CN112561468A - Sleep-in reminding method and device, readable storage medium and computer equipment - Google Patents
Sleep-in reminding method and device, readable storage medium and computer equipment Download PDFInfo
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Abstract
The present disclosure relates to the technical field of sleep reminding, and in particular, to a sleep reminding method, an apparatus, a readable storage medium, and a computer device, wherein the method includes: acquiring recommended sleep duration of a user; acquiring a preset alarm clock time, and acquiring a recommended sleep time based on a difference value between the preset alarm clock time and the recommended sleep time; reminding the user to fall asleep at a sleep reminding time before the recommended sleep time; according to the method and the device, the recommended sleep-in time is obtained through the difference value between the preset alarm clock time and the recommended sleep time, and the user is reminded to fall asleep at the sleep-in reminding time before the recommended sleep-in time, so that the technical problem that the sleep-in reminding function is not intelligent enough in the prior art is solved, and the technical effects of setting the personalized sleep-in reminding time for different users and guaranteeing the sleep time and the sleep quality of the users are achieved.
Description
Technical Field
The present disclosure relates to the technical field of sleep reminding, and in particular, to a sleep reminding method, an apparatus, a readable storage medium, and a computer device.
Background
With the development of entertainment functions of electronic devices, users gradually lose time control. For example, it is obvious that the user needs to go to work and study in the morning, but the user is addicted in electronic equipment such as a computer and a mobile phone and cannot pull out the mobile phone, and the user holds the mobile phone to brush the user in the late night. The above situation easily causes the user to have poor spirit state on the next day. In the past, the lack of sleep not only seriously affects the work and study efficiency of the user, but also may bring about various health problems. Therefore, many users wish to change the habit of sleeping late, but do not know when to fall asleep, start to prepare at that time, and lack the continence to stay asleep.
At present, most of devices such as mobile terminals have an alarm clock function, and a user can set an alarm clock according to needs to prompt the user to get up or fall asleep. However, the simple reminding function realized by only setting the alarm clock by the user is not intelligent enough, and intelligent reminding is not provided for different users.
Therefore, there is a need in the art for an intelligent sleep reminding scheme to improve the sleep quality of a user, so as to scientifically guide the user to sleep.
Disclosure of Invention
The utility model provides a sleep reminding method, a sleep reminding device, a readable storage medium and a computer device, which solves the technical problems that the sleep reminding function in the prior art is not intelligent enough and the sleep quality of a user cannot be improved, so that the user is guided to sleep scientifically.
In a first aspect, the present disclosure provides a sleep reminding method, including:
acquiring recommended sleep duration of a user;
acquiring a preset alarm clock time, and acquiring a recommended sleep time based on a difference value between the preset alarm clock time and the recommended sleep time;
and reminding the user to fall asleep at a sleep reminding time before the recommended sleep time.
In some embodiments, the step of obtaining the recommended sleep duration of the user includes:
acquiring a recommended sleep time corresponding to the age of the user.
In some embodiments, the step of obtaining the recommended sleep duration of the user includes:
determining recommended sleep duration according to the user sleep information and the user fatigue value; the user sleep information comprises a previous-day falling sleep time length, a previous-day light sleep time length and a previous-day deep sleep time length.
In some embodiments, the step of determining the recommended sleep duration according to the user sleep information and the user fatigue value includes:
obtaining the sleep duration of the previous day according to the sleep information of the user;
acquiring a user fatigue value;
and correcting the sleep duration of the previous day based on the user fatigue value to obtain the recommended sleep duration.
In some embodiments, the obtaining the user fatigue value includes:
acquiring a feedback fatigue value, a user bed-staying time length and a detection fatigue value;
calculating a user fatigue value by adopting a first calculation formula; the first calculation formula is: p ═ i + j + k)/3;
wherein p represents a user fatigue value, i represents a feedback fatigue value, j represents a user bed-staying duration, and k represents a detection fatigue value.
In some embodiments, the obtaining the user fatigue value includes:
and acquiring a feedback fatigue value sent by a user through a terminal.
