Vehicle carrying state identification method, electronic equipment, electronic system and storage medium

Abstract

The invention is suitable for the technical field of outdoor sports, and provides a vehicle carrying state identification method, electronic equipment, an electronic system and a storage medium, and the method comprises the steps: obtaining acceleration data of a user; and determining the state of the user according to the acceleration, wherein the state of the user comprises a vehicle-carrying state. The acceleration data of the user can accurately reflect acceleration changes when the user is in different states in the riding process, whether the user is in the vehicle carrying state or not in the riding process can be accurately judged based on the acceleration data of the user, and the user does not need to manually record or post-mark in the riding process; and the efficiency and the accuracy of vehicle carrying state identification are greatly improved.

Description

Methods for identifying the state of carrying a vehicle, electronic devices, electronic systems, and storage media. Technical Field

[0001] This application belongs to the field of outdoor sports technology, and in particular relates to a method for recognizing the state of carrying a vehicle, electronic devices, electronic systems, and storage media. Background Technology

[0002] With the increasing popularity of cycling, how to accurately and efficiently record the state of carrying a bike during a ride to record road conditions has become a pain point of concern in the industry.

[0003] However, currently, the recording of the status of carrying the cart is mostly done manually by the user or marked afterward, which often leads to problems such as untimely recording and errors in the recording.

[0004] Therefore, how to accurately and efficiently identify the user's carrying status during cycling has become a pressing technical problem that needs to be solved. Summary of the Invention

[0005] This application provides a method, electronic device, electronic system, and storage medium for recognizing the state of carrying a bicycle, which can solve the problem of how to accurately and efficiently recognize the state of carrying a bicycle during cycling.

[0006] In a first aspect, embodiments of this application provide a method for identifying a carrying vehicle state, the method comprising:

[0007] Obtain the user's acceleration data;

[0008] The user's state is determined based on acceleration, including the state of carrying the cart.

[0009] In the above technical solution, the user's acceleration data can accurately reflect the changes in acceleration when the user is in different states during cycling. Based on the user's acceleration data, it can be accurately determined whether the user is carrying the bike during cycling. There is no need for the user to manually record or mark it after the ride, which greatly improves the efficiency and accuracy of identifying the carrying bike state.

[0010] Secondly, embodiments of this application provide an electronic device, which includes a processor and a storage medium;

[0011] Storage media are used to store computer programs;

[0012] The processor is used to execute computer programs to implement the methods as described in any embodiment of the first aspect.

[0013] Thirdly, embodiments of this application provide a method for identifying the state of carrying a vehicle, applied to an electronic system. The electronic system includes an electronic device and a remote terminal communicatively connected to the electronic device. The method includes:

[0014] Acquire user acceleration data collected by electronic devices;

[0015] The remote control terminal determines the user's status based on acceleration data, including the user's carrying status.

[0016] Fourthly, embodiments of this application provide an electronic system, which includes an electronic device and a remote terminal communicatively connected to the electronic device. The electronic device is used to collect acceleration data from a user.

[0017] A remote terminal includes a processor and a storage medium, the storage medium being used to store computer programs;

[0018] The processor is used to execute computer programs to implement the methods as described in any embodiment of the third aspect.

[0019] Fifthly, embodiments of this application provide a storage medium for storing a computer program that can be executed to implement the method as described in any of the embodiments of the first or third aspect.

[0020] Sixthly, embodiments of this application provide a computer program product that, when run, causes the method in any of the embodiments of the first or third aspect to be executed.

[0021] It is understood that the beneficial effects of the second to sixth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 is a schematic diagram of the structure of an electronic device provided in an embodiment of this application;

[0024] Figure 2 is a flowchart illustrating a method for identifying the state of carrying a cart according to an embodiment of this application;

[0025] Figure 3 is a schematic diagram of the positive directions of the X-axis, Y-axis and Z-axis of the triaxial acceleration in the embodiments of this application;

[0026] Figure 4 is a flowchart illustrating another method for identifying the state of carrying a vehicle provided in an embodiment of this application;

[0027] Figure 5 is a flowchart of a method for recognizing the state of carrying a cart in an application scenario according to an embodiment of this application;

[0028] Figure 6 is a flowchart illustrating another method for identifying the state of carrying a vehicle provided in an embodiment of this application;

[0029] Figure 7 is a schematic diagram of the structure of an electronic system provided in an embodiment of this application;

[0030] Figure 8 is a flowchart illustrating another method for identifying the state of carrying a vehicle provided in an embodiment of this application. Detailed Implementation

[0031] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0032] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0033] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0034] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0035] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0036] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0037] It should be noted that the information collection process (such as the collection process of user acceleration data or physiological parameters) / feature extraction process involved in this application is performed with the user's knowledge and permission. That is, the information collection process / feature extraction process complies with relevant standards and does not constitute an act that harms the public interest.

[0038] Recognizing a user's bike-carrying status during cycling can clearly identify non-cycling sections of the route, which is crucial for route recording and sharing among users. Currently, determining bike-carrying status mostly relies on users manually marking it on electronic devices or recording the cycling process with a camera and then analyzing the cyclist's posture changes using image processing technology. However, manual marking by users carries the risk of mismarking, missing markings, or multiple markings, while video monitoring requires processing large amounts of video and image data, consuming a significant amount of time to determine bike-carrying status.

[0039] To address the aforementioned issues, and considering that a user's acceleration changes abruptly during cycling, such as switching from cycling to carrying the bike, this application proposes a method, electronic device, electronic system, and storage medium for identifying the carrying-the-bike state. This method, based on the user's acceleration data, can quickly and accurately determine the user's carrying-the-bike state without requiring manual recording by the user or processing of large amounts of video or image data, significantly improving the efficiency and accuracy of carrying-the-bike state recognition.

[0040] The following section first introduces an electronic device for recognizing the carrying status using the method described in this application embodiment. It should be noted that the vehicle used in this application embodiment is a bicycle. Figure 1 is a schematic diagram of the structure of an electronic device according to an embodiment of this application. As shown in Figure 1, the electronic device 100 includes a processor 110 and a motion sensor 120.

[0041] Electronic device 100 can be a wearable device worn on the wrist, such as a sports watch, cycling computer, or smart bracelet, which the user can wear on their wrist during cycling. Motion sensor 120 can include devices that can detect acceleration, such as a three-axis accelerometer or a six-axis sensor (including an accelerometer and a gyroscope). Processor 110 is used to receive acceleration data sent by motion sensor 120, determine the user's state based on the acceleration, including whether the user is carrying the bike; motion sensor 120 is used to collect the user's acceleration data and send the acceleration data to processor 110.

