Adaptive tension adjustment method and system for wearable terminal

Abstract

The present application relates to the technical field of wearable devices, and discloses a method and system for adaptively adjusting tightness of a wearable terminal, the method comprising obtaining information on a user's daily routine, determining activity time periods corresponding to a number of daily activity states of the user, and generating a state time period form; obtaining the current time node and terminal dynamic data to determine the actual activity state of the user; obtaining the user's wrist circumference data, matching a target strap length and a positioning identifier of a corresponding available positioning structure based on the wrist circumference data and the actual activity state, and setting the target positioning identifier; generating a strap adjustment signal based on the target positioning identifier and sending the signal to the wearable terminal; the present application has the effect of improving the scientificity of tightness adjustment of the wearable terminal.

Description

Technical Field

[0001] The present application relates to the technical field of wearable devices, and in particular to a method and system for adaptively adjusting tightness of a wearable terminal. Background Art

[0002] With the development and popularization of intelligent devices, the categories and demands of wearable terminals are increasing, among which smart bracelets are widely used. At present, many smart bracelets have health detection functions, such as heart rate detection, blood oxygen saturation detection, blood pressure detection, breathing detection, sleep quality detection, exercise detection, etc., and most smart bracelets have the function of adjusting the tightness of the strap, and users can adjust the tightness of the strap according to their needs. However, if the strap is adjusted too loosely, it is easy to cause poor accuracy of human body data collected by the health detection function, while if the strap is adjusted too tight, it is easy to cause poor wearing comfort. Therefore, the above-mentioned related technologies have the problem that it is difficult for users to adjust the strap to an appropriate tightness. Summary of the invention

[0003] In order to improve the scientificity of tightness adjustment of a wearable terminal, the present application provides a method and system for adaptive tightness adjustment of a wearable terminal.

[0004] The first invention objective of this application is achieved by adopting the following technical solution:

[0005] The method for adaptively adjusting tightness of a wearable terminal includes:

[0006] Obtain the user's work and rest routine information, determine the activity time periods corresponding to the user's several daily activity states, and generate a state time period form;

[0007] Obtain the current time node and terminal dynamic data to determine the user's actual activity status;

[0008] Obtain the user's wrist circumference data, match the target watchband length and the corresponding positioning identifier of the available positioning structure based on the wrist circumference data and the actual activity state, and set it as the target positioning identifier;

[0009] Generate a strap adjustment signal based on the target positioning identifier and send it to the wearable terminal;

[0010] The wearable terminal is connected to an adjustable strap, and the adjustable strap is provided with a plurality of available positioning structures marked with corresponding positioning identifiers; the activity state includes a rest state, a motion state, a normal state, a health detection state and a charging state.

[0011] By adopting the above technical solution, the user's work and rest regularity information is obtained to determine the activity time periods corresponding to various activity states in the user's daily life, thereby generating a state time period form, wherein the activity states include resting state, exercise state, normal state, health detection state and charging state, so as to improve the accuracy of the user's actual activity state judgment in combination with the current time period, and plan the health detection time and the strap length of each time period for the user; the current time node and terminal dynamic data are obtained to determine the user's actual activity state according to the user's active state and the current time period; the user's wrist circumference data is obtained, and the target strap length suitable for the user's actual activity state is matched in combination with the wrist circumference data and the actual activity state, and the positioning identifier of the corresponding available positioning structure is determined and set as the target positioning identifier, so as to facilitate the subsequent adjustment of the strap length; based on the target positioning identifier, a strap adjustment signal is generated and sent to the wearable terminal, so that the user can know the target positioning identifier corresponding to the target strap length, so as to guide the user to adjust the strap to be fixed by a suitable available positioning structure, thereby improving the scientificity of the tightness adjustment of the wearable terminal.

[0012] In a preferred example of the present application, the user's work and rest regularity information is obtained, and the activity time periods corresponding to the user's several daily activity states are determined to generate a state time period form, including:

[0013] Receive the user's work and rest declaration information, and generate initial work and rest regularity information based on the work and rest declaration information;

[0014] Obtain the user's actual activity status in real time to generate some daily activity change information and add it to the activity status statistics form;

[0015] Determine the nature of the target date one by one, extract the preset number of latest single-day activity change information to be analyzed from the activity status statistics form for the nature of the target date, and perform fitting processing on each activity status and corresponding activity time period in the extracted single-day activity change information to update the work and rest regularity information;

[0016] Generate status period form based on the latest work and rest regularity information;

[0017] The work and rest declaration information refers to the work and rest plan information input by the user; the activity status statistics form stores all single-day activity change information in the most recent evaluation cycle according to different date properties; the date properties include starting working day, middle working day, ending working day, starting holiday, middle holiday, and ending holiday.

[0018] By adopting the above technical solution, when the user starts to use the wearable terminal, initial work and rest regularity information is generated based on the work and rest plan input by the user, so as to subsequently determine the user's activity status in different time periods; the user's actual activity status on each date is obtained in real time to generate a number of single-day activity change information, and stored in the activity status statistical form according to the date properties; the target date properties are determined one by one, and the latest single-day activity change information of the target date properties to be analyzed is extracted from the activity status statistical form, and the extracted single-day activity change information of the number to be analyzed is fitted, so as to update the work and rest regularity information according to the user's actual activity situation when using the wearable terminal; a status time period form is generated based on the latest generated work and rest regularity information, so as to improve the accuracy of the activity status and the corresponding activity time period recorded in the status time period form.