In some embodiments, the step of modifying the previous day sleep duration based on the user fatigue value comprises:
s10, calculating the deep sleep ratio through a deep sleep ratio calculation formula;
the deep sleep proportion calculation formula is as follows: v ═ S/(S + Q);
wherein v is the deep sleep proportion, S is the deep sleep time length of the previous day, and Q is the light sleep time length of the previous day;
s11, if the deep sleep proportion is larger than or equal to a first proportion value and the sleep time length of the previous day is larger than or equal to the recommended sleep time length corresponding to the age of the user, correcting the deep sleep proportion through a first correction formula;
the first correction formula is as follows: z ═ T + (Q + S) (1+ p);
wherein Z is recommended sleep time, T is sleep time of the previous day, and p is a user fatigue value;
s12, if the deep sleep proportion is larger than or equal to the first proportion value and the sleep time length of the previous day is smaller than the recommended sleep time length corresponding to the age of the user, correcting the deep sleep proportion through a second correction formula;
the second correction formula is as follows: z is A;
wherein A is the recommended sleep duration corresponding to the age of the user;
s13, if the deep sleep proportion is smaller than the first proportion value and the previous day sleep time length is larger than or equal to the recommended sleep time length corresponding to the age of the user, correcting the user through a third correction formula;
the third correction formula is as follows: z ═ a (1+ p);
s14, if the deep sleep proportion is smaller than the first proportion value and the sleep time length of the previous day is smaller than the recommended sleep time length corresponding to the age of the user, correcting the user by a fourth correction formula;
the fourth correction formula is as follows: z ═ T + (Q + S) (1+ p)) (1+ (0.2-v) × 5).
In some embodiments, the method further comprises:
monitoring whether the user falls asleep or not after the recommended sleep-falling time;
if the user does not fall asleep, reminding the user to fall asleep, and executing the step of monitoring whether the user falls asleep again after the first preset time.
In some embodiments, the sleep onset reminding time is a second preset time, a third preset time, and/or a fourth preset time before the sleep onset recommended time.
In some embodiments, the step of reminding the user to fall asleep at a sleep reminding time before the recommended sleep time includes:
and when the sensor detects that the user is influencing the sleep action, reminding the user to fall asleep every fifth preset time.
In some embodiments, the obtaining the recommended sleep duration of the user further includes:
acquiring recommended sleep time of preset days;
and averaging the recommended sleep time of the preset days to be used as the recommended sleep time of the user.
In some embodiments, when the user is reminded to fall asleep at the sleep reminding time, preset content is played.
In a second aspect, the present disclosure provides a sleep reminding device, comprising:
the device comprises an acquisition unit, a processing unit and a control unit, wherein the acquisition unit is used for acquiring the recommended sleep time of a user;
the recommending unit is used for acquiring a preset alarm clock time and obtaining a recommended sleep-in time based on a difference value between the preset alarm clock time and the recommended sleep duration;
and the reminding unit is used for reminding the user of falling asleep at the sleep-falling reminding time before the recommended sleep-falling time.
In a third aspect, the present disclosure provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of the first aspect.
In a fourth aspect, the present disclosure provides a computer device comprising a processor and a memory, the memory having stored thereon a computer program which, when executed by the processor, implements the method of the first aspect.
According to the sleep reminding method, the sleep reminding device, the readable storage medium and the computer equipment, the recommended sleep duration of a user is obtained; acquiring a preset alarm clock time, and acquiring a recommended sleep time based on a difference value between the preset alarm clock time and the recommended sleep time; and reminding the user to fall asleep at a sleep reminding time before the recommended sleep time.
The method and the device predict the recommended sleep time in time according to the age, the sleep habit and the getting-up time of the user, judge the sleep quality of the user by monitoring the required sleep time, the sleep quality, the light sleep time and the deep sleep time of the user, and update the personalized recommended sleep time of the user in time according to the fatigue degree fed back by the user after getting-up, thereby achieving the function of personalized multi-round voice sleep prompt.