[0042] In some embodiments, the processor 110 includes a carrying-cart state recognition unit, which is used to determine the user's upper limb posture based on acceleration data, the upper limb posture including lifting and putting down; and to determine the user's state based on the upper limb posture. Considering that the user's upper limb posture may change while carrying the cart, resulting in abrupt changes in acceleration, the user's upper limb posture can be accurately and quickly identified based on the abrupt changes in acceleration data, thus achieving efficient and accurate recognition of the carrying-cart state.

[0043] In some embodiments, the bicycle-carrying state recognition unit is further configured to determine the user's lower limb movements based on acceleration data, including walking; and to determine the user's state based on upper limb posture and lower limb movements. Considering that users may walk while carrying a bicycle, and that the acceleration data during this process differs from that during cycling, analysis of the acceleration data can clarify whether the user is carrying a bicycle or walking. Therefore, even when the user's upper limb posture is identified as carrying a bicycle, it is still necessary to determine if the user is walking to confirm that the user is in a bicycle-carrying state. This comprehensive consideration of the correlation between the user's upper limb posture and lower limb movements during bicycle carrying improves the accuracy of bicycle-carrying state recognition.

[0044] In some embodiments, the processor 110 further includes a current movement speed determination unit, and the electronic device 100 further includes a locator 130. The locator 130 can be a Global Positioning System (GPS) module, a Global Navigation Satellite System (GNSS) module, or a BeiDou Navigation Satellite System (BDS) module, etc. In this embodiment, a GNSS module is used as an example. The sampling frequency of the locator 130 can be set to a low-frequency second sampling frequency, for example, 1 Hz.

[0045] The locator 130 is used to collect the user's current movement speed and send the current movement speed to the processor 110; the current movement speed judgment unit is used to obtain the current movement speed received by the processor 110 and determine whether the current movement speed is less than or equal to a preset first speed threshold; the carrying state recognition unit is also used to determine the user's state based on the upper limb posture when the current movement speed is less than or equal to the first speed threshold. In this way, when recognizing the user's carrying state, the factor that the user's current movement speed will not be too fast during the carrying process is taken into consideration, and the accuracy of the carrying state recognition is further improved by comprehensively judging the current movement speed and acceleration.

[0046] In some embodiments, the electronic device 100 is further connected to a cycling accessory 200, and the processor 110 further includes a cycling data processing unit. The cycling accessory 200 is used to collect cycling data of the vehicle, including at least one of the vehicle's current speed, cadence, or cadence power; and to send the cycling data to the processor 110. The cycling data processing unit is used to acquire the cycling data received by the processor 110 and determine whether the cycling data meets a first condition. The first condition is that the cycling data meets at least one of the following conditions: the speed is less than or equal to a preset second speed threshold; the cadence is less than or equal to a preset cadence threshold; and the cadence power is less than or equal to a preset power threshold. The carrying status recognition unit is further used to determine the user's status based on upper limb posture and lower limb movement when the cycling data is detected to meet the first condition.

[0047] This technical solution considers that users do not use the pedals while carrying the bike (cadence and cadence power are low or zero), and the bike is in a relatively stationary state (speed is low or zero). It determines whether the bike meets the characteristics of a carrying scenario by judging whether the bike's riding data meets the first specified condition. Therefore, when judging whether a user is carrying a bike based on upper limb posture and lower limb movements determined by acceleration data, this further considers the conditions that the bike's riding data should meet in a carrying state, which can avoid misjudgments of the carrying state and further improve the accuracy of bike-carrying state identification.

[0048] In some embodiments, the cycling accessory 200 includes at least one of a speedometer, a cadence meter, or a power meter. The speedometer is used to collect the vehicle's operating speed, the cadence meter is used to collect the vehicle's cadence, and the power meter is used to collect the vehicle's cadence power. It is understood that the speedometer can be installed at the vehicle's wheel hub, measuring the wheel's rotational speed and calculating the vehicle's operating speed by combining the wheel's diameter; the cadence meter can be installed at the vehicle's crank or sprocket; and the power meter can be installed at the vehicle's crank, sprocket, or pedals. The sampling frequency of the cycling accessory can also be set to a second sampling frequency, which reduces the amount of data the processor needs to process while collecting valid data, improving the efficiency of carrying the bicycle in the correct position.

[0049] In some embodiments, the processor 110 further includes a state switching unit, which is used to set the user's current state to the "carrying a cart" state when the user's current state is in the "carrying a cart" state; or, if the user's current state is not in the "carrying a cart" state, to set the user's current state to the "not carrying a cart" state; and after determining that the current state is the "carrying a cart" state, to record the duration of the "carrying a cart" state. In this technical solution, the processor can promptly set and update the user's current state and record the duration of the "carrying a cart" state through the state switching unit, without requiring the user to manually record or set it, resulting in a good user experience.

[0050] In some embodiments, the electronic device 100 further includes a communication module 140 for establishing a communication connection between the electronic device 100 and the cycling accessory 200, so that the processor 110 can acquire cycling data. The communication module 140 is also used to establish a communication connection between the electronic device 100 and a remote terminal, so that the remote terminal can manage the electronic device 100.

[0051] It is understood that the electronic device 100 can communicate wirelessly or wiredly with the cycling accessory 200 using the communication module 140. The communication standard or protocol used for this wireless communication can be Bluetooth, Advanced Network Technologies (ANT), or Advanced Network Technologies Plus (ANT+), etc. The electronic device 100 can also communicate wirelessly with the cycling accessory 200 using the communication module 140. In this case, the communication standard or protocol used for wireless communication can be Bluetooth, Global System for Mobile Communication (GSM), General Packet Radio Service (GPRS), Long Term Evolution (LTE), or Wireless Local Area Network (WIFI), etc.

[0052] In some embodiments, the electronic device 100 further includes a display 150 for displaying the user's status. For example, the display 150 may also display the user's current location, the duration of the carrying status, and the user's physiological parameters (including heart rate, body temperature, or steps). The user can promptly grasp their current status through the electronic device's display, resulting in a good user experience.

[0053] In some embodiments, the electronic device 100 further includes a power module 160 for providing power to the electronic device 100 so that the electronic device 100 can perform the steps in any of the above embodiments.

