A power assist adjustment method, device, electronic device and medium for a power-assisted vehicle

Abstract

The present application relates to a method, device, electronic device and medium for assisting power adjustment of a power-assisted vehicle, and relates to the technical field of electric power-assisted vehicles. The method includes obtaining user information and real-time heart rate information; determining whether the real-time heart rate information is abnormal; if it is abnormal, obtaining image information and determining whether the user has an accident based on the image information; if no accident occurs, performing assisting power adjustment based on the user information and the real-time heart rate information; if an accident occurs, determining an adjustment level based on the image information and performing assisting power adjustment based on the adjustment level. The present application has the effect of enabling the power-assisted vehicle to perform targeted assisting power adjustment under different circumstances.

Description

Technical Field

[0001] The present application relates to the technical field of electric assisted vehicles, and in particular, to a method, device, electronic device and medium for adjusting the assistance of an assisted vehicle. Background Art

[0002] With the improvement of people's living standards, bicycles are not only ordinary means of transportation, but also the first choice for people's entertainment, leisure and exercise. Among them, common exercise bicycles include electric assisted vehicles. During the riding process, the exerciser combines human power and electric power to jointly provide the driving force for the electric bicycle to move forward, thereby achieving the purpose of physical exercise.

[0003] At present, users can adjust the assistance of the assisted vehicle during the riding process. However, accidents may occur during the riding process of users, and it is difficult for the assisted vehicle to perform targeted assistance adjustment based on different situations. Summary of the Invention

[0004] In order to enable the assisted vehicle to perform targeted assistance adjustment under different situations, the present application provides a method, device, electronic device and medium for adjusting the assistance of an assisted vehicle.

[0005] In a first aspect, the present application provides a method for adjusting the assistance of an assisted vehicle, adopting the following technical solution:

[0006] A method for adjusting the assistance of an assisted vehicle includes:

[0007] Obtain user information and real-time heart rate information;

[0008] Judge whether the real-time heart rate information is abnormal;

[0009] If it is abnormal, obtain image information, and judge whether the user has an accident based on the image information;

[0010] If no accident occurs, perform assistance adjustment based on the user information and the real-time heart rate information;

[0011] If an accident occurs, determine the adjustment level based on the image information, and perform assistance adjustment based on the adjustment level.

[0012] By adopting the above technical solutions, user information and real-time heart rate information are obtained. According to different situations of the user, the assistance is adjusted accordingly. It is judged whether the real-time heart rate is abnormal. If it is abnormal, it indicates that the user may have overexercised or had an accident. Image information is obtained, and based on the image information, it is judged whether the user has had an accident. The image information can intuitively reflect the current state of the user. If no accident has occurred, it indicates that the user may have overexercised. Based on the user information and real-time heart rate information, the assistance is adjusted, thereby reducing the possibility of the user having an accident. If an accident has occurred, it indicates that the current situation of the user is relatively dangerous. The adjustment level is determined based on the image information, and the assistance is adjusted based on the adjustment level, so that the power-assisted vehicle can minimize secondary damage to the user during the process of adjusting the assistance. By adopting the above method, the power-assisted vehicle realizes targeted assistance adjustment under different situations, so that the user is safer during the cycling exercise process.

[0013] In another possible implementation manner, the judging whether the real-time heart rate information is abnormal includes:

[0014] Obtain an exercise plan;

[0015] Determine at least one preset heart rate information based on the user information and the exercise plan;

[0016] Calculate the fitting value between the preset heart rate information at the current moment and the real-time heart rate information;

[0017] Judge whether the fitting value is less than a preset value;

[0018] If it is less than the preset value, it is determined that the real-time heart rate information is abnormal;

[0019] If it is not less than the preset value, it is determined that the real-time heart rate information is not abnormal.

[0020] By adopting the above technical solutions, an exercise plan is obtained. At least one preset heart rate information is determined based on the user information and the exercise plan, and different preset heart rate information is obtained for different user information and exercise plans. Calculate the fitting value between the preset heart rate information at the current moment and the real-time heart rate information. The larger the fitting value, the more consistent the current exercise state of the user is with the exercise plan. Judge whether the fitting value is less than the preset value. If it is less, it indicates that the fitting value is small, the real-time heart rate information is abnormal, and the current exercise state of the user does not match the exercise plan; if it is not less, it indicates that the real-time heart rate information is not abnormal, and the current exercise state of the user matches the exercise plan.

[0021] In another possible implementation manner, the judging whether the user has had an accident based on the image information includes:

[0022] Extract the facial features of the user based on the image information, where the facial features include facial expressions and facial colors;

[0023] Judge whether the facial features are normal based on the user information;

[0024] If normal, it is determined that no accident has occurred;

[0025] If not normal, it is determined that an accident has occurred.

[0026] By adopting the above technical solution, the facial features of the user are extracted based on the image information, and the facial features can intuitively reflect the current state of the user. Judge whether the facial features are normal based on the user information. If normal, it means that the user is in a normal mood during cycling and it is determined that no accident has occurred; if not normal, it means that the user is currently excited and it is determined that an accident has occurred.

[0027] In another possible implementation manner, the assistance adjustment based on the user information and the real-time heart rate information includes:

[0028] Determine the adjustment time for adjusting the real-time heart rate information to the preset heart rate information based on the user information;

[0029] Determine the adjustment rule based on the user information, where the adjustment rule includes linear adjustment and non-linear adjustment;

[0030] Perform assistance adjustment according to the adjustment rule within the adjustment time.

[0031] By adopting the above technical solution, determine the adjustment time for adjusting the real-time heart rate information to the preset heart rate information based on the user information, and the adjustment times for different users are different. Determine the adjustment rule based on the user information, select a suitable adjustment rule according to different situations of the user, and perform assistance adjustment according to the adjustment rule within the adjustment time to make the adjustment process more suitable for the user's own situation.

[0032] In another possible implementation manner, the determination of the adjustment level based on the image information includes:

[0033] Determine the emotion level of the user based on the facial expression;

[0034] Determine the health level of the user based on the facial color;

[0035] Determine the adjustment level based on the emotion level and the health level.

[0036] By adopting the above technical solution, the emotional level of the user is determined based on facial expressions, and then the current emotional state of the user is known. The health level of the user is determined based on facial color, and then the current health state of the user is known. The adjustment level is determined based on the emotional level and the health level. The combination of the health level and the emotional level makes the adjustment level more accurate, and the determination of multiple dimensions controls the adjustment level required by the user more accurately.

[0037] In another possible implementation manner, the assisting adjustment based on the adjustment level includes:

[0038] Determining an adjustment speed based on the adjustment level;

[0039] Adjusting the assistance to zero based on the adjustment speed.

[0040] By adopting the above technical solution, the adjustment speed is determined based on the adjustment level, and different adjustment levels correspond to different adjustment speeds. The assistance is adjusted to zero based on the adjustment speed. After an accident occurs to the user, the assistance is adjusted to zero at an appropriate speed so that the user can stop riding and rest, reducing the possibility of secondary injury to the user by the power-assisted vehicle.

[0041] In another possible implementation manner, after determining the adjustment level based on the image information, it further includes:

[0042] Obtaining sound information;

[0043] Extracting keywords from the sound information;

[0044] Generating rescue information based on the image information, the user information, and the keywords;

[0045] Outputting the rescue information.

[0046] By adopting the above technical solution, sound information is obtained. The sound information may include the user's distress information. Keywords of the sound information are extracted to know the part where the user is injured or the current state of the user. Rescue information is generated based on the image information, the user information, and the keywords, and the rescue information is output so that the user can be rescued in time.

[0047] In a second aspect, the present application provides a method for assisting adjustment of a power-assisted vehicle, adopting the following technical solution:

[0048] A method for assisting adjustment of a power-assisted vehicle includes:

[0049] An acquisition module, configured to acquire user information and real-time heart rate information;

[0050] An abnormal judgment module, configured to judge whether the real-time heart rate information is abnormal;

[0051] An accident judgment module, configured to obtain image information when an exception occurs, and judge whether the user has an accident based on the image information;

[0052] A first adjustment module, configured to perform assistance adjustment based on the user information and the real-time heart rate information when no accident occurs;

[0053] A second adjustment module, configured to determine an adjustment level based on the image information and perform assistance adjustment based on the adjustment level when an accident occurs.

[0054] By adopting the above technical solution, the acquisition module acquires user information and real-time heart rate information, and performs corresponding assistance adjustments according to different situations of the user. The abnormal judgment module judges whether the real-time heart rate is abnormal. If it is abnormal, it indicates that the user may have overexercised or had an accident. The accident judgment module acquires image information and judges whether the user has an accident based on the image information. The image information can intuitively reflect the current state of the user. If no accident occurs, it indicates that the user may have overexercised. The first adjustment module adjusts the assistance based on the user information and the real-time heart rate information, thereby reducing the possibility of the user having an accident. If an accident occurs, it indicates that the current situation of the user is relatively dangerous. The second adjustment module determines an adjustment level based on the image information and performs assistance adjustment based on the adjustment level to minimize secondary damage to the user during the process of adjusting the assistance of the power-assisted vehicle. By adopting the above method, the power-assisted vehicle realizes targeted assistance adjustment under different situations, making the user safer during the cycling exercise process.

[0055] In another possible implementation manner, when the abnormal judgment module judges whether the real-time heart rate information is abnormal, it is specifically configured to:

[0056] Obtain an exercise plan;

[0057] Determine at least one preset heart rate information based on the user information and the exercise plan;

[0058] Calculate the fitting value between the preset heart rate information at the current moment and the real-time heart rate information;

[0059] Judge whether the fitting value is less than a preset value;

[0060] If it is less than the preset value, determine that the real-time heart rate information is abnormal;

[0061] If it is not less than the preset value, determine that the real-time heart rate information is not abnormal.

[0062] In another possible implementation manner, when the accident judgment module judges whether the user has an accident based on the image information, it is specifically configured to:

[0063] Extract the facial features of the user based on the image information, where the facial features include facial expressions and facial colors;

[0064] Judge whether the facial features are normal based on the user information;

[0065] If normal, it is determined that no accident has occurred;

[0066] If abnormal, it is determined that an accident has occurred.

[0067] In another possible implementation, when the first adjustment module performs assistance adjustment based on the user information and the real-time heart rate information, it specifically is used for:

[0068] Determine the adjustment time for adjusting the real-time heart rate information to the preset heart rate information based on the user information;

[0069] Determine the adjustment rule based on the user information, where the adjustment rule includes linear adjustment and non-linear adjustment;

[0070] Perform assistance adjustment according to the adjustment rule within the adjustment time.

[0071] In another possible implementation, when the second adjustment module determines the adjustment level based on the image information, it specifically is used for:

[0072] Determine the emotion level of the user based on the facial expression;

[0073] Determine the health level of the user based on the facial color;

[0074] Determine the adjustment level based on the emotion level and the health level.

[0075] In another possible implementation, when the second adjustment module performs assistance adjustment based on the adjustment level, it specifically is used for:

[0076] Determine the adjustment speed based on the adjustment level;

[0077] Adjust the assistance to zero based on the adjustment speed.

[0078] In another possible implementation, the device further includes:

[0079] An acquisition sound module, used to acquire sound information;

[0080] An extraction module, used to extract keywords of the sound information;

[0081] A generation module, used to generate rescue information based on the image information, the user information, and the keywords;

[0082] An output module for outputting the rescue information.

[0083] By adopting the above technical solution,

[0084] In a third aspect, the present application provides an electronic device, adopting the following technical solution:

[0085] An electronic device, comprising:

[0086] One or more processors;

[0087] A memory;

[0088] One or more applications, wherein one or more applications are stored in the memory and configured to be executed by one or more processors, and the one or more applications are configured to: execute an assistance adjustment method for a power-assisted vehicle shown in any possible implementation manner of the first aspect.

[0089] In a fourth aspect, the present application provides a computer-readable storage medium, adopting the following technical solution:

[0090] A computer-readable storage medium, comprising: a computer program stored therein that can be loaded and executed by a processor to implement an assistance adjustment method for a power-assisted vehicle shown in any possible implementation manner of the first aspect.

[0091] In summary, the present application includes at least one of the following beneficial technical effects:

[0092] 1. Obtain user information and real-time heart rate information, perform corresponding assistance adjustment according to different situations of the user, determine whether the real-time heart rate is abnormal. If it is abnormal, it indicates that the user may have overexercised or had an accident. Obtain image information, and based on the image information, determine whether the user has had an accident. The image information can intuitively reflect the current state of the user. If no accident has occurred, it indicates that the user may have overexercised. Adjust the assistance based on the user information and real-time heart rate information, thereby reducing the possibility of the user having an accident. If an accident has occurred, it indicates that the current situation of the user is relatively dangerous. Determine the adjustment level based on the image information, and perform assistance adjustment based on the adjustment level, so that the power-assisted vehicle minimizes secondary damage to the user during the process of adjusting the assistance. By adopting the above method, the power-assisted vehicle realizes targeted assistance adjustment under different situations, making the user safer during the cycling exercise process;

[0093] 2. Obtain an exercise plan, determine at least one preset heart rate information based on user information and the exercise plan, and different preset heart rate information corresponds to different user information and exercise plans. Calculate the fitting value between the preset heart rate information at the current moment and the real-time heart rate information. The larger the fitting value, the more consistent the user's current exercise state is with the exercise plan. Determine whether the fitting value is less than a preset value. If it is less, it means that the fitting value is small and the real-time heart rate information is abnormal, and the user's current exercise state does not match the exercise plan; if it is not less, it means that the real-time heart rate information is normal and the user's current exercise state matches the exercise plan. Brief Description of the Drawings

[0094] Figure 1 is a schematic flowchart of a method for adjusting the assistance of a power-assisted vehicle according to an embodiment of the present application.

[0095] Figure 2 is a schematic flowchart of a device for adjusting the assistance of a power-assisted vehicle according to an embodiment of the present application.

[0096] Figure 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Detailed Description of the Embodiment

[0097] The following will further describe the present application in detail with reference to the accompanying Figures 1-3 drawings.

[0098] Those skilled in the art can make modifications to this embodiment without creative contributions according to their needs after reading this specification, but as long as they are within the scope of the claims of the present application, they are protected by the Patent Law.

[0099] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the scope of protection of the present application.

[0100] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after, unless otherwise specified.

[0101] The following will further describe the embodiments of the present application in detail with reference to the drawings of the specification.

[0102] An embodiment of the present application provides an assistance adjustment method for a power-assisted vehicle, which is executed by an electronic device. The electronic device can be a server or a terminal device. The server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected through wired or wireless communication methods, which are not limited in the embodiment of the present application. For example, Figure 1 As shown, the method includes steps S101, S102, S103, S104, and S105.

[0103] Step S101: Obtain user information and real-time heart rate information.

[0104] In the embodiment of the present application, the user information may include the user's age, height, weight, and face image information before riding, etc. The electronic device can obtain the user information input by the user through the terminal device, or the electronic device can obtain the user information from the database. The electronic device can obtain the real-time heart rate information sent by the heart rate sensor set on the handlebar. The real-time heart rate information can be the user's heart rate value per second or a heart rate curve.

[0105] Step S102: Determine whether the real-time heart rate information is abnormal.

[0106] In the embodiment of the present application, the electronic device determines whether the real-time heart rate information is abnormal. If the real-time heart rate information is abnormal, it means that the user does not conform to the exercise plan set before exercise during the exercise process. If the real-time heart rate information shows that the user's current heart rate is too high, it means that the user's exercise intensity is too large and an accident may occur, and it is determined that the real-time heart rate information is abnormal; if the real-time heart rate information shows that the user's current heart rate is too low, it means that the user may be unwell during the riding process, and it is determined that the real-time heart rate is abnormal.

[0107] Step S103: If an abnormality occurs, obtain image information and determine whether the user has had an accident based on the image information.

[0108] For the embodiments of the present application, if the electronic device determines that the real-time heart rate information is abnormal, the electronic device acquires image information. The electronic device can acquire the image information collected by the monitoring device carried by the user's head during cycling, or acquire the image information collected by the monitoring device installed on the bicycle handlebar. The monitoring device mainly captures the user's face. The electronic device determines whether the user has had an accident based on the image information. The face of the user captured by the monitoring device can intuitively show the user's current state. According to the state of the user during cycling, it is further determined whether the user has had an accident. If the current state is not good, it indicates that the user is very likely to have had an accident.

[0109] Step S104, if no accident occurs, perform assistance adjustment based on the user information and the real-time heart rate information.

[0110] For the embodiments of the present application, if the electronic device determines that the user has not had an accident, it means that the abnormality of the user's current real-time heart rate information is only caused by too high exercise intensity. The electronic device performs assistance adjustment based on the user information and the real-time heart rate information, and selects the most suitable assistance adjustment method for the user in combination with the user information, thereby greatly meeting the user's exercise needs.

[0111] Step S105, if an accident occurs, determine the adjustment level based on the image information and perform assistance adjustment based on the adjustment level.

[0112] For the embodiments of the present application, if the electronic device determines that the user has had an accident, the electronic device determines the adjustment level based on the image information. The image information intuitively reflects the user's current state, and different states correspond to different adjustment levels. Perform assistance adjustment based on the adjustment level so that after it is determined that the user has had an accident, a suitable adjustment method can be selected to minimize the damage to the user.

[0113] A possible implementation manner of the embodiments of the present application. When step S102 determines whether the real-time heart rate information is abnormal, it specifically includes step S1021 (not shown in the figure), step S1022 (not shown in the figure), step S1023 (not shown in the figure), step S1024 (not shown in the figure), step S1025 (not shown in the figure), and step S1026 (not shown in the figure), where

[0114] Step S1021, acquire the exercise plan.

[0115] For the embodiments of the present application, the electronic device can acquire the exercise plan set by the user through the terminal device, or the electronic device can also acquire the exercise plan set by the user in advance from the database. The exercise plan may include the exercise state that the user wants to achieve during exercise. For example:

[0116] The exercise plan obtained by the electronic device from the database has a total exercise duration of 1 hour, and the effective aerobic exercise lasts for 40 minutes.

[0117] Step S1022, determine at least one preset heart rate information based on the user information and the exercise plan.

[0118] For the embodiments of the present application, the electronic device determines at least one preset heart rate information based on the user information and the exercise plan. Different user information results in different preset heart rate information. For example:

[0119] Assume that the user information shows that the user is 24 years old. Taking step S1021 as an example: at least one preset heart rate information is that the heart rate remains at 60 - 100 beats per minute from 0 - 10 minutes, 125 - 145 beats per minute from 10 - 50 minutes, and 120 - 80 beats per minute from 50 - 60 minutes;

[0120] Assume that the user information shows that the user is 60 years old. Taking step S1021 as an example: at least one preset heart rate information is that the heart rate remains at 60 - 100 beats per minute from 0 - 10 minutes, 100 - 125 beats per minute from 10 - 50 minutes, and 125 - 80 beats per minute from 50 - 60 minutes.

[0121] The electronic device can generate a preset heart rate curve based on at least one preset heart rate information. The abscissa of the curve is the exercise time, and the ordinate is the preset heart rate value.

[0122] Step S1023, calculate the fitting value between the preset heart rate information at the current moment and the real - time heart rate information.

[0123] For the embodiments of the present application, the electronic device calculates the fitting value between the preset heart rate information at the current moment and the real - time heart rate information. The electronic device can generate a real - time heart rate curve based on the real - time heart rate information sent by the heart rate sensor. The abscissa of the curve is the exercise time, and the ordinate is the real - time heart rate value. Compare the real - time heart rate curve with the preset heart rate curve generated in step S1022 to judge the similarity between the two. The electronic device can complete the judgment of the curve similarity through matlab software, or the electronic device can also use other methods for comparison. The finally obtained fitting value can be presented in the form of a percentage. For example: the fitting value of the real - time heart rate curve and the preset heart rate curve is 80%. The larger the fitting value, the more in line with the exercise plan the user's current exercise state is.

[0124] Step S1024, judge whether the fitting value is less than the preset value.

[0125] For the embodiments of the present application, the electronic device determines whether the fitting value is less than a preset value. The preset value can also be determined based on user information. If it is determined based on user information that the user is relatively young and has good physical fitness, it indicates that even if there is a deviation, it may have little impact on the user himself. The preset value can be set relatively low. If the user is relatively old and not very strong physically, the preset value is set relatively high to avoid accidents during the user's exercise. For example:

[0126] For young users, the preset value can be set to 75%, and for old users, the preset value can be set to 85%.

[0127] Step S1025, if it is less than the preset value, it is determined that the real-time heart rate information is abnormal.

[0128] For the embodiments of the present application, if the electronic device determines that the fitting value is less than the preset value, it indicates that the real-time heart rate information does not match the preset heart rate information, and the electronic device determines that the real-time heart rate is abnormal. For example:

[0129] Suppose the fitting value is 72% and the preset value is 75%, then the electronic device determines that the fitting value is less than the preset value, and the real-time heart rate information is abnormal.

[0130] Step S1026, if it is not less than the preset value, it is determined that the real-time heart rate information is not abnormal.

[0131] For the embodiments of the present application, if the electronic device determines that the fitting value is not less than the preset value, it indicates that the real-time heart rate information matches the preset heart rate information, and the electronic device determines that the real-time heart rate is not abnormal. For example:

[0132] Suppose the fitting value is 80% and the preset value is 75%, then the electronic device determines that the fitting value is not less than the preset value, and the real-time heart rate information is not abnormal.

[0133] A possible implementation manner of the embodiments of the present application. When step S103 determines whether the user has an accident based on the image information, it specifically includes step S1031 (not shown in the figure), step S1032 (not shown in the figure), step S1033 (not shown in the figure), and step S1034 (not shown in the figure), where

[0134] Step S1031, extract the facial features of the user based on the image information.

[0135] Among them, the facial features include facial expressions and facial colors.

[0136] For the embodiments of this application, the electronic device extracts the user's facial features based on the image information, analyzes the image information, and can generate facial expressions of various emotions of the user using the image generation method StyleGAN based on the facial feature images pre-entered by the user. The newly obtained image information is input into the trained model using a neural network, and thus the user's current facial expression can be known.

[0137] When the electronic device extracts the facial color of the user based on the image information, the electronic device analyzes the image information, and can extract the user's facial contour based on the gray value based on the facial feature images pre-entered by the user, change the color in the facial contour, and thus obtain the user's different facial colors in different emotions. The newly obtained image information is input into the trained model using a neural network, and thus the user's current facial color can be known.

[0138] Step S1032, determine whether the facial features are normal based on the user information.

[0139] For the embodiments of this application, the electronic device determines whether the facial features are normal based on the user information. The user information includes the facial image information pre-entered by the user. The electronic device uses a neural network to input the newly obtained image information into the trained model, and can know whether the user's current facial features are normal by obtaining the training result. If there are no significant differences in both the facial expression and the facial color, it indicates that the facial features are normal.

[0140] Step S1033, if it is normal, determine that no accident has occurred.

[0141] For the embodiments of this application, if the electronic device determines that the facial features are normal, the electronic device determines that the user has not had an accident and the user is in a normal cycling exercise state.

[0142] Step S1034, if it is not normal, determine that an accident has occurred.

[0143] For the embodiments of this application, if the electronic device determines that the facial features are not normal, the electronic device determines that the user has had an accident and the user's current cycling exercise state is abnormal.

[0144] A possible implementation manner of the embodiments of this application. When step S104 performs assist adjustment based on the user information and the real-time heart rate information, it specifically includes step S1041 (not shown in the figure), step S1042 (not shown in the figure), and step S1043 (not shown in the figure), where

[0145] Step S1041, determine the adjustment time for adjusting the real-time heart rate information to the preset heart rate information based on the user information.

[0146] For the embodiments of this application, the electronic device determines the adjustment time for adjusting the real-time heart rate information to the preset heart rate information based on the user information, which includes the user's age, physical condition, etc. For young and physically strong users, the adjustment time can be set shorter because they have better physical conditions and can accept sudden assistance adjustments. For older users with average physical conditions, the adjustment time is set longer. Since their physical conditions are average, too fast adjustment may cause unnecessary damage to the user's body. Among them, the physical condition can calculate a weight value based on the user's height and weight as a scale for measuring the physical condition. The electronic device determines the adjustment time based on the weight value and age. For example:

[0147] The user information obtained by the electronic device is a 30-year-old male with a height of 175 cm and a weight of 65 kg. For a male with a height of 175 cm, the standard weight = (height - 80) × 70% = (175 - 80) × 70% = 66.5 kg, and the weight value = (66.5 - 65) ÷ 66.5 = 2.25%. Then the electronic device obtains the adjustment time of 2 minutes for a 30-year-old male with a weight value of 2.25% in the database. The database of the electronic device stores the adjustment time corresponding to different weight values for each age.

[0148] Step S1042: Determine the adjustment rule based on the user information.

[0149] Among them, the adjustment rules include linear adjustment and non-linear adjustment.

[0150] For the embodiments of this application, the electronic device determines the adjustment rule based on the user information. Among them, the user information includes the exercise curve during the user's historical exercise. The abscissa of the exercise curve is time, and the ordinate is the assistance value. Check the deceleration rule of the user during the exercise, and judge whether the user is used to linear deceleration or non-linear deceleration based on the exercise curve. Select the adjustment rule based on the user's habitual adjustment rule. Among them, non-linear adjustment can be to perform assistance adjustment according to the rule of a parabola function. For example:

[0151] The exercise curve in the user information obtained by the electronic device shows a straight line rule during deceleration. Therefore, the electronic device determines that the adjustment rule of this user is linear adjustment; if the exercise curve in the user information shows a curve rule during deceleration, the electronic device determines that the adjustment rule of this user is non-linear adjustment.

[0152] Step S1043: Perform assistance adjustment according to the adjustment rule within the adjustment time.

[0153] For the embodiments of this application, the electronic device performs assistance adjustment according to the adjustment rule within the adjustment time. For example:

[0154] Assume that the adjustment time is 2 minutes and the adjustment rule is linear adjustment. The electronic device determines that the user's current heart rate is relatively high based on the real-time heart rate information. The electronic device needs to adjust the user's heart rate value from 130 beats per minute to 125 beats per minute through adjustment assistance. Then the electronic device determines that the current assistance value is 2.5, where the assistance value can be the ratio of the power value to the human power value. The electronic device linearly and evenly reduces the assistance value of 2.5 to 1.5 within 2 minutes.

[0155] In a possible implementation manner of the embodiments of the present application, when determining the adjustment level based on the image information in step S105, it specifically includes step S1051 (not shown in the figure), step S1052 (not shown in the figure), and step S1053 (not shown in the figure), where

[0156] Step S1051, determining the user's emotion level based on the facial expression.

[0157] For the embodiments of the present application, after analyzing the image information, the electronic device can directly obtain the user's current emotional state. The electronic device matches the emotional state with the emotion levels in the database, and then knows the user's current emotion level. For example:

[0158] No emotion is level 0. The emotions indicating the degree of pain are divided into levels 1 to 10; the emotions indicating happiness are divided into levels 1 to 10. The electronic device determines that the user's current emotional state is pain, and then compares the determined specific state with the pain levels one by one, and then obtains that the current user's emotion level is pain level 4.

[0159] Step S1052, determining the user's health level based on the facial color.

[0160] For the embodiments of the present application, the electronic device determines the user's health level based on the facial color. The greater the difference between the user's facial color and the rosy facial color when a person is in a normal state, the lower the health level. For example:

[0161] The electronic device determines based on the image information that the facial color is pale. The health level of a rosy complexion is level 10. Then the electronic device compares the facial color analyzed based on the image information with the facial colors in the database one by one, and then knows that the corresponding health level under this facial color is level 3.

[0162] Step S1053, determining the adjustment level based on the emotion level and the health level.

[0163] For the embodiments of the present application, the electronic device determines the adjustment level based on the emotion level and the health level. When the emotion level is higher and the health level is lower, it indicates that the user's current situation is relatively severe and the assistance needs to be adjusted to zero as soon as possible so that the user can get rest as soon as possible. Among them, the adjustment level can be the difference between the emotion level and the health level. For example:

[0164] If the emotion level is 8 and the health level is 3, then the adjustment level = 8 - 3 = 5;

[0165] If the emotion level is 5 and the health level is 6, then the adjustment level = 5 - 6 = -1.

[0166] In a possible implementation manner of the embodiment of the present application, when performing assist adjustment based on the adjustment level in step S105, it specifically includes step S1054 (not shown in the figure) and step S1055 (not shown in the figure), where

[0167] Step S1054, determining the adjustment speed based on the adjustment level.

[0168] For the embodiment of the present application, the electronic device determines the adjustment speed based on the adjustment level. Different adjustment levels correspond to different adjustment speeds, and the corresponding relationship between the level and the speed is stored in the database of the electronic device. For example:

[0169] When the electronic device determines that the adjustment level is 5, the electronic device obtains from the database that the adjustment speed corresponding to the adjustment level of 5 is a voltage value that drops by 0.1 V per second, thereby reducing the discharge value of the power-assisted vehicle.

[0170] Step S1055, adjusting the assistance to zero based on the adjustment speed.

[0171] For the embodiment of the present application, the electronic device adjusts the assistance to zero based on the adjustment speed. After adjusting to zero, if no human power is generated, the vehicle will not move forward. If the user has an accident, due to inertia, the power-assisted vehicle can still sense human power, so the power-assisted vehicle will continue to provide assistance, which may cause harm to the user. Timely adjusting it to zero can reduce the harm of the power-assisted vehicle to the user.

[0172] In a possible implementation manner of the embodiment of the present application, the method further includes step S106 (not shown in the figure), step S107 (not shown in the figure), step S108 (not shown in the figure), and step S109 (not shown in the figure), where

[0173] Step S106, obtaining sound information.

[0174] For the embodiment of the present application, the electronic device can obtain the sound information collected by the sound sensor installed on the power-assisted vehicle, or the electronic device can also obtain the sound information collected by the user's terminal device, which is not limited here. Among them, the sound information includes the voice of the user speaking during the ride.

[0175] Step S107, extracting keywords from the sound information.

[0176] For the embodiments of this application, the electronic device extracts keywords from the sound information. After the user has an accident, they may subconsciously make a distress sound. Among them, after the electronic device receives the distress sound, it can analyze it through natural language technology and then extract keywords. For example:

[0177] If the sound information obtained by the electronic device is the voice information of "My leg hurts badly", the electronic device extracts the keywords "leg" and "pain" based on natural language technology.

[0178] Step S108, generate rescue information based on the image information, user information, and keywords.

[0179] For the embodiments of this application, the electronic device generates rescue information based on the image information, user information, and keywords. Taking step S107 as an example:

[0180] The electronic device obtains that the user information is a 30-year-old male named Zhang San, the image information includes Zhang San's current facial state, and the keywords are "leg" and "pain". Then the rescue information generated by the electronic device includes the text information of the 30-year-old male Zhang San having a leg pain and the image information including Zhang San's facial state.

[0181] Step S109, output the rescue information.

[0182] For the embodiments of this application, the electronic device outputs the rescue information. The electronic device can send the rescue information to the terminal device of the rescue personnel, or the electronic device can send the rescue information to the terminal device of the nearby personnel, so that the user can get timely assistance.

[0183] The above embodiments introduce a method for adjusting the assistance of a power-assisted vehicle from the perspective of the method flow. The following embodiments introduce a device for adjusting the assistance of a power-assisted vehicle from the perspective of virtual modules or virtual units. For details, please refer to the following embodiments.

[0184] The embodiments of this application provide a device 20 for adjusting the assistance of a power-assisted vehicle, as Figure 2 shown. The device 20 for adjusting the assistance of a power-assisted vehicle may specifically include:

[0185] An acquisition module 201, configured to acquire user information and real-time heart rate information;

[0186] A judgment abnormality module 202, configured to judge whether the real-time heart rate information is abnormal;

[0187] A judgment accident module 203, configured to, when an abnormality occurs, acquire image information and judge whether the user has an accident based on the image information;

[0188] A first adjustment module 204, configured to, when no accident occurs, perform assistance adjustment based on the user information and the real-time heart rate information;

[0189] The second adjustment module 205 is configured to determine an adjustment level based on the image information and perform assistance adjustment based on the adjustment level when an accident occurs.

[0190] By adopting the above technical solution, the acquisition module 201 acquires user information and real-time heart rate information, and performs corresponding assistance adjustment according to different situations of the user. The abnormal judgment module 202 judges whether the real-time heart rate is abnormal. If it is abnormal, it indicates that the user may have exercised excessively or had an accident. The accident judgment module 203 acquires image information and judges whether the user has had an accident based on the image information. The image information can intuitively reflect the current state of the user. If no accident occurs, it indicates that the user may have exercised excessively. The first adjustment module 204 adjusts the assistance based on the user information and the real-time heart rate information, thereby reducing the possibility of the user having an accident. If an accident occurs, it indicates that the current situation of the user is relatively dangerous. The second adjustment module 205 determines an adjustment level based on the image information and performs assistance adjustment based on the adjustment level, so as to minimize the secondary injury to the user during the assistance adjustment of the power-assisted vehicle. By adopting the above method, the power-assisted vehicle realizes targeted assistance adjustment in different situations, making the user safer during the cycling exercise process.

[0191] In a possible implementation manner of the embodiment of the present application, when the abnormal judgment module 202 judges whether the real-time heart rate information is abnormal, it is specifically configured to:

[0192] Obtain an exercise plan;

[0193] Determine at least one preset heart rate information based on the user information and the exercise plan;

[0194] Calculate the fitting value between the preset heart rate information at the current moment and the real-time heart rate information;

[0195] Judge whether the fitting value is less than a preset value;

[0196] If it is less than the preset value, it is determined that the real-time heart rate information is abnormal;

[0197] If it is not less than the preset value, it is determined that the real-time heart rate information is not abnormal.

[0198] In a possible implementation manner of the embodiment of the present application, when the accident judgment module 203 judges whether the user has had an accident based on the image information, it is specifically configured to:

[0199] Extract the facial features of the user based on the image information, where the facial features include facial expressions and facial colors;

[0200] Judge whether the facial features are normal based on the user information;

[0201] If it is normal, it is determined that no accident has occurred;

[0202] If not normal, it is determined that an accident has occurred.

[0203] In a possible implementation manner of the embodiment of the present application, when the first adjustment module 204 performs assistance adjustment based on user information and real-time heart rate information, it is specifically used for:

[0204] Determine the adjustment time for adjusting the real-time heart rate information to the preset heart rate information based on the user information;

[0205] Determine the adjustment rule based on the user information, and the adjustment rule includes linear adjustment and non-linear adjustment;

[0206] Perform assistance adjustment according to the adjustment rule within the adjustment time.

[0207] In a possible implementation manner of the embodiment of the present application, when the second adjustment module 205 determines the adjustment level based on the image information, it is specifically used for:

[0208] Determine the emotion level of the user based on the facial expression;

[0209] Determine the health level of the user based on the facial color;

[0210] Determine the adjustment level based on the emotion level and the health level.

[0211] In a possible implementation manner of the embodiment of the present application, when the second adjustment module 205 performs assistance adjustment based on the adjustment level, it is specifically used for:

[0212] Determine the adjustment speed based on the adjustment level;

[0213] Adjust the assistance to zero based on the adjustment speed.

[0214] In a possible implementation manner of the embodiment of the present application, the device 20 further includes:

[0215] An acquisition sound module, used to acquire sound information;

[0216] An extraction module, used to extract keywords of the sound information;

[0217] A generation module, used to generate rescue information based on the image information, user information, and keywords;

[0218] An output module, used to output the rescue information.

[0219] In the embodiment of the present application, the first adjustment module and the second adjustment module may be the same adjustment module or different adjustment modules.

[0220] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0221] An embodiment of the present application provides an electronic device, such as Figure 3 shown Figure 3 The electronic device 30 shown includes: a processor 301 and a memory 303. Among them, the processor 301 and the memory 303 are connected, such as connected through a bus 302. Optionally, the electronic device 30 may further include a transceiver 304. It should be noted that in practical applications, the transceiver 304 is not limited to one, and the structure of the electronic device 30 does not constitute a limitation to the embodiments of the present application.

[0222] The processor 301 may be a CPU (Central Processing Unit, central processor), a general-purpose processor, a DSP (Digital Signal Processor, data signal processor), an ASIC (Application Specific Integrated Circuit, application-specific integrated circuit), an FPGA (Field Programmable Gate Array, field programmable gate array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logic blocks, modules, and circuits described in connection with the disclosure of the present application. The processor 301 may also be a combination that implements a computing function. For example, it includes a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0223] The bus 302 may include a path for transmitting information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect, peripheral component interconnect standard) bus or an EISA (Extended Industry Standard Architecture, extended industry standard architecture) bus, etc. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, Figure 3 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0224] The memory 303 can be a ROM (Read Only Memory), or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory), or other types of dynamic storage devices that can store information and instructions. It can also be an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, or any other medium that can be used to carry or store the desired application program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0225] The memory 303 is used to store the application program code for executing the solution of this application, and is controlled by the processor 301 for execution. The processor 301 is used to execute the application program code stored in the memory 303 to implement the content shown in the foregoing method embodiments.