The multi-turn voice prompt system helps a user to enter a sleep preparation state and a sleep falling state earlier through the multi-turn voice prompt function, and when the user does not fall asleep in time, the user is reminded of falling asleep every five minutes. And calculating the total sleep time required by the user by combining the age of the user, the monitored time length required by the user to fall asleep, the light sleep time and the deep sleep time and the next day fatigue degree feedback of the user. And performing multi-turn voice prompt 30 minutes before the time when the user falls asleep, and performing voice prompt once every 5 minutes when detecting that the user is busy in other things in the time, thereby realizing personalized multi-turn asleep prompt.
According to the method and the device, the recommended sleep-in time is obtained through the difference value between the preset alarm clock time and the recommended sleep time, and the user is reminded to fall asleep at the sleep-in reminding time before the recommended sleep-in time, so that the technical problem that the sleep-in reminding function is not intelligent enough in the prior art is solved, and the technical effects of setting the personalized sleep-in reminding time for each user and guaranteeing the sleep time and the sleep quality of the user are achieved.
Drawings
The present disclosure will be described in more detail hereinafter on the basis of embodiments and with reference to the accompanying drawings:
fig. 1 is a schematic flow chart of a sleep reminding method according to an embodiment of the present disclosure;
fig. 2 is a block diagram of a sleep reminding device according to an embodiment of the present disclosure;
fig. 3 is a schematic flow chart of another sleep onset reminding method provided in the embodiment of the present disclosure;
FIG. 4 illustrates an initial setup flow diagram of an application scenario;
fig. 5 is a block diagram of a computer device according to an embodiment of the present disclosure.
In the drawings, like parts are designated with like reference numerals, and the drawings are not drawn to scale.
Detailed Description
In order to make those skilled in the art better understand the disclosure and how to implement the disclosure by applying technical means to solve the technical problems and achieve the corresponding technical effects, the technical solutions in the embodiments of the disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the disclosure, and it is obvious that the described embodiments are only partial embodiments of the disclosure, but not all embodiments. The embodiments and the features of the embodiments of the present disclosure can be combined with each other without conflict, and the formed technical solutions are all within the protection scope of the present disclosure. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
Example one
Fig. 1 is a schematic flow chart of a sleep-onset reminding method according to an embodiment of the present disclosure. As shown in fig. 1, a method for reminding falling asleep includes:
acquiring recommended sleep duration of a user;
acquiring a preset alarm clock time, and acquiring a recommended sleep time based on a difference value between the preset alarm clock time and the recommended sleep time;
and reminding the user to fall asleep at a sleep reminding time before the recommended sleep time.
Wherein the recommended sleep time length is an optimal sleep time length suitable for the user. The preset alarm time is set by the user when the scheme of the present disclosure is first used, or modified in use. The recommended sleep time is the time suitable for the user to start sleeping, and the user can be ensured to have proper sleep duration and sleep proportion when getting up at the alarm clock time of the next day. The sleep-in reminding time is one or more times before the recommended sleep-in time, and at the sleep-in reminding time, an environment suitable for the user to sleep is created through measures such as acousto-optic taste and the like. It will be appreciated that in some cases, the user may also set a painless wake mode.
According to the embodiment, the recommended sleep-in time is obtained by presetting the alarm clock time and the difference value of the recommended sleep time, and the user is reminded to fall asleep at the sleep-in reminding time before the recommended sleep-in time, so that the technical problem that the sleep-in reminding function is not intelligent enough in the prior art is solved, and the technical effects of setting the personalized sleep-in reminding time for different users and guaranteeing the sleep time and the sleep quality of the user are achieved.
Example two
On the basis of the above embodiment, the step of obtaining the recommended sleep duration of the user includes:
acquiring a recommended sleep time corresponding to the age of the user.
Fig. 4 shows a flow chart of initial setup of an application scenario. In this embodiment, the user registers through the terminal when using for the first time, inputs personal information and age, and selects preset sleep-aid content from the played material library to remind the user to play when falling asleep. In addition, the user needs to input the time to get up the next day to preset the alarm time.
When the user data is received for the first time, due to the lack of the user sleep data, specific personalized parameters such as recommended sleep duration and the like cannot be obtained from the user data. However, based on the age information of the user, the average required sleep time length a of the age group can be obtained by combining network query, and the average required sleep time length a of the age group is taken as the recommended sleep time length.
