maintains a certain posture for a long time, especially a posture that may put pressure on the cervical spine (such as looking down for a long time), it can promptly remind the user to adjust their head posture or perform appropriate neck movements.

[0047] In one feasible implementation, steps S01 to S02 may be included before step S30:

[0048] Step S01: Determine the posture category of the current head posture based on the degree of influence of the current head posture on the cervical spine state.

[0049] It should be noted that the impact of current head posture on cervical spine condition is assessed based on the relative position of the head and cervical spine, as well as the duration of posture maintenance. Posture categories can be divided into normal, slightly impaired, moderately impaired, and severely impaired. For example, a normal posture might correspond to keeping the head upright or slightly tilted forward, while a severely impaired posture might correspond to prolonged excessive forward or backward tilting. Different posture categories correspond to different thresholds and reminder methods.

[0050] Understandably, posture categories can be based on medical research and expert advice, combined with cervical spine biomechanical models. For example, head postures can be divided into three categories: normal, slightly impaired, moderately impaired, and severely impaired, each corresponding to different thresholds and alert intensities. Normal and slightly impaired postures might correspond to common postures in normal work and daily life, moderately impaired postures might correspond to poor postures maintained for extended periods, and severely impaired postures might correspond to extreme postures that are extremely detrimental to the cervical spine, such as extreme head-down or head-up postures. This classification mechanism helps to more accurately determine the urgency of warnings, thereby providing more appropriate reminders.

[0051] Step S02: Determine the corresponding threshold based on the pose category of the current head pose.

[0052] It should be noted that the corresponding thresholds are the posture maintenance duration thresholds for different head postures. The posture maintenance duration thresholds for slight head tilting, head tilting, and head tilting are set as the slight poor posture maintenance duration thresholds, while the posture maintenance duration thresholds for severe head tilting, head tilting, and head tilting are set as the severe poor posture maintenance duration thresholds. Furthermore, the slight poor posture maintenance duration threshold is set to be greater than the severe poor posture maintenance duration threshold.

[0053] Specifically, for postures deemed seriously unhealthy (such as extreme head-down or head-up postures), an emergency alert will be issued within a short period of time (e.g., within a few minutes) to ensure that users can respond and adjust quickly. For slightly unhealthy posture deviations, a more lenient alert interval (e.g., every half hour to an hour) will be given to avoid excessive disturbance and to ensure that users can pay attention to and improve their posture in a timely manner.

[0054] This embodiment provides a status monitoring method. This embodiment first collects the head posture data of the subject under test in real time; identifies the current head posture of the subject under test based on the head posture data; and generates corresponding status notification information when the duration of the current head posture reaches a threshold. This improves the accuracy of user head posture monitoring and can accurately identify the user's bad posture and provide timely reminders.

[0055] In summary, this embodiment identifies the current head posture of the test subject by collecting head posture data in real time. It can monitor the user's head posture in real time, accurately identify poor postures of the test subject, and generate corresponding status notification information when the duration of the current head posture reaches the corresponding threshold, thus providing timely status reminders. This overcomes the technical defects of existing head posture monitoring technologies, which cannot accurately identify subtle changes in head posture, resulting in poor head posture monitoring accuracy and the inability to provide timely status reminders. This improves the accuracy of user head posture monitoring, enabling accurate identification of poor user postures and timely reminders.

[0056] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in Embodiment 1 above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 3 Step S20 further includes steps S201-S203:

[0057] Step S201: Filter the head posture data to obtain filtered head posture data.

[0058] It should be noted that filtering refers to smoothing the acquired head pose data using specific algorithms to reduce the impact of noise and outliers. Examples include mean filtering, median filtering, or Gaussian filtering. This embodiment does not impose specific limitations on this method. In this embodiment, mean filtering can be used, which involves averaging a certain number of consecutive data points to reduce noise. Mean filtering helps improve the accuracy of pose data, thereby making the determination of the current head pose more precise.

[0059] Specifically, by setting the number of mean filter points, mean filtering of triaxial acceleration data is achieved, thereby smoothing the data and reducing interference caused by data jitter.

[0060] Step S202: Determine the angle data of the head posture based on the filtered head posture data.

[0061] It should be noted that the head posture angle data is calculated using a specific algorithm, which can accurately extract head tilt, rotation and other posture information from the filtered data. This angle data reflects the real-time state of the user's cervical spine.

[0062] In one feasible implementation, step S202 may include steps A10 to A13:

[0063] Step A10: Determine a first acceleration, a second acceleration, and a third acceleration based on the filtered head posture data, wherein the directions of the first acceleration, the second acceleration, and the third acceleration are perpendicular to each other.

[0064] It should be noted that the first acceleration is the acceleration data of the accelerometer along the X-axis, the second acceleration is the acceleration data of the accelerometer along the Y-axis, and the third acceleration is the acceleration data of the accelerometer along the Z-axis. Their directions are perpendicular to each other, and the combination of the three can provide complete motion information of the head in three-dimensional space.

[0065] Step A11: Determine a first characteristic angle, a second characteristic angle, a third characteristic angle, and a first target angle based on the first acceleration, the second acceleration, and the third acceleration. The first characteristic angle, the second characteristic angle, and the third characteristic angle are used to characterize the component proportions of acceleration relative to the overall resultant acceleration in different directions and their directional angular relationships. The first target angle is used to characterize the degree of tilt of the head of the object under test relative to the horizontal plane.

[0066] It should be noted that characteristic angles are used to characterize the proportion of acceleration components relative to the overall resultant acceleration in different directions and their angular relationships. These include at least the first to third characteristic angles. The first characteristic angle, Rate_xg, is the ratio of X-axis acceleration to resultant gravitational acceleration (converted to an angle); the second characteristic angle, Rate_yg, is the ratio of Y-axis acceleration to resultant gravitational acceleration (converted to an angle); and the third characteristic angle, Rate_zg, is the ratio of Z-axis acceleration to resultant gravitational acceleration (converted to an angle). The first target angle, namely the pitch angle, reflects the degree of head tilt relative to the horizontal plane. By calculating these angles, the current state of the user's cervical spine can be accurately depicted.

[0067] Step A12: Determine a second target angle based on the first acceleration and the third acceleration. The second target angle is used to characterize the degree of rotation of the object under test in the horizontal plane.

[0068] It should be noted that the second target angle, roll angle, is calculated using X-axis and Z-axis acceleration data. It represents the degree of head rotation in the horizontal plane. Roll angle can be used to understand the lateral bending state of the user's cervical spine.

[0069] Understandably, the pitch and roll angles of the head are calculated using the Euler angle transformation algorithm. This algorithm decomposes the rotation of an object in three-dimensional space into three independent rotational angles: pitch, roll, and yaw. The roll angle (Roll) is calculated as follows:

[0070] Roll=abs(arctan(acc_x / acc_z))

[0071] Where Roll represents the roll angle, acc_x is the first acceleration, i.e., the X-axis acceleration data, and acc_z is the third acceleration, i.e., the Z-axis acceleration data.

[0072] Step A13: The first feature angle, the second feature angle, the third feature angle, the pitch angle, and the roll angle are used as the angle data of the head posture.

[0073] It should be noted that, in this embodiment, the calculated pitch and roll angles, combined with the determined characteristic angles, can comprehensively describe the head's posture in three-dimensional space and serve as the angular data of the head posture.

[0074] In one feasible implementation, step A11 specifically includes steps A110 to A112:

[0075] Step A110: Determine the pitch angle based on the first acceleration, the second acceleration, and the third acceleration;

[0076] It should be noted that the pitch angle is the degree of tilt of the head relative to the horizontal plane, and it is also calculated using the Euler angle conversion algorithm. The pitch angle is calculated as follows:

[0077] Pitch=abs(arctan(acc_y / sqrt(acc_x*acc_x+acc_z+acc_z)))

[0078] Where Pitch is the pitch angle, acc_x is the first acceleration (X-axis acceleration data), acc_y is the second acceleration (Y-axis acceleration data), and acc_z is the third acceleration (Z-axis acceleration data).

[0079] It is worth noting that in the calculation of the pitch angle and roll angle, the absolute value is taken to ensure that the calculated angle result is positive.

[0080] Step A111: Determine the resultant gravitational acceleration based on the first acceleration, the second acceleration, and the third acceleration;

[0081] It should be noted that the resultant gravitational acceleration is the vector sum of the first, second, and third accelerations, reflecting the total gravitational components acting on the head in three-dimensional space. The formula for calculating the resultant gravitational acceleration is as follows:

[0082] acc_g = sqrt(acc_x) 2 +acc_y 2 +acc_z 2 )

[0083] Where acc_g is the resultant gravitational acceleration, acc_x is the first acceleration, i.e., the X-axis acceleration data, acc_y is the second acceleration, i.e., the Y-axis acceleration data, and acc_z is the third acceleration, i.e., the Z-axis acceleration data.

[0084] Step A112: Calculate the first characteristic angle, the second characteristic angle, and the third characteristic angle based on the resultant gravitational acceleration and the first acceleration, the second acceleration, and the third acceleration, respectively.

[0085] It should be noted that the ratios of the X-axis, Y-axis, and Z-axis to the resultant gravitational acceleration (converted to angles) are, in order, the first characteristic angle Rate_xg, the second characteristic angle Rate_yg, and the third characteristic angle Rate_zg, and are calculated as follows:

[0086]

[0087] In this context, Rate_xg, Rate_yg, and Rate_zg represent the first characteristic angle, the second characteristic angle, and the third characteristic angle, respectively. acc_g represents the resultant gravitational acceleration, acc_x represents the first acceleration (X-axis acceleration data), acc_y represents the second acceleration (Y-axis acceleration data), and acc_z represents the third acceleration (Z-axis acceleration data).

[0088] Step S203: Identify the current head posture of the object to be tested based on the angle data.

[0089] It should be noted that the headset can comprehensively and in real time recognize various head postures of the wearer, including but not limited to normal upright posture, head down (such as when using a mobile phone for a long time or reading), head up (such as looking up at the starry sky or leaning back to rest), and head tilting to the left and right (such as looking at objects on both sides or stretching the neck). This embodiment does not impose specific limitations on these postures.

[0090] It is understood that this implementation also presets a head posture maintenance duration threshold and a head posture identifier threshold. After determining the wearer's current head posture, the current posture identifier is incremented by 1. If the current posture identifier is greater than the corresponding set head posture identifier threshold within the set posture maintenance duration threshold range, the wearer is reminded to adjust their head posture or move around.

[0091] In one feasible implementation, step S203 may include steps B10 to B12:

[0092] Step B10: Obtain the angle range corresponding to different head postures.

[0093] It should be noted that the angle ranges corresponding to different head postures are preset, including the angle range of normal head posture, head down, head up, and head side posture. This embodiment does not impose specific limitations on these.

[0094] It is understandable that the head-down and head-up postures share a set of angles, and the head-to-left and head-to-right postures are collectively referred to as the head-tilting postures, which also share a set of angles.

[0095] It is worth noting that in this embodiment, the angle range of head-down and head-up postures is divided into two groups: the angle range of slightly head-down and head-up postures and the angle range of severely head-down and head-up postures. Similarly, the angle range of head-tilting postures is divided into two groups: the angle range of slightly head-tilting postures and the angle range of severely head-tilting postures.

[0096] Step B11: Match the angle data with the angle range corresponding to the different head postures to obtain initial head posture information.

[0097] It should be noted that the angle values ​​are matched with preset different posture angle ranges to initially determine the wearer's current head posture, i.e., the initial head posture information, including normal head posture, head-down and head-up posture, and head-tilting posture. This embodiment does not impose specific limitations on this.

[0098] Step B12: Determine the current head posture of the object under test based on the initial head posture information and the angle data.

[0099] It should be noted that, based on the initial head posture information, further analysis of subtle changes in angle data is conducted to more accurately identify the head posture of the object under test.

[0100] Understandably, if the wearer's initial head posture is determined to be either a head-down or head-up posture, the sign of the accelerometer Y-axis data acc_y is used to distinguish between head-down and head-up postures: when acc_y > 0, the current posture is determined to be head-up; when acc_y < 0, the current posture is determined to be head-down.

[0101] It is worth noting that if the wearer's initial head posture is determined to be a tilted head posture, the left-facing and right-facing head postures are distinguished based on the sign of the accelerometer X-axis data acc_x: when acc_x > 0, the current head posture is determined to be a left-facing head posture; when acc_x < 0, the current head posture is determined to be a right-facing head posture.

[0102] Specifically, this embodiment also sets a threshold for undesirable posture angles. When the head posture angle of the subject being tested (such as the forward tilt angle of the neck, the side tilt angle of the head, etc.) exceeds these preset undesirable posture angle thresholds, a warning or suggestion will be issued immediately to guide the user to correct the head posture in time. The warning or suggestion can be given through vibration, sound or visual cues.

[0103] In one feasible implementation, step B10 specifically includes steps B100 to B102:

[0104] Step B100: Collect acceleration data of the user under different head postures.

[0105] It should be noted that the acceleration data of the user in different head postures is also collected by the accelerometer in the headset device. In this method, the collected acceleration data includes, but is not limited to, the X-axis, Y-axis, and Z-axis acceleration data in normal upright posture, head down, head up, and head side posture.

[0106] Step B101: Determine the angle features corresponding to different head postures based on the acceleration data.

[0107] It should be noted that the angle features corresponding to each head posture are determined based on the acceleration data under each head posture, including the first feature angle Rate_xg, the second feature angle Rate_yg, the third feature angle Rate_zg, the pitch angle, and the roll angle. The specific calculation method is the same as the calculation method of the same angle mentioned above, and will not be repeated here in this implementation.

[0108] Step B102: Determine the angle range corresponding to different head postures based on the angle features.

[0109] It should be noted that the Z-axis angle ratio to the net gravitational acceleration (Rate_zg) is used to set the normal head posture angle range; the Z-axis and Y-axis angle ratios to the net gravitational acceleration (Rate_zg and Rate_yg) are used to set the head-down and head-up posture angle ranges. Additionally, the Pitch angle is used to distinguish between slight head-down and head-up posture angle ranges and severe head-down and head-up posture angle ranges; the Z-axis and X-axis angle ratios to the net gravitational acceleration (Rate_zg and Rate_xg) are used to set the head-tilting posture angle range. Additionally, the Roll angle is used to distinguish between slight and severe head-tilting posture angle ranges. Figure 4 As shown, Figure 4 A schematic diagram showing the setting of angle threshold ranges for different head postures.

[0110] In this embodiment, the head posture data is smoothed by filtering to reduce interference caused by data jitter, thereby improving the accuracy of the head posture data. The angle data of the head posture is determined based on the filtered head posture data, and then the current head posture of the object under test is accurately identified.

[0111] For example, to help understand the implementation flow of the state monitoring method obtained by combining this embodiment with the above embodiment one, please refer to... Figure 5 , Figure 5 A simplified flowchart of a state monitoring method is provided, specifically: real-time acquisition of head posture data; mean filtering of the data; calculation of real-time feature angles; matching of real-time feature angles with preset threshold ranges for each posture angle; determination of real-time head posture; determination of whether the real-time head posture maintenance time exceeds a preset posture maintenance time threshold; if it exceeds, prompting the user to adjust the posture or move the head.

[0112] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the status monitoring method of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0113] This application also provides a condition monitoring device, please refer to... Figure 6 The status monitoring device includes:

[0114] The acquisition module 10 is used to acquire the head posture data of the object under test in real time.

[0115] The recognition module 20 is used to identify the current head posture of the object under test based on the head posture data.

[0116] The reminder module 30 is used to generate corresponding status notification information when the duration of the current head posture reaches a threshold.

[0117] This embodiment provides a status monitoring device that collects head posture data of the subject under test in real time; identifies the current head posture of the subject under test based on the head posture data; and generates corresponding status notification information when the duration of the current head posture reaches a threshold, thereby improving the accuracy of user head posture monitoring and enabling accurate identification of the user's poor posture and timely reminders.

[0118] In summary, this embodiment identifies the current head posture of the test subject by collecting head posture data in real time. It can monitor the user's head posture in real time, accurately identify poor postures of the test subject, and generate corresponding status notification information when the duration of the current head posture reaches the corresponding threshold, thus providing timely status reminders. This overcomes the technical defects of existing head posture monitoring technologies, which cannot accurately identify subtle changes in head posture, resulting in poor head posture monitoring accuracy and the inability to provide timely status reminders. This improves the accuracy of user head posture monitoring, enabling accurate identification of poor user postures and timely reminders.

[0119] Optionally, the recognition module 20 is further configured to filter the head posture data to obtain filtered head posture data; determine the angle data of the head posture based on the filtered head posture data; and identify the current head posture of the object to be tested based on the angle data.

[0120] Optionally, the recognition module 20 is further configured to determine a first acceleration, a second acceleration, and a third acceleration based on the filtered head posture data, wherein the directions of the first acceleration, the second acceleration, and the third acceleration are perpendicular to each other; determine a first feature angle, a second feature angle, a third feature angle, and a first target angle based on the first acceleration, the second acceleration, and the third acceleration, wherein the first feature angle, the second feature angle, and the third feature angle are used to characterize the component proportions of acceleration in different directions relative to the overall resultant acceleration and their angular relationships, and the first target angle is used to characterize the degree of tilt of the head of the test object relative to the horizontal plane; determine a second target angle based on the first acceleration and the third acceleration, wherein the second target angle is used to characterize the degree of rotation of the test object in the horizontal plane; and use the first feature angle, the second feature angle, the third feature angle, the pitch angle, and the roll angle as the angle data of the head posture.

[0121] Optionally, the identification module 20 is further configured to determine the pitch angle based on the first acceleration, the second acceleration, and the third acceleration; determine the resultant gravity acceleration based on the first acceleration, the second acceleration, and the third acceleration; and calculate the first characteristic angle, the second characteristic angle, and the third characteristic angle based on the resultant gravity acceleration and the first acceleration, the second acceleration, and the third acceleration, respectively.

[0122] Optionally, the recognition module 20 is further configured to obtain the angle range corresponding to different head postures; match the angle data with the angle range corresponding to the different head postures to obtain initial head posture information; and determine the current head posture of the object to be tested based on the initial head posture information and the angle data.

[0123] Optionally, the recognition module 20 is further configured to collect acceleration data of the user under different head postures; determine the angle features corresponding to different head postures based on the acceleration data; and determine the angle range corresponding to different head postures based on the angle features.

[0124] Optionally, the state monitoring device further includes a determination module, which is used to determine the posture category of the current head posture based on the degree of influence of the current head posture on the cervical spine state; and to determine a corresponding threshold based on the posture category of the current head posture.

[0125] The condition monitoring device provided in this application, employing the condition monitoring method described in the above embodiments, can solve the technical problems of discomfort and limitations caused by long-term use of traditional orthodontic products. Compared with the prior art, the beneficial effects of the condition monitoring device provided in this application are the same as those of the condition monitoring method provided in the above embodiments, and other technical features of the condition monitoring device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0126] This application provides a wearable device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the status monitoring method in Embodiment 1 above.

[0127] The following is for reference. Figure 7 The diagram illustrates a structural schematic suitable for implementing the embodiments of this application. The wearable devices in the embodiments of this application may include, but are not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 7 The wearable device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of this application.

[0128] like Figure 7As shown, the wearable device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the wearable device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows the wearable device to communicate wirelessly or wiredly with other devices to exchange data. While wearable devices with various systems are shown in the figures, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0129] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0130] The wearable device provided in this application, employing the status monitoring method described in the above embodiments, can solve the technical problems of discomfort and limitations caused by long-term use of traditional orthodontic products. Compared with the prior art, the beneficial effects of the wearable device provided in this application are the same as those of the status monitoring method provided in the above embodiments, and other technical features of the wearable device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0131] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0132] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0133] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the state monitoring method described in the above embodiments.

[0134] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0135] The aforementioned computer-readable storage medium may be included in the wearable device; or it may exist independently and not assembled into the wearable device.

[0136] The aforementioned computer-readable storage medium carries one or more programs that, when executed by a wearable device, cause the wearable device to: collect head posture data of the subject under test in real time; identify the current head posture of the subject under test based on the head posture data; and generate corresponding status notification information when the duration of the current head posture reaches a threshold.

[0137] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0138] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0139] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0140] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described state monitoring method. This solves the technical problems of discomfort and limitations caused by long-term use of traditional orthodontic products. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the state monitoring method provided in the above embodiments, and will not be repeated here.

[0141] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the state monitoring method described above.

[0142] The computer program product provided in this application can solve the technical problems of discomfort and limitations caused by long-term use of traditional orthodontic products. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the state monitoring method provided in the above embodiments, and will not be repeated here.

[0143] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A condition monitoring method, characterized in that, The method includes: Real-time acquisition of head posture data of the object under test; Identify the current head posture of the object under test based on the head posture data; When the duration of the current head pose reaches a threshold, a corresponding status notification message is generated.

2. The method as described in claim 1, characterized in that, The step of identifying the current head posture of the object under test based on the head posture data includes: The head pose data is filtered to obtain filtered head pose data. The angle data of the head posture is determined based on the filtered head posture data. The current head posture of the object under test is identified based on the angle data.

3. The method as described in claim 2, characterized in that, The step of determining the angle data of the head posture based on the filtered head posture data includes: A first acceleration, a second acceleration, and a third acceleration are determined based on the filtered head posture data, wherein the directions of the first acceleration, the second acceleration, and the third acceleration are perpendicular to each other; The first characteristic angle, the second characteristic angle, the third characteristic angle, and the first target angle are determined based on the first acceleration, the second acceleration, and the third acceleration. The first characteristic angle, the second characteristic angle, and the third characteristic angle are used to characterize the component proportions of the acceleration relative to the overall resultant acceleration in different directions and their directional angular relationships. The first target angle is used to characterize the degree of tilt of the head of the object under test relative to the horizontal plane. A second target angle is determined based on the first acceleration and the third acceleration, and the second target angle is used to characterize the degree of rotation of the object under test in the horizontal plane; The first feature angle, the second feature angle, the third feature angle, the pitch angle, and the roll angle are used as the angle data of the head posture.

4. The method as described in claim 3, characterized in that, The step of determining the first feature angle, the second feature angle, the third feature angle, and the first target angle based on the first acceleration, the second acceleration, and the third acceleration includes: The pitch angle is determined based on the first acceleration, the second acceleration, and the third acceleration. The resultant gravitational acceleration is determined based on the first acceleration, the second acceleration, and the third acceleration; The first characteristic angle, the second characteristic angle, and the third characteristic angle are calculated based on the resultant gravitational acceleration and the first acceleration, the second acceleration, and the third acceleration, respectively.

5. The method as described in claim 2, characterized in that, Identifying the current head posture of the object under test based on the angle data includes: Obtain the angle range corresponding to different head postures; The angle data is matched with the angle range corresponding to the different head postures to obtain the initial head posture information; The current head posture of the object under test is determined based on the initial head posture information and the angle data.

6. The method as described in claim 5, characterized in that, The process of obtaining the angle range corresponding to different head postures includes: Collect acceleration data of users in different head postures; Based on the acceleration data, determine the angular features corresponding to different head postures; The angle range corresponding to different head postures is determined based on the aforementioned angle characteristics.

7. The method according to any one of claims 1 to 6, characterized in that, Before generating the corresponding status notification information when the duration of the current head pose reaches a threshold, the method further includes: The posture category of the current head posture is determined based on the degree of influence of the current head posture on the cervical spine status; The corresponding threshold is determined based on the posture category of the current head posture.

8. A condition monitoring device, characterized in that, The status monitoring device includes: The acquisition module is used to acquire head posture data of the object under test in real time. The recognition module is used to identify the current head posture of the object under test based on the head posture data; The reminder module is used to generate corresponding status notification information when the duration of the current head posture reaches a threshold.

9. A wearable device, characterized in that, The wearable device performs the status monitoring method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium stores a state monitoring program, which, when executed by a processor, implements the state monitoring method as described in any one of claims 1 to 7.

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