[0226] Among them, the electronic device includes but is not limited to: mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet Computers), PMPs (Portable Multimedia Players), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 3 The shown electronic device is only an example and should not impose any limitations on the functions and usage scope of the embodiments of the present disclosure.

[0227] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When it runs on a computer, the computer can execute the corresponding content in the foregoing method embodiment. Compared with the related art, in the embodiment of the present application, user information and real-time heart rate information are obtained, and the assistance is adjusted correspondingly according to different situations of the user. It is judged whether the real-time heart rate is abnormal. If it is abnormal, it means that the user may exercise excessively or have an accident. Image information is obtained, and it is judged whether the user has an accident based on the image information. The image information can intuitively reflect the current state of the user. If no accident occurs, it means that the user may exercise excessively, and the assistance is adjusted based on the user information and the real-time heart rate information, thereby reducing the possibility of the user having an accident. If an accident occurs, it means that the current situation of the user is relatively dangerous. The adjustment level is determined based on the image information, and the assistance is adjusted based on the adjustment level, so that the power-assisted vehicle can minimize the secondary injury to the user during the process of adjusting the assistance. By adopting the above method, the power-assisted vehicle realizes targeted assistance adjustment in different situations, so that the user is safer during the cycling exercise process.

[0228] It should be understood that although the steps in the flowchart of the accompanying drawings are shown in sequence according to the indication of the arrows, these steps do not necessarily have to be executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps is not strictly limited in order, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages. These sub-steps or stages do not necessarily have to be executed at the same time, but can be executed at different times, and their execution order does not necessarily have to be in sequence, but can be executed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.

[0229] The above are only some embodiments of the present application. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present application, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present application.

Claims

1. A method for adjusting the assistance of a power-assisted vehicle, characterized in that, Including: Obtain user information and real-time heart rate information; Judge whether the real-time heart rate information is abnormal; If it is abnormal, obtain image information, and judge whether the user has an accident based on the image information; If no accident occurs, perform assistance adjustment based on the user information and the real-time heart rate information; If an accident occurs, determine the adjustment level based on the image information, and perform assistance adjustment based on the adjustment level; The judging whether the user has an accident based on the image information includes: Extract the facial features of the user based on the image information, where the facial features include facial expressions and facial colors; Judge whether the facial features are normal based on the user information; If it is normal, determine that no accident has occurred; If it is not normal, determine that an accident has occurred; The determining the adjustment level based on the image information includes: Determine the emotion level of the user based on the facial expression; Determine the health level of the user based on the facial color; Determine the adjustment level based on the emotion level and the health level; The performing assistance adjustment based on the adjustment level includes: Determine the adjustment speed based on the adjustment level; Adjust the assistance to zero based on the adjustment speed.

2. The power assistance adjustment method of a power-assisted vehicle according to claim 1, characterized in that The judging whether the real-time heart rate information is abnormal includes: Obtain an exercise plan; Determine at least one preset heart rate information based on the user information and the exercise plan; Calculate the fitting value between the preset heart rate information at the current moment and the real-time heart rate information; Judge whether the fitting value is less than a preset value; If it is less than the preset value, determine that the real-time heart rate information is abnormal; If it is not less than the preset value, determine that the real-time heart rate information is not abnormal.

3. The power assist adjustment method of a power-assisted vehicle according to claim 2, characterized in that, The performing assistance adjustment based on the user information and the real-time heart rate information includes: Determine the adjustment time for adjusting the real-time heart rate information to the preset heart rate information based on the user information; Determine the adjustment rule based on the user information, where the adjustment rule includes linear adjustment and non-linear adjustment; Perform assistance adjustment according to the adjustment rule within the adjustment time.

4. The power assistance adjustment method of a power-assisted vehicle according to claim 1, characterized in that, After determining the adjustment level based on the image information, it further includes: Obtain sound information; Extract keywords of the sound information; Generate rescue information based on the image information, the user information and the keywords; Output the rescue information.

5. A power assist adjustment device for a power-assisted vehicle, characterized in that, Including: An acquisition module, used to acquire user information and real-time heart rate information; An abnormal judgment module, used to judge whether the real-time heart rate information is abnormal; An accident judgment module, used to obtain image information when an abnormality occurs, and judge whether the user has an accident based on the image information; A first adjustment module, used to perform assistance adjustment based on the user information and the real-time heart rate information when no accident occurs; A second adjustment module, used to determine the adjustment level based on the image information and perform assistance adjustment based on the adjustment level when an accident occurs; The accident judgment module is specifically used for the judging whether the user has an accident based on the image information, including: Extract the facial features of the user based on the image information, where the facial features include facial expressions and facial colors; Judge whether the facial features are normal based on the user information; If normal, it is determined that no accident has occurred; If not normal, it is determined that an accident has occurred; The second adjustment module is specifically configured to determine the adjustment level based on the image information, including: Determine the user's emotion level based on the facial expression; Determine the user's health level based on the facial color; Determine the adjustment level based on the emotion level and the health level; The second adjustment module is specifically configured to perform assistance adjustment based on the adjustment level, including: Determine the adjustment speed based on the adjustment level; Adjust the assistance to zero based on the adjustment speed.

6. An electronic device, characterized in that, It includes: One or more processors; A memory; One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to: execute an assistance adjustment method for a power-assisted vehicle according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements an assistance adjustment method for a power-assisted vehicle according to any one of claims 1 to 4.

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