[0054] In some embodiments, the electronic device 100 further includes a storage medium for storing a computer program, and the processor 110 is capable of executing the computer program to perform the method for identifying the carrying state in any of the embodiments shown in FIG2 to FIG6.

[0055] In this embodiment, the processor 110 involved in the electronic device 100 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0056] The storage medium in electronic device 100 can be its internal storage unit, such as the memory chip of electronic device 100. It can also be an external storage device of electronic device 100, such as a smart media card (SMC), secure digital card (SD), flash card, etc. equipped on electronic device 100.

[0057] The following details the method for identifying the carrying state in the embodiments of this application. Figure 2 is a flowchart illustrating a method for identifying the carrying state in an embodiment of this application. This method is executed by an electronic device, which can be the electronic device 100 shown in the embodiment of Figure 1. As shown in Figure 2, the method includes the following steps:

[0058] Step S101: Obtain the user's acceleration data.

[0059] The electronic device uses its own motion sensor to collect acceleration data of the user's hand at a first sampling frequency. The acceleration data includes the acceleration of the user's hand along three axes (X-axis, Y-axis, and Z-axis) at different times, also known as triaxial acceleration, which are the first acceleration along the X-axis, the second acceleration along the Y-axis, and the third acceleration along the Z-axis. In this embodiment, after the user wears the electronic device while riding a vehicle, as shown in Figure 3, with the electronic device as the origin, the positive direction of the X-axis is along the user's arm pointing outwards from the user's palm; the positive direction of the Z-axis is a coordinate axis perpendicular to the surface of the user's arm pointing towards the sky; and the positive direction of the Y-axis is the direction indicated by the X-axis after rotating 90 degrees counterclockwise around the Z-axis.

[0060] In this way, the directions indicated by the first, second, and third accelerations are three different directions relative to the user's wrist. Electronic devices, with the help of motion sensors, can more accurately capture subtle changes in gravitational acceleration during movement. Considering the changes in the user's upper limb posture, especially the hand posture, when carrying the bike, capturing the accelerations in these three directions can provide a reliable data benchmark for judging the carrying status, improving the accuracy of this judgment.

[0061] Acceleration data can be data obtained by performing a Fast Fourier Transform (FFT) on the raw acceleration data collected by the motion sensor and filtering it based on a preset cutoff frequency (e.g., 1 Hz), or it can be the raw acceleration data, which is the data indicating acceleration output by the motion sensor. This embodiment uses raw acceleration data as an example. Performing FFT and filtering operations on the raw acceleration data can obtain the frequency domain characteristics and frequency components of the acceleration of each axis, facilitating the analysis of periodic changes and vibration modes in the acceleration data to identify the user's state. It can also filter out interfering data in the raw acceleration data, improving the accuracy of judging the carrying status.

[0062] The first sampling frequency can be any one of 10 Hz, 20 Hz, 25 Hz, 50 Hz, 80 Hz, 100 Hz, 200 Hz, 500 Hz, and 1000 Hz, or any value within the range of any two of the above values ​​as endpoints. Other frequencies can also be set as needed; this application does not impose specific limitations. It is understood that the electronic device can select different sampling frequencies as the first sampling frequency based on different monitoring modes. For example, for slow activities such as walking or yoga, a lower sampling frequency (e.g., 10 Hz or 20 Hz) can be selected as the first sampling frequency; for high-speed activities such as cycling, running, or swimming, a higher sampling frequency (e.g., 50 Hz or 80 Hz) can be selected as the first sampling frequency.

[0063] Step S102: Determine the user's state based on the acceleration. The user's state includes the state of carrying the cart.

[0064] For motion sensors, assuming no other accelerations (e.g., acceleration from swinging an arm), they will default to sensing gravitational acceleration. Gravitational acceleration always points downwards and vertically to the ground. During a user's hand movements, due to changes in hand motion, gravitational acceleration will exhibit different components along the X, Y, and Z axes. This information can be used to determine hand posture. Furthermore, when a user is carrying a bicycle, their upper limbs are typically raised with their palms facing upwards. In this state, the components of gravitational acceleration along the X, Y, and Z axes have distinct characteristics. Electronic devices can analyze the characteristics between the first, second, and third accelerations in the acceleration data to determine whether the user is carrying a bicycle.

[0065] In one example, when the electronic device detects that the first acceleration is greater than or equal to a preset first acceleration threshold at the current moment, it determines that the user's state is the carrying state; when it detects that the first acceleration is less than the preset first acceleration threshold, it determines that the user's state is the non-carrying state.

[0066] In another example, the electronic device can also determine the user's state as "carrying a cart" if the acceleration data at the current moment meets a second condition. The second condition is that the first acceleration is greater than or equal to a preset first acceleration threshold, and both the second and third accelerations are less than a preset second acceleration threshold. The preset first acceleration threshold is greater than the preset second acceleration threshold. The preset first acceleration threshold is generally greater than 0.5g (g is the acceleration due to gravity), for example, 0.7g or 0.8g, and the second acceleration threshold is generally less than 0.5g, for example, 0.4g or 0.2g. If the acceleration data does not meet the second condition, the user's state is determined to be "not carrying a cart."

[0067] In another example, the electronic device can also determine the user's gait based on the frequency and amplitude of each acceleration over a period of time (including the current moment) in the acceleration data; if the gait is walking and the acceleration data collected at the current moment meets the second condition, the user's state is determined to be carrying a cart; or, if the gait is determined to be not walking or the acceleration data at the previous moment does not meet the second condition, the user's state is determined to be not carrying a cart.

[0068] It should be noted that, based on the positive X-axis, Y-axis, and Z-axis settings shown in Figure 3, when the user's hand is raised and palm facing upwards while carrying the cart, the smaller the angle (or 0°) between the positive X-axis and the direction indicated by gravitational acceleration, the larger the component of gravitational acceleration on the X-axis will be. In other words, the value of the first acceleration will be close to a gravitational acceleration. In the above example, since the setting of the positive X-axis only considers the magnitude of acceleration when identifying the user's cart-carrying state, there is no need for complex coordinate transformations to determine the acceleration component of the user's hand in the direction indicated by gravitational acceleration. The cart-carrying state can be identified through simple judgment steps, improving the efficiency of cart-carrying state recognition.