In the embodiment, the corresponding recommended sleep time length can be obtained by obtaining the age of the user when the method is applied for sleep reminding for the first time, the recommended sleep time length of the user meets the sleep requirement of the age of the user, and the user is guaranteed to have enough sleep length.
EXAMPLE III
On the basis of the above embodiment, the step of obtaining the recommended sleep duration of the user includes:
determining recommended sleep duration according to the user sleep information and the user fatigue value; the user sleep information comprises a previous-day falling sleep time length, a previous-day light sleep time length and a previous-day deep sleep time length.
The time length of falling asleep in the previous day, the time length of shallow sleeping in the previous day and the time length of deep sleeping in the previous day can be obtained through monitoring and collection, after the user uses the sleep reminding function, the recommended sleeping time length of the second day (namely the current day) is predicted through the collected time length T of falling asleep in the previous day, the time length Q of shallow sleeping in the previous day of the user, the time length S of deep sleeping in the previous day of the user and the user fatigue value p, and therefore the recommended sleeping time is obtained based on the difference value between the preset alarm clock time and the recommended sleeping time length.
According to the embodiment, the recommended sleep time is determined by combining the previous-day falling asleep time, the previous-day light sleeping time, the previous-day deep sleeping time and the user fatigue value, so that the technical effects of providing personalized sleep time and recommended falling asleep time for the user are achieved.
Example four
On the basis of the above embodiment, the step of determining the recommended sleep duration according to the user sleep information and the user fatigue value includes:
obtaining the sleep duration of the previous day according to the sleep information of the user;
acquiring a user fatigue value;
and correcting the sleep duration of the previous day based on the user fatigue value to obtain the recommended sleep duration.
Specifically, the previous-day sleeping time period T can be obtained by collecting the previous-day sleeping time period, the previous-day light sleeping time period, and the previous-day deep sleeping time period, and the previous-day sleeping time period is corrected by the acquired user fatigue value p, so that the recommended sleeping time period on the second day (that is, the current day) is predicted, and the recommended sleeping time period is obtained based on the difference between the preset alarm clock time and the recommended sleeping time period. Wherein, the user fatigue value p can reflect the fatigue degree when the user wakes up the next day.
According to the embodiment, the previous-day sleep duration is corrected based on the user fatigue value, and the recommended sleep duration can be corrected according to the fatigue degree of the user, so that the recommended sleep duration of the next day meets the requirements of the user, and the intelligent recommendation effect is achieved.
EXAMPLE five
On the basis of the above embodiment, the obtaining of the user fatigue value includes:
acquiring a feedback fatigue value, a user bed-staying time length and a detection fatigue value;
calculating a user fatigue value by adopting a first calculation formula; the first calculation formula is: p ═ i + j + k)/3;
wherein p represents a user fatigue value, i represents a feedback fatigue value, j represents a user bed-staying duration, and k represents a detection fatigue value.
The feedback fatigue value is a quantized value of the fatigue degree fed back by a user through electronic equipment such as a terminal after getting up, for example, the score range which can be selected by the user is 0-5, the fatigue degree is shown from light to heavy from low to high, and the score selected by the user is proportionally scaled to a preset interval [0, 0.15 ]; the user bed-staying time length can be obtained by the difference value between the preset alarm clock time and the user bed-up time, or the difference value between the preset alarm clock time and the user waking time; the detection fatigue value can be obtained by detecting the state of the user after getting up by detection equipment such as a millimeter wave radar, a vision sensor and the like. After the feedback fatigue value, the user bed-staying duration and the detection fatigue value are obtained, averaging the feedback fatigue value, the user bed-staying duration and the detection fatigue value to obtain a user fatigue value which accurately reflects the user fatigue degree. As a preferable example, the bed-dependent time duration may be obtained by counting the time for the user to delay getting-up and scaling the time for the user to delay getting-up to a preset interval, for example, when the user delays getting-up and the time duration of the delay is within 0-1.5 hours, scaling the user bed-dependent time duration j to the [0, 0.15] interval according to the time duration of the delay; when the delay time exceeds 1.5 hours, the value of j is 0.15. The detected fatigue value can be obtained by a machine vision measurement mode, for example, the facial state of the user after getting up can be collected by vision collection on an air conditioner or by app through a mobile phone camera, so as to obtain the detected fatigue value k. Similarly, the detection fatigue value can be zoomed to the [0, 0.15] interval, that is, when the detection fatigue value is in the range of 0-1.5, the detection fatigue value k is zoomed to the [0, 0.15] interval, when the detection fatigue value k exceeds 1.5, k is 1.5, and by zooming the feedback fatigue value i, the bed-dependent time j of the user and the detection fatigue value k to the same preset interval, the dimension can be unified, the calculation of the user fatigue value is convenient, and the fatigue degree of the user can be accurately reflected.
