Wearable music device with volume reward
The wearable music device uses bioelectric signal analysis to adjust audio volume based on mental status, addressing the need for constant monitoring in existing systems, improving relaxation, focus, and sleep quality.
Patent Information
- Application Number
- PCT/CN2024/084449
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2024-03-28
- Publication Date
- 2025-10-02
AI Technical Summary
Existing music systems that adjust emotions based on user preferences or EEG technology require users to constantly monitor their mental status through apps, disrupting relaxation and mental perception.
A wearable music device that uses bioelectric signal acquisition via electrodes to analyze mental status through machine learning, adjusting audio volume to reward mental states without requiring constant user attention.
Provides real-time, interactive mental status adjustment through volume changes, allowing users to improve relaxation, focus, and sleep quality without needing to monitor app displays, thus enhancing mental wellness and healthiness.
Smart Images

Figure CN2024084449_02102025_PF_FP_ABST
Abstract
Description
WEARABLE MUSIC DEVICE WITH VOLUME REWARDTECHNICAL FIELD
[0001] The present inventive subject matter relates generally to a wearable device. More particularly, the present inventive subject matter relates to a wearable music device and method capable of adjusting mental status through volume reward.BACKGROUND
[0002] With accelerating of people’s life pace, the pressure of life is increasing, and people’s mental health is getting more and more attention. At the same time, music becomes one of the most popular enjoyable entertainments for almost everyone. It can improve the mental health of users through interactive design with users. The existing systems and methods for music to adjust people’s emotions are mainly based on people’s preferences to select their existing favorite music to adjust emotions. Some music products with the electroencephalography (EEG) technology and music function may also be found in the market, but those products mainly rely on APPs to display users’ general emotional level. The users always need to stare at the APP displays for a long time, in which the APPs may show their continuous mental status, which significantly affects users’ mental perceptions, especially when the users would like to take a rest or close their eyes to enjoy the psychological adjustment.
[0003] Therefore, there is a need to provide a music interactive product through which, the users may learn to take care of their own mental status, consciously exercise, improve and keep their good inner status, improve on their relaxation, focus, fatigue status, etc., and further may help them on going to sleep and improve their sleep quality, under the help of such interactive design.
[0004] SUMMARY OF THE INVENTIVE SUBJECT MATTER
[0005] In order to overcome the shortcomings and deficiencies in the prior art, the purpose of the inventive subject matter is to provide a wearable music device capable of adjusting mental status of person using his / her own bioelectric signals to generate volume rewards for adjusting mental status.
[0006] In one aspect, a wearable music device capable of adjusting mental status through volume reward is provided. The wearable music device comprises a bioelectric data acquiring module which is configured to acquire bioelectric signals via electrodes arranged in the wearable music device and adhered to human scalp and convert the acquired bioelectric signals to real-time bioelectric data. The bioelectric data acquiring module further feeds the real-time bioelectric data to a mental state analysis module, whereby performs analysis of real-time mental status through a machine learning algorithm. The wearable music device further comprises a volume reward module which is configured to adjust volume of an audio signal received from a user device, based on the real-time mental status from the mental state analysis module. The audio signal can be playback by at least one speaker arranged in the wearable music device according to the adjusted volume by the volume reward module.
[0007] In another aspect, a method capable of adjusting mental status through volume reward of a wearable music device is provided. The method comprises steps of acquiring bioelectric signals and converting the acquired bioelectric signals to real-time bioelectric data by a bioelectric data acquiring module. Then, the bioelectric data acquiring module feeds the real-time bioelectric data to a mental state analysis module, whereby performing analysis of real-time mental status through a machine learning algorithm. The method comprises steps of adjusting volume of an audio signal received from a user device by a volume reward module, based on the real-time mental status from the mental state analysis module, and the audio signal can be playback by at least one speaker arranged in the wearable music device according to the adjusted volume by the volume reward module.
