A motion detection method and device

Abstract

The present application discloses a motion detection method and apparatus, the method is based on a wearable device, the method comprising: under the condition that the user is in an effective motion state, according to the vital sign data of the user in the effective motion state, determining the first motion level corresponding to the effective motion state; and, according to the motion data of the user in the effective motion state, determining the second motion level corresponding to the effective motion state; the first motion level and / or the second motion level at least show: the motion intensity when the user is in the effective motion state; according to the first motion level and the second motion level, obtaining the motion status information of the user in the effective motion state. It can be seen that the motion detection process in this specification comprehensively determines the motion status information of the user based on the first motion level and the second motion level and based on different dimensions, so that the obtained motion status information is more objective and can more accurately characterize the user's motion status.

Description

Technical Field

[0001] The present application relates to the field of intelligent detection technology, and in particular to a motion detection method and device. Background Art

[0002] Nowadays, with the improvement of people's quality of life and the increase in demand for quality of life, users' attention to health status is gradually increasing.

[0003] In some cases, health conditions can be characterized by exercise status information. Exercise status information can reflect the user's exercise amount, exercise intensity, etc. to a certain extent. In the prior art, exercise status information is mostly determined manually. For example, after user Zhang San completes exercise, exercise status information such as exercise duration and exercise type (running, climbing, high jump, etc.) is manually entered into the device. On the one hand, the operation burden of user Zhang San is increased; on the other hand, manual entry still has the problem of large errors. Summary of the invention

[0004] The embodiments of this specification provide a motion detection method and device to partially solve the above problems existing in the prior art.

[0005] The embodiments of this specification adopt the following technical solutions:

[0006] This specification provides a motion detection method, which is based on a wearable device and includes:

[0007] Under the condition that the user is in an effective exercise state, a first exercise level corresponding to the effective exercise state is determined according to the vital sign data of the user in the effective exercise state; and a second exercise level corresponding to the effective exercise state is determined according to the exercise data of the user in the effective exercise state; the first exercise level and / or the second exercise level at least show: the exercise intensity of the user when the user is in the effective exercise state;

[0008] According to the first exercise level and the second exercise level, the exercise status information of the user in the effective exercise state is obtained.

[0009] In an optional embodiment of the present specification, before the method, the method further includes:

[0010] Obtaining the user's motion state according to the motion data;

[0011] If the duration of the indicator parameter shown by the motion state of the user being greater than the indicator threshold corresponding to the indicator parameter is not less than the time threshold, it is determined that the motion state of the user is a valid motion state.

[0012] In an optional embodiment of the present specification, the indicator parameter is the modulus of acceleration shown by the motion state of the user.

[0013] In an optional embodiment of the present specification, determining the first level of exercise corresponding to the effective exercise state according to the vital sign data of the user in the effective exercise state includes: determining the mean value of the vital sign data of the user in the effective exercise state; screening out the exercise level that matches the mean value of the vital sign data from the preset exercise levels, and determining it as the first level of exercise corresponding to the effective exercise state; and / or,

[0014] Determining a second level of exercise corresponding to the effective exercise state based on the exercise data of the user in the effective exercise state includes: determining an average of the exercise data of the user in the effective exercise state; and screening out an exercise level that matches the average of the exercise data from among the preset exercise levels, and determining it as the second level of exercise corresponding to the effective exercise state.

[0015] In an optional embodiment of the present specification, obtaining the exercise status information of the user in the effective exercise state according to the first exercise level and the second exercise level includes:

[0016] The exercise status information of the user in the exercise effective state is determined according to the maximum exercise intensities shown in the first exercise level and the second exercise level.

[0017] In an optional embodiment of the present specification, obtaining the exercise status information of the user in the effective exercise state according to the first exercise level and the second exercise level includes:

[0018] According to the first exercise level and the second exercise level, obtaining the available exercise level of the user in the effective exercise state at this time as the exercise status information of the user in the effective exercise state;

[0019] After the method, it also includes:

[0020] The exercise status information of the user in the specified time period is obtained according to the available exercise levels of each effective state of each exercise in the specified time period.

[0021] In an optional embodiment of this specification, the method is performed by a wearable device;

[0022] The method further includes: displaying the motion status information on the wearable device; and / or sending the motion status information to an associated device that is communicatively connected to the wearable device, so that the associated device displays the motion status information.

[0023] This specification provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned motion detection method is implemented.

[0024] The present specification provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned motion detection method when executing the program.

[0025] At least one of the above technical solutions adopted in the embodiments of this specification can achieve the following beneficial effects:

[0026] The motion detection process in this specification comprehensively determines the user's motion status information based on the first motion level and the second motion level, based on different dimensions, so that the obtained motion status information is more objective and can more accurately represent the user's motion status. Among them, the first motion level is obtained based on the user's vital signs data. Since the user's vital signs are usually different in different motion states, the vital signs can be combined with factors such as the user's physique to measure the user's motion status when in this motion state; the second motion level is obtained based on the user's motion data. The motion process is usually accompanied by the user's body movements. The second motion level obtained based on the motion data can more directly measure the user's motion status when in this motion state, thereby making the motion status information obtained through the motion detection process in this specification more accurate and reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0028] Figure 1 A schematic diagram of a wearable device structure and interaction between the wearable device and associated devices provided in an embodiment of this specification;

[0029] Figure 2 A motion detection process provided by an embodiment of this specification;

[0030] Figure 3 A schematic diagram of the structure of a motion detection device provided in an embodiment of this specification;

[0031] Figure 4 The embodiments of this specification provide corresponding to Figure 2 Schematic diagram of electronic equipment. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solutions and advantages of this specification more clear, the technical solutions of this application will be clearly and completely described below in combination with the specific embodiments of this specification and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in the specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0033] It is understandable that users may perform purposeful exercises in their daily lives, such as fitness exercises for the purpose of exercise, etc.; they may also perform exercises with exercise properties without purpose, such as climbing stairs for the purpose of going home, etc. These exercises may be used to measure the user's exercise status. It is less difficult to make statistics for purposeful exercises, but the user still needs to manually perform the corresponding operations (for example, the user manually enters the start time of the exercise, etc.); for purposeless exercises, it is more difficult for the user to pay attention to his or her own exercise status in real time and calculate the indicators of the exercise status. In addition, even if the user can evaluate the exercise status in a timely manner, the user may not have the corresponding professional level to obtain an objective evaluation result.

[0034] In some scenarios, such as when the user is a child, it will be more difficult to effectively detect the user's motion status.

[0035] In view of this, the present specification provides a motion detection method to at least partially solve the problems existing in the prior art, such as the difficulty in determining motion status information and the difficulty in determining motion status information for specific groups such as children.

[0036] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0037] In an optional embodiment of the present specification, the motion detection process is based on a wearable device, which may have a detection function, and the wearable device may be worn or worn together with the user to move and detect at least one of vital sign data and motion data. Moreover, after the wearable device collects the vital sign data and / or motion data, the wearable device performs a subsequent motion status information determination process based on the collected data. That is, in this embodiment, the motion detection process may be performed by the wearable device.

[0038] In another optional embodiment of the present specification, the motion detection process is based on a wearable device, which may have a detection function, and the wearable device may be worn or worn together with the user to move and detect at least one of vital sign data and motion data. However, after the wearable device collects the vital sign data and / or motion data, the wearable device sends the collected data to the server, and the server performs a subsequent motion status information determination process based on the data collected by the wearable device. That is, in this embodiment, the motion detection process can be performed by the server.

[0039] It can be seen that the execution subject of the process in this specification can be selected and / or adjusted according to the actual scene. For the convenience of explanation, the object that executes the motion detection process is referred to as a designated execution subject in this specification.

[0040] From the above description of the wearable device, it can be seen that no matter what the execution subject is, the wearable device has at least a detection function for at least one of vital sign data and motion data. In an optional embodiment of this specification, the wearable device may include: Figure 1 The structure shown.

[0041] Figure 1 The wearable device shown may include: a vital sign data acquisition unit and a motion data acquisition unit. The vital sign data acquisition unit is used to collect the vital sign data of the user, and the vital sign data may include at least one of the following: heart rate, electrocardiogram, blood pressure, pulse, respiratory rate, blood oxygen saturation, body temperature, etc. The motion data acquisition unit is used to collect motion data, and the motion data may include at least one of the following: cadence, number of steps, exercise duration, exercise distance, speed during exercise, acceleration during exercise, etc.

[0042] In an optional embodiment of the present invention, the vital sign data acquisition unit may include a photoplethysmograph (PPG) acquisition device (e.g., a photoelectric sensor). The motion data acquisition unit may include an acceleration sensor, which may be used to collect three-axis velocity data of the user during motion.

[0043] Figure 2 A motion detection process provided in an embodiment of this specification may specifically include the following steps:

[0044] S200: Under the condition that the user is in an effective exercise state, determining a first exercise level corresponding to the effective exercise state according to vital sign data of the user in the effective exercise state.

[0045] The effective state of exercise refers to an exercise state that can achieve a preset goal, and the preset goal can be determined according to the actual situation of the user. For example, if the preset goal is to exercise, whether an exercise state is an effective state of exercise can be judged according to the exercise intensity.

[0046] In actual scenarios, the user may have multiple exercise states, and different exercise states may indicate different exercise intensities. In this specification, exercise intensity can be characterized by the range of motion during exercise, the physical energy consumed during exercise, and the duration of exercise when the range of motion is large / the physical energy consumed during exercise is high.

[0047] The greater the range of motion, and / or the more energy consumed during exercise, and / or the longer the duration of exercise, the greater the exercise intensity. For example, when a user is typing on a computer, although the user's arms also move to a certain extent during the process, the exercise intensity is small and should not be considered to be in an effective exercise state. In contrast, when a user is running, the physical energy consumption is greater and the exercise intensity is greater, so it should be considered to be in an effective exercise state.

[0048] In the following, how to judge whether a motion state is a valid motion state will be described.

[0049] In an optional embodiment of the present specification, several exercise levels can be predetermined and stored in the designated execution subject, and different exercise levels correspond to different exercise intensities. For example, the exercise levels are arranged in order, and the higher the order of the exercise level, the greater the exercise intensity corresponding to the exercise level.

[0050] The process of determining the first level of exercise can be: determining the mean value of the vital sign data of the user in the effective state of the exercise; and selecting the exercise level that matches the mean value of the vital sign data from the preset exercise levels, and determining it as the first level of exercise corresponding to the effective state of the exercise. It can be seen that the first level of exercise in this description can at least characterize the user's exercise status based on various dimensions of the vital sign data.

[0051] S202: Determine a second exercise level corresponding to the effective exercise state according to the exercise data of the user in the effective exercise state.

[0052] Correspondingly, in an optional embodiment of the present specification, the process of determining the second level of exercise may be: determining the average value of the user's exercise data in the effective state of the exercise; and selecting the exercise level that matches the average value of the exercise data from the preset exercise levels, and determining it as the second level of exercise corresponding to the effective state of the exercise. It can be seen that the second level of exercise in the present specification can at least characterize the user's exercise status based on various dimensions of the exercise data.

[0053] It should be noted that in this specification, the order of determining the first level of movement and determining the second level of movement is not prioritized.

[0054] S204: Obtaining the exercise status information of the user in the effective exercise state according to the first exercise level and the second exercise level.

[0055] In particular, since the wearable device needs to be worn on the user's limbs when in use, the user may move only part of the limbs during exercise, rather than the entire body. For example, when riding a bicycle, the user's arm movements are small. At this time, if the wearable device is a smart watch, the motion status information obtained based on the motion data will not be able to characterize the motion status information caused by the user's leg movements. For another example, for users with good physique and regular exercise, after strenuous exercise, vital signs data such as heart rate will not change like those of ordinary users, and the motion status information obtained based on the vital signs data will not be able to characterize the motion status information caused by the user's leg movements. By adopting the process in this specification to merge the first level of exercise and the second level of exercise, the problem of obtaining inaccurate motion status information based on one-sided data can be avoided to a large extent, and it is more suitable for electronic products such as smart watches and smart bracelets worn on local limbs of the human body.

[0056] The motion status information in this specification may include various contents and representation methods.

[0057] Specifically, the exercise status information may be at least one of the following: duration of the effective state of this exercise, physical energy consumed in the effective state of this exercise (for example, the amount of body fat consumed), a judgment result on whether the effective state of this exercise meets the exercise volume requirement (the exercise volume requirement may be set by the user, or may be a result obtained based on data statistics of multiple users), a degree of completion of the exercise volume of this effective state relative to the target exercise volume within a preset time period (the preset time period may be set by the user, or may be a result obtained based on data statistics of multiple users, for example, 1 day. The degree of completion may be represented by a percentage, for example, "10% of the target exercise volume has been completed in this effective state of exercise"), changes in data corresponding to indicator parameters in this effective state of exercise over time (for example, changes in step frequency over time), etc.

[0058] In addition, the representation method of the motion status information may be at least one of the following: graphics, text, voice, vibration signal, etc.

[0059] It can be seen that the motion detection process in this specification comprehensively determines the user's motion status information based on the first motion level and the second motion level and based on different dimensions, so that the obtained motion status information is more objective and can more accurately characterize the user's motion status. Among them, the first motion level is obtained based on the user's vital signs data. Since the user's vital signs are usually different in different motion states, the vital signs can be combined with factors such as the user's physique to measure the user's motion status when in this motion state; the second motion level is obtained based on the user's motion data. The motion process is usually accompanied by the user's body movements. The second motion level obtained based on the motion data can more directly measure the user's motion status when in this motion state, thereby making the motion status information obtained through the motion detection process in this specification more accurate and reasonable.

[0060] Especially for devices such as smart watches that are worn on the user's body, there may be a problem that the motion data collection results are difficult to reflect the user's full motion status due to different types of motion. In addition, the existing indicators for measuring the user's vital signs are also difficult to be personalized for different users and combined with the user's physique, so there may be a problem that the collected vital signs data cannot reflect the user's full motion status. The process in this manual combines the first level of motion and the second level of motion to obtain more comprehensive motion status information, which can avoid the "problem of difficulty in reflecting the full picture of the user's motion status" to a large extent, and is especially suitable for wearable devices such as smart watches that are aimed at mass users.

[0061] From the foregoing content, it can be seen that the first level of exercise and the second level of exercise in this manual respectively characterize the user's effective exercise state from different dimensions. In order to further accurately characterize the information shown by the effective exercise state, this manual obtains the exercise status information under the effective exercise state by fusing the first level of exercise and the second level of exercise.

[0062] In an optional embodiment of the present specification, the fusion process may be: determining the exercise status information of the user in the effective exercise state according to the maximum exercise intensity shown in the first exercise level and the second exercise level. Specifically, the information of the exercise level corresponding to the maximum exercise intensity shown in the first exercise level and the second exercise level may be directly used as the exercise status information.

[0063] For example, when the wearable device is an electronic watch, and the user's current effective exercise state is caused by riding a bicycle, the exercise intensity shown in the first exercise level obtained based on the user's vital signs data will be greater than the exercise intensity shown in the second exercise level, that is, the exercise intensity shown in the first exercise level is the maximum exercise intensity (at this time, the first exercise level can be used as an available exercise level to obtain the exercise status information of the user in the effective exercise state based on the available exercise level).

[0064] It is understandable that when riding a bicycle, although the user is exercising, the user's arm movements are not large, resulting in a smaller exercise intensity shown in the second exercise level. However, through the process in this embodiment, errors caused by one-sided representation of the effective state of exercise by data in one aspect can be effectively avoided.

[0065] In another optional embodiment of the present specification, the fusion process may be: weighting the amount of exercise shown in the first level with a first weight to obtain a first weighted result; weighting the amount of exercise shown in the second level with a second weight to obtain a second weighted result. Based on the average of the first weighted result and the second weighted result, the exercise status information of the user in the effective exercise state is determined. Specifically, the information of the exercise level corresponding to the average value may be directly used as the exercise status information. The first weight and the second weight may be set by the user, or may be obtained based on the user's exercise status information in history.

[0066] On the one hand, the exercise state is determined by objective factors. For example, the amount of exercise for running 10 kilometers is bound to be greater than that for running 1 kilometer. However, in actual scenarios, the physical fitness of different people cannot be generalized. For different users, a personalized strategy suitable for the user can be formulated based on the difference in the user's personal physical fitness. In this embodiment, the effective state of the user's current exercise is measured based on the user's historical exercise status, which is conducive to making the obtained exercise status information accurately reflect the individual situation of the user.

[0067] At this point, the motion status information is obtained, which can effectively characterize the effective state of this motion.

[0068] However, in actual scenarios, within a day or a week, the user may be in a valid exercise state multiple times (there is a certain time interval between two consecutive valid exercise states, and multiple valid exercise states are not continuous). And one of the valid exercise states may not be sufficient to achieve the preset goal.

[0069] In order to be able to integrate the motion status information obtained from multiple valid motion states from a more macro level to measure the user's motion status, in an optional embodiment of the present specification, the motion status information of the user in the specified time period can be obtained according to the available motion levels of each valid motion state in the specified time period. Specifically, the motion status information of each available motion level can be counted (for example, the information of each dimension of the motion status information is summed separately), and the result obtained by the statistics is used as the motion status information of the user in the specified time period. The specified time period can be set by the user or can be the result obtained based on the data statistics of multiple users.

[0070] As can be seen from the above content, in actual scenarios, the user's motion state may not be a valid motion state. Therefore, the actual motion states should be screened to filter out the valid motion states and remove the invalid motion states (invalid motion states include static states).

[0071] In an optional embodiment of the present specification, before executing step S200, the designated execution subject or other execution subjects other than the designated execution subject may also obtain the user's motion state according to the motion data. In the present specification, the motion state may be comprehensively characterized from multiple dimensions by different motion data, for example, the motion state may be jointly characterized by the step frequency, the number of steps, and the motion duration.

[0072] If the duration of the indicator parameter shown by the motion state of the user being greater than the indicator threshold corresponding to the indicator parameter is not less than the time threshold, it is determined that the motion state of the user is a valid motion state. Thereafter, the subsequent steps of determining the motion level can be performed for the valid motion state; if the result of the judgment is that the motion state is not a valid motion state (that is, the motion state is an invalid motion state), the motion state of the user can be obtained again, and a judgment is performed on whether the re-acquired motion state is a valid motion state.

[0073] The index parameter can be determined according to the actual scenario. For example, in some scenarios, the step frequency can be used as the index parameter, and the step frequency shown in the motion state can be compared with the index threshold corresponding to the step frequency. If the step frequency shown in the motion state is greater than the index threshold corresponding to the step frequency for a period of time that is not less than the time threshold, the motion state is determined to be a valid motion state. Alternatively, the modulus of acceleration (acc) shown in the user's motion state can be used to calculate the acceleration modulus. mod ) is determined as the indicator parameter. In addition, the indicator parameter can also be other, which are not listed here one by one.

[0074] When the modulus of acceleration is used as an indicator parameter, the modulus of acceleration can be obtained by the following formula (1).

[0075]

[0076] Wherein, ax is the acceleration in the x direction; ay is the acceleration in the y direction; az is the acceleration in the z direction. For example, the x direction may be the east-west direction; the y direction may be the north-south direction; and the z direction may be the vertical direction.

[0077] For another example, in some scenarios, the step frequency and the speed during exercise are used as index parameters, and the step frequency shown in the exercise state can be compared with the index threshold corresponding to the step frequency, and the speed shown in the exercise state can be compared with the index threshold corresponding to the speed. If the time when both are greater than their corresponding index thresholds is not less than the time threshold, the exercise state is determined to be a valid exercise state.

[0078] In this specification, the time threshold may be determined based on at least one of the user's age and the user's geographical location. Taking the user's geographical location as an example, if the user's geographical location (which can be detected by the wearable device) is the user's home, the time threshold should not be too large. If the user's geographical location is a park, the time threshold should not be too small.

[0079] In an optional embodiment of this specification, the wearable device further includes: Figure 1 After obtaining the motion status information through the aforementioned process of this specification, the motion status information can be displayed on the wearable device through the display unit, so that the user can immediately know the motion status information. The display unit can be a screen.

[0080] In another optional embodiment of the present specification, the designated execution subject is connected to the associated device in communication (when the designated execution subject is a wearable device, the interaction state between the wearable device and the associated device is as follows: Figure 1 After the designated execution subject obtains the motion status information, the motion status information is sent to the associated device, so that the associated device displays the motion status information.

[0081] When the wearable device is an electronic watch for children, the associated device may be the parent terminal corresponding to the electronic watch. In this case, the parent terminal can obtain the child's exercise status in a timely manner through the wearable device, which is conducive to the parent's supervision of the child. In particular, when children are studying in schools or kindergartens, schools usually do not allow children to wear mobile phones. When the wearable device in this specification is used for children, it can detect all scenes experienced by children in their lives.

[0082] Optionally, at least one of the aforementioned indicator parameters, preset goals, preset exercise levels, preset time periods, specified time periods, types of vital sign data, and types of exercise data can be set by an associated device.

[0083] It should be noted that the wearable device in this specification may be an electronic watch, an electronic bracelet, an electronic glasses, etc. In addition, the wearable device in this specification may also be a portable heart rate monitor, a blood pressure monitor, etc., which are used to realize the detection function.

[0084] The associated device may be a mobile terminal such as a computer, a PDA, or a mobile phone; or it may be a wearable device such as an electronic watch (eg, a smart watch) or an electronic glasses.

[0085] Based on the same idea, the present specification also provides a corresponding motion detection device such as Figure 3 The motion detection device is applied to the designated execution subject.

[0086] Figure 3 A schematic diagram of the structure of a motion detection device provided in an embodiment of this specification includes:

[0087] The first exercise level determination module 300 is configured to: when a user is in an effective exercise state, determine the first exercise level corresponding to the effective exercise state according to the vital sign data of the user in the effective exercise state.

[0088] The second exercise level determination module 302 is configured to: determine the second exercise level corresponding to the effective exercise state based on the exercise data of the user in the effective exercise state; the first exercise level and / or the second exercise level at least show: the exercise intensity of the user when the user is in the effective exercise state.

[0089] The exercise status information determination module 304 is configured to obtain the exercise status information of the user in the effective exercise state according to the first exercise level and the second exercise level.

[0090] In an optional embodiment of the present specification, the device further includes: a valid motion state determination module 306 .

[0091] The effective motion state judgment module 306 is configured to: obtain the motion state of the user based on the motion data; if the duration of the indicator parameter shown by the user's motion state is greater than the indicator threshold corresponding to the indicator parameter and is not less than the time threshold, then it is determined that the user's motion state is a valid motion state.

[0092] In an optional embodiment of the present specification, the indicator parameter is the modulus of acceleration shown by the motion state of the user.

[0093] In an optional embodiment of the present specification, the first exercise level determination module 300 is specifically configured as follows: determining the mean value of the vital sign data of the user in the effective exercise state; and screening out the exercise level that matches the mean value of the vital sign data among the preset exercise levels, and determining it as the first exercise level corresponding to the effective exercise state.

[0094] In an optional embodiment of the present specification, the second exercise level determination module 302 is specifically configured to: determine the average exercise data of the user in the effective exercise state; among the preset exercise levels, screen out the exercise level that matches the average exercise data, and determine it as the second exercise level corresponding to the effective exercise state.

[0095] In an optional embodiment of the present specification, the exercise status information determination module 304 is specifically configured to: determine the exercise status information of the user in the effective exercise state according to the maximum exercise intensity shown in the first exercise level and the second exercise level.

[0096] In an optional embodiment of the present specification, the exercise status information determination module 304 is specifically configured as: according to the first exercise level and the second exercise level, obtaining the available exercise level of the user in the current effective exercise state as the exercise status information of the user in the effective exercise state.

[0097] In an optional embodiment of the present specification, the device may further include: a summarizing module 308 .

[0098] The aggregation module 308 is configured to obtain the user's exercise status information within the specified time period according to the available exercise levels of each effective state of each exercise within the specified time period.

[0099] In an optional embodiment of the present specification, the device may further include: a display module 310 and / or an interaction module 312 .

[0100] The display module 310 is configured to display the exercise status information on the wearable device.

[0101] The interaction module 312 is configured to: send the motion status information to an associated device that is communicatively connected to the wearable device, so that the associated device displays the motion status information.

[0102] The present specification also provides a computer-readable storage medium, which stores a computer program, which can be used to execute the above Figure 2 Provides motion detection process.

[0103] The embodiments of this specification also propose Figure 4 The schematic structure diagram of the electronic device shown in FIG. Figure 4 At the hardware level, the electronic device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, and may also include other hardware required for the business. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to achieve the above Figure 2 Of course, in addition to the software implementation, this specification does not exclude other implementations, such as logic devices or a combination of software and hardware, etc., that is, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0104] In the 1990s, improvements to a technology could be clearly distinguished as hardware improvements (for example, improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the method flow). However, with the development of technology, many improvements to the method flow today can be regarded as direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that an improvement in a method flow cannot be implemented using a hardware entity module. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to ask a chip manufacturer to design and produce a dedicated integrated circuit chip. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0105] The controller can be implemented in any appropriate manner, for example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (such as software or firmware) that can be executed by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that in addition to implementing the controller in a purely computer-readable program code manner, the controller can be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, this controller can be considered as a hardware component, and the devices included therein for implementing various functions can also be regarded as structures within the hardware component. Or even, the devices for implementing various functions can be regarded as both software modules for implementing the method and structures within the hardware component.

[0106] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0107] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0108] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0109] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0110] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0111] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0112] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0113] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0114] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0115] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0116] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0117] The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0118] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0119] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A motion detection method, characterized in that: The method is based on a wearable device and comprises: Under the condition that the user is in an effective exercise state, a first exercise level corresponding to the effective exercise state is determined according to the vital sign data of the user in the effective exercise state; and a second exercise level corresponding to the effective exercise state is determined according to the exercise data of the user in the effective exercise state; the first exercise level and / or the second exercise level at least show: the exercise intensity of the user when the user is in the effective exercise state; According to the first exercise level and the second exercise level, obtaining the exercise status information of the user in the effective exercise state; The obtaining, according to the first exercise level and the second exercise level, the exercise status information of the user in the effective exercise state includes: Determine the exercise status information of the user in the effective exercise state according to the maximum exercise intensity shown in the first exercise level and the second exercise level; Prior to the method, the method further includes: The motion state of the user is obtained based on the motion data; if the duration of an indicator parameter shown by the motion state of the user in a state greater than an indicator threshold corresponding to the indicator parameter is not less than a time threshold, it is determined that the motion state of the user is the valid motion state, and the indicator parameter is the modulus value of the acceleration shown by the motion state of the user.

2. The method according to claim 1, characterized in that Determining the first level of exercise corresponding to the effective exercise state according to the vital sign data of the user in the effective exercise state includes: determining the mean value of the vital sign data of the user in the effective exercise state; screening out the exercise level that matches the mean value of the vital sign data from preset exercise levels, and determining it as the first level of exercise corresponding to the effective exercise state; and / or, Determining the second level of exercise corresponding to the effective exercise state based on the exercise data of the user in the effective exercise state includes: determining the average of the exercise data of the user in the effective exercise state; and screening out the exercise level that matches the average of the exercise data from among the preset exercise levels, and determining it as the second level of exercise corresponding to the effective exercise state.

3. The method according to claim 1, characterized in that The obtaining, according to the first exercise level and the second exercise level, the exercise status information of the user in the effective exercise state further includes: According to the first exercise level and the second exercise level, obtaining the available exercise level of the user in the effective exercise state at this time as the exercise status information of the user in the effective exercise state; After the method, it also includes: The exercise status information of the user in the specified time period is obtained according to the available exercise levels of each effective state of each exercise in the specified time period.

4. The method according to any one of claims 1 to 3, characterized in that: The method is performed by a wearable device; The method further includes: displaying the motion status information on the wearable device; and / or sending the motion status information to an associated device that is communicatively connected to the wearable device, so that the associated device displays the motion status information.

5. A motion detection device, characterized in that: The device is used to implement the method according to any one of claims 1 to 4.

6. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 4 is implemented.

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