According to the embodiment, the user fatigue value is obtained by feeding back the fatigue value, the user bed-staying time and the detection fatigue value, the subjective feedback fatigue degree and the objective fatigue degree of the user are reflected to the correction of the recommended sleep time, and the technical effect of providing the personalized sleep time and the recommended sleep time for the user is finally achieved.
EXAMPLE six
On the basis of the above embodiment, the obtaining of the user fatigue value includes:
and acquiring a feedback fatigue value sent by a user through a terminal.
In this embodiment, the user can score his or her fatigue degree through the terminal after getting up, for example, the score range that the user can select is 0-5, the fatigue degree is from light to heavy as from low to high, and the score selected by the user is scaled to a preset interval. The preset interval can be set according to actual requirements, but the fatigue degree of the user after sleeping is not too high, so that the user can only fluctuate within a small fatigue degree range, and the preset interval is reasonably set to be [0, 0.15 ].
EXAMPLE seven
On the basis of the foregoing embodiment, the step of correcting the sleep duration of the previous day based on the user fatigue value includes:
s10, calculating the deep sleep ratio through a deep sleep ratio calculation formula;
the deep sleep proportion calculation formula is as follows: v ═ S/(S + Q);
wherein v is the deep sleep proportion, S is the deep sleep time length of the previous day, and Q is the light sleep time length of the previous day;
s11, if the deep sleep proportion is larger than or equal to a first proportion value and the sleep time length of the previous day is larger than or equal to the recommended sleep time length corresponding to the age of the user, correcting the deep sleep proportion through a first correction formula;
the first correction formula is as follows: z ═ T + (Q + S) (1+ p);
wherein Z is recommended sleep time, T is sleep time of the previous day, and p is a user fatigue value;
s12, if the deep sleep proportion is larger than or equal to the first proportion value and the sleep time length of the previous day is smaller than the recommended sleep time length corresponding to the age of the user, correcting the deep sleep proportion through a second correction formula;
the second correction formula is as follows: z is A;
wherein A is the recommended sleep duration corresponding to the age of the user;
s13, if the deep sleep proportion is smaller than the first proportion value and the previous day sleep time length is larger than or equal to the recommended sleep time length corresponding to the age of the user, correcting the user through a third correction formula;
the third correction formula is as follows: z ═ a (1+ p);
s14, if the deep sleep proportion is smaller than the first proportion value and the sleep time length of the previous day is smaller than the recommended sleep time length corresponding to the age of the user, correcting the user by a fourth correction formula;
the fourth correction formula is as follows: z ═ T + (Q + S) (1+ p)) (1+ (0.2-v) × 5).
When the previous day sleep time length is corrected based on the user fatigue value, firstly, the sleep condition of the user is acquired, for example, the deep sleep proportion v of the user and the recommended sleep time length A corresponding to the age of the user are acquired. In the present embodiment, the deep sleep ratio is a ratio of the previous-day deep sleep time period to the previous-day sleep time period. It is understood that the previous-day sleep time period may be the sum of the previous-day deep sleep time period and the previous-day light sleep time period, and may also be the sum of the previous-day falling sleep time period, the previous-day deep sleep time period and the previous-day light sleep time period.
Wherein the first proportional value may be set to 20%, and after the deep sleep proportion v of the user and the recommended sleep time length a corresponding to the age of the user are obtained, the policy for correcting the previous-day sleep time length is determined based on the relationship between the deep sleep proportion v and the first proportional value and the relationship between the recommended sleep time length a corresponding to the age of the user and the previous-day sleep time length.