[0069] In this embodiment, the user's acceleration data can accurately reflect the changes in acceleration when the user is in different states during cycling. Based on the user's acceleration data, it can be accurately determined whether the user is in a carrying state during cycling, without the need for the user to manually record or mark it after the ride, which greatly improves the efficiency and accuracy of carrying state identification.

[0070] Figure 4 is a flowchart illustrating another method for identifying the carrying status in an embodiment of this application. This method is executed by an electronic device, which can be the electronic device 100 shown in the embodiment of Figure 1. As shown in Figure 4, the method includes the following steps:

[0071] Step S201: Obtain the user's acceleration data.

[0072] For details, please refer to step S101 in the embodiment shown in Figure 2, which will not be repeated here.

[0073] Step S202: Determine the user's upper limb posture based on the acceleration data.

[0074] The upper limb posture includes lifting and putting down. If the electronic device detects that the acceleration data at the current moment meets the second condition, it determines that the user's upper limb posture is lifting; if the acceleration data at the current moment does not meet the second condition, it determines that the user's upper limb posture is putting down.

[0075] Step S203: Determine the user's state based on upper limb posture.

[0076] The electronic device can determine the user's state as "carrying a cart" when the upper limb posture is determined to be "lifting"; and determine the user's state as "not lifting" when the upper limb posture is determined to be "lowering".

[0077] In some embodiments, to further improve the accuracy of recognizing the carrying status, the method further includes:

[0078] Get the user's current movement speed;

[0079] Determining the user's state based on upper limb posture includes:

[0080] If the current moving speed is less than or equal to a preset first speed threshold, the user's state is determined based on the upper limb posture.

[0081] The preset first speed threshold can be 10 km / h or 5 km / h, etc., which is lower than the user's actual cycling speed. This embodiment does not impose specific limitations. The electronic device's locator periodically collects the user's location information at different times, determines and outputs the user's current speed based on the collected location information, thus obtaining the user's current speed. The electronic device compares the current speed with the preset first speed threshold. If it is, it proceeds to the step of determining the user's state based on upper limb posture; otherwise, it determines the user's state as not carrying the bike. Therefore, when identifying the user's carrying bike state, the current speed is used as a judgment factor, avoiding misidentification of scenarios such as the user's carrying bike posture during cycling as carrying the bike state. The comprehensive judgment based on the current speed and upper limb posture further improves the accuracy of carrying bike state recognition.

[0082] In some embodiments, to further improve the accuracy of recognizing the carrying status, the method further includes:

[0083] Acquire riding data of the user's vehicle, including at least one of the vehicle's current speed, cadence, or cadence power.

[0084] Determining the user's state based on upper limb posture includes:

[0085] When the current moving speed is less than or equal to a preset first speed threshold and the cycling data meets a first condition, the user's state is determined based on the upper limb posture. The first condition is that the cycling data meets at least one of the following conditions: the running speed is less than or equal to a preset second speed threshold; the cadence is less than or equal to a preset cadence threshold; and the cadence power is less than or equal to a preset power threshold.

[0086] The preset first speed threshold can be 0 km / h or 0.5 km / h, which is much smaller than the vehicle's operating speed when being ridden. The preset cadence threshold can be 0 rpm or 5 rpm, which is much smaller than the vehicle's cadence when being ridden. The preset power threshold can be 0 watts or 3 W, which is much smaller than the vehicle's cadence power when being ridden. This application embodiment does not impose specific limitations.

[0087] Cycling accessories, such as speedometers, cadence meters, and / or power meters, can be installed in the vehicle to communicate with electronic devices. These accessories periodically collect cycling data and send it to the electronic devices, which then receive this data. The electronic devices determine if the cycling data meets a first condition. If it does, and the current speed is less than or equal to a preset first speed threshold, the user's state is determined based on upper limb posture. Thus, when identifying a user carrying a bicycle, the cycling data is taken into account. By judging whether the cycling data meets the prescribed first condition, it is determined whether the bicycle is relatively stationary during the carrying process. This comprehensive judgment, combining cycling data, current speed, and upper limb posture, further improves the accuracy of bicycle-carrying state recognition, avoiding misjudgments.

[0088] In some embodiments, determining the user's state based on upper limb posture includes the following steps (1) to (3):

[0089] Step (1): If the upper limb posture is detected as "lifting", determine whether the user has started to lift the car based on the upper limb posture.

[0090] Step (2): If the user starts carrying the cart, determine whether the user has stopped carrying the cart based on the upper limb posture.

[0091] Step (3) defines the user's state between the first moment and the second moment as the carrying state. The first moment includes the moment when the user starts carrying the vehicle, and the second moment includes the moment when the user stops carrying the vehicle.

[0092] When the electronic device detects that the user's upper limb posture is "lifting," it determines that the user has started lifting the cart, and this moment is designated as the first moment. Subsequently, when the electronic device first detects that the user's upper limb posture is "lowering," it determines that the user has finished lifting the cart, and this moment is designated as the second moment. The time interval between the start and end of lifting the cart (between the first and second moments) is then defined as the duration of the user's cart-lifting activity, and the user's state during this time interval is consistently defined as the cart-lifting state.

[0093] In the above technical solution, the time period between when a user starts and ends carrying the bike is recorded in the bike-carrying status. This can accurately record the duration of each bike-carrying session during cycling, providing a reliable data foundation for subsequent data analysis on non-cycling routes and / or physical fitness tests.

[0094] In some embodiments, determining whether a user has started carrying a cart based on upper limb posture includes:

[0095] The duration of the upper limb posture for carrying is obtained;

[0096] If the duration is greater than or equal to a preset duration threshold, the user is determined to have started carrying the cart; and the moment when the upper limb posture of carrying is detected is determined as the first moment.

[0097] The preset duration threshold can be 3 seconds (s) or 2 seconds, etc., and this application embodiment does not impose a specific limitation. When the electronic device detects that the user's upper limb posture at the current moment is lifting, it can control its own timer to increment the count, thereby obtaining the current count duration of the timer (the current count duration is the duration). If it is determined that the duration is less than the preset duration threshold, it returns to the step of obtaining the user's acceleration data; if it is determined that the duration is greater than or equal to the preset duration threshold, it determines that the user has started lifting the cart, controls its own timer to increment the count, and returns to the step of obtaining the user's acceleration data.

[0098] When the electronic device determines that the user's upper limb posture is lowered at the current moment, it will clear the timer to set the duration to zero and return to the step of acquiring the user's acceleration data.

