A wearable music metronome

Abstract

The embodiment of the present disclosure provides a wearable music metronome, including a sensor, a processor, and an output device, wherein the sensor obtains environmental noise data and a user's current activity state; the processor determines the mode and intensity of rhythm prompts based on the environmental noise data and the user's current activity state; selects a corresponding output device according to the determined rhythm prompt mode; and adjusts the parameters of the output device to match the determined rhythm prompt intensity. Through the solution of the embodiment of the present disclosure, it is possible to solve how to provide rhythm prompts according to different environmental conditions.

Description

Technical Field

[0001] The present application relates to the technical field of music metronomes, and in particular to a wearable music metronome. Background Art

[0002] Wearable music metronomes are wearable devices such as bracelets or chest straps that output stable beat prompts according to the user's needs and the rhythm of the music, helping users to better control their sense of rhythm and musical expression. However, an important problem faced by such music metronomes in practical applications is how to intelligently adjust the output mode and intensity of the rhythm prompts according to factors such as the noise level, light conditions, and the user's motion state in different environments, so as to ensure that accurate and easy-to-perceive beat signals can be effectively provided in various environments. Summary of the invention

[0003] In view of this, an embodiment of the present disclosure provides a wearable music metronome, which at least partially solves the problems existing in the prior art.

[0004] A wearable music metronome of the present application includes a sensor, a processor and an output device, and is characterized in that:

[0005] The sensor acquires environmental noise data and the user's current activity status;

[0006] The processor determines the mode and intensity of the rhythm prompt based on the environmental noise data and the current activity state of the user;

[0007] Selecting a corresponding output device according to the determined rhythm prompting method; and

[0008] Adjust the parameters of the output device to match the determined rhythmic cue intensity.

[0009] According to one embodiment, the step of determining the mode and intensity of the rhythm prompt based on the environmental noise data and the user's current activity state further includes:

[0010] Analyze the spectrum characteristics of environmental noise;

[0011] Determine whether the user's current activity is high-intensity exercise;

[0012] Selecting a suitable rhythm prompt mode based on the spectrum characteristics and activity status;

[0013] If the user's activity state is still, the frequency of the rhythm prompt is set to f=1, where f represents the frequency of the rhythm prompt.

[0014] According to one embodiment, the step of selecting a suitable rhythm prompt mode based on the spectrum characteristics and the activity state further includes:

[0015] Calculate the energy density E of the ambient noise;

[0016] Determine whether the user is in a noisy environment;

[0017] Based on the energy density E and the user's current activity state, adjust the volume and amplitude of the rhythm prompt;

[0018] If the energy density E > K, set the volume V to the maximum volume V_max, where E represents the energy density of the ambient noise, K represents a preset energy density threshold, V represents the output volume, and V_max represents the maximum volume.

[0019] According to one embodiment, the step of adjusting the volume and amplitude of the rhythm prompt based on the energy density E and the user's current activity state further includes:

[0020] Determine whether the user's activity state is low-intensity or medium-intensity exercise;

[0021] Measure the current background noise level L;

[0022] Based on the background noise level L, adjust the amplitude A of the vibration prompt;

[0023] If L > M, set the amplitude A to A_max, where L represents the current background noise level, M represents a preset background noise threshold, A represents the amplitude of the vibration prompt, and A_max represents the maximum amplitude.

[0024] According to one embodiment, the step of adjusting the amplitude A of the vibration prompt based on the background noise level L further includes:

[0025] Obtain the main frequency F_main of the current ambient noise;

[0026] Determine whether the noise frequency is within the audible range;

[0027] Adjust the prompt frequency F_tip based on F_main;

[0028] If F_main < F_min or F_main > F_max, set F_tip to F_default, where F_main represents the main frequency, F_min represents the minimum frequency, F_max represents the maximum frequency, and F_default represents the default prompt frequency.

[0029] According to one embodiment, the step of adjusting the prompt frequency F_tip based on F_main further includes:

[0030] Calculate the main peak position P_main of the noise spectrum;

[0031] Determine whether the user requires simultaneous visual and audio cues;

[0032] Select synchronous or asynchronous prompt mode based on P_main;

[0033] If P_main is greater than a threshold value N, the prompt mode is set to a synchronization mode, where P_main represents the main peak position and N represents the main peak position threshold.

[0034] According to one embodiment, the step of selecting a suitable rhythm prompt mode based on the spectrum characteristics and the activity state further includes:

[0035] Determine whether the user is currently wearing headphones;

[0036] Calculate the impact of environmental noise on wearing headphones H;

[0037] Adjust the prompt mode based on the user's headset status and H;

[0038] If H>G, the prompt mode is set to vibration prompt, where H represents the impact of environmental noise on wearing headphones, and G represents the preset impact threshold.

[0039] According to one embodiment, the step of adjusting the prompt mode based on the state of the user wearing the headset and H further includes:

[0040] Determine whether the user is indoors;

[0041] Determine if there is any other sound interference I;

[0042] Select appropriate sound or vibration prompt based on I;

[0043] If I>T, the prompt mode is set to dual-mode prompt of sound and vibration, where I represents the intensity of other sound interference and T represents the interference threshold.