After a user lies down and calms down, detecting the sleep condition of the user through a sensor, and recording the time taken by the user to fall asleep, the light sleep time of the user and the deep sleep time of the user as parameters for calculating the personalized sleep reminding; on the basis, the recommended sleeping time length of the next day is predicted by using the user fatigue value as a calibration coefficient. The deep sleep ratio is obtained by the user light sleep time and the user deep sleep time, for example, the sleep time is normal when the deep sleep ratio is between 20% and 40%, and if the sleep time is less than 20%, the sleep time is increased appropriately.
In the embodiment, the sleep time a to be kept for each age group is obtained through scientific data, the sleep time a is compared with the actual total sleep time, then the sleep quality is judged through the deep sleep proportion, when the deep sleep proportion is lower than 20%, the sleep quality is poor, and at the moment, the total sleep time is increased appropriately. In addition, individual differences of each person are fed back through the user fatigue value, so that the recommended sleep time length is calibrated more humanely.
In the present embodiment, when the deep sleep ratio is low, the total sleep time period is increased within a certain limit according to the user fatigue value. In addition, if the sleep duration of the user reaches the standard and the deep sleep proportion is low after long-term monitoring, online consultation, medical recommendation, nerve calming products and the like can be pushed to the user.
Example eight
On the basis of the above embodiment, the method further includes:
monitoring whether the user falls asleep or not after the recommended sleep-falling time;
if the user does not fall asleep, reminding the user to fall asleep, and executing the step of monitoring whether the user falls asleep again after the first preset time.
Wherein the first preset time period may be set to 5 minutes.
In the embodiment, the user can be effectively monitored by monitoring the sleep condition of the user after the recommended sleep time, so as to urge the user to sleep as soon as possible. After the reminding, whether the user falls asleep is monitored again after the first preset time so as to determine whether the reminding is continued, thereby achieving the technical effect of monitoring whether the user falls asleep in real time, being beneficial to improving the sleep quality of the user and helping the user to develop a good sleep habit.
Example nine
Fig. 3 is a schematic flow chart of another sleep onset reminding method provided in the embodiment of the present disclosure. As shown in fig. 3, on the basis of the above embodiment, the sleep onset reminding time is located before the sleep onset recommended time for a second preset time, a third preset time, and/or a fourth preset time.
Wherein the second preset time period may be set to 30 minutes, the third preset time period may be set to 10 minutes, and the fourth preset time period may be set to 5 minutes. That is, the user is reminded to fall asleep 30 minutes, 10 minutes, and/or 5 minutes before the recommended time to fall asleep. For example, the user can receive a sleep preparation prompt 30 minutes and 10 minutes before sleep, and start listening to the playing content such as sleep-aid music 5 minutes before sleep.
In this embodiment, the sleep-in reminding time of the user is obtained by subtracting the recommended sleep duration from the preset alarm time, and then the sleep-in reminding is performed at one or more sleep-in reminding times before the sleep-in reminding time. Most sleep reminders are single announcements, and for users with poor partial continence, the effect of this approach is not good enough. The user is reminded of sleeping and preparing to sleep through multiple turns of voice, so that the user is scientifically guided to prepare for rest, and the user is helped to relax the mood, prepare for falling asleep and start to rest in time.
Example ten
On the basis of the above embodiment, the step of reminding the user to fall asleep at the sleep-in reminding time before the recommended sleep-in time includes:
and when the sensor detects that the user is influencing the sleep action, reminding the user to fall asleep every fifth preset time.
Wherein, the action affecting sleep may be playing mobile phone, watching television, etc., and the fifth preset time period may be set to 5 minutes. The sensor may be a millimeter wave radar or a vision sensor. For example, when it is monitored by a millimeter wave radar or a visual sensor that a user still plays a mobile phone when the user arrives at a sleep time to influence sleep actions, a voice prompt prompting the user to sleep is performed every 5 minutes.