[0019] In a preferred example of the present application: the single-day activity change information records the activity status corresponding to all unit time periods of the day;

[0020] The step of fitting each activity state and the corresponding activity period in the extracted daily activity change information to update the work and rest regularity information includes:

[0021] Based on the extracted daily activity change information, the probability ratio of various activity states in each unit time period is counted, and the activity state with the largest probability ratio is set as the proposed activity state of the corresponding unit time period;

[0022] Based on the proposed activity status of each unit time period, determine the initial activity time period of each proposed activity status;

[0023] Determine the target activity state one by one from each of the proposed activity states, calculate the total duration and interval time of two adjacent primary activity periods corresponding to all the target activity states, determine the proposed activity state corresponding to the interval period and define it as the interval activity state;

[0024] Calculate the quotient of the interval time and the total duration as the interval ratio, and when the interval time is less than a preset first threshold and the interval ratio is less than a preset second threshold, merge two adjacent primary activity periods;

[0025] After merging / combining the primary activity time periods of all the proposed activity states, the secondary activity time periods of each proposed activity state are determined to update the work and rest regularity information;

[0026] If the two merged primary activity periods are not in the interval activity state before and after, the interval activity state is directly modified to the target activity state to merge the two primary activity periods;

[0027] If the two merged primary activity periods are in an interval activity state before / after, the interval period is moved forward / backward to merge the two primary activity periods.

[0028] By adopting the above technical scheme, the single-day activity change information records the activity status corresponding to all unit time periods of the day, which is convenient for determining the user's activity status on the day. Based on the extracted information of several single-day activity change information, the probability ratio of each unit time period in various activity statuses is counted, and the activity state with the largest probability ratio is set as the proposed activity state of the corresponding unit time period, so as to update the work and rest regularity information according to the user's historical activity status in the future; based on the proposed activity status of each unit time period, the initial activity time period of each proposed activity state in the date of the target date nature is determined; the target activity state is determined one by one from each proposed activity state, the total duration and interval time of the two adjacent initial activity time periods corresponding to all target activity states are calculated, and the proposed activity state corresponding to the interval time period is determined and defined as the interval activity state, so as to facilitate the subsequent Fitting processing is performed on activity states and activity periods; the quotient of the interval time and the total duration is calculated as the interval ratio. When the interval time is less than the first threshold and the interval ratio is less than the second threshold, it is necessary to perform the merging processing of the two primary activity periods. If the two primary activity periods to be merged are not in the interval activity state before and after, the simulated activity state of the interval period is directly modified to the target activity state, thereby completing the merging of the two primary activity periods. If the two primary activity periods to be merged are in the interval activity state before and / or after, the interval period is moved forward and / or backward, thereby completing the merging of the two primary activity periods and the merging of the interval periods. After the primary activity periods of all simulated activity states are merged / merged, the secondary activity periods of each simulated activity state are determined, thereby updating the work and rest regularity information.

[0029] In a preferred example of the present application: the step of obtaining the wrist circumference data of the user and matching the target watchband length and the corresponding positioning identifier of the available positioning structure based on the wrist circumference data and the actual activity state includes:

[0030] Obtaining a positioning mark corresponding to the positioning structure actually used by the adjustable strap to calculate the first strap length value;

[0031] Obtaining deformation data of the adjustable strap, and calculating the user's wrist circumference data based on the first strap length value and the deformation data;

[0032] Match the corresponding target looseness from the preset state looseness table based on the actual activity state, and calculate the corresponding target strap length based on the wrist circumference data and the target looseness;

[0033] Based on the combination of the basic length of the adjustable strap and the single-stage adjustment length, the number of single-stage adjustment lengths required to be closest to the target strap length is matched to determine the corresponding positioning mark of the available positioning structure and set it as the target positioning mark;

[0034] The adjustable strap is provided with a positioning detection sensor for detecting the positioning structure actually in use and a deformation detection sensor for detecting deformation data of the adjustable strap; the single-stage adjustment length refers to the strap length between each pair of adjacent positioning structures.

[0035] By adopting the above technical solution, the positioning mark corresponding to the current actual use positioning structure of the adjustable strap is obtained to calculate the current first strap length value of the adjustable strap; the deformation data of the adjustable strap is obtained, and the wrist circumference data of the user is calculated based on the sum of the first strap length value and the deformation data, so as to obtain and continuously update the wrist circumference data of the user without the user specifically measuring the wrist circumference; based on the actual activity state, the target looseness adapted to the actual activity state is matched from a preset state looseness form, and the corresponding target strap length is calculated based on the wrist circumference data and the target looseness, so as to facilitate determination of the tightness of the strap suitable for the actual activity state; based on several combinations of the basic length of the adjustable strap and the single-stage adjustment lengths between adjacent positioning structures, the number of single-stage adjustment lengths required to be closest to the target strap length is matched, so as to determine the positioning mark of the corresponding available positioning structure and set it as the target positioning mark, so as to facilitate subsequent guidance of the tightness adjustment of the strap.

[0036] In a preferred example of the present application, the acquisition of the current time node and the terminal dynamic data to determine the actual activity status of the user includes:

[0037] Get the current time node and enter it into the status period form to determine the corresponding basic status;

[0038] Obtain terminal dynamic data, and determine the user's actual activity status based on the terminal dynamic data and corresponding status change rules;

[0039] The terminal dynamic data includes data on the moving direction, moving speed, and moving acceleration of the wearable terminal; the state change rule records the rest change value range, exercise change value range, and state maintenance value range.

[0040] By adopting the above technical solution, the current time node is obtained, and combined with the status time period form, the basic status of the current time node is determined, which is convenient for subsequent determination of the actual activity status; the terminal dynamic data is obtained, and based on the terminal dynamic data and the corresponding status change rules, it is determined whether the basic status needs to be changed to determine the user's actual activity status, thereby improving the accuracy of the user's actual activity status.

[0041] The second invention objective of this application is achieved by the following technical solution:

[0042] The system for self-adapting tightness adjustment for a wearable terminal is applied to any one of the self-adapting tightness adjustment methods for a wearable terminal described above, comprising:

[0043] The status period form generation module is used to obtain the user's work and rest regularity information, determine the activity periods corresponding to the user's several daily activity states, and generate the status period form;

[0044] The actual activity status determination module is used to obtain the current time node and terminal dynamic data to determine the actual activity status of the user;

[0045] A strap length setting module, used to obtain the user's wrist circumference data, match the target strap length and the corresponding positioning identifier of the available positioning structure based on the wrist circumference data and the actual activity state, and set it as the target positioning identifier;

[0046] A strap adjustment signal generating module, used to generate a strap adjustment signal based on the target positioning identifier and send the signal to the wearable terminal;

[0047] The wearable terminal is connected to an adjustable strap, and the adjustable strap is provided with a plurality of available positioning structures marked with corresponding positioning identifiers; the activity state includes a rest state, a motion state, a normal state, a health detection state and a charging state.

[0048] In a preferred example of the present application: the status period form generation module includes:

[0049] The initial work and rest routine setting submodule is used to receive the work and rest routine declaration information of the user and generate the initial work and rest routine information based on the work and rest declaration information;

[0050] The actual activity status statistics submodule is used to obtain the user's actual activity status in real time to generate a number of daily activity change information and add it to the activity status statistics form;

[0051] The work and rest rule information update submodule is used to determine the target date properties one by one, extract the preset number of latest single-day activity change information to be analyzed for the target date properties from the activity status statistics form, and perform fitting processing on each activity state and the corresponding activity time period in the extracted single-day activity change information to update the work and rest rule information;

[0052] The status period determination submodule is used to generate a status period form based on the latest work and rest regularity information;

[0053] The work and rest declaration information refers to the work and rest plan information input by the user; the activity status statistics form stores all single-day activity change information in the most recent evaluation cycle according to different date properties; the date properties include starting working day, middle working day, ending working day, starting holiday, middle holiday, and ending holiday.

[0054] In a preferred example of the present application: the work and rest rule information updating submodule includes:

[0055] The proposed activity state setting submodule is used to count the probability proportions of various activity states in each unit time period based on the extracted single-day activity change information, and set the activity state with the largest probability proportion as the proposed activity state of the corresponding unit time period;

[0056] A primary activity time period determination submodule is used to determine the primary activity time period of each proposed activity state based on the proposed activity state of each unit time period;

[0057] The interval activity state determination submodule is used to determine the target activity state from each of the simulated activity states one by one, calculate the total duration and interval time of two adjacent primary activity periods corresponding to all the target activity states, determine the simulated activity state corresponding to the interval period and define it as the interval activity state;

[0058] A primary activity period merging submodule, used to calculate the quotient of the interval time and the total duration as the interval ratio, and when the interval time is less than a preset first threshold and the interval ratio is less than a preset second threshold, merge two adjacent primary activity periods;

[0059] The submodule for determining the secondary activity time period is used to determine the secondary activity time period of each proposed activity state after merging / merging the primary activity time periods of all proposed activity states to update the work and rest regularity information;

[0060] If the two merged primary activity periods are not in the interval activity state before and after, the interval activity state is directly modified to the target activity state to merge the two primary activity periods;

[0061] If the two primary activity periods to be merged are in an interval activity state before / after, the interval period is moved forward / backward to merge the two primary activity periods;

[0062] The single-day activity change information records the activity status corresponding to all unit time periods on that day.

[0063] The third invention objective of this application is achieved by the following technical solution:

[0064] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for adaptively adjusting tightness of a wearable terminal when executing the computer program.

[0065] The fourth invention objective of this application is achieved by the following technical solution:

[0066] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned method for adaptively adjusting tightness of a wearable terminal are implemented.

[0067] In summary, the present application includes at least one of the following beneficial technical effects:

[0068] 1. Obtain the user's work and rest routine information to determine the activity time periods corresponding to various activity states in the user's daily life, thereby generating a state time period form, where the activity states include resting state, exercise state, normal state, health detection state and charging state, so as to improve the accuracy of the user's actual activity state judgment in combination with the current time period, and plan the health detection time and the strap length of each time period for the user; obtain the current time node and terminal dynamic data to determine the user's actual activity state according to the user's active state and the current time period; obtain the user's wrist circumference data, combine the wrist circumference data and the actual activity state, match the target strap length suitable for the user's actual activity state, determine the corresponding positioning identifier of the available positioning structure and set it as the target positioning identifier, so as to facilitate the subsequent adjustment of the strap length; generate a strap adjustment signal based on the target positioning identifier and send it to the wearable terminal, so that the user can know the target positioning identifier corresponding to the target strap length, so as to guide the user to adjust the strap to be fixed by a suitable available positioning structure, thereby improving the scientificity of the wearable terminal tightness adjustment.

[0069] 2. When the user starts to use the wearable terminal, the initial work and rest routine information is generated based on the work and rest plan input by the user, so as to subsequently determine the user's activity status in different time periods; the user's actual activity status on each date is obtained in real time to generate a number of single-day activity change information, and stored in the activity status statistical form according to the date properties; the target date properties are determined one by one, and the latest single-day activity change information of the target date properties to be analyzed is extracted from the activity status statistical form, and the extracted single-day activity change information to be analyzed is fitted so as to update the work and rest routine information according to the user's actual activity situation when using the wearable terminal; a status time period form is generated based on the latest generated work and rest routine information, so as to improve the accuracy of the activity status and corresponding activity time period recorded in the status time period form.

[0070] 3. Obtain the positioning mark corresponding to the actual positioning structure currently in use of the adjustable strap to calculate the current first strap length value of the adjustable strap; obtain the deformation data of the adjustable strap, and calculate the user's wrist circumference data based on the sum of the first strap length value and the deformation data, so as to obtain and continuously update the user's wrist circumference data without the user specifically measuring the wrist circumference; based on the actual activity state, match the target looseness corresponding to the actual activity state from the preset state looseness form, and calculate the corresponding target strap length based on the wrist circumference data and the target looseness, so as to facilitate the determination of the strap tightness suitable for the actual activity state; based on several combinations of the basic length of the adjustable strap and the single-stage adjustment lengths between adjacent positioning structures, match the number of single-stage adjustment lengths required to be closest to the target strap length, so as to determine the positioning mark of the corresponding available positioning structure and set it as the target positioning mark, so as to facilitate the subsequent guidance of the tightness adjustment of the strap. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 This is a flow chart of a method for adaptively adjusting tightness of a wearable terminal in Embodiment 1 of the present application.

[0072] Figure 2 It is a principle block diagram of the tightness adaptive adjustment system for a wearable terminal in the second embodiment of the present application.