[0044] According to one embodiment, the step of selecting a suitable sound or vibration prompt based on I further includes:

[0045] Measure the current user psychological state S;

[0046] Calculate the coefficient C of the influence of psychological state on the prompt mode;

[0047] Choose the appropriate prompt method based on S and C;

[0048] If C*S>P, the prompt mode is set to vibration prompt, where S represents the user's psychological state, C represents the influence coefficient, and P represents the preset prompt selection threshold.

[0049] According to one embodiment, the step of selecting a suitable prompting method based on S and C further includes:

[0050] Determine the user's current activity duration D;

[0051] Calculate the impact of duration on user comfort F;

[0052] Select the final prompt method based on D and F;

[0053] If F*D>Q, set the prompt mode to intermittent prompt, where D represents the activity duration, F represents the influence factor, and Q represents the comfort threshold.

[0054] The embodiment of the present disclosure provides a wearable music metronome, including a sensor, a processor, and an output device, wherein the sensor obtains environmental noise data and a user's current activity state; the processor determines the mode and intensity of rhythm prompts based on the environmental noise data and the user's current activity state; selects a corresponding output device according to the determined rhythm prompt mode; and adjusts the parameters of the output device to match the determined rhythm prompt intensity. Through the solution of the embodiment of the present disclosure, it is possible to solve how to provide rhythm prompts according to different environmental conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the multiple drawings represent the same or similar parts or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments disclosed in the present application and should not be regarded as limiting the scope of the present application.

[0056] Figure 1 It is a flow chart of a method for controlling output of a wearable music metronome;

[0057] Figure 2 is a flow chart for determining the manner and intensity of rhythm cues based on ambient noise data and the user's current activity state;

[0058] Figure 3 is a flow chart for selecting an appropriate rhythm cueing mode based on spectral features and activity status;

[0059] Figure 4 is a flow chart for adjusting the volume and amplitude of the rhythm cue based on the energy density E and the user's current activity state;

[0060] Figure 5 is a flow chart for adjusting the amplitude A of the vibration prompt based on the background noise level L;

[0061] Figure 6 It is a flow chart of adjusting the prompt frequency F_tip based on F_main;

[0062] Figure 7is a flow chart for selecting an appropriate rhythm cueing mode based on spectral features and activity status;

[0063] Figure 8 is a flowchart of adjusting the prompt method based on the state of the user wearing the headphones and the impact of environmental noise on wearing the headphones;

[0064] Fig. 9 is a flow chart for selecting appropriate sound or vibration cues based on other sound distractions;

[0065] Fig.10 It is a flowchart for selecting appropriate prompting methods based on the user's psychological state and influence coefficient;

[0066] Fig.11 It is a structural block diagram of the wearable music metronome of the present application. DETAILED DESCRIPTION

[0067] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0068] First, refer to Fig.11 , a schematic diagram of the structure of a wearable music metronome 1100 of the present invention is described, and the music metronome 1100 includes:

[0069] Sensor 1101 , which may include a noise sensor, a gyroscope, etc., to obtain environmental noise data and the user's current activity status.

[0070] Processor 1102, the processor 1102 can determine the mode and intensity of the rhythm prompt based on the environmental noise data and the user's current activity status.

[0071] Output device 1103: Output device 1103 may be, for example, a vibrator, earphones, LED lights or other output devices, and is used to output audio, vibration or other signals.

[0072] In addition, in the present application, the processor 1102 also adjusts the parameters of the output device 1103 to match the determined rhythm cue intensity.

[0073] Other components and functions of the wearable music metronome 1100 will be described in detail below. Figure 1-Figure 10 Further description is given.

[0074] Next, refer to Figure 1 , describes a wearable music metronome output control method of the present invention. The method includes four main steps, namely:

[0075] S101: Acquire environmental noise data and the user's current activity status;

[0076] S102: Determine the mode and intensity of rhythm prompting based on the environmental noise data and the current activity state of the user;

[0077] S103: selecting a corresponding output device according to the determined rhythm prompting method;

[0078] S104: adjusting the parameters of the output device to match the determined rhythm prompt intensity. These four steps work together to ensure that the music metronome can provide appropriate rhythm prompts to the user under different environmental conditions.

[0079] First, obtain environmental noise data and the user's current activity status, which can be collected through built-in or external sensors. For example, wearable devices can integrate sound sensors, accelerometers, and other biometric sensors that can monitor the environmental noise level and the user's motion status in real time. Specifically, the sound sensor detects the surrounding sound environment, such as background noise, the volume of the concert scene, etc., while the accelerometer can sense the user's body movement, such as running speed, the intensity of dance movements, etc. In this process, the system will continue to collect and analyze this data to determine the best rhythm prompt strategy.

[0080] Subsequently, the method and intensity of the rhythm prompt are determined based on the acquired environmental noise data and the user's current activity status. Specifically, the data collected in the first step can be analyzed to determine what method (such as vibration, light prompt, sound) and intensity to use for rhythm prompts. In one embodiment, when a user is exercising intensively in a gym, if the surrounding environment is noisy, the system may choose to enhance vibration prompts or use bone conduction technology to transmit audio, thereby ensuring that the user can still clearly feel the beat in a high-noise environment. At the same time, according to changes in the user's heart rate, the system may also dynamically adjust the intensity and frequency of the rhythm to help users better maintain the rhythm of exercise.

[0081] Next, select the corresponding output device according to the determined rhythm prompt method. In this step, the control system will select the most suitable hardware device for rhythm prompts according to the method set in the previous step. Specifically, if it is a vibration reminder, the system will choose a vibration motor worn on the wrist or waist; if it is a sound prompt, it may activate the built-in speaker or play the beat sound through headphones connected by Bluetooth; for light prompts, the LED light group will be lit. Each output method is designed to adapt to specific scenarios to ensure that users experience the most suitable rhythm feeling. For example, when meditating in a quiet environment, light prompts may be the best choice to avoid disturbing others.

[0082] Finally, adjust the parameters of the output device to match the determined rhythm prompt intensity. Specifically, the system will adjust the working parameters of the output device according to the method and intensity requirements determined in the previous step. For example, adjust the amplitude of the vibration, the brightness of the light, or the loudness of the sound. In this way, the user can obtain consistent and effective rhythm support regardless of the environment. In a specific embodiment, when the user is walking outdoors, in order to cope with wind noise interference, the system will appropriately increase the audio output power of the bone conduction headphones to ensure that the beat can be clearly transmitted to the user even in the presence of wind noise.

[0083] Through the above four steps, this wearable music metronome output control method can flexibly adjust the mode and intensity of rhythm prompts according to different environmental conditions and user activity status, providing a beat experience that better meets personal needs.

[0084] Next, refer to Figure 2 , describing the steps of the present invention for determining the manner and intensity of rhythm cues based on environmental noise data and the user's current activity status.

[0085] S201: Analyze the spectrum characteristics of the ambient noise. In this step, the ambient noise signal collected by the sensor on the wearable device is converted into a spectrum diagram to analyze the components and characteristics of the sound in more detail. For example, in one embodiment, the device uses a fast Fourier transform (FFT) algorithm to process the collected audio data to obtain the energy distribution at different frequencies.

[0086] S202: Determine whether the user's current activity is high-intensity exercise. In this step, the wearable device uses built-in sensors such as accelerometers or gyroscopes to detect the user's movement, and identifies the user's activity state, such as running, walking, or stillness, through a preset algorithm model. In a specific example, when the step frequency detected by the device is higher than a certain threshold (such as 100 times per minute), it is considered that the user is performing high-intensity exercise.

[0087] S203: Select an appropriate rhythm prompt mode based on the spectrum characteristics and activity status. During the selection process, the system will decide what type of beat sound to emit, such as speed, loudness, etc., according to the specific needs of the user and the characteristics of the ambient noise. Specifically, if it is detected that the user is jogging in a noisy environment, the system may select a low-frequency sound wave with a frequency slightly higher than the average background noise as the prompt sound, which ensures that the user can hear it clearly without disturbing the people around too much.

[0088] S204: If the user's activity state is still, set the frequency of the rhythm prompt to f=1, where f represents the frequency of the rhythm prompt in Hertz. This means that a prompt tone is given every second. The parameter range is usually between 0.5Hz and 2Hz, because sounds below or above this range may make people feel too slow or too fast, which is not conducive to concentration. The best setting is 1Hz because this frequency just fits most people's perception of a normal heartbeat, which helps users maintain a stable mood and sense of rhythm. For example, when the user sits down to rest and turns on this function, a clear and gentle click sound will be heard every second, which is a good auxiliary for heart rate synchronization in gentle activities such as meditation and yoga.

[0089] Next, refer to Figure 3 , describing the steps of selecting a suitable rhythm prompt mode based on spectrum characteristics and activity status of the present invention.

[0090] S301: Calculate the energy density E of the ambient noise. This step aims to quantify the background noise level in the current environment. The energy density E is usually calculated by analyzing the spectrum data, for example, the noise characteristics can be extracted using techniques such as short-time Fourier transform (STFT) or Mel-frequency cepstral coefficients (MFCC). E can range from very low values ​​to very high values, depending on the acoustic conditions of the surrounding environment. In order to make the algorithm more robust, the value of E is usually normalized.

[0091] S302: Determine whether the user is in a noisy environment. Based on the calculated energy density E, it can be determined whether the current environment is a noisy environment by comparing it with the preset energy density threshold K. If E is greater than K, the user is determined to be in a noisy environment; otherwise, it is determined to be a quiet environment. The key to this step lies in the selection of the threshold K. Generally speaking, K should be tested and adjusted multiple times based on common environmental noise levels to ensure that the threshold is neither too high nor too low to achieve a better discrimination effect. For example, in one embodiment, K can be set to a noise level of 50dB, which means that when the background noise exceeds 50dB, the system will consider the user to be in a noisy environment.

[0092] S303: Based on the energy density E and the user's current activity state, adjust the volume and amplitude of the rhythm prompt. The goal of this step is to provide the most suitable rhythm prompt for the user in different environments, ensuring that the user can clearly hear the prompt sound even in a noisy environment. For example, if the user is jogging and the environment is relatively quiet, the volume and amplitude of the prompt sound should be appropriately lowered to avoid interfering with the user's natural auditory experience; if the user is doing high-intensity training in the gym and the ambient noise is large, the volume and amplitude should be increased to ensure that the user can clearly receive the beat prompt.

[0093] S304: If the energy density E>K, set the volume V to the maximum volume V_max. Here V represents the currently set output volume, and V_max represents the maximum volume allowed by the device. When the ambient noise exceeds the preset threshold K, in order to ensure that the user can still hear the beat cues in a high-noise environment, the system automatically sets the volume V to V_max. For example, assuming that V_max is set to 90dB, then when E exceeds 50dB, the volume V will be immediately set to 90dB to ensure the visibility and audibility of the beat cues. This step is set to cope with sudden or continuous high noise situations, to protect users from missing key beat cues due to background noise, and to prevent users from being overly disturbed in a low-noise environment.

[0094] Next, refer to Figure 4 , describing the steps of the present invention for adjusting the volume and amplitude of the rhythm prompt based on the energy density E and the user's current activity state.

[0095] S401: Determine whether the user's activity status is low-intensity or medium-intensity exercise;

[0096] S402: measuring the current background noise level L;

[0097] S403: adjusting the amplitude A of the vibration prompt based on the background noise level L;

[0098] S404: If L>M, set the amplitude A to A_max, where L represents the current background noise level, M represents the preset background noise threshold, A represents the amplitude of the vibration prompt, and A_max represents the maximum amplitude.

[0099] In the present invention, the user's activity state is first determined. This step measures the user's heart rate, cadence and acceleration through built-in sensors to determine whether the user is in a low-intensity exercise state or a medium-intensity exercise state. The user's activities at different intensities will affect the way of perceiving the beat of the music, so the way of adjusting the rhythm prompt will also be different. For example, when it is detected that the user is jogging, it is determined to be a medium-intensity exercise; when the user is walking or moving slowly, it is considered to be a low-intensity exercise. It is understandable that other criteria can also be used to determine medium-intensity exercise or low-intensity exercise.

[0100] The system then measures the current background noise level L. Background noise can come from the surrounding environment, such as the sound of traffic on the street or music in the gym. This step is done through a microphone or other noise sensor to ensure that the rhythm prompts can still be effectively conveyed to the user in a noisy environment. Specifically, if the user is in a very noisy gym, the background noise may reach a high level, such as around 70 decibels.

[0101] Based on the measured background noise level L, the next step is to adjust the amplitude A of the vibration prompt. The adjustment of the amplitude A is based on the background noise level L to ensure that the user can clearly perceive the rhythm prompt in a noisy environment. In one embodiment, if L is lower than the preset background noise threshold M, the value of A is increased linearly to adapt it to the noise level, thereby maintaining a comfortable user experience; and if L exceeds M, in order to ensure the user's safety and effective experience, A is directly set to A_max. Here, M is a critical value set based on user test data, usually between 50-60 decibels, and the optimal value is 55 decibels. A can range from 0 to 100% of the maximum amplitude, with the optimal value of 80% A_max for normal use and 100% A_max for emergency situations. The purpose of this is to ensure that rhythm prompts can be accurately received by users under various noise conditions.

[0102] For example, in one specific implementation, if the user is running in a noisy park (L = 75 dB), the system will immediately set the amplitude A to the maximum value A_max above the preset threshold M (assuming M = 55 dB). At this time, even in a noisy environment, the user can clearly feel the vibration prompt to ensure the effective operation of the music metronome. On the other hand, if the user is walking in a quiet home (L = 30 dB), the amplitude A can be adjusted to a lower level (e.g., 20% A_max) to avoid unnecessary interference.

[0103] Through these steps, the present invention can not only provide personalized music rhythm prompts, but also optimize the user experience according to actual environmental conditions, so that users can efficiently use the music metronome in various sports scenarios.

[0104] Next, refer to Figure 5 , describing the steps of adjusting the amplitude A of the vibration prompt based on the background noise level L of the present invention.

[0105] S501: Obtain the main frequency F_main of the current environmental noise. This step is completed by the acoustic sensor built into the wearable device. The sensor detects the noise in the surrounding environment in real time and analyzes the most important frequency component. For example, assuming that the background noise in the current environment is mainly caused by urban traffic, the main frequency F_main is 1000Hz.

[0106] S502: Determine whether the noise frequency is within the audible range. This step is to determine whether the main frequency of the noise will affect the user's hearing perception. Generally speaking, the audible frequency range of the human ear is 20Hz to 20,000Hz. If F_main is within this range, continue to the next step; otherwise, skip the subsequent steps and go directly to the last step. In one embodiment, if F_main is detected to be 1000Hz, which is within the audible range, proceed to the next step; if F_main is 25,000Hz, it is not within the audible range and the last step will be executed.

[0107] S503: Adjust the prompt frequency F_tip based on F_main. This step is to calculate an optimized vibration prompt frequency so that the vibration prompt will not conflict with the background noise. The specific adjustment formula can be expressed as F_tip = k*F_main+C, where k is the adjustment coefficient and C is the offset constant. The value of k is generally between 0.8 and 1.2, and the optimal value is 1.0, which means that the original frequency remains unchanged; the value of C is between -100 and 100Hz, and the optimal value is 0Hz, which means that the offset is not increased. The significance of this formula is to adjust the prompt frequency so that it varies near the main frequency of the noise, but avoids overlap, thereby improving the user experience. Specifically, if F_main is 1000Hz, F_tip can be set to 1.0*1000Hz+100Hz=1100Hz.

[0108] S504: If F_main < F_min or F_main > F_max, set F_tip to F_default. Here, F_min and F_max respectively define the minimum and maximum operating frequencies of the system, usually set as F_min = 20 Hz and F_max = 20,000 Hz. If F_main exceeds this range, it indicates that the frequency of the current background noise is not within the range supported by the system. At this time, to ensure that the user can receive a clear vibration prompt, F_tip will be set to the preset default prompt frequency F_default, such as 1000 Hz. This can ensure that the user can receive effective prompt information even in extreme environments.

[0109] Through the above steps, the wearable music metronome can provide more accurate and comfortable vibration prompts under different environmental noise conditions, enhancing the user experience.

[0110] Next, refer to Figure 6 , and specifically describe the steps of adjusting the prompt frequency F_tip based on F_main in the present invention.

[0111] S601: Calculate the main peak position P_main of the noise spectrum. In this step, it is necessary to analyze the noise spectrum in the current environment and find the main peak position P_main through spectrum analysis, that is, the frequency point with the maximum noise energy. For example, the position of the main peak can be accurately extracted through the FFT (Fast Fourier Transform) method.

[0112] S602: Determine whether the user needs to synchronize visual and sound prompts. This step involves the design of the user interface, and the user can clearly select whether to receive visual and sound prompts simultaneously through the application settings option. In one embodiment, the user checks an option in the application of the wearable music metronome to decide whether to synchronize visual and sound prompts.

[0113] S603: Select a synchronous or asynchronous prompt mode based on P_main.

[0114] S604: If the value of P_main is greater than the set threshold N, set the prompt mode to the synchronous mode; otherwise, set it to the asynchronous mode. The purpose of this step is to ensure that the prompt information will not be interfered by the noise in the environment. P_main represents the main peak position, and N represents the preset main peak position threshold. The range of P_main is usually between 20 Hz and 20,000 Hz, and the optimal value of N can be adjusted according to different usage scenarios, but it is generally recommended to be set to about 5,000 Hz. P_main > N indicates that the noise energy is concentrated in the higher frequency band, which may cause the sound prompt to be unclear. Therefore, selecting the synchronous mode can enable the user to better perceive the prompt.

[0115] For example, in a specific usage scenario, suppose the user is attending an outdoor music festival and the surrounding environment is full of noisy sounds. The wearable music metronome first analyzes the ambient noise through FFT and detects that P_main is at 6,000Hz, which is significantly greater than the preset threshold of 5,000Hz. The system determines that the noisy environment has a significant interference with the sound prompt, and automatically switches the prompt mode to the synchronous mode, so that the user can see the changes in the visual indicator light and hear the beat, ensuring that the music beat information can be effectively transmitted.

[0116] Next, refer to Figure 7 , describing the steps of selecting a suitable rhythm prompt mode based on spectrum features and activity status according to another embodiment of the present invention.

[0117] S701: Determine whether the user is currently wearing headphones. This step involves detecting whether the user is wearing headphones. This operation is completed through sensors or manual confirmation by the user to ensure that the system understands the user's current device usage status so that appropriate adjustments can be made in subsequent steps.

[0118] S702: Calculate the impact H of environmental noise on wearing headphones. This step uses audio analysis technology to measure the noise level in the environment and evaluate the impact of such noise on the sound quality of the user's headphones. H usually ranges from 0 to 100, and the larger the value, the more serious the impact of environmental noise on the headphones. The optimal value may vary depending on the actual application scenario, but it is usually set at around 50, which means that hearing will be greatly affected in this environment.

[0119] S703: Adjust the prompt mode based on the state of the user wearing headphones and H. This step combines the information of the previous two steps to determine whether the prompt mode needs to be adjusted. If the user wears headphones and the ambient noise is loud, the system may adjust the volume or switch to other prompt modes to ensure that the user can clearly receive the rhythm prompt.

[0120] S704: If H>G, set the prompt mode to vibration prompt, where H represents the impact of environmental noise on the headphones, and G represents the preset impact threshold. Here G is a preset constant value, which represents the threshold of the impact of environmental noise on the headphones. When H exceeds G, the system considers that the environmental noise is too loud and is not suitable for transmitting sound quality information through the headphones, so it switches to vibration prompt, such as the vibration generated by the built-in vibrator of the wearable device, to ensure that the user can still feel the rhythm.

[0121] For example, in one embodiment, a user is jogging in a park, wearing Bluetooth headphones and listening to music. The system detects that there is a lot of traffic noise around through the built-in microphone, and calculates H=60, while the preset threshold G=50. Therefore, the system decides to switch the prompt mode to vibration prompt. The user can still feel the clear rhythm while wearing headphones without being disturbed by the surrounding noise. This improves the user experience, allowing users to accurately follow the rhythm to exercise even in a noisy environment.

[0122] Next, refer to Figure 8 , describing the steps of the present invention based on the state of the user wearing headphones and H adjusting the prompt method.

[0123] S801: Determine whether the user is indoors;

[0124] S802: Determine whether there is other sound interference I at present;

[0125] S803: Selecting an appropriate sound or vibration prompt based on I;

[0126] S804: If I>T, the prompt mode is set to sound and vibration dual-mode prompt, where I represents the intensity of other sound interference and T represents the interference threshold.

[0127] The step of determining whether the user is indoors is achieved through sensors or the built-in positioning system of the device. When the user is detected inside a building or other closed environment, it is determined to be an indoor environment. Determining the specific environment of the user can help to better adjust the prompt method in the subsequent steps.

[0128] The step of determining whether there is other sound interference I at present involves real-time monitoring of the surrounding environmental noise. The other sound interference I here can be any non-target sound source such as background music and conversation. A microphone or other audio sensor is usually used to collect environmental noise data, and the interference intensity I is calculated through signal processing technology.

[0129] Selecting a suitable sound or vibration prompt based on I means deciding which type of prompt is more suitable based on the interference intensity I obtained in the previous step. For example, in a low-interference environment, a relatively soft sound prompt may be sufficient to achieve the purpose; whereas in a high-interference environment, a more obvious vibration prompt or a higher sound volume is required.

[0130] If I>T, set the prompt mode to dual-mode prompt of sound and vibration, that is, when the detected interference intensity I exceeds the set threshold T, the system will issue a sound prompt and a vibration prompt at the same time. This ensures that even in a noisy environment, the user can still clearly perceive the rhythm indication of the music metronome. The interference threshold T here is an important parameter that can be adjusted according to the actual application scenario. Its typical range is approximately between 30dB and 80dB, and the optimal value is generally set at around 60dB. 60dB is selected as the default T value because the noise in most life scenarios will not continue to be higher than this value, and too high a T value may cause some important prompts to be ignored.

[0131] In a specific embodiment, suppose a user is attending an indoor concert, and the live music is very loud, causing the surrounding environmental noise to reach 80dB. In this case, if the traditional single-mode sound prompt is used, it is easy to be covered by the background music, making it difficult for the user to hear the rhythm instructions. Therefore, when the system detects that the interference intensity I=80dB exceeds the preset interference threshold T=60dB, the dual-mode prompt mode will be activated. At this time, in addition to playing the beat sound normally, the small vibration motor built into the earplug will also generate a corresponding vibration frequency, so that the wearer can not only listen with the ears but also feel each beat through the skin, so as to more accurately grasp the beat rhythm of the song.

[0132] Next, refer to Fig. 9 , describing the steps of selecting appropriate sound or vibration prompts based on I of the present invention.

[0133] S901: Measure the current user's psychological state S. In this step, the system obtains the user's real-time psychological state through the built-in psychological state monitoring module. This state can be different emotional expressions such as relaxation, tension, anxiety, etc. For example, the user's psychological state can be comprehensively evaluated through physiological indicators such as heart rate and skin conductance, as well as the user's facial expressions or self-reported data.

[0134] S902: Calculate the influence coefficient C of the psychological state on the prompt method. In this step, the system calculates a value that can reflect the sensitivity of the current psychological state to the prompt method based on the pre-defined psychological state model and historical data. Specifically, the value range of C is usually between 0 and 1, 0 means that it is almost unaffected by the psychological state, and 1 means that it is very affected by the psychological state. The optimal value of the influence coefficient C depends on the specific needs and scenarios of the user, and usually needs to be determined through a large amount of experimental data. For example, if the user's psychological state is in a tense state, the value of C may be close to 1, indicating that the psychological state at this time highly affects the choice of prompt method.

[0135] S903: Select an appropriate prompting method based on S and C. According to the user's mental state S and influence coefficient C obtained from the previous two steps, the system will select the most suitable sound or vibration prompting method. For example, in one embodiment, if the user's current mental state S is a high-tension state (such as an increased heart rate) and the influence coefficient C is also close to 1, the system will tend to select a softer prompting method to avoid further aggravating the user's tension.

[0136] S904: If C*S > P, set the prompting method to vibration prompting. Here, S represents the user's mental state, C represents the influence coefficient, and P represents a preset prompting selection threshold. In this formula, the value of P is usually set to 0.7, which means that only when the product of the mental state and the influence coefficient exceeds a certain threshold will the system select vibration prompting; otherwise, it will select sound prompting. The reason for this setting is that when the user is in a relatively high-tension state, vibration prompting can attract the user's attention more effectively than sound prompting, and at the same time, it will not overly stimulate the user. In one embodiment, assume that the user's mental state S is 0.8 and the influence coefficient C is 0.9. Then C*S = 0.72, which exceeds the threshold P = 0.7. Therefore, the system selects vibration prompting to help the user better follow the rhythm. Conversely, if C*S < P, sound prompting is selected. Specifically, if the user's mental state is relatively calm, even when in a motion state, the influence coefficient may be relatively low. In this case, the system will select a gentle sound prompting to maintain the user's comfortable experience.

[0137] Next, refer to Fig.10 to further describe the steps of selecting an appropriate prompting method based on S and C in the present invention.

[0138] S1001: Determine the user's current activity duration D. This step refers to obtaining the length of time the user is currently engaged in an activity through sensors or user input. This step ensures that the system can make appropriate adjustments based on the user's actual activity duration.

[0139] S1002: Calculate the influence F of the duration on the user's comfort. Here, F is a factor that measures the influence of the activity duration on the user's mental and physical comfort. The value range of F is usually between 0 and 1, where 0 means no influence and 1 means extreme discomfort. The specific calculation of F can be determined through the user's feedback data or existing physiological psychology models, such as by combining indicators such as heart rate and muscle tension. The optimal value of F depends on the specific application scenario, but it is usually recommended to be initially set to about 0.5, indicating a medium influence level.

[0140] S1003: Select the final prompting method based on D and F. In this step, the system selects the most suitable prompting method for the user based on the duration of the user's activity and its impact on comfort. For example, if the user is doing a long dance practice and the calculated F value is high, the system may choose a softer and shorter prompting method to avoid excessively interfering with the user's movement rhythm.

[0141] S1004: If F*D>Q, set the prompt mode to intermittent prompt, where D represents the duration of the activity, F represents the impact factor, and Q represents the comfort threshold. The value range of Q is usually between 1 and 100. The optimal value depends on the specific user experience test results. It is usually recommended to set it to 50 initially. The meaning of the formula is to compare the product of the activity duration and the comfort impact degree with the comfort threshold. If it exceeds the threshold, it is considered that the current prompt mode may have a negative impact on the user experience and should be changed to intermittent prompt to reduce the user's discomfort.

[0142] For example, in one embodiment, a user is using a wearable music metronome for dance practice, and the system's sensors record that the current activity duration is 30 minutes (D=30). The impact factor F is calculated to be 0.7 through the user's real-time heart rate data. The comfort threshold Q is set to 50. At this time, it is calculated that F*D=0.7*30=21, which is less than the threshold of 50, so the system will continue to use a continuous prompting method. However, if the user's practice time is extended to 100 minutes (D=100), F remains unchanged at 0.7, and it is calculated that F*D=0.7*100=70, which exceeds the threshold of 50. At this time, the system will automatically adjust to intermittent prompts, playing a rhythm reminder every 5 minutes to prevent the user from feeling tired or distracted.

[0143] Through the above steps, the system can dynamically adjust the prompt mode under different activity conditions, thereby improving the user experience and maintaining efficient music beat synchronization.

[0144] A wearable music metronome provided by an embodiment of the present disclosure includes a sensor, a processor, and an output device, wherein the sensor obtains environmental noise data and a user's current activity state; the processor determines the mode and intensity of rhythm prompts based on the environmental noise data and the user's current activity state; selects a corresponding output device according to the determined rhythm prompt mode; and adjusts the parameters of the output device to match the determined rhythm prompt intensity. Through the solution of the embodiment of the present disclosure, it is possible to solve how to provide rhythm prompts according to different environmental conditions.

[0145] The methods, programs, systems, devices, etc. of the embodiments of the present invention may be executed or implemented in a single or multiple networked computers, or may be practiced in a distributed computing environment. In the embodiments of this specification, in these distributed computing environments, tasks may be performed by remote processing devices connected via a communication network.

[0146] Those skilled in the art should understand that the embodiments of the present specification may be provided as methods, systems or computer program products. Therefore, those skilled in the art may imagine that the functional modules / units or controllers and related method steps described in the above embodiments may be implemented in software, hardware or a combination of software / hardware.

[0147] Unless explicitly stated, the actions or steps of the methods, programs, and embodiments of the present invention do not have to be performed in a specific order and can still achieve the desired results. In some implementations, multitasking and parallel processing are also possible or may be advantageous.

[0148] In this article, multiple embodiments of the present invention are described, but for the sake of brevity, the description of each embodiment is not exhaustive, and the same or similar features or parts between the embodiments may be omitted. In this article, "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" are meant to be applicable to at least one embodiment or example according to the present invention, but not all embodiments. The above terms do not necessarily mean to refer to the same embodiment or example. In the absence of contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples.

[0149] The exemplary systems and methods of the present invention have been specifically shown and described with reference to the above embodiments, which are merely examples of the best modes for implementing the present systems and methods. It will be appreciated by those skilled in the art that various changes may be made to the embodiments of the systems and methods described herein when implementing the present systems and / or methods without departing from the spirit and scope of the present invention as defined in the appended claims.

Claims

1. A wearable music metronome, comprising a sensor (1101), a processor (1102) and an output device (1103), characterized in that: The sensor (1101) acquires environmental noise data and the user's current activity state; The processor (1102) determines the manner and intensity of rhythm prompts based on the environmental noise data and the user's current activity state; Selects a corresponding output device (1103) according to the determined rhythm prompt manner; And Adjusts the parameters of the output device to match the determined rhythm prompt intensity.

2. A wearable music metronome according to claim 1, characterized in that: The step of determining the manner and intensity of rhythm prompts based on the environmental noise data and the user's current activity state further includes: Analyzing the spectral characteristics of environmental noise; Judging whether the user's current activity is high-intensity exercise; Selecting a suitable rhythm prompt mode based on the spectral characteristics and activity state; If the user's activity state is stationary, set the frequency of the rhythm prompt to f = 1, where f represents the frequency of the rhythm prompt.

3. A wearable music metronome according to claim 2, characterized in that: The step of selecting a suitable rhythm prompt mode based on the spectral characteristics and activity state further includes: Calculating the energy density E of environmental noise; Judging whether the user is in a noisy environment; Adjusting the volume and amplitude of the rhythm prompt based on the energy density E and the user's current activity state; If the energy density E > K, set the volume V to the maximum volume V_max, where E represents the energy density of environmental noise, K represents a preset energy density threshold, V represents the output volume, and V_max represents the maximum volume.

4. A wearable music metronome according to claim 3, characterized in that: The step of adjusting the volume and amplitude of the rhythm prompt based on the energy density E and the user's current activity state further includes: Determining whether the user's activity state is low-intensity or medium-intensity exercise; Measuring the current background noise level L; Adjusting the amplitude A of the vibration prompt based on the background noise level L; If L > M, set the amplitude A to A_max, where L represents the current background noise level, M represents a preset background noise threshold, A represents the amplitude of the vibration prompt, and A_max represents the maximum amplitude.

5. A wearable music metronome according to claim 4, characterized in that: The step of adjusting the amplitude A of the vibration prompt based on the background noise level L further includes: Obtaining the main frequency F_main of the current environmental noise; Judging whether the noise frequency is within the audible range; Adjusting the prompt frequency F_tip based on F_main; If F_main < F_min or F_main > F_max, set F_tip to F_default, where F_main represents the main frequency, F_min represents the minimum frequency, F_max represents the maximum frequency, and F_default represents the default prompt frequency.

6. A wearable music metronome according to claim 5, characterized in that: The step of adjusting the prompt frequency F_tip based on F_main further includes: Calculating the main peak position P_main of the noise spectrum; Determining whether the user needs to synchronize visual and sound prompts; Selecting a synchronous or asynchronous prompt mode based on P_main; If P_main is greater than the threshold N, set the prompt mode to the synchronous mode, where P_main represents the main peak position and N represents the main peak position threshold.

7. A wearable music metronome according to claim 2, characterized in that: The step of selecting a suitable rhythm prompt mode based on the spectrum characteristics and the activity state further includes: Determine whether the user is currently wearing headphones; Calculate the impact of environmental noise on wearing headphones H; Adjust the prompt mode based on the user's headset status and H; If H>G, the prompt mode is set to vibration prompt, where H represents the impact of environmental noise on wearing headphones, and G represents the preset impact threshold.

8. A wearable music metronome according to claim 7, characterized in that: The step of adjusting the prompt mode based on the state of the user wearing the headset and H further includes: Determine whether the user is indoors; Determine if there is any other sound interference I; Select appropriate sound or vibration prompt based on I; If I>T, the prompt mode is set to dual-mode prompt of sound and vibration, where I represents the intensity of other sound interference and T represents the interference threshold.

9. A wearable music metronome according to claim 8, characterized in that: The step of selecting a suitable sound or vibration prompt based on I further includes: Measure the current user psychological state S; Calculate the coefficient C of the influence of psychological state on the prompt mode; Choose the appropriate prompt method based on S and C; If C*S>P, the prompt mode is set to vibration prompt, where S represents the user's psychological state, C represents the influence coefficient, and P represents the preset prompt selection threshold.

10. A wearable music metronome according to claim 9, characterized in that: The step of selecting a suitable prompting method based on S and C further includes: Determine the user's current activity duration D; Calculate the impact of duration on user comfort F; Select the final prompt method based on D and F; If F*D>Q, set the prompt mode to intermittent prompt, where D represents the activity duration, F represents the influence factor, and Q represents the comfort threshold.

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