[0099] In the aforementioned technical solution, the user is only confirmed to have started carrying the bike after the duration of the upper limb posture being "lifted" is greater than or equal to a preset duration threshold. This avoids misinterpreting actions such as brief accelerations or vibrations during riding that cause sudden changes in acceleration as carrying the bike, thus increasing the reliability of bike-carrying action recognition. Furthermore, by defining the moment the upper limb posture of "lifting" is detected as the first moment after confirming that the user has indeed started carrying the bike, the starting time of the bike-carrying state can be precisely determined to the moment when the user first adopts the "lifting" posture. This allows for accurate recording of the duration the user is in the bike-carrying state, further improving the reliability of bike-carrying state recognition.

[0100] In some embodiments, determining whether a user has finished carrying the cart based on upper limb posture includes:

[0101] After detecting that the user has started carrying the bike, and if the user's upper limbs are in a lowered position, the system determines that the user has stopped carrying the bike; and the moment when the user's upper limbs are in a lowered position is determined as the second moment.

[0102] The electronic device determines that the user has finished carrying the cart when it first detects that the user's upper limbs are in a lowered position after the user has started carrying the cart. Determining the moment when the user's upper limbs are detected to be in a lowered position as the second moment allows the end time corresponding to the carrying state to be accurate to the moment when the user's upper limbs are first in a lowered position after the user starts carrying the cart. This can accurately record the duration of the user's carrying state and improve the reliability of the carrying state recognition.

[0103] In one application scenario, a three-axis accelerometer is used as the motion sensor, and a GNSS module is used as the locator, as shown in Figure 5. When cycling accessories (including speedometers, cadence meters, and / or power meters) are connected to the electronic device, the electronic device can acquire three-axis accelerometer data (i.e., acceleration data) and GNSS speed information (i.e., current movement speed). The electronic device can also acquire data from the speedometer (if present), cadence meter (if present), and power meter (if present) (i.e., running speed, cadence count, and cadence power, which constitute cycling data). Based on the acceleration data, the electronic device can identify whether the user is currently in a carrying gait (including determining whether the upper limb posture is carrying the bike). If the user is not in a carrying gait (the upper limb posture is not carrying the bike), the electronic device will set the user's current state to a non-carrying state, and the electronic device will acquire data again.

[0104] If the user is in a carrying gait (upper limb posture is carrying), the electronic device will determine whether the current movement speed is within the speed range given for carrying the bike (i.e., whether the current movement speed is less than or equal to a preset first speed threshold). If it is not within the given speed range (the current movement speed is greater than the preset first speed threshold), the electronic device will set the user's current state to a non-carrying bike state and re-acquire data. If it is within the given speed range (the current movement speed is less than or equal to the preset first speed threshold), the electronic device will then determine whether the running speed (if any), cadence (if any), and cadence power (if any) are all zero (i.e., whether the cycling data meets the first condition).

[0105] If the cycling data does not meet the first condition, the electronic device sets the user's current state to a non-carrying state and reacquires data. If the cycling data meets the first condition, the electronic device uses a timer to determine whether the above state (upper limb posture is carrying, current movement speed is less than or equal to a preset first speed threshold, and cycling data meets the first condition) lasts for 3 seconds (the specific duration is adjustable) or more (that is, whether the duration of the upper limb posture being carried is greater than or equal to a preset duration threshold). If not, the electronic device sets the user's current state to a non-carrying state and reacquires data. If yes, the user's (current) state is determined to be a carrying state.

[0106] In this embodiment, considering that acceleration data can reflect the acceleration of the user's upper limbs under different motion states, the user's state is determined to be a carrying state when the user's upper limb posture is determined to be lifting, and the user's state is determined to be a non-carrying state when the upper limb posture is determined to be directional. This achieves precise judgment of the carrying state based on the user's upper limb posture, distinguishing the carrying state from states such as pulling or pushing the cart, and improving the accuracy of the carrying state recognition.

[0107] Figure 6 is a flowchart illustrating another method for identifying the carrying status in an embodiment of this application. This method is executed by an electronic device, which can be the electronic device 100 shown in the embodiment of Figure 1. As shown in Figure 6, the method includes the following steps:

[0108] Step S301: Obtain the user's acceleration data.

[0109] For details, please refer to step S201 in the embodiment shown in Figure 4, which will not be repeated here.

[0110] Step S302: Determine the user's upper limb posture based on the acceleration data.

[0111] For details, please refer to step S202 in the embodiment shown in Figure 4, which will not be repeated here.

[0112] Step S303: Determine the user's lower limb movements based on the acceleration data.

[0113] Lower limb movements include walking. When a user walks, the amplitude and frequency of the triaxial acceleration of the hands exhibit significant characteristics; for example, the frequency and amplitude of the acceleration show regular changes. In this way, electronic devices can analyze the user's lower limb movements from the acceleration data.

[0114] In one example, the electronic device extracts the triaxial acceleration within a first time period from the acceleration data to obtain a first triaxial acceleration set. The first time period includes the current moment. Preferably, the first time period can be the most recent 8 seconds of the current moment. It is understood that the first time period can also include other durations of time, such as the current moment.

[0115] The electronic device performs a Fast Fourier Transform on the accelerations in the first triaxial acceleration set to obtain the amplitude and frequency of each acceleration (it can be understood that if the acceleration data is the data after FFT of the original acceleration data and filtering based on a preset cutoff frequency, then this step is not necessary and the process can proceed directly to the next step).

[0116] For the accelerations under each axis in the first three-axis acceleration set, select the two accelerations with larger amplitudes in descending order of amplitude; if the amplitude of one of the selected accelerations is less than 25% of the amplitude of the other (or 20% or other values, which can be set by yourself), then discard the acceleration with the smaller amplitude.

[0117] The K-means clustering algorithm is used to cluster the frequencies of the remaining accelerations. The basic idea of ​​the K-means algorithm is to cluster around k points in space, classifying objects as those closest to them. The cluster center values ​​are iteratively updated until the optimal condition is met. For example, to divide k points into c classes, the K-means algorithm can be used to perform the following steps:

[0118] Step (1) Select initial cluster centers for c classes; the initial cluster centers can be randomly selected from k points;

[0119] Step (2) In the i-th iteration, for any sample (the object to be classified), calculate its distance to each cluster center and classify the sample into the class containing the cluster center with the shortest distance.

[0120] Step (3) Update the cluster center of the class; the mean of each point in the class can be updated to the cluster center of the class;

[0121] Step (4): For all c cluster centers, repeat steps (2) to (3). If the value remains unchanged (the cluster centers no longer change or change very little), then stop the iteration. Otherwise, continue updating (cluster centers are reclassified) until the condition is met (the value remains unchanged). Therefore, after using the K-means algorithm to cluster the remaining acceleration frequencies, the cluster centers corresponding to each frequency class can be obtained.

[0122] Obtain the cluster center corresponding to each frequency category, resulting in multiple cluster centers. If multiple cluster centers satisfy a third condition, determine that the user's lower limb movement is walking. If multiple cluster centers do not satisfy the third condition or one of them indicates walking, determine that the user's lower limb movement is not walking. The third condition is that the frequencies indicated by multiple cluster centers satisfy any of the following three conditions:

[0123] 1. The frequencies indicated by multiple cluster centers are all greater than the frequency threshold (e.g., 1Hz or 2Hz, the frequency corresponding to low-frequency periodic movement (walking), and the frequencies indicated by multiple cluster centers are the same.

[0124] 2. The frequencies indicated by multiple cluster centers are all greater than the frequency threshold, and the difference between the frequencies indicated by any two cluster centers is less than or equal to a preset difference (e.g., 1 Hz or 0.5 Hz).

[0125] 3. The difference between the frequencies indicated by any two cluster centers is greater than a preset difference, there is a multiple relationship between the frequencies indicated by any two cluster centers, and the standard deviation of all frequencies under each cluster center is less than the first preset threshold (e.g., 0.1 or 0.05).

[0126] For example, the electronic device performs FFT on the first, second, and third accelerations along the X, Y, and Z axes within the most recent 8 seconds. For each acceleration along each axis, the frequencies (points) containing the two largest peaks (amplitudes) are selected. When selecting peaks, if the second largest peak is less than 25% of the largest peak, only one largest peak is selected for that axis, discarding the second largest peak (this is because when the amplitude difference between two accelerations is too large, it usually indicates that one of the accelerations is an outlier or noise; discarding it can reduce noise interference, improve clustering accuracy, and thus improve the accuracy of lower limb movement judgment). This results in a maximum of 6 candidate frequencies, denoted as f_ax1, f_ax2, f_ay1, f_ay2, f_az1, f_az2, and the vector formed by these 6 frequencies is denoted as f_acc.

[0127] The K-means algorithm is used to cluster f_acc. Suppose that each frequency in f_acc is to be classified into two classes. The two cluster centers after the final clustering are C1 and C2.

[0128] When the two cluster centers C1 and C2 are very close or even the same (i.e., f_acc is around the same frequency), the lower limb movement may be walking or some unwanted low-frequency periodic movement. Therefore, in order to exclude non-walking periodic states, if the frequencies of C1 and C2 exceed a certain frequency threshold, such as 1Hz, the lower limb movement is considered to be walking.

[0129] When f_acc has two cluster centers that are relatively far apart (the frequency difference indicated by C1 and C2 is greater than a preset difference), the standard deviation of the f_acc frequencies near the two cluster centers is determined. The standard deviations sigma1 for frequencies belonging to C1 and sigma2 for frequencies belonging to C2 are calculated. If both sigma1 and sigma2 are less than a first preset threshold (e.g., ...), and the two cluster centers C1 and C2 show a multiple relationship (i.e., C1 = n * C2, or C2 = n * C1, where n is a positive integer), this indicates that the lower limb movement is a regular walking motion, and the lower limb movement is considered walking. If neither of these conditions is met, the lower limb movement is considered non-walking.

[0130] In another example, before extracting the triaxial acceleration within a first time period from the acceleration data, the electronic device also determines whether the user's lower limbs are in motion based on the acceleration data. If the lower limbs are stationary, the lower limb movement is determined to be non-walking. If the lower limbs are in motion, the device proceeds to extract the triaxial acceleration within the first time period from the acceleration data to determine the lower limb movement. Specifically, the electronic device extracts the triaxial acceleration within a second time period from the acceleration data, obtaining a second triaxial acceleration set. The second time period includes the current moment, and the first time period includes the second time period. The device then determines the standard deviation of the acceleration in the second triaxial acceleration set. If the determined standard deviation is greater than or equal to a second preset threshold (e.g., 1 or 2), the device determines that the lower limbs are in motion; if the standard deviation is less than the second preset threshold, the device determines that the lower limbs are stationary. In this way, by determining whether the lower limbs are moving based on the acceleration data before determining the lower limb movement, the device ensures that the lower limb movement is genuine walking, improving the accuracy of the lower limb movement determination.

[0131] Step S304: Determine the user's state based on upper limb posture and lower limb movement.

[0132] The electronic device can determine the user's state as "carrying a cart" if the lower limb movement is walking and the upper limb posture is carrying; and determine the user's state as "not carrying a cart" if the upper limb posture is putting down or the lower limb movement is not walking.

[0133] In some embodiments, to further improve the accuracy of identifying the carrying state, the user's state is determined based on upper limb posture and lower limb movement, including: when walking is detected as the lower limb movement, the user's state is determined based on the upper limb posture. For details on how the electronic device determines the user's state based on the upper limb posture, please refer to step S203 in the embodiment shown in Figure 4, which will not be elaborated here. In this technical solution, the user's state is determined based on the upper limb posture only when the lower limb movement is walking. This ensures that the user is identified as carrying the cart while walking, thus ensuring that the user is genuinely carrying the cart and improving the accuracy of the carrying state identification.

[0134] Continuing with the application scenario shown in Figure 5, first determine whether the user's lower limb movement is walking based on acceleration data. If the lower limb movement is walking, then determine whether the upper limb posture is carrying a load based on acceleration data. If the lower limb movement is walking and the upper limb posture is carrying a load, determine that the user is currently in a carrying gait. If the lower limb movement is not walking or the upper limb posture is lowered, determine that the user is not currently in a carrying gait.

[0135] In this embodiment, the user's upper limb posture and lower limb movement are determined based on acceleration data. The user's state is determined by considering whether the lower limb movement is walking and whether the upper limb posture is carrying the bike. This not only accurately determines whether the user is carrying the bike during cycling, but also eliminates the need for the user to manually record or mark the bike after the ride, greatly improving the efficiency and accuracy of bike-carrying state recognition.

[0136] Considering that the electronic devices in the above embodiments are usually connected to remote terminals in daily applications, in order to make the identification of the carrying status applicable to more application scenarios, and to save the computing resources of electronic devices to increase the battery life of electronic devices and improve the user experience, this application embodiment also provides an electronic system to realize the method of identifying the carrying status. As shown in Figure 7, Figure 7 is a schematic diagram of the structure of an electronic system in this application embodiment. The electronic system includes an electronic device 100 and a remote terminal 300, and the electronic device 100 establishes a communication connection with the remote terminal 300.

[0137] The electronic device 100 is used to collect the user's acceleration data and send the acceleration data to the remote terminal 300. It can be understood that the electronic device 100 can be the electronic device in the embodiment shown in Figure 1. The electronic device 100 can send the acceleration data to the remote terminal 300 through its own communication module 140.

[0138] The remote terminal 300 is used to receive acceleration data sent by the electronic device 100 and determine the user's status based on the acceleration data. The user's status includes the status of carrying the cart.

[0139] The remote terminal 300 can be a mobile phone, tablet computer, in-vehicle equipment, augmented reality (AR) / virtual reality (VR) device, laptop computer, ultra-mobile personal computer (UMPC), netbook, personal digital assistant (PDA), or other device that can establish a communication connection with the electronic device 100.

[0140] In some embodiments, the electronic device 100 is further configured to send the collected current movement speed of the user to the remote terminal 300; the remote terminal 300 is specifically configured to determine the user's state based on the upper limb posture when the current movement speed is detected to be less than or equal to a first speed threshold.

[0141] In some embodiments, the electronic system further includes a cycling accessory 200, which establishes a communication connection with the electronic device 100. The electronic device 100 is also used to receive cycling data sent by the cycling accessory 200 and send the cycling data to the remote terminal 300. Of course, the cycling accessory 200 can also directly connect to the remote terminal 300 to send the cycling data it has collected to the remote terminal 300.

[0142] The remote terminal 300 is also used to determine the user's lower limb movements based on acceleration data, including walking; and to determine the user's state based on upper limb posture and lower limb movements when cycling data meets a first condition.

[0143] It should be noted that, through the communication connection with the electronic device, the remote terminal 300 can execute all the steps performed by the electronic device except for data acquisition after obtaining the data collected by the electronic device 100 (including acceleration data, and may also include current movement speed and cycling data) in the embodiments shown in Figures 1 to 6.

[0144] The remote terminal 300 includes a processor and a storage medium, the storage medium being used to store a computer program; the processor being used to execute the computer program to implement the method for recognizing the carrying status as shown in any embodiment of FIG8.

[0145] In this embodiment, the processors involved in the remote terminal 300 can be central processing units (CPUs), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0146] The storage medium in the remote terminal 300 can be its internal storage unit, such as its internal memory chip. It can also be an external storage device of the remote terminal 300, such as a Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the remote terminal 300. Furthermore, the storage medium can include both internal storage units and external storage devices of the remote terminal 300. The storage medium is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program in the embodiment shown in Figure 8. The storage medium can also be used to temporarily store data that has been output or will be output.

[0147] Figure 8 is a flowchart illustrating another method for recognizing the carrying status in an embodiment of this application. This method is applied to the electronic system shown in Figure 7. As shown in Figure 8, the method includes the following steps:

[0148] Step S501: Obtain the user's acceleration data collected by the electronic device.

[0149] After collecting acceleration data, the electronic device will send the acceleration data to a remote terminal, thus enabling the electronic system to obtain the acceleration data.

[0150] Step S502: Control the remote terminal to determine the user's status based on the acceleration data.

[0151] The user's state includes the carrying state. The specific implementation method of the electronic system controlling the remote terminal to determine the user's state based on acceleration data is the same as step S202 in the embodiment shown in Figure 2, except that the executing entities are different, which will not be described in detail here.

[0152] In some embodiments, the method further includes: controlling a remote terminal to determine the user's upper limb posture based on acceleration data, the upper limb posture including lifting and putting down; determining the user's upper limb posture based on acceleration data includes: controlling the remote terminal to determine the user's state based on the upper limb posture.

[0153] In some embodiments, the remote terminal controls the determination of the user's upper limb posture based on acceleration data, the upper limb posture including lifting and putting down; determining the user's upper limb posture based on acceleration data includes: the remote terminal controls the determination of the user's state based on the upper limb posture.

[0154] In some embodiments, determining the user's state based on upper limb posture includes: when the upper limb posture is detected as "lifting", controlling the remote terminal to determine whether the user has started lifting the vehicle based on the upper limb posture; when the user is detected to have started lifting the vehicle, controlling the remote terminal to determine whether the user has stopped lifting the vehicle based on the upper limb posture; controlling the remote terminal to determine the user's state between a first time and a second time as the vehicle-lifting state, the first time including the time when the user is detected to have started lifting the vehicle, and the second time including the time when the user is detected to have stopped lifting the vehicle.

[0155] In some embodiments, determining whether a user has started carrying a cart based on upper limb posture includes: controlling a remote terminal to acquire the duration of the upper limb posture being "carrying"; if the duration is greater than or equal to a preset duration threshold, controlling the remote terminal to determine that the user has started carrying the cart; and controlling the remote terminal to determine the moment when the upper limb posture is detected as "carrying" as the first moment.

[0156] In some embodiments, determining whether a user has finished carrying the cart based on upper limb posture includes: after detecting that the user has started carrying the cart, if the upper limb posture is lowered, controlling the remote terminal to determine that the user has finished carrying the cart; and controlling the remote terminal to determine the moment when the upper limb posture is lowered as the second moment.

[0157] In some embodiments, the method further includes: controlling a remote terminal to determine the user's lower limb movements based on acceleration data, the lower limb movements including walking; and determining the user's state based on upper limb posture, including: controlling the remote terminal to determine the user's state based on upper limb posture and lower limb movements.

[0158] In some embodiments, determining the user's state based on upper limb posture and lower limb movement includes: when lower limb movement is detected as walking, controlling a remote terminal to determine the user's state based on upper limb posture.

[0159] In some embodiments, the method further includes: acquiring the user's current movement speed collected by the electronic device; determining the user's state based on the upper limb posture, including: when the current movement speed is less than or equal to a preset first speed threshold, controlling a remote terminal to determine the user's state based on the upper limb posture.

[0160] In some embodiments, the electronic system further includes a cycling accessory for transmitting collected cycling data of the user's bicycle to an electronic device. The cycling data includes at least one of the vehicle's operating speed, cadence, or cadence power at the current moment. The method further includes: acquiring the cycling data transmitted by the electronic device; determining the user's state based on upper limb posture, including: when the current moving speed is less than or equal to a preset first speed threshold and the cycling data meets a first condition, controlling a remote terminal to determine the user's state based on the upper limb posture, wherein the first condition is that the cycling data meets at least one of the following conditions: the operating speed is less than or equal to a preset second speed threshold; the cadence is less than or equal to a preset cadence threshold; and the cadence power is less than or equal to a preset power threshold.

[0161] The steps performed by the electronic system to control the remote terminal in the above embodiments can be found in the corresponding steps performed by the electronic devices in the embodiments shown in Figures 2 to 6, and will not be repeated here.

[0162] This application also provides a computer-readable storage medium storing a computer program that can be executed to implement the method for recognizing the carrying state in any of the above embodiments.

[0163] This application provides a computer program product that can be executed to implement the method for recognizing the carrying status of a cart in any of the above embodiments.

[0164] This application implements all or part of the processes in the methods of the above embodiments, which can be accomplished by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate form. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0165] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0166] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0167] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0168] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0169] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for recognizing the state of carrying a vehicle, characterized in that, The method includes: acquiring the user's acceleration data; determining the user's state based on the acceleration, wherein the user's state includes a carrying vehicle state.

2. The method as described in claim 1, characterized in that, The method further includes: determining the user's upper limb posture based on the acceleration data, the upper limb posture including lifting and putting down; determining the user's upper limb posture based on the acceleration data includes: determining the user's state based on the upper limb posture.

3. The method as described in claim 2, characterized in that, The step of determining the user's state based on the upper limb posture includes: when the upper limb posture is detected as "lifting", determining whether the user has started carrying the vehicle based on the upper limb posture; when the user has started carrying the vehicle, determining whether the user has stopped carrying the vehicle based on the upper limb posture; and determining the user's state between a first time and a second time as the vehicle-carrying state, wherein the first time includes the time when the user is detected to have started carrying the vehicle, and the second time includes the time when the user is detected to have stopped carrying the vehicle.

4. The method as described in claim 3, characterized in that, The step of determining whether the user has started carrying the cart based on the upper limb posture includes: obtaining the duration of the upper limb posture as "carrying"; determining that the user has started carrying the cart if the duration is greater than or equal to a preset duration threshold; and determining the moment when the upper limb posture as "carrying" is detected as the first moment.

5. The method as described in claim 3, characterized in that, The step of determining whether the user has finished carrying the cart based on the upper limb posture includes: after detecting that the user has started carrying the cart, if the upper limb posture is lowered, determining that the user has finished carrying the cart; and determining the moment when the upper limb posture is lowered as the second moment.

6. The method according to any one of claims 2 to 5, characterized in that, The method further includes: determining the user's lower limb movements based on the acceleration data, the lower limb movements including walking; determining the user's state based on the upper limb posture includes: determining the user's state based on the upper limb posture and the lower limb movements.

7. The method as described in claim 6, characterized in that, The method further includes: determining the user's state based on the upper limb posture and the lower limb movement, including: when the lower limb movement is detected as walking, determining the user's state based on the upper limb posture.

8. An electronic device, characterized in that, The electronic device includes a processor and a storage medium; the storage medium is used to store a computer program; the processor is used to execute the computer program to implement the method for identifying the carrying state as described in any one of claims 1-7.

9. A method for recognizing the state of carrying a vehicle, characterized in that, An application to an electronic system, the electronic system including an electronic device and a remote terminal communicatively connected to the electronic device, the method comprising: acquiring acceleration data of a user collected by the electronic device; and controlling the remote terminal to determine the user's state based on the acceleration data, the user's state including a carrying vehicle state.

10. The method as described in claim 9, characterized in that, The method further includes: controlling the remote terminal to determine the user's upper limb posture based on the acceleration data, the upper limb posture including lifting and putting down; determining the user's upper limb posture based on the acceleration data includes: controlling the remote terminal to determine the user's state based on the upper limb posture.

11. The method as described in claim 10, characterized in that, The step of determining the user's state based on the upper limb posture includes: when the upper limb posture is detected as "lifting", controlling the remote terminal to determine whether the user has started carrying the vehicle based on the upper limb posture; when the user is detected to have started carrying the vehicle, controlling the remote terminal to determine whether the user has stopped carrying the vehicle based on the upper limb posture; controlling the remote terminal to determine the user's state between a first time and a second time as the "carrying vehicle" state, wherein the first time includes the time when the user is detected to have started carrying the vehicle, and the second time includes the time when the user is detected to have stopped carrying the vehicle.

12. The method as described in claim 11, characterized in that, The step of determining whether the user has started carrying the cart based on the upper limb posture includes: controlling the remote terminal to obtain the duration of the upper limb posture as "carrying"; if the duration is greater than or equal to a preset duration threshold, controlling the remote terminal to determine that the user has started carrying the cart; and controlling the remote terminal to determine the moment when the upper limb posture as "carrying" is detected as the first moment.

13. The method as described in claim 11, characterized in that, The step of determining whether the user has finished carrying the cart based on the upper limb posture includes: after detecting that the user has started carrying the cart, and when detecting that the upper limb posture is lowered, controlling the remote terminal to determine that the user has finished carrying the cart; and controlling the remote terminal to determine the moment when the upper limb posture is lowered as the second moment.

14. The method as described in claim 10, characterized in that, The method further includes: controlling the remote terminal to determine the user's lower limb movements based on the acceleration data, the lower limb movements including walking; and determining the user's state based on the upper limb posture, which includes: controlling the remote terminal to determine the user's state based on the upper limb posture and the lower limb movements.

15. The method as described in claim 14, characterized in that, Determining the user's state based on the upper limb posture and the lower limb movement includes: when the lower limb movement is detected as walking, controlling the remote terminal to determine the user's state based on the upper limb posture.

16. An electronic system, characterized in that, The electronic system includes an electronic device and a remote terminal communicatively connected to the electronic device. The electronic device is used to collect the user's acceleration data. The remote terminal includes a processor and a storage medium. The storage medium is used to store a computer program. The processor is used to execute the computer program to implement the method for identifying the carrying state as described in any one of claims 9 to 15.

17. A storage medium, characterized in that, The storage medium is used to store a computer program that can be executed to implement the method for identifying the carrying status as described in any one of claims 1 to 7 or 9-15.

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