[0073] Figure 3 It is a schematic diagram of the equipment in Example 3 of the present application. DETAILED DESCRIPTION

[0074] The following is combined with Figures 1 to 3 This application is described in further detail. Embodiment 1

[0075] Reference Figure 1 The present application discloses a method for adaptively adjusting tightness of a wearable terminal, which specifically comprises the following steps:

[0076] S10: Acquire the user's work and rest regularity information, determine the activity time periods corresponding to the user's several daily activity states, and generate a state time period form.

[0077] In this embodiment, the wearable terminal is connected to an adjustable strap, and the adjustable strap is provided with several available positioning structures marked with corresponding positioning identifications; specifically, the adjustable strap can be a pin buckle type, a sliding adjustment type, or other fixed structures with graded adjustment or infinite adjustment. Taking the pin buckle type as an example, the available positioning structure can be a pinhole set on the strap, and each pinhole is marked with corresponding identification information; the activity state includes a rest state, a motion state, a normal state, a health detection state, and a charging state; among them, the normal state refers to a state other than the rest state, the motion state, the health detection state, and the charging state, the health detection state refers to a state in which the wearable terminal is required to perform user health detection work, and the charging state refers to the state when the wearable terminal is removed by the user.

[0078] Specifically, the user's work and rest routine information is obtained to determine the activity time periods corresponding to various activity states in the user's daily life, thereby generating a status time period form, where the activity states include resting state, exercise state, normal state, health detection state and charging state, so as to facilitate the subsequent combination of the current time period to improve the accuracy of judging the user's actual activity state, and plan the health detection time and the strap length for each time period for the user.

[0079] Wherein, in step S10, it includes:

[0080] S11: receiving the work and rest report information of the user, and generating initial work and rest regularity information based on the work and rest report information.

[0081] In this embodiment, the work and rest report information refers to the work and rest plan information input by the user, for example, 0:00 to 8:00 every day is the rest state, 8:00 to 9:00 is the exercise state, 9:00 to 18:00 is the daily state, etc.

[0082] Specifically, when the user starts to use the wearable terminal, initial work and rest regularity information is generated based on the work and rest plan input by the user, so as to subsequently determine the activity status of the user in different time periods.

[0083] S12: Acquire the actual activity status of the user in real time to generate a number of daily activity change information and add it to the activity status statistics form.

[0084] In this embodiment, the activity status statistics form stores all single-day activity change information in the most recent evaluation cycle according to different date properties; the single-day activity change information records the activity status corresponding to all unit time periods of the day. Preferably, a unit time period can be set to 1 minute, or it can be set to 5 minutes or other durations according to actual needs.

[0085] Specifically, the actual activity status of the user on each date is obtained in real time to generate a number of single-day activity change information, and the information is stored in an activity status statistical form according to the nature of the date.

[0086] S13: Determine the target date properties one by one, extract a preset number of the latest single-day activity change information to be analyzed from the activity status statistics form for the target date properties, and perform fitting processing on each activity status and the corresponding activity time period in the extracted single-day activity change information to update the work and rest regularity information.

[0087] In this embodiment, the date properties include the starting working day, the middle working day, the ending working day, the starting holiday, the middle holiday, and the ending holiday; for example, when the user works from Monday to Friday, Monday is the starting working day, Tuesday to Thursday are the middle working days, and Friday is the ending working day; when the user is on holiday from the 1st to the 7th of a month, the 1st is the starting holiday, the 7th is the ending holiday, and the 2nd to the 6th are the middle holidays, among which a single working day with holidays before and after is regarded as the ending working day, and two consecutive working days with holidays before and after are regarded as the starting working day and the ending working day, a single holiday with both working days before and after is regarded as the ending holiday, and two consecutive holidays with both working days before and after are regarded as the middle holiday and the ending holiday; the time node for dividing the date can be set to 3 a.m., or 1 hour after the sleep time set by the user.

[0088] The number to be analyzed refers to a value set for analyzing the activity status of the user in the target date properties. Preferably, the number to be analyzed can be set to 10, or different numbers to be analyzed can be set for different date properties. When the single-day activity change information extracted from the activity status statistics form for the target date properties is less than the number to be analyzed, the step of fitting the date properties and updating the work and rest information in S13 is skipped. After the fitting of the target date properties and the updating of the work and rest information are completed, the new target date properties are re-determined, and the step of S13 is re-executed until the fitting and updating of the work and rest information of all types of target date properties are completed.

[0089] Specifically, the target date properties are determined one by one, the latest single-day activity change information of the target date properties to be analyzed is extracted from the activity status statistics form, and the extracted single-day activity change information of the number to be analyzed is fitted so as to update the work and rest regularity information according to the user's actual activity situation when using the wearable terminal.

[0090] S14: Generate a status period form based on the latest work and rest regularity information.

[0091] Specifically, a status period form is generated based on the latest generated work and rest rule information, so as to improve the accuracy of the activity status and the corresponding activity period recorded in the status period form.

[0092] Wherein, in step S13, it includes:

[0093] S131: Based on the extracted daily activity change information, the probability ratios of various activity states in each unit time period are counted, and the activity state with the largest probability ratio is set as the simulated activity state of the corresponding unit time period.

[0094] Specifically, the daily activity change information records the activity status corresponding to all unit time periods of the day, which is convenient for determining the user's activity status on that day. Based on the extracted information of several daily activity change information, the probability ratio of each unit time period in various activity statuses is counted, and the activity state with the largest probability ratio is set as the simulated activity state of the corresponding unit time period, so as to subsequently update the work and rest regularity information according to the user's historical activity status; for example, in a unit time period [00:00, 00:05) of the ten extracted daily activity change information, there are 7 in the rest state, 1 in the exercise state, and 2 in the daily state, then the simulated activity state of the unit time period is set to the rest state.

[0095] S132: Based on the simulated activity status of each unit time period, determine the initial activity time period of each simulated activity status.

[0096] Specifically, based on the proposed activity status of each unit time period, the initial activity time period of each proposed activity status in the date of the target date nature is determined.

[0097] S133: Determine the target activity state one by one from each simulated activity state, calculate the total duration and interval time of two adjacent preliminary activity periods corresponding to all target activity states, determine the simulated activity state corresponding to the interval period and define it as the interval activity state.

[0098] In this embodiment, the interval period and interval activity status refer to the status temporarily set when executing the merge processing / merge judgment of the initial activity period. The interval period and interval activity status are a status relative to the initial activity period that needs to be merged / merged.

[0099] Specifically, the target activity state is determined one by one from each simulated activity state, the total duration and interval time of two adjacent primary activity periods corresponding to all target activity states are calculated, and the simulated activity state corresponding to the interval period is determined and defined as the interval activity state, so as to facilitate the subsequent fitting processing of the activity state and activity period; for example, when in a certain date property, the primary activity period in which the simulated activity state is the rest state includes [00:00, 03:00) and [03:05, 07:00), wherein the simulated activity state is the movement state, and the corresponding primary activity period is the period [03:00, 03:05), then [03:00, 03:05) is the interval period relative to the periods [00:00, 03:00) and [03:05, 07:00), and the corresponding movement state is the interval activity state; the corresponding total duration is 415 minutes, and the interval time is 5 minutes.

[0100] S134: Calculate the quotient of the interval time and the total duration as the interval ratio, and when the interval time is less than a preset first threshold and the interval ratio is less than a preset second threshold, merge two adjacent preliminary activity time periods.

[0101] In this embodiment, the first threshold refers to the threshold used for comparison with the interval time, and the duration of the first threshold is at least greater than one unit time period. Preferably, the first threshold can be set to 11 minutes; the second threshold refers to the threshold used for comparison with the interval ratio. Preferably, the second threshold can be set to 10%.

[0102] Since users may easily intersperse a longer period of a specific activity state with a shorter period of other types of activity states, such as getting up to go to the toilet during sleep at night or stretching during work breaks during the day, these states should not be considered as changes in the user's activity state.

[0103] Specifically, the quotient of the interval time and the total duration is calculated as the interval ratio. When the interval time is less than the first threshold and the interval ratio is less than the second threshold, it is necessary to perform the merging process of the two primary activity periods. Among them, if the two primary activity periods to be merged are not in the interval activity state before and after, the simulated activity state of the interval period is directly modified to the target activity state, thereby completing the merging of the two primary activity periods. If the two primary activity periods to be merged are in the interval activity state before and / or after, the interval period is moved forward and / or backward, thereby completing the merging of the two primary activity periods and the merging of the interval period.

[0104] If the two merged primary activity periods are not in the interval activity state before and after, the interval activity state is directly modified to the target activity state to merge the two primary activity periods.

[0105] If the two merged primary activity periods are in interval activity state before / after, the interval period will be moved forward / backward to merge the two primary activity periods. For example, the user is in exercise state at [20:00, 20:30) and [20:34, 21:00), and there is a short period of daily state at [20:30, 20:34) due to rest. The user is in daily state before and after [20:00, 21:00), then the interval period of daily state can be evenly distributed and transferred to the two exercise state. The two primary activity periods of the user's exercise state after merging are [20:02, 20:32) and [20:32, 20:58).

[0106] S135: After merging / merging judgment of the primary activity time periods of all the simulated activity states, the secondary activity time periods of each simulated activity state are determined to update the work and rest regularity information.

[0107] Specifically, after the primary activity time periods of all simulated activity states are merged / merged, the secondary activity time period of each simulated activity state is determined, thereby updating the work and rest pattern information; for example, when the two primary activity time periods of the user's exercise state are [20:02, 20:32) and [20:32, 20:58), the merged secondary activity time period is [20:02, 20:58).

[0108] S20: Acquire the current time node and terminal dynamic data to determine the actual activity status of the user.

[0109] Specifically, the current time node and terminal dynamic data are obtained to determine the user's actual activity status according to the user's active status and current time period.

[0110] Wherein, in step S20, it includes:

[0111] S21: Obtain the current time node and input it into the status period form to determine the corresponding basic status.

[0112] Specifically, the current time node is obtained, and combined with the status time period form, the basic status of the current time node is determined to facilitate the subsequent determination of the actual activity status.

[0113] S22: Acquire terminal dynamic data, and determine the actual activity status of the user based on the terminal dynamic data and corresponding status change rules.

[0114] In this embodiment, the terminal dynamic data includes data on the moving direction, moving speed, and moving acceleration of the wearable terminal. Parameters of heart rate and blood oxygen saturation can also be added as terminal dynamic data according to actual needs to improve the accuracy of judging the user's activity status; the state change rule records the rest change numerical range, the exercise change numerical range, and the state maintenance numerical range; the rest change numerical range refers to the value range of the terminal dynamic data when the user is changed from other states to the rest state, the exercise change numerical range refers to the value range of the terminal dynamic data when the user is changed from other states to the exercise state, and the state maintenance numerical range refers to the value range of the terminal dynamic data when the user maintains the current state.

[0115] Specifically, the terminal dynamic data is obtained, and based on the terminal dynamic data and the corresponding state change rules, it is determined whether the basic state needs to be changed to determine the actual activity state of the user, thereby improving the accuracy of the actual activity state of the user.

[0116] S30: Obtain the wrist circumference data of the user, match the target watchband length and the corresponding positioning identifier of the available positioning structure based on the wrist circumference data and the actual activity state, and set it as the target positioning identifier.

[0117] Specifically, the user's wrist circumference data is obtained, and the target strap length suitable for the user's actual activity status is matched in combination with the wrist circumference data and the actual activity status, and the positioning identifier of the corresponding available positioning structure is determined and set as the target positioning identifier to facilitate subsequent adjustment of the strap length.

[0118] Wherein, in step S30, it includes:

[0119] S31: Obtain a positioning mark corresponding to the positioning structure actually used by the adjustable watch strap to calculate a first watch strap length value.

[0120] In this embodiment, the adjustable watch strap is provided with a positioning detection sensor for detecting the positioning structure actually in use. Preferably, the positioning detection sensor may be a strain sensor provided at a plurality of available positioning structures, and the positioning structure actually in use is determined by detecting the deformation of the available positioning structure of the watch strap.

[0121] Specifically, a positioning mark corresponding to the currently actually used positioning structure of the adjustable watch strap is obtained to calculate the current first strap length value of the adjustable watch strap.

[0122] S32: Obtain deformation data of the adjustable strap, and calculate the user's wrist circumference data based on the first strap length value and the deformation data.

[0123] In this embodiment, the adjustable strap is provided with a deformation detection sensor for detecting deformation data of the adjustable strap, and the deformation data refers to the deformation length data of the adjustable strap measured by the deformation detection sensor; preferably, the deformation detection sensor may be a strain sensor arranged at the strap, which detects the deformation amount of the strap so as to assist in detecting the wrist circumference data of the user; the first strap length value and the deformation data both refer to the length at the contact surface between the adjustable strap and the user's wrist.

[0124] Specifically, the deformation data of the adjustable strap is obtained, and the wrist circumference data of the user is calculated based on the sum of the first strap length value and the deformation data, so as to obtain and continuously update the wrist circumference data of the user without the user specifically measuring the wrist circumference.

[0125] S33: matching a corresponding target looseness from a preset state looseness table based on the actual activity state, and calculating a corresponding target strap length based on the wrist circumference data and the target looseness.

[0126] In this embodiment, the state looseness table refers to a table used to match the user's activity state with the target looseness; the target looseness refers to the ratio of the target watchband length to the wrist circumference data.

[0127] Preferably, the target easing degrees corresponding to the resting state, the exercise state, the normal state, and the health detection state are 1.05, 0.95, 1.05, and 0.95, respectively, and may also be set to other values ​​according to actual needs.

[0128] Specifically, based on the actual activity state, the target looseness corresponding to the actual activity state is matched from the preset state looseness form, and the corresponding target strap length is calculated based on the wrist circumference data and the target looseness, so as to determine the strap tightness suitable for the actual activity state.

[0129] S34: Based on the combination of the basic length of the adjustable strap and the single-stage adjustment length, the number of single-stage adjustment lengths required to be closest to the target strap length is matched to determine the positioning mark of the corresponding available positioning structure and set it as the target positioning mark.

[0130] In this embodiment, the single-stage adjustment length refers to the length of the strap between each pair of adjacent positioning structures. For example, when the adjustable strap is a pin buckle type, the single-stage adjustment length is the length between two adjacent pinholes.

[0131] Specifically, based on several combinations of the basic length of the adjustable strap and the single-stage adjustment lengths between adjacent positioning structures, the number of single-stage adjustment lengths required to be closest to the target strap length is matched to determine the positioning mark of the corresponding available positioning structure and set it as the target positioning mark, so as to facilitate subsequent guidance on the tightness adjustment of the strap.

[0132] S40: Generate a strap adjustment signal based on the target positioning identifier and send it to the wearable terminal.

[0133] In this embodiment, the strap adjustment signal refers to a signal used to generate strap adjustment prompt information, and the strap adjustment signal is associated with a corresponding target positioning identifier.

[0134] Specifically, a strap adjustment signal is generated based on the target positioning identifier and sent to the wearable terminal, so that the user can know the target positioning identifier corresponding to the target strap length, so as to guide the user to adjust the strap to be fixed through a suitable available positioning structure, thereby improving the scientific nature of the tightness adjustment of the wearable terminal.

[0135] It should be understood that the serial numbers of the steps in the above embodiments do not imply a sequence of execution. The execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application. Embodiment 2

[0136] A system for adaptively adjusting tightness of a wearable terminal, which corresponds to the method for adaptively adjusting tightness of a wearable terminal in the above embodiment.

[0137] like Figure 2 As shown, the elasticity adaptive adjustment system for wearable terminals includes a state period form generation module, an actual activity state determination module, a strap length setting module and a strap adjustment signal generation module. The detailed description of each functional module is as follows:

[0138] The status period form generation module is used to obtain the user's work and rest regularity information, determine the activity periods corresponding to the user's several daily activity states, and generate the status period form;

[0139] The actual activity status determination module is used to obtain the current time node and terminal dynamic data to determine the actual activity status of the user;

[0140] A strap length setting module, used to obtain the user's wrist circumference data, match the target strap length and the corresponding positioning identifier of the available positioning structure based on the wrist circumference data and the actual activity state, and set it as the target positioning identifier;

[0141] The strap adjustment signal generation module is used to generate a strap adjustment signal based on the target positioning identifier and send it to the wearable terminal.

[0142] Among them, the status period form generation module also includes:

[0143] The initial work and rest routine setting submodule is used to receive the work and rest routine declaration information of the user and generate the initial work and rest routine information based on the work and rest declaration information;

[0144] The actual activity status statistics submodule is used to obtain the user's actual activity status in real time to generate a number of daily activity change information and add it to the activity status statistics form;

[0145] The work and rest rule information update submodule is used to determine the target date properties one by one, extract the preset number of latest single-day activity change information to be analyzed for the target date properties from the activity status statistics form, and perform fitting processing on each activity state and the corresponding activity time period in the extracted single-day activity change information to update the work and rest rule information;

[0146] The status period determination submodule is used to generate a status period form based on the latest work and rest regularity information.

[0147] Among them, the work and rest regularity information update submodule also includes:

[0148] The proposed activity state setting submodule is used to count the probability proportions of various activity states in each unit time period based on the extracted single-day activity change information, and set the activity state with the largest probability proportion as the proposed activity state of the corresponding unit time period;

[0149] A primary activity time period determination submodule is used to determine the primary activity time period of each proposed activity state based on the proposed activity state of each unit time period;

[0150] The interval activity state determination submodule is used to determine the target activity state from each of the simulated activity states one by one, calculate the total duration and interval time of two adjacent primary activity periods corresponding to all the target activity states, determine the simulated activity state corresponding to the interval period and define it as the interval activity state;

[0151] A primary activity period merging submodule, used to calculate the quotient of the interval time and the total duration as the interval ratio, and when the interval time is less than a preset first threshold and the interval ratio is less than a preset second threshold, merge two adjacent primary activity periods;

[0152] The submodule for determining the secondary activity time period is used to determine the secondary activity time period of each simulated activity state after merging the primary activity time periods of all simulated activity states to update the work and rest regularity information.

[0153] The actual activity state determination module further includes:

[0154] The basic state determination submodule is used to obtain the current time node and input it into the state period form to determine the corresponding basic state;

[0155] The actual activity evaluation submodule is used to obtain terminal dynamic data and determine the user's actual activity status based on the terminal dynamic data and the corresponding status change rules.

[0156] The strap length setting module further includes:

[0157] A first strap length value calculation submodule, used to obtain a positioning mark corresponding to the positioning structure actually used by the adjustable strap, so as to calculate a first strap length value;

[0158] A wrist circumference data calculation submodule, used to obtain deformation data of the adjustable strap, and calculate the user's wrist circumference data based on the first strap length value and the deformation data;

[0159] A target strap length calculation submodule, used to match the corresponding target looseness from a preset state looseness table based on the actual activity state, and calculate the corresponding target strap length based on the wrist circumference data and the target looseness;

[0160] The target positioning identifier setting submodule is used to match the number of single-stage adjustment lengths required to be closest to the target strap length based on the combination of the basic length of the adjustable strap and the single-stage adjustment length, so as to determine the positioning identifier of the corresponding available positioning structure and set it as the target positioning identifier.

[0161] For the specific limitations of the adaptive tightness adjustment system for wearable terminals, please refer to the limitations of the adaptive tightness adjustment method for wearable terminals in the above text, which will not be repeated here; the various modules in the above-mentioned adaptive tightness adjustment system for wearable terminals can be implemented in whole or in part by software, hardware and a combination thereof; the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules. Embodiment 3

[0162] A computer device, which may be a server, may have an internal structure as shown in Figure 3 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store work and rest regularity information, status time period forms, current time nodes, terminal dynamic data, actual activity status, wrist circumference data, target strap length, target positioning identification, strap adjustment signal, and other data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a method for adaptively adjusting tightness for a wearable terminal.

[0163] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0164] S10: Acquire the user's work and rest regularity information, determine the activity time periods corresponding to the user's several daily activity states, and generate a state time period form;

[0165] S20: Obtain the current time node and terminal dynamic data to determine the actual activity status of the user;

[0166] S30: Acquire the wrist circumference data of the user, match the target watchband length and the corresponding positioning identifier of the available positioning structure based on the wrist circumference data and the actual activity state, and set it as the target positioning identifier;

[0167] S40: Generate a strap adjustment signal based on the target positioning identifier and send it to the wearable terminal.

[0168] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0169] S10: Acquire the user's work and rest regularity information, determine the activity time periods corresponding to the user's several daily activity states, and generate a state time period form;

[0170] S20: Obtain the current time node and terminal dynamic data to determine the actual activity status of the user;

[0171] S30: Acquire the wrist circumference data of the user, match the target watchband length and the corresponding positioning identifier of the available positioning structure based on the wrist circumference data and the actual activity state, and set it as the target positioning identifier;

[0172] S40: Generate a strap adjustment signal based on the target positioning identifier and send it to the wearable terminal.

[0173] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink), DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0174] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0175] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments may still be modified, or some of the features thereof may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for adaptively adjusting tightness of a wearable terminal, characterized in that: include: Obtain the user's work and rest routine information, determine the activity time periods corresponding to the user's several daily activity states, and generate a state time period form; Obtain the current time node and terminal dynamic data to determine the user's actual activity status; Obtain the user's wrist circumference data, match the target watchband length and the corresponding positioning identifier of the available positioning structure based on the wrist circumference data and the actual activity state, and set it as the target positioning identifier; Generate a strap adjustment signal based on the target positioning identifier and send it to the wearable terminal; The wearable terminal is connected to an adjustable strap, and the adjustable strap is provided with a plurality of available positioning structures marked with corresponding positioning identifiers; the activity state includes a rest state, a motion state, a normal state, a health detection state and a charging state; The obtaining of the current time node and terminal dynamic data to determine the actual activity status of the user includes: Get the current time node and enter it into the status period form to determine the corresponding basic status; The terminal dynamic data is obtained, and the actual activity status of the user is determined based on the terminal dynamic data and the corresponding state change rules; the terminal dynamic data includes the data of the movement direction, movement speed, and movement acceleration of the wearable terminal; the state change rules record the rest change value range, exercise change value range, and state maintenance value range.

2. The method for adaptively adjusting tightness of a wearable terminal according to claim 1, characterized in that: The step of obtaining the user's work and rest regularity information and determining the activity time periods corresponding to the user's several daily activity states to generate a state time period form includes: Receive the user's work and rest declaration information, and generate initial work and rest regularity information based on the work and rest declaration information; The actual activity status of the user is obtained in real time to generate a number of single-day activity change information and add them to the activity status statistical form; the target date properties are determined one by one, and a preset number of the latest single-day activity change information to be analyzed are extracted from the activity status statistical form for the target date properties, and each activity status and the corresponding activity time period in the extracted single-day activity change information are fitted to update the work and rest regularity information; Generate status period form based on the latest work and rest regularity information; The work and rest declaration information refers to the work and rest plan information input by the user; the activity status statistics form stores all single-day activity change information in the most recent evaluation cycle according to different date properties; the date properties include starting working day, middle working day, ending working day, starting holiday, middle holiday, and ending holiday.