According to the embodiment, the user is effectively reminded of falling asleep by detecting the influence on the sleep action, and the condition that the sleep quality cannot be guaranteed because the user misses the optimal sleep opportunity is avoided.
EXAMPLE eleven
On the basis of the above embodiment, the obtaining of the recommended sleep duration of the user further includes:
acquiring recommended sleep time of preset days;
and averaging the recommended sleep time of the preset days to be used as the recommended sleep time of the user.
Wherein, the preset days can be set as 5 days, 6 days, 7 days and the like.
In the embodiment, the recommended sleep duration of the user is averaged and taken as the recommended sleep duration of the user, so that the single sample is prevented from being excessively large in deviation, and the technical effect of accurately determining the recommended sleep duration of the user is achieved.
Example twelve
On the basis of the above embodiment, the preset content is played while the user is reminded to fall asleep at the sleep reminding moment.
In this embodiment, for example, 5 minutes before sleeping, the user is reminded to prepare for sleeping and start playing programs such as sleep-aid music or sleep-aid items preset by the user, so as to remind the user to prepare for resting, and help the user to relax the mood in time and create an atmosphere suitable for falling asleep.
EXAMPLE thirteen
Fig. 2 is a block diagram of a sleep reminding device according to an embodiment of the present disclosure, and as shown in fig. 2, the sleep reminding device includes:
the device comprises an acquisition unit, a processing unit and a control unit, wherein the acquisition unit is used for acquiring the recommended sleep time of a user;
the recommending unit is used for acquiring a preset alarm clock time and obtaining a recommended sleep-in time based on a difference value between the preset alarm clock time and the recommended sleep duration;
and the reminding unit is used for reminding the user of falling asleep at the sleep-falling reminding time before the recommended sleep-falling time.
Wherein the recommended sleep time length is an optimal sleep time length suitable for the user. The preset alarm time is set by the user when the scheme of the present disclosure is first used, or modified in use. The recommended sleep time is the time suitable for the user to start sleeping, and the user can be ensured to have proper sleep duration and sleep proportion when getting up at the alarm clock time of the next day. The sleep-in reminding time is one or more times before the recommended sleep-in time, and at the sleep-in reminding time, an environment suitable for the user to sleep is created through measures such as acousto-optic taste and the like.
According to the embodiment, the recommended sleep-in time is obtained by presetting the alarm clock time and the difference value of the recommended sleep time, and the user is reminded to fall asleep at the sleep-in reminding time before the recommended sleep-in time, so that the technical problem that the sleep-in reminding function is not intelligent enough in the prior art is solved, and the technical effects of setting the personalized sleep-in reminding time for different users and guaranteeing the sleep time and the sleep quality of the user are achieved.
Example fourteen
On the basis of the above embodiments, the present embodiment provides a computer-readable storage medium on which a computer program is stored, which, when executed by a processor, implements the method of the above embodiments.
The storage medium may be a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application mall, etc.
Example fifteen
On the basis of the above embodiments, fig. 5 is a block diagram of a computer device according to an embodiment of the present disclosure. The present embodiment provides a computer device, which includes a memory and a processor, where the memory stores a computer program, and the processor implements the method of the above embodiment when executing the computer program.
In some preferred embodiments, the air conditioner comprises the computer device, so that the air conditioner can realize the sleep reminding method of the present disclosure.
The Processor may be an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a controller, a microcontroller, a microprocessor, or other electronic components, and is configured to perform the method of the above embodiments.
The Memory may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk or optical disk.
In the embodiments provided in the present disclosure, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
It should be noted that, in the present disclosure, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the recitation of an element by the phrase "comprising an … …" does not exclude the presence of additional like elements in the process, method, article, or apparatus that comprises the element.
Although the embodiments disclosed in the present disclosure are described above, the above description is only for the convenience of understanding the present disclosure, and is not intended to limit the present disclosure. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the disclosure as defined by the appended claims.
Claims (15)
1. A sleep reminding method is characterized by comprising the following steps:
acquiring recommended sleep duration of a user;
acquiring a preset alarm clock time, and acquiring a recommended sleep time based on a difference value between the preset alarm clock time and the recommended sleep time;
and reminