Head motion detection method and apparatus

Abstract

A head motion detection method and apparatus. In the detection method, a three-axis acceleration sensor is used to measure a pitch angle, a roll angle and a yaw angle during head motion to calculate a current attitude value, so as to further calculate a trend value on the basis of a change in the attitude value, such that the attitude value and the trend value are combined to detect a head motion situation, which facilitates the easy and intuitive acquisition of the number of head motions and the amplitude of each motion, with high accuracy. The detection apparatus comprises an outer sponge (1) adapted to a head size, an inner sponge (2), and a circuit module embedded between the outer sponge (1) and the inner sponge (2), wherein the circuit module is used for implementing the head motion detection method to detect head motions. The head motion detection apparatus has a simple structure and compact installation, and both an outer sponge and an inner sponge use a flexible design, thereby ensuring comfortable wearing and almost no interference to a subject.

Description

A method and device for detecting head motion Technical Field

[0001] This invention relates to the field of motion detection technology, and more particularly to a method and device for detecting head motion. Background Technology

[0002] Sleep is crucial for human health, not only for the body's recovery, integration, and memory consolidation, but also directly related to growth and development, energy storage, and the maintenance of immune function. A World Health Organization (WHO) survey shows that 27% of the global population suffers from varying degrees of sleep problems. This data reveals that sleep disorders have become a serious threat to the health of people worldwide. Therefore, effectively monitoring people's daily sleep patterns, enabling them to understand their own sleep issues, and making timely improvements to their sleep is extremely important.

[0003] Sleep monitoring systems can be broadly categorized into two types: non-contact systems, such as those based on microwave radar, and contact systems, such as polysomnography (PSG). While microwave radar-based systems achieve unobtrusive monitoring, their accuracy is limited due to interference from clothing and bedding, and incomplete signal collection. PSG, considered the "gold standard" for diagnosing sleep disorders, typically requires subjects to undergo monitoring of their sleep activities over multiple nights at a qualified hospital. The numerous electrodes and complex connections can cause psychological stress and physical discomfort, potentially making it harder for subjects to fall asleep.

[0004] Among the many sleep monitoring systems available, those offering a good user experience while maintaining a reasonable level of accuracy, such as those based on heart rate variability, are often preferred by users. These systems typically use sensors to detect body movements to aid in monitoring, making the distinction between sleep and wakefulness more accurate. Based on the different sensors used, this paper introduces the current state of related technologies from three aspects: monitoring based on microwave technology, flexible force sensors, and accelerometers.

[0005] Microwave-based monitoring utilizes the microwave Doppler principle, employing radio frequency bio-radar to emit a continuous radio frequency signal. This signal is reflected by the target and received by a receiver. The signal with the largest amplitude is separated from the echo signal, representing body movements. In practical applications, wavelet transform is used to preprocess the separated body movement signal, calculating its energy value and extreme values, thereby extracting the number of body movements. This type of technology achieves non-invasive monitoring of the subject, without affecting their normal sleep; however, the acquired signals are highly susceptible to interference, resulting in low accuracy.

[0006] Monitoring based on flexible force sensors primarily uses mattresses as the monitoring medium. These sensors are either capacitive or resistive, converting changes in pressure signals into changes in capacitance or resistance, which are then further converted into electrical quantities (voltage, current, etc.) for output. Before and after each body movement, the pressure dot matrix image shows corresponding changes. After image denoising, the amplitude and frequency characteristics of the body movement are analyzed using frame difference or image grayscale centroid methods. Based on these characteristics, the movement is categorized into large, medium, small, and stationary movements, and then quantified. The advantages of this technology are similar to those of microwave-based monitoring, as it causes almost no interference to the subject. The disadvantage is that if the subject turns over frequently, they may be outside the monitoring range of the pressure dot matrix.

[0007] Accelerometer-based monitoring typically uses the triaxial accelerometer from the MPU6050 sensor, summing the squares and taking the square root to synthesize a one-dimensional acceleration value. There are three common methods for measuring body motion: 1) the time threshold method, which records the duration for which the composite acceleration exceeds a reference value per unit time; 2) the digital integration method, which records the integral of the composite acceleration over time per unit time, i.e., the area under the composite acceleration curve; and 3) the zero-crossing method, which records the number of times the composite acceleration exceeds a reference value (slightly larger than zero) per unit time. The advantage of these techniques is their suitability for wearable applications and higher accuracy than the previous two methods. However, relying solely on acceleration to directly reflect the frequency and amplitude of body movements still results in insufficient precision. Technical issues

[0008] This invention provides a head motion detection method and device, which solves the technical problem that existing accelerometer-based body motion detection methods only use acceleration to directly reflect the number and amplitude of body movements, and the detection results are still not accurate enough. Technical solutions

[0009] To address the above technical problems, this invention provides a head motion detection method, comprising the following steps:

[0010] S1. Acquire the pitch angle, roll angle, and yaw angle measured by a triaxial accelerometer fixed to the head at a fixed frequency;

[0011] S2. Calculate the current attitude value based on the pitch angle, roll angle, and yaw angle at the current sampling time; the current attitude value is equal to the square root of the sum of the squares of the pitch angle, roll angle, and yaw angle, and then rounded down.

[0012] S3. Determine the current trend value based on the difference between the current attitude value and the previous attitude value;

[0013] S4. If the current trend value corresponds to an unchanged trend, increment the number of consecutive unchanged trends by 1; otherwise, reset the number of consecutive unchanged trends to zero.

[0014] S5. Determine whether the number of times the continuous trend remains unchanged exceeds the threshold for continuous trend. If yes, proceed to step S9; otherwise, proceed to the next step.

[0015] S6. Calculate the absolute difference between the current trend value and the previous trend value. If the absolute difference is greater than 0, record the absolute difference between the previous posture value and the last posture value of the previous movement as the amplitude of the current movement and proceed to step S9. Otherwise, proceed to the next step.

[0016] S7. Calculate the absolute difference between the current attitude value and the last attitude value of the previous movement. If the absolute difference exceeds the attitude absolute difference threshold, proceed to the next step; otherwise, go to step S10.

[0017] S8. The number of head movements is incremented by 1 and proceeds to step S10.

[0018] S9. Assign the previous attitude value to the last attitude value of the previous movement, assign 0 to the number of times the continuous trend remains unchanged, assign 0 to the absolute difference between the current attitude value and the last attitude value of the previous movement, and proceed to the next step.

[0019] S10. Assign the current attitude value to the previous attitude value, assign the current trend value to the previous trend value, and return to step S2.

[0020] Furthermore, in step S2, the current attitude value is equal to the square root of the sum of the squares of the pitch angle, roll angle, and yaw angle, and then rounded down.

[0021] Further, in step S3, if the difference between the current attitude value and the previous attitude value is greater than 0, then the current trend value trend_cur is the first preset value; if the difference between the current attitude value and the previous attitude value is less than 0, then the current trend value trend_cur is the second preset value; if the difference between the current attitude value and the previous attitude value is equal to 0, then the current trend value trend_cur is the third preset value; the first preset value, the second preset value, and the third preset value are all different from each other.

[0022] Furthermore, the first preset value is 1, the second preset value is 2, and the third preset value is 0.

[0023] The present invention also provides a head motion detection device, the key feature of which is: it includes an outer sponge adapted to the size and shape of the head, an inner sponge, and a circuit module embedded between the outer sponge and the inner sponge. The circuit module is provided with a main board, and the main board is used to implement the head motion detection method described above.

[0024] Specifically, the circuit module also includes a battery module, a display and button module, and a magnetic charging port that are electrically connected to the motherboard, wherein the display and button module and the magnetic charging port are openly embedded on the surface of the outer sponge.

[0025] Specifically, the outer sponge and the inner sponge are configured as flexible structures that can be bent inward into a ring structure that fits the size of the head.

[0026] Specifically, the outer sponge and the inner sponge are provided with interlocking Velcro at their ends.

[0027] Specifically, the battery module includes a battery, a top frame shell, and a bottom frame shell, with the battery fixed in the top frame shell and the bottom frame shell.

[0028] Specifically, the head motion detection device further includes an upper frame shell, a middle frame shell, and a lower frame shell, and the motherboard and display and button module are fixed in the upper frame shell, the middle frame shell, and the lower frame shell. Beneficial effects

[0029] This invention provides a head motion detection method that uses a triaxial accelerometer to measure the pitch, roll, and yaw angles during head movement to calculate the current attitude value. Based on changes in the attitude value, a trend value is further calculated. The attitude and trend values ​​are then combined to detect head movement, providing a clear and intuitive way to obtain the number of head movements and the amplitude of each movement. Extensive experiments have verified the accuracy of this method. Furthermore, this method requires low computational power and is easily applicable to wearable devices.

[0030] This invention provides a head movement detection device, which includes an outer sponge, an inner sponge adapted to the size of the head, and a circuit module embedded between the outer and inner sponges. The circuit module implements the aforementioned head movement detection method to detect head movements, displaying the number of detected movements, the amplitude of each movement, and the remaining battery power on a screen. The outer and inner sponges are designed to fit the size and shape of the head, making it easy to wear and complete head movement detection. This head movement detection device has a simple structure and compact installation. Both the outer and inner sponges are flexible, providing a comfortable wearing experience and being lightweight, allowing for stable wear on the user's head. It can detect the user's head movements regardless of their specific movements, with minimal interference to the subject. Furthermore, the detection method implemented by the circuit module ensures high detection accuracy. Attached Figure Description

[0031] Figure 1 is a flowchart of a head motion detection method provided in an embodiment of the present invention;

[0032] Figure 2 is a graph showing nine trends in attitude values ​​provided in an embodiment of the present invention.

[0033] Figure 3 is a schematic diagram of motion-related missed detection provided in an embodiment of the present invention;

[0034] Figure 4 is a graph showing the experimental results provided in the embodiment of the present invention;

[0035] Figure 5 is a structural diagram of a head motion detection device provided in an embodiment of the present invention.

[0036] Reference numerals: 1-Outer sponge, 2-Inner sponge, 3-Main board, 4-Battery module, 41-Battery, 42-Top frame shell, 43-Bottom frame shell, 5-Display and button module, 6-Magnetic charging port, 71-Upper frame shell, 72-Middle frame shell, 73-Lower frame shell. Embodiments of the present invention

[0037] The embodiments of the present invention are described in detail below with reference to the accompanying drawings. The embodiments are given for illustrative purposes only and should not be construed as limiting the present invention. The accompanying drawings are for reference and illustration only and do not constitute a limitation on the scope of patent protection of the present invention, because many changes can be made to the present invention without departing from the spirit and scope of the present invention.

[0038] An embodiment of the present invention provides a head motion detection method, as shown in the flowchart of Figure 1, which includes the following steps:

[0039] S1. Acquire pitch, roll, and yaw angles at a fixed frequency using a triaxial accelerometer fixed to the head.

[0040] S2. Calculate the current attitude value (pose_cur) based on the pitch, roll and yaw angles at the current sampling time.

[0041] S3. Determine the current trend value (trend_cur) based on the difference between the current pose value (pose_cur) and the previous pose value (pose_pre).

[0042] S4. If the current trend value (trend_cur) corresponds to an unchanged trend, increment the number of consecutive unchanged trends (trend_unchange) by 1; otherwise, clear the number of consecutive unchanged trends (trend_unchange) to zero.

[0043] S5. Determine whether the number of times the continuous trend remains unchanged (trend_unchange) exceeds the continuous trend unchanged threshold (TREND_THRESHOLD). If yes, proceed to step S9; otherwise, proceed to the next step.

[0044] S6. Calculate the absolute difference (diff_trend) between the current trend value (trend_cur) and the previous trend value (trend_pre). If the absolute difference (diff_trend) is greater than 0, record the absolute difference (|pose_pre - pose_last|) between the previous pose value (pose_pre) and the last pose value of the previous movement as the amplitude of the current movement and proceed to step S9; otherwise, proceed to the next step.

[0045] S7. Calculate the absolute difference (diff_pose) between the current pose value (pose_cur) and the last pose value (pose_last) of the previous movement. If the absolute difference (diff_pose) exceeds the pose absolute difference threshold (ACTION_THRESHOLD), proceed to the next step; otherwise, go to step S10.

[0046] S8. Increment the total number of head movements (total_action) by 1 and proceed to step S10;

[0047] S9. Assign the previous pose value (pose_pre) to the last pose value (pose_last) of the previous movement, set the number of times the continuous trend remains unchanged (trend_unchange) to 0, set the absolute difference (diff_pose) between the current pose value and the last pose value of the previous movement to 0, and proceed to the next step.

[0048] S10. Assign the current pose value (pose_cur) to the previous pose value (pose_pre), assign the current trend value (trend_cur) to the previous trend value (trend_pre), and return to step S2.

[0049] The following provides a more detailed explanation of each step.

[0050] Before step S1, the following steps are also included:

[0051] S0. Initialization: Assign the first calculated pose value (pose[0]) to the last pose value (pose_last) and the previous pose value (pose_last) of the previous movement. Assign the previous trend value to 0, the number of times the continuous trend remains unchanged (trend_unchange) to 0, the number of head movements (total_action) to 0, the threshold for continuous trend invariance (TREND_THRESHOLD) to a, and the threshold for absolute pose difference (ACTION_THRESHOLD) to b. In this example, a=3 and b=30 are chosen based on the results of multiple experiments by multiple people to achieve the highest detection accuracy.

[0052] In step S1, the triaxial accelerometer used in this example is the MPU6050 sensor. In other embodiments, other triaxial accelerometers, such as the LIS3DH, can be used.

[0053] In step S2, the current attitude value (pose_cur) is equal to the square root of the sum of the squares of the pitch angle, roll angle, and yaw angle, rounded down.

[0054] (1)

[0055] Here, [·] indicates rounding down to the nearest integer. The advantages of rounding are twofold: first, it filters out glitches, making subsequent detection easier; second, it eliminates the zero-drift problem of the sensor. This rounding is reasonable because head motion detection considers a process, and the currently ignored decimal part will be compensated for to some extent in the next moment, thus not affecting the detection.

[0056] Each moment can be used as the current moment, and the attitude value at the corresponding moment is calculated using formula (1). The attitude value at the previous moment corresponding to the current attitude value (pose_cur) is the previous attitude value (pose_pre).

[0057] To obtain an effective detection method for the next steps, it is necessary to analyze the changing trend of the pose. As shown in Figure 2, the changes in the pose before and after time T can be abstracted into 9 cases, divided into 3 categories. The first category corresponds to (a1), (a2), and (a3) ​​in Figure 2, where the trend is upward before time T; the second category corresponds to (b1), (b2), and (b3) in Figure 2, where the trend is downward before time T; and the third category corresponds to (c1), (c2), and (c3) in Figure 2, where the trend remains unchanged before time T. Through analysis, the following ideas can be easily derived: First, when the trend does not change before and after time T, no new movement occurs, as seen in (a1), (b1), and (c1); second, when there is an upward or downward trend after time T, new movement may occur, but the subsequent magnitude of change needs to be further observed, as seen in (a2), (b2), (c2), and (c3); third, when the trend remains unchanged after time T, the previous possible movement ends, as seen in (a3) ​​and (b3).

[0058] In step S3, based on the aforementioned Pose change trend, this example obtains the current trend value (trend_cur) based on the difference (diff) between the current pose value (pose_cur) and the previous pose value (pose_pre).

[0059] First, calculate the difference (diff) between the current pose value (pose_cur) and the previous pose value (pose_pre):

[0060] (2)

[0061] If diff > 0, the current trend value trend_cur = 1 (first preset value); if diff < 0, the current trend value trend_cur = 2 (second preset value); if diff = 0, the current trend value trend_cur = 0 (third preset value). The values ​​1, 2, and 0 of the current trend value trend_cur represent an upward trend, a downward trend, and an unchanged trend, respectively. In other embodiments, the first, second, and third preset values ​​can be other combinations of mutually exclusive values.

[0062] In step S4, when the trend corresponding to the current trend value trend_cur is upward or downward (i.e., trend_cur is not equal to 0), the number of consecutive trends that remain unchanged is reset to zero; while when the trend remains unchanged (trend_cur equals 0), the number of consecutive trends that remain unchanged is incremented by 1.

[0063] In step S5, it is determined whether the number of consecutive unchanged trends (trend_unchange) exceeds the threshold (TREND_THRESHOLD). If it does, proceed to step S9; otherwise, proceed to the next step. The purpose of this step is to solve the motion detection failure problem shown in Figure 3. In Figure 3(a), the trend is upward before time T1, remains unchanged between T1 and T2, and continues upward after T2. Since the trend remains unchanged between T1 and T2, it is still considered an upward trend. Therefore, a new motion that may occur after T2 may be considered a continuation of the motion before T1. When the interval between T1 and T2 is long enough, the motion after T2 can be considered new, not just a continuation of the previous motion, and a false negative will occur. The problem that may occur in Figure 3(b) is similar.

[0064] In step S6, the absolute difference (diff_trend) between the current trend value (trend_cur) and the previous trend value (trend_pre) is first calculated:

[0065] (3)

[0066] If diff_trend > 0, it indicates a trend change (if the number of head movements has been counted since the last trend change, then...). (Record |pose_pre-pose_last| as the amplitude of this movement), proceed to step S9, otherwise proceed to the next step.

[0067] In step S7, the absolute difference (diff_pose) between the current pose value (pose_cur) and the last pose value (pose_last) of the previous movement is first calculated:

[0068] (4)

[0069] If diff_pose exceeds the absolute pose difference threshold ACTION_THRESHOLD, proceed to the next step; otherwise, go to step S10.

[0070] In step S9, some data and parameters are reset, the previous pose value (pose_pre) is assigned to the last pose value of the previous movement (pose_last), the number of times the continuous trend remains unchanged (trend_unchange) is set to 0, and the absolute difference between the current pose value and the last pose value of the previous movement (diff_pose) is set to 0. That is:

[0071] (5)

[0072] In step S10, the previous value and the previous trend are updated. The current pose value (pose_cur) is assigned to the previous pose value (pose_pre), and the current trend value (trend_cur) is assigned to the previous trend value (trend_pre). That is:

[0073] (6)

[0074] Then proceed to step S2 to enter the next round of testing.

[0075] A large number of experiments were conducted using the above method with a detection cycle of 30 seconds. Figure 4 shows some of the experimental results, including the detection results of 9 detection cycles from (a) to (i). As can be seen from Figure 4, this method can detect the number of head movements under various head movement conditions based on the Pose value, which is consistent with actual visual observation, and the amplitude recorded for each movement matches the actual situation.

[0076] This invention provides a head motion detection method that uses a triaxial accelerometer to measure the pitch, roll, and yaw angles during head movement to calculate the current attitude value. Based on changes in the attitude value, a trend value is further calculated. The attitude value and trend value are then combined to detect head movement, providing a clear and intuitive way to obtain the number of head movements and the amplitude of each movement. Extensive experiments have verified the accuracy of this method. Furthermore, this method requires low computational power and is easily applicable to wearable devices.

[0077] To apply the above-mentioned head motion detection method, the present invention provides a head motion detection device, the structure of which is shown in Figure 5. It includes an outer sponge 1, an inner sponge 2 adapted to the size and shape of the head, and a circuit module embedded between the outer sponge 1 and the inner sponge 2. The circuit module is provided with a main board 3, which is used to implement the above-mentioned head motion detection method.

[0078] Specifically, the outer sponge 1 and inner sponge 2 are designed with a flexible structure that can be bent inward into a ring shape to fit the size of the head, making it easy to wear on the head. The ends of the outer sponge 1 and inner sponge 2 are equipped with interlocking Velcro straps.

[0079] Specifically, as shown in Figure 5, the circuit module also includes a battery module electrically connected to the motherboard 3, a display and button module 5, and a magnetic charging port 6. The display and button module 5 and the magnetic charging port 6 are openly embedded on the surface of the outer sponge 1, making it convenient for users to view the display screen, operate the buttons, and charge.

[0080] Specifically, the battery module includes a battery 41 and a top frame shell 42 and a bottom frame shell 43 for fixing and protecting the battery 41.

[0081] Specifically, in order to fix and protect the motherboard 3 and the display and button module 5, the head motion detection device also includes an upper frame shell 71, a middle frame shell 72 and a lower frame shell 73.

[0082] Specifically, the motherboard 3 is located on the right side of the inner sponge 2. The display and button module 5 is electrically connected to the motherboard 3 and is located on the outside of the outer sponge 1. The battery 41 is located on the left side of the inner sponge 2, and the magnetic charging port 6 is located on the right side of the outer sponge 1. The inner sponge 2 and the outer sponge 1 are sealed together by a fabric covering.

[0083] The specific installation steps for the head motion detection device provided in this embodiment are as follows:

[0084] 1) Fix the motherboard 3 to the lower frame shell 73 with screws, and fix it to the inner sponge 2 with a small amount of environmentally friendly glue;

[0085] 2) The display and button module 5 is clipped onto the middle frame shell 72 and reinforced onto the lower frame shell 73 by positioning posts;

[0086] 3) Install the upper frame shell 71 onto the middle frame shell 72;

[0087] 4) Fix the battery 41 inside the top frame shell 42 and the bottom frame shell 43, and fix it with a little environmentally friendly glue and sponge;

[0088] 5) Apply a small amount of eco-friendly adhesive to fix the magnetic charging port 6 to the outer sponge 1;

[0089] 6) Sew the inner sponge 2 and the outer sponge 1 together and seal the edges with a fabric strip.

[0090] The operating procedure for this device is as follows:

[0091] 1) Align the concave area of ​​the device with the bridge of the nose and eyes, and secure it to the user's head using the Velcro at both ends.

[0092] 2) After pressing and holding the button for 2 seconds to power on, the motherboard 3 acquires the detection signal and then obtains the pitch, roll, and yaw angle data of the sensor from the most recent recording cycle (30 seconds) at a certain frequency. Head movements are detected using the aforementioned head movement detection method, and the number of detected movements and the magnitude of each movement are displayed on the OLED screen. Simultaneously, the motherboard 3 also displays the coulomb counter's battery level data on the OLED screen.

[0093] 3) After the test is completed, press and hold the button for 2 seconds to turn off the device.

[0094] 4) During testing, if the power display area flashes, charging is required immediately. When charging, the included magnetic charger must be used; the charging progress will be displayed on the screen. During charging, the magnetic charger charges battery 41 and simultaneously sends a charging signal to motherboard 3. Motherboard 3 then displays the power data from the coulomb counter on the OLED screen.

[0095] It should also be noted that this device does not limit the installation method or position of the circuit module on the inner sponge 2 and the outer sponge 1, nor does it limit the structure of the circuit module, nor does it limit whether the inner and outer sponges are fixed with Velcro. A head motion detection device suitable for wearing on the head can be designed based on actual needs and limitations.

[0096] This embodiment provides a head movement detection device, which includes an outer sponge 1 and an inner sponge 2 adapted to the size of the head, and a circuit module embedded between the outer sponge 1 and the inner sponge 2. The circuit module is used to implement the head movement detection method described above to detect head movements, and displays the number of detected movements, the amplitude of each movement, and the remaining battery power on a display screen. The outer sponge 1 and inner sponge 2 are designed to fit the size and shape of the head, making it easy to wear on the user's head to complete the head movement detection. This head movement detection device has a simple structure and compact installation. Both the outer sponge 1 and inner sponge 2 are flexible, providing a comfortable wearing experience for the user and having a light weight, allowing it to be worn stably on the user's head. Regardless of the user's movement, it can detect the user's head movements with almost no interference to the subject. Furthermore, the detection method implemented by the circuit module ensures high detection accuracy.

[0097] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A method for detecting head motion, characterized in that, Including the following steps: S1. Acquire the pitch angle, roll angle, and yaw angle measured by a triaxial accelerometer fixed to the head at a fixed frequency; S2. Calculate the current attitude value based on the pitch angle, roll angle, and yaw angle at the current sampling time; the current attitude value is equal to the square root of the sum of the squares of the pitch angle, roll angle, and yaw angle, and then rounded down. S3. Determine the current trend value based on the difference between the current attitude value and the previous attitude value; S4. If the current trend value corresponds to an unchanged trend, increment the number of consecutive unchanged trends by 1; otherwise, reset the number of consecutive unchanged trends to zero. S5. Determine whether the number of times the continuous trend remains unchanged exceeds the threshold for continuous trend. If yes, proceed to step S9; otherwise, proceed to the next step. S6. Calculate the absolute difference between the current trend value and the previous trend value. If the absolute difference is greater than 0, record the absolute difference between the previous posture value and the last posture value of the previous movement as the amplitude of the current movement and proceed to step S9. Otherwise, proceed to the next step. S7. Calculate the absolute difference between the current attitude value and the last attitude value of the previous movement. If the absolute difference exceeds the attitude absolute difference threshold, proceed to the next step; otherwise, go to step S10. S8. The number of head movements is incremented by 1 and proceeds to step S10. S9. Assign the previous attitude value to the last attitude value of the previous movement, assign 0 to the number of times the continuous trend remains unchanged, assign 0 to the absolute difference between the current attitude value and the last attitude value of the previous movement, and proceed to the next step. S10. Assign the current attitude value to the previous attitude value, assign the current trend value to the previous trend value, and return to step S2.

2. The head motion detection method according to claim 1, characterized in that: In step S3, if the difference between the current attitude value and the previous attitude value is greater than 0, then the current trend value trend_cur is the first preset value; if the difference between the current attitude value and the previous attitude value is less than 0, then the current trend value trend_cur is the second preset value; if the difference between the current attitude value and the previous attitude value is equal to 0, then the current trend value trend_cur is the third preset value; the first preset value, the second preset value, and the third preset value are all different.

3. The head motion detection method according to claim 2, characterized in that: The first preset value is 1, the second preset value is 2, and the third preset value is 0.

4. A head motion detection device, characterized in that: The device includes an outer sponge (1) adapted to the size and shape of the head, an inner sponge (2), and a circuit module embedded between the outer sponge (1) and the inner sponge (2). The circuit module is provided with a main board (3), which is used to implement a head movement detection method according to any one of claims 1 to 3.

5. The head motion detection device according to claim 4, characterized in that: The circuit module also includes a battery module (4), a display and button module (5), and a magnetic charging port (6) electrically connected to the motherboard (3), wherein the display and button module (5) and the magnetic charging port (6) are openly embedded on the surface of the outer sponge (1).

6. The head motion detection device according to claim 4, characterized in that: The outer sponge (1) and the inner sponge (2) are configured as flexible structures that can be bent inward into a ring structure that fits the size of the head.

7. The head motion detection device according to claim 6, characterized in that: The outer sponge (1) and the inner sponge (2) are provided with Velcro straps that cooperate with each other at their tail ends.

8. A head motion detection device according to claim 5, characterized in that: The battery module (4) includes a battery (41), a top frame shell (42) and a bottom frame shell (43), and the battery (41) is fixed in the top frame shell (42) and the bottom frame shell (43).

9. A head motion detection device according to claim 4, characterized in that: The head motion detection device also includes an upper frame shell (71), a middle frame shell (72) and a lower frame shell (73), and the motherboard (3) and the display and button module (5) are fixed in the upper frame shell (71), the middle frame shell (72) and the lower frame shell (73).

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