3. The method for adaptively adjusting tightness of a wearable terminal according to claim 2, characterized in that: The single-day activity change information records the activity status corresponding to all unit time periods of the day; The step of fitting each activity state and the corresponding activity period in the extracted daily activity change information to update the work and rest regularity information includes: Based on the extracted daily activity change information, the probability ratios of various activity states in each unit time period are counted, and the activity state with the largest probability ratio is set as the proposed activity state for the corresponding unit time period; Based on the proposed activity status of each unit time period, determine the initial activity time period of each proposed activity status; Determine the target activity state one by one from each of the proposed activity states, calculate the total duration and interval time of two adjacent preliminary activity periods corresponding to all the target activity states, determine the proposed activity state corresponding to the interval period and define it as the interval activity state; calculate the quotient of the interval time and the total duration as the interval ratio, and when the interval time is less than a preset first threshold and the interval ratio is less than a preset second threshold, merge the two adjacent preliminary activity periods; After merging / combining the primary activity time periods of all the proposed activity states, the secondary activity time periods of each proposed activity state are determined to update the work and rest regularity information; If the two merged primary activity periods are not in the interval activity state before and after, the interval activity state is directly modified to the target activity state to merge the two primary activity periods; If the two merged primary activity periods are in an interval activity state before / after, the interval period is moved forward / backward to merge the two primary activity periods.

4. The method for adaptively adjusting tightness of a wearable terminal according to claim 1, characterized in that: The step of obtaining the wrist circumference data of the user and matching the target watchband length and the corresponding positioning identifier of the available positioning structure based on the wrist circumference data and the actual activity state includes: Obtaining a positioning mark corresponding to the positioning structure actually used by the adjustable strap to calculate the first strap length value; Obtaining deformation data of the adjustable strap, and calculating the user's wrist circumference data based on the first strap length value and the deformation data; Match the corresponding target looseness from the preset state looseness table based on the actual activity state, and calculate the corresponding target strap length based on the wrist circumference data and the target looseness; Based on the combination of the basic length of the adjustable strap and the single-stage adjustment length, the number of single-stage adjustment lengths required to be closest to the target strap length is matched to determine the corresponding positioning mark of the available positioning structure and set it as the target positioning mark; The adjustable strap is provided with a positioning detection sensor for detecting the positioning structure actually in use and a deformation detection sensor for detecting deformation data of the adjustable strap; the single-stage adjustment length refers to the strap length between each pair of adjacent positioning structures.

5. A self-adaptive adjustment system for a wearable terminal, characterized in that: The method for adaptively adjusting tightness of a wearable terminal as claimed in any one of claims 1 to 4 comprises: The status period form generation module is used to obtain the user's work and rest regularity information, determine the activity periods corresponding to the user's several daily activity states, and generate the status period form; The actual activity status determination module is used to obtain the current time node and terminal dynamic data to determine the actual activity status of the user; A strap length setting module, used to obtain the user's wrist circumference data, match the target strap length and the corresponding positioning identifier of the available positioning structure based on the wrist circumference data and the actual activity state, and set it as the target positioning identifier; A strap adjustment signal generating module, used for generating a strap adjustment signal based on a target positioning identifier and sending the signal to a wearable terminal; the wearable terminal is connected to an adjustable strap, and the adjustable strap is provided with a plurality of available positioning structures marked with corresponding positioning identifiers; the activity state includes a resting state, a moving state, a normal state, a health detection state and a charging state; The actual activity state determination module further includes: The basic state determination submodule is used to obtain the current time node and input it into the state period form to determine the corresponding basic state; The actual activity evaluation submodule is used to obtain terminal dynamic data and determine the user's actual activity status based on the terminal dynamic data and the corresponding status change rules; The terminal dynamic data includes data on the moving direction, moving speed, and moving acceleration of the wearable terminal; the state change rule records the rest change value range, exercise change value range, and state maintenance value range.

6. The self-adaptive tightness adjustment system for a wearable terminal according to claim 5, characterized in that: The status period form generation module includes: The initial work and rest routine setting submodule is used to receive the work and rest routine declaration information of the user and generate the initial work and rest routine information based on the work and rest declaration information; The actual activity status statistics submodule is used to obtain the user's actual activity status in real time to generate a number of daily activity change information and add it to the activity status statistics form; The work and rest rule information update submodule is used to determine the target date properties one by one, extract the preset number of latest single-day activity change information to be analyzed for the target date properties from the activity status statistics form, and perform fitting processing on each activity state and the corresponding activity time period in the extracted single-day activity change information to update the work and rest rule information; The status period determination submodule is used to generate a status period form based on the latest work and rest regularity information; The work and rest declaration information refers to the work and rest plan information input by the user; the activity status statistics form stores all single-day activity change information in the most recent evaluation cycle according to different date properties; the date properties include starting working day, middle working day, ending working day, starting holiday, middle holiday, and ending holiday.

7. The self-adaptive tightness adjustment system for a wearable terminal according to claim 6, characterized in that: The work and rest rule information updating submodule includes: The proposed activity state setting submodule is used to count the probability proportions of various activity states in each unit time period based on the extracted single-day activity change information, and set the activity state with the largest probability proportion as the proposed activity state of the corresponding unit time period; A primary activity time period determination submodule is used to determine the primary activity time period of each proposed activity state based on the proposed activity state of each unit time period; The interval activity state determination submodule is used to determine the target activity state from each of the simulated activity states one by one, calculate the total duration and interval time of two adjacent primary activity periods corresponding to all the target activity states, determine the simulated activity state corresponding to the interval period and define it as the interval activity state; The primary activity period merging submodule is used to calculate the quotient of the interval time and the total duration as the interval ratio. When the interval time is less than the preset first threshold and the interval ratio is less than the preset second threshold, two adjacent primary activity periods are merged; the secondary activity period determination submodule is used to perform a merging process / merging judgment on the primary activity periods of all the simulated activity states, and then determine the secondary activity periods of each simulated activity state to update the work and rest regularity information; If the two merged primary activity periods are not in the interval activity state before and after, the interval activity state is directly modified to the target activity state to merge the two primary activity periods; If the two primary activity periods to be merged are in an interval activity state before / after, the interval period is moved forward / backward to merge the two primary activity periods; The single-day activity change information records the activity status corresponding to all unit time periods on that day.

8. A computer 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 computer program, the steps of the method for adaptively adjusting tightness for a wearable terminal as described in any one of claims 1 to 4 are implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for adaptively adjusting tightness for a wearable terminal as claimed in any one of claims 1 to 4 are implemented.

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