[0008] In yet another aspect, a non-transitory computer readable medium storing instruction is provided which, when executed by one or more processors, cause the one or more processor to perform the above method capable of adjusting mental status through volume reward of a wearable music device.BRIEF DESCRIPTION OF THE DRAWINGS
[0009] The present inventive subject matter may be better understood from reading the following description of non-limiting embodiments, with reference to the attached drawings. In the figures, like reference numeral designates corresponding parts, wherein below:
[0010] FIG. 1 illustrates an exemplary block diagram 100 of a wearable music device capable of adjusting mental status by generating volume rewards based on a user’s bioelectric signal, according to one or more embodiments of the present inventive subject matter;
[0011] FIG. 2 illustrates an exemplary flowchart 200 of a method capable of adjusting mental status by generating volume rewards based on a user’s bioelectric signal, according to one or more embodiments of the present inventive subject matter;
[0012] FIG. 3 illustrates an exemplary schematic diagram 300 of a user interface (UI) of the corresponding APP for enabling and setting the volume reward function, according to one or more embodiments of the present invention subject matter; and
[0013] FIG. 4A and FIG. 4B illustrate exemplary diagrams for comparation of mental status curves 400, 410 of a tester using the wearable music device with the volume reward function enabled and disabled, respectively, according to one or more embodiments of the present inventive subject matter.DETAILED DESCRIPTION
[0014] The detailed description of the one or more embodiments of the present inventive subject matter is disclosed hereinafter; however, it is understood that the disclosed embodiments are merely exemplary of the inventive subject matter that may be embodied in various and alternative forms. The figures are not necessarily to scale; some features may be exaggerated or minimized to show details of particular components. Therefore, specific structural and function details disclosed herein are not to be interpreted as limiting, but merely as a representative basis for teaching one skilled in the art to variously employ the present inventive subject matter.
[0015] FIG. 1 illustrates an exemplary block diagram 100 of a wearable music device 110 capable of adjusting mental status by generating volume reward based on a bioelectric signal acquired from a user 120, according to one or more embodiments of the present inventive subject matter. The wearable music device 110 can be in the form of such as a music belt, a pair of TWS, or a headphone, etc., and can be worn by a user 120 on head, for example. As shown in FIG. 1, the wearable music device 110 may comprise a bioelectric data acquiring module 112, a mental status analysis module 114, a volume reward module 116 and at least one speaker 118.
[0016] The bioelectric data acquiring module 112 may be connected with at least one bioelectric acquiring sensor with electrodes (not shown) to acquire bioelectric signals 122 of the user 120. As many scientific researches have shown that human brainwave signals may be strongly correlated with their cognitive behaviors and mental activities, the EEG signals can be acquired by applying EEG electrodes to the user 120, such as, placing the EEG electrodes on the user’s scalp. The acquired EEG signals may be processed and converted into bioelectric data 124 reflecting human’s real-time mental status. In this way, the electrodes connecting with the bioelectric data acquiring module 112 are placed on the user’s scalp according to certain rules to acquire, for example, brainwave EEG signals, which can be used to detect unconscious brain activity, so as to observe the process of brainwave activity.
[0017] In another example, the bioelectric data acquiring module 112 may be configured to collect PPG (photoplethysmography) signals to monitor the change of human pulse. A physiological sign HRV (heart rate variability) derived from the PPG signals can be considered as a reflection of people’s psychological stress level. In the example, the user 120 may wears one or more photoelectric sensors at such places with high blood perfusion values of human body, so as to calculate the trend of the HR (heart rate) and HRV index by collecting a fluctuation signal in arterial blood. The PPG can be combined with the EEG signals and converted to the bioelectric data of the user 120 wearing the wearable music device 110, so as to estimate his / her blood oxygen saturation and other physiological indicators, which reflects the real-time mental status thereof.
[0018] Those bioelectric data 124 of the user 120 collected in the bioelectric data acquiring module 112 can be fed to the mental status analysis module 114 for analyzing and evaluating the user’s mental status. This mental status analysis module 114 can be implemented with a machine learning algorithm. For example, the machine learning algorithm, such as a self-built machine learning model or a well-trained neural network, in the mental status analysis module 114 may classify and analyze the bioelectric data 124 of the users 120 fed therein, and then outputs quantitative analysis results reflecting mental status for each of mental status modes, that is, the mental status values 126.
[0019] In one or more embodiments of the inventive subject matter, the mental status analysis module 114 outputs results reflecting the user’s mental status in aspects such as relaxation, focus, engagement, fatigue / drowsiness or the like. In some examples, the results of the mental status analysis may reflect the user’s sleep stage and sleep quality, etc., which thus can be further used in a way to solve the mental fatigue.
[0020] Next, in the volume reward module 116, based on the mental status values 126 reflecting the user’s current status, which are received from the mental status analysis module 114, the volume reward module 116 may automatically adjust the volume reward 128 of the music 132 playback in the speaker 118. The user 120 listens to the music 132 in the speaker 118 and interactively feeds back his / her bioelectric signals 122 to the volume reward 128 of the music 132 while adjusting the mental status. The mental status is the one selected from several aspects of Relaxation, Focus, Engagement, Fatigue / Drowsiness or the like. The volume rewarded music 132 played in the speaker 118 may be a music 134, a song, and the like, streamed from an audio player on a user device 130, via a wireless connection, such as Bluetooth, WIFI, and the like, for example. In the example, the user 120 may choose his / her favorite music or song to play, or the music or song can be pushed to a preset music playlist by the network according to the selected mental status to be adjusted. Therefore, the final output volume of the music 132 contains the real-time information of the selected mental status mode, and now the user can not only listen to the music 132, but also obtain his / her real-time mental status information.
[0021] The wearable music device 110 can be with the volume reward function enabled / disabled 136 by the user 120 using, for example, an applicable APP installed in the user device 130. When the volume reward function is enabled, and once the user finishes a music 132 playback, there will be a recording report 138 about the selected mental status mode of the user 120 during the listening of the music 132. The user 120 may review the recording report 138 from the APP displays on the user device 130.
[0022] FIG. 2 illustrates an exemplary flowchart of a method capable of adjusting mental status by generating volume reward based on a user’s bioelectric signal, according to one or more embodiments of the present inventive subject matter. At first, in step S210, the user wears the wearable music device, and electrodes of the bioelectric sensor (s) on the wearable music device can be placed properly on the user. In an example, for the wearable music device in form of a headband, the user can wear it on the head and place the EEG electrodes on his / her scalp. In another example, for the wearable music device in form of a pair of TWS, the user can wear them on the ears, and enable PPG sensors to collect PPG signals at the auricle, while the EEG electrodes may be also easily applied on the scalp to acquire EEG signals.
[0023] The user may select the music or song he / she would like to listen to on the user device, and start playing it on the speaker in the wearable music device. In step S220, when the user wants to adjust his / her mental status, he / she can enable the volume reward function through the user interface on the user device. For example, referring to FIG. 3, the user can turn on the volume reward function by sliding the volume reward on / off button 310 on the APP interface 300. Then, he / she can get the music output volume adjusted by the volume reward module, while the music output volume contains the real-time information on the selected mental status mode.
[0024] In step S230, the user may set up a maximum volume for the volume reward process. The rewarded volume will not exceed the maximum volume. The final output volume will be modulated based on the MAX volume, which will contain the mental status information of the mental status selected in the following step. In way of an example, with a normal highest volume level of 10, when the user wants to relax while closing eyes, the MAX volume can be set relatively high, such as at 9 or 10; when the user wants to increase their focus through volume reward while working or writing, the MAX volume may be set not too high, such as at 8. In yet another example, when the user wants to assist with sleep, the MAX volume can be set to be slightly lower, such as at 6.
[0025] The user may select any of the various mental-status modes, and then enjoy the emotional regulation brought by the music with adjusting its volume reward for such mental status. In step S240, the user can select the mode of mental status to adjust by entering the corresponding user interface on the user device. In one example, the user at present may be willing to adjust and relax his / her mental status and currently under the “Relaxation” mode, and the music volume is positively related with the real-time status value of the “Relaxation” according to a machine-internal requirement and configuration, when the user select and enter into the “Relaxation” menu. Thus, the user can get real-time feedback on his / her “Relaxation” via the volume output being heard. The calmer, the larger music volume can be heard, the better immersed experience will come.
[0026] The mental status values from the mental status analysis results can be defined in a specific value range from 0 to 100, for example. Lower mental status values indicate poorer mental status, while higher mental status values indicate better mental status. For example, the mental status analysis module may output the mental status value of 52 for the “Engagement” status. Moreover, the mental status analysis module may output a mental status value of 53 for “Focus” , and of 53 for “Relaxation” status. These results of values are approximated to a median value of 50 of the specific value range of 0-100, indicating that the mental status for the corresponding aspect is at a medium level. In the example, the mental state analysis module may output the mental status value of 26 for “Fatigue” , which is lower than the median value of 50, indicating that the user’s current mental status for “Fatigue” is relatively mild, and the user feels refreshed at the moment.
[0027] On one hand, in step S250, the mental status values derived by the mental status analysis module may be assessed by, for example, comparing it with the median value of its value range. The volume reward mechanism may be different depending on whether the mental status value is lower or higher than the median value. When the real-time Mental status value is lower the median value, which is considered as Low “Mental Status Value” , indicating that the mental status of such mode is poor. In this case, a larger proportion of volume reward may be applied to achieve a certain improvement in the mental status, such as shown in step S250, and the volume reward will be more obvious for the user to learn and improve the mental status mode easily.
[0028] For example, the user will hear the final music volume output which is positively related with the real-time mental status values of “Engagement” according to the machine-internal requirement and configuration, when user enters into the “Engagement” menu. Thus, the user can get real-time feedback on his / her “Engagement” via the volume output being heard. With more engagement, the larger music volume will be heard, the better immersed experience will come. And the volume reward mechanism may be different based on the mental status values on “Engagement” is assessed as lower or higher than the medium value. As previously noted, when the real-time “Engagement” status value is lower than the median value and is considered as Low “Mental Status Value” , the volume reward will be more obvious for the user to learn and improve the “Engagement” easily. In this case, a larger proportion of volume reward may be applied to achieve a certain improvement in the mental status. For example, a volume reward turning up from 3 to 6 can be applied to attempt to increase a current mental status value for the “Engagement” mode from 40 to 41, that is, the volume reward is raised by 3 to improve the mental status value by 1.
[0029] On the other hand, when the real-time mental status value is higher than the median value, which is considered as High “Mental Status Value” , the volume reward will be in less obvious, for the user to learn and improve the mental status mode gently. In this case, a smaller proportion of volume reward may be applied to achieve the certain improvement in the mental status, such as shown in step S260.
[0030] For example, the user may want to adjust his / her mental status of “Focus” . Under the selected “Focus” mode, the music volume output is positively related with the real-time mental status value of the “Focus” mode according to the machine-internal requirement and configuration, when user enters into the “Focus” menu. Thus, the user can get real-time feedback on his / her “Focus” mental status via the volume output heard. With more concentration, the larger music volume will be heard, the better immersed experience will come. And the volume reward mechanism will be different when the mental status value for “Focus” is now higher from lower than the median value. When the real-time mental status value for “Focus” is higher than the median value, which is considered as High “Mental Status Value” , the volume reward will be less obvious for the user to study and improve the “Focus” gently. In this case, a smaller proportion of volume reward may be applied to achieve the certain improvement in the mental status. For example, a volume reward turning up from 6 to 6.5 can be applied to attempt to increase a current mental status value for the mode from 52 to 53, that is, the volume reward is raised by 0.5 to improve the mental status value by 1.
[0031] In contrast, in an example, the user will hear the final music volume output, which is negatively related with the mental status value of the selected “Fatigue” mode according to the machine-internal requirement and configuration, when user enters into the “Fatigue (Relieving) ” menu. Thus, the user can get quick feedback on his / her “Fatigue” status via the volume output being heard. With more concentration, the more relieving on fatigue, with the Lower “Mental Status Value” for fatigue / drowsiness, the larger music volume user will hear. The larger output volume gets, the better immersed experience will come, and it is telling the user that he / she is more attentive and with less fatigue. Then, the volume reward mechanism will be less obvious, which means that a smaller proportion of volume reward may be applied to achieve the certain improvement in the mental status, when the real-time mental status value for “Fatigue” lower than the median value as the better fatigue relieved.
[0032] In summary, in the wearable music device provided in the inventive subject matter, the mental status may be adjusted through the music volume reward. When the real-time mental status is poor, the volume reward module adjusts the volume reward in a larger proportion, and the volume reward mechanism will be more obvious; And when the real-time mental status is good, the volume reward module adjusts the volume reward in a smaller proportion, and the volume reward mechanism will be less obvious. And, in step S270, the user may finally get continuous music with rewarded volume output.
[0033] Additional or alternatively, the user can further select a different volume reward mode for “Fatigue / Drowsiness” mental status, allowing him / her to achieve a different purpose when using this wearable music device. In one example for encouraging and helping the user change his / her mental status to be falling asleep easily, the volume reward mechanism may become more obvious with the mental status value of “Fatigue / Drowsiness” continues to rise. For example, when the “Drowsiness” value is getting higher than 70, it is considered as High “Mental Status Value” indicating the user is extremely drowsy. At this time, the volume reward mechanism may lower the output volume of the music to a noticeably softer level. Additional or alternatively, when the acquired bioelectric data detects that the user has fallen asleep, the music playback can be automatically cut off to complete the sleep assistance.
[0034] During the implementation of the abovesaid volume reward function, the user’s mental status can be adjusted in the Volume reward module according to the user’s settings. These settings can be entered or selected by the user while operating the APP on a user device which, for example, may be connected to the wearable music device via a wire or wireless connection. The user device may comprise but are not limited to a smart phone, a PAD, a personal computer, etc. A corresponding APP applicable for the wearable music device provided in the inventive subject matter can be installed on the user device, and the user may setup the desired mental or emotional mode to be adjusted on the user device through a user interface (IU) .
[0035] In a traditional UI, there may be a status bar for the user to find the real-time status. The user who would like to know the value of the real-time relaxation, or say how relaxed he or she is, needs to carefully and continuously stare at the changes on the status bar displayed on the APP. This continuous action may be unfriendly or even contrary to the purpose of relaxation. Usually, when a user wants to relax, he or she would be simply relaxed, or even closes the eyes. Therefore, this UI design may be unfriendly to users or to a large extent hinder their relaxation, which thus may affect the user’s experience.
[0036] FIG. 3 illustrates an exemplary schematic diagram 300 of a user interface (UI) of the corresponding APP for enabling and setting the volume reward function, according to one or more embodiments of the present invention subject matter. In the example as shown in FIG. 3, after the user enabled the volume reward function by sliding the on / off button 310, and selected and entered into the interface for “Focus” mode 320, the volume of the music heard by the user can be automatically adjusted by the volume reward module and output to the user via the at least one speaker arranged in the wearable music device. The volume may reflect real-time information of the selected “Focus” mental status of the user, continuously. And the user may like to exercise how to become relaxed, and also user would like to know how relaxed he can become.
[0037] At the same time, the APP may still have real-time status bars 330 for the selected mental status modes, so that the user can easily review the status displayed thereon for a short time. As shown in FIG. 3, these status bars 330 allow the user to easily observe his / her current mental status with a glance.
[0038] Once the user finishes the music playing, there will be a recording report on the selected mental status mode of the user during the listening of the music, the user can compare their subjective feelings with the report for recalling and summarizing. The user can further find if his / her mental status has been improved or not by checking the history report.
[0039] Because the user now can get a very direct and real-time feedback on his / her mental status selected from the final music output, the user can consciously take care on how to exercise and improve his / her mental status, for example, the user can exercise to improve the “Focus” , the user can exercise on working, on writing, and on reading, etc., attentively to improve his” Focus” , but don’t need to watch the APP frequently to see the real-time value or trend for his inner mental status.
[0040] Due to the user can always get direct or quick feedback so freely from the final music output, then user will know he or she is on the right way or not to exercise himself for inner “Focused” , or inner “Relaxed” , etc. Then the user can adjust him / herself easily and find his / her own way to keep a good mental status. Such volume reward Design can largely improve the actual function for such wearable music device, user can easily and freely to exercise, and keep on his / her good mental status and thus improve the mental wellness and healthiness.
[0041] FIG. 4A and FIG. 4B illustrate exemplary diagrams for comparation of mental status curves 400, 410 of a tester using the wearable music device with the volume reward function enabled and disabled, respectively, according to one or more embodiments of the present inventive subject matter. Firstly, a tester wearing the wearable music device attempts to write attentively with the music on, and with the volume reward function enabled. The final volume output may contain the information of his / her real-time “Focus” mental status. So, the tester does not look at the APP to see his / her real-time “Focus” value frequently. The “Focus” tested mental status values are almost all higher than the median value of 50 (the median level of the mental status indicating by the dotted line) , as shown in FIG. 4A. From the test results we can see that the tester is attentive and quieter, and less distractive, which is very good for the Focus exercising.
[0042] In contrast, the tester wearing the wearable music device attempts to write attentively with the music on, but with the volume reward function disabled. Thus, the final volume output does not contain any information of mental status. In this case, the tester frequently looks at the APP to see his / her real-time Focus values. The Focus test values fall to below 50 as the tester frequently looks at the APP, as shown by the curve segment between the durations marked as 420 in FIG. 4B, and the overall Focus values are generally lower than the previous test with the volume reward enabled. It can be seen from the test results that the tester is less attentive and less quiet, and more distractive, which is not good for the Focus exercising.
[0043] The wearable music device provided herein, for example, a music belt, true-wireless earbud or headphone, etc., is not only a music speaker, but also an interactive product, through which users can learn to take care their inner mental status, consciously exercise, improve and keep in their good inner status, and can improve on their relaxation, focus, fatigue status, etc., and also help them on going to sleep, and improve their sleep quality, under the help of such interactive design with user on APP.
[0044] The wearable music device emphatically defines an intelligent and interactive volume reward function capable of adjusting mental status. The volume reward function defines the relationship between the system final output volume and the users’ brainwave status, for example “relaxation” , “focus” , etc., through which, gives users a direct and real-time feedback on their cognitive and mental status. Users can release their eyes, don’ t need always to watch the APP with the help of this design, and still get the feedback for their inner mental status. Thus, the users can get an immersive experience, and easily form a good habit to exercise and keep their good inner mental status which they want, while listening to the loved music, thus, to improve their mental wellness and healthiness, and benefit largely from the device.
[0045] The wearable music device needs both wireless music playback design, and cooperating with the bioelectric data acquiring technology, such as brainwave EEG, PPG, and the two integrated. Especially, it aims for a friendly and easy interactive design where users may enjoy music, but further to the users, it can detect the users’ real-time bioelectric data, and translate into the users’ instant cognitive and mental status, such as the real-time relaxation of user, the real-time focus of user, the fatigue of user, etc. And then most important, and most meaningful, the device can not only give users an insight on their real-time inner mental status, but also can give users continuous and interactive guide on improvement and keep of their good inner status for mental wellness and healthiness.
[0046] In the foregoing specification, the inventive subject matter has been described with reference to specific embodiments thereof. It will, however, be evident that various modifications and changes may be made thereto without departing from the broader scope of the invention. For example, the above-described process flows are described with reference to a particular ordering of process actions. However, the ordering of many of the described process actions may be changed without affecting the scope or operation of the invention. The specification and drawings are, accordingly, to be regarded in an illustrative rather than restrictive sense.
[0047] As used in the disclosure, an element or step listed in the singular form and preceded by the word “one / a” should be understood as not excluding a plurality of said elements or steps, unless such exception is specifically stated. Furthermore, references to “embodiments” or “examples” of the disclosure are not intended to be construed as exclusive, also including the existence of other embodiments of the recited features. The terms “first” , “second” , “third” , etc. are used only for identification and are not intended to emphasize a numerical requirement or positioning order of their objects.
[0048] References in the present inventive subject matter to the system for verifying rechargeable battery encryption in electronic apparatus and the method thereof include the following content:
[0049] Item 1: In one or more embodiments, the present inventive subject matter provides a wearable music device capable of adjusting mental status with volume reward, comprising:
[0050] a bioelectric data acquiring module configured to acquire bioelectric signals and convert them to real-time bioelectric data;
[0051] a mental state analysis module configured to receive the real-time bioelectric data and perform analysis of real-time mental status through a machine learning algorithm;
[0052] a volume reward module configured to adjust volume of an audio signal received from a user device, based on the real-time mental status from the mental state analysis module; and
[0053] at least one speaker configured to playback the audio signal based on the adjusted volume by the volume reward module.
[0054] Item 2: The wearable music device of item 1, wherein the bioelectric signals comprise EEG signals, and wherein the bioelectric signals further comprise PPG signals.
[0055] Item 3: The wearable music device of item 1 or 2, wherein the analysis of the real-time mental status in the mental state analysis module comprises calculating real-time mental status values for each of mental status modes, wherein the real-time mental state values are in a specific value range, and wherein a corresponding mental state is associated with the real-time mental state values within the specific value range and larger real-time mental state values correspond to a better mental state.
[0056] Item 4. The wearable music device of any of items 1 to 3, wherein the mental status modes comprise at least one of Relaxation, Focus, Engagement, Fatigue or Drowsiness.
[0057] Item 5. The wearable music device of any of items 1 to 4, wherein the volume reward module adjusts the maximum output volume of the device based on user settings.
[0058] Item 6. The wearable music device of any of items 1 to 5, wherein:
[0059] the volume of the audio signal is adjusted positively related with the real-time mental status values for any mental status mode of Relaxation, Focus or Engagement; and
[0060] the volume of the audio signal is adjusted negatively related with the real-time mental status values for any mental status mode of Fatigue or Drowsiness.
[0061] Item 7. The wearable music device of any of items 1 to 6, wherein:
[0062] when the real-time mental status is good, a smaller proportion of volume reward may be applied to achieve a certain improvement for the mental status mode; and
[0063] when the real-time mental status is poor, a larger proportion of volume reward may be applied to achieve a certain improvement for the mental status mode.
[0064] Item 8. The wearable music device of any of items 1 to 7, wherein:
[0065] the real-time mental status is good when the real-time mental status value is higher than a median value of the specific value range; and
[0066] when the real-time mental status is poor when the real-time mental status value is lower than the median value of the specific value range.
[0067] Item 9. The wearable music device of any of items 1 to 8, wherein in a sleep assistance for a user, the volume of the audio signal is adjusted in the mental status mode of drowsiness, and the audio signal is cut off when the bioelectric data detects, in real time, that the user has fallen in sleep.
[0068] Item 10. The wearable music device of any of items 1 to 9, wherein the wearable music device comprises at least one of a music belt, a pair of TWS or a headphone.
[0069] Item 11: In one or more embodiments, the present inventive subject matter provides a method capable of adjusting mental status through volume reward of a wearable music device, comprising following steps of:
[0070] acquiring, by a bioelectric data acquiring module, bioelectric signals and converting them to real-time bioelectric data;
[0071] receiving, by a mental state analysis module, the real-time bioelectric data, and performing analysis of real-time mental status through a machine learning algorithm;
[0072] adjusting, by a volume reward module, volume of an audio signal received from a user device, based on the real-time mental status from the mental state analysis module; and
[0073] playback, by at least one speaker, the audio signal based on the adjusted volume by the volume reward module.
[0074] Item 12: The method of item 11, wherein the bioelectric signals comprise EEG signals, and wherein the bioelectric signals further comprise PPG signals.
[0075] Item 13: The method of item 11 or 12, wherein the analysis of the real-time mental status in the mental state analysis module comprises calculating real-time mental status values for each of mental status modes, wherein the real-time mental state values are in a specific value range, and wherein a corresponding mental state is associated with the real-time mental state values within larger the real-time mental state values within the specific value range correspond with a better mental state.
[0076] Item 14: The method of any of items 11-13, wherein the mental status modes comprise at least one of Relaxation, Focus, Engagement, Fatigue or Drowsiness.
[0077] Item 15: The method of any of items 11-14, wherein the volume reward module adjusts the maximum output volume of the device based on user settings.
[0078] Item 16: The method of any of items 11-15, wherein:
[0079] the volume of the audio signal is adjusted positively related with the real-time mental status values for any mental status mode of Relaxation, Focus or Engagement; and
[0080] the volume of the audio signal is adjusted negatively related with the real-time mental status values for any mental status mode of Fatigue or Drowsiness.
[0081] Item 17: The method of any of items 11-16, wherein:
[0082] when the real-time mental status is good, a smaller proportion of volume reward may be applied to achieve a certain improvement for the mental status mode; and
[0083] when the real-time mental status is poor, a larger proportion of volume reward may be applied to achieve a certain improvement for the mental status mode.
[0084] Item 18: The method of any of items 11-17, wherein:
[0085] the real-time mental status is good when the real-time mental status value is higher than a median value of the specific value range; and
[0086] when the real-time mental status is poor when the real-time mental status value is lower than the median value of the specific value range.
[0087] Item 19: The method of any of items 11-18, wherein in a sleep assistance for a user, the volume of the audio signal is adjusted in the mental status mode of drowsiness, and the audio signal is cut off when the bioelectric data detects, in real-time, that the user has fallen in sleep.
[0088] Item 20: The method of any of items 11-19, wherein the wearable music device comprises at least one of a music belt, a pair of TWS or a headphone.
[0089] Item 21: In one or more embodiments, the present inventive subject matter provides a non-transitory computer readable medium storing instruction that, when executed by one or more processors, cause the one or more processor to perform the method according to any of items 11-20.
Claims
1.A wearable music device capable of adjusting mental status with volume reward, comprising:a bioelectric data acquiring module configured to acquire bioelectric signals and convert them to real-time bioelectric data;a mental state analysis module configured to receive the real-time bioelectric data and perform analysis of real-time mental status through a machine learning algorithm;a volume reward module configured to adjust volume of an audio signal received from a user device, based on the real-time mental status from the mental state analysis module; andat least one speaker configured to playback the audio signal based on the adjusted volume by the volume reward module.2.The wearable music device according to claim 1, wherein the bioelectric signals comprise EEG signals, and wherein the bioelectric signals further comprise PPG signals.3.The wearable music device according to claim 1, wherein the analysis of the real-time mental status in the mental state analysis module comprises calculating real-time mental status values for each of mental status modes, wherein the real-time mental state values are in a specific value range, and wherein a corresponding mental state is associated with the real-time mental state values within the specific value range and larger real-time mental state values correspond to a better mental state.4.The wearable music device according to claim 3, wherein the mental status modes comprise at least one of Relaxation, Focus, Engagement, Fatigue or Drowsiness.5.The wearable music device according to claim 1, wherein the volume reward module adjusts the maximum output volume of the device based on user settings.6.The wearable music device according to claim 4, wherein:the volume of the audio signal is adjusted positively related with the real-time mental status values for any mental status mode of Relaxation, Focus or Engagement; andthe volume of the audio signal is adjusted negatively related with the real-time mental status values for any mental status mode of Fatigue or Drowsiness.7.The wearable music device according to claim 4, wherein:when the real-time mental status is good, a smaller proportion of volume reward may be applied to achieve a certain improvement for the mental status mode; andwhen the real-time mental status is poor, a larger proportion of volume reward may be applied to achieve a certain improvement for the mental status mode.8.The wearable music device according to claim 7, wherein:the real-time mental status is good when the real-time mental status value is higher than a median value of the specific value range; andwhen the real-time mental status is poor when the real-time mental status value is lower than the median value of the specific value range.9.The wearable music device according to claim 4, wherein in a sleep assistance for a user, the volume of the audio signal is adjusted in the mental status mode of drowsiness, and the audio signal is cut off when the bioelectric data detects, in real time, that the user has fallen in sleep.10.The wearable music device according to claim 1, wherein the wearable music device comprises at least one of a music belt, a pair of TWS or a headphone.11.A method capable of adjusting mental status through volume reward of a wearable music device, comprising following steps of:acquiring, by a bioelectric data acquiring module, bioelectric signals and converting them to real-time bioelectric data;receiving, by a mental state analysis module, the real-time bioelectric data, and performing analysis of real-time mental status through a machine learning algorithm;adjusting, by a volume reward module, volume of an audio signal received from a user device, based on the real-time mental status from the mental state analysis module; andplayback, by at least one speaker, the audio signal based on the adjusted volume by the volume reward module.12.The method according to claim 11, wherein the bioelectric signals comprise EEG signals, and wherein the bioelectric signals further comprise PPG signals.13.The method according to claim 11, wherein the analysis of the real-time mental status in the mental state analysis module comprises calculating real-time mental status values for each of mental status modes, wherein the real-time mental state values are in a specific value range, and wherein larger the real-time mental state values within the specific value range correspond with a better mental state.14.The method according to claim 13, wherein the mental status modes comprise at least one of Relaxation, Focus, Engagement, Fatigue or Drowsiness.15.The method according to claim 11, wherein the volume reward module adjusts the maximum output volume of the device based on user settings.16.The method according to claim 14, wherein:the volume of the audio signal is adjusted positively related with the real-time mental status values for any mental status mode of Relaxation, Focus or Engagement; andthe volume of the audio signal is adjusted negatively related with the real-time mental status values for any mental status mode of Fatigue or Drowsiness.17.The method according to claim 14, wherein:when the real-time mental status is good, a smaller proportion of volume reward may be applied to achieve a certain improvement for the mental status mode; andwhen the real-time mental status is poor, a larger proportion of volume reward may be applied to achieve a certain improvement for the mental status mode.18.The method according to claim 17, wherein:the real-time mental status is good when the real-time mental status value is higher than a median value of the specific value range; andwhen the real-time mental status is poor when the real-time mental status value is lower than the median value of the specific value range.19.The method according to claim 14, wherein in a sleep assistance for a user, the volume of the audio signal is adjusted in the mental status mode of drowsiness, and the audio signal is cut off when the bioelectric data detects, in real time, that the user has fallen in sleep.20.The method according to claim 11, wherein the wearable music device comprises at least one of a music belt, a pair of TWS or a headphone.
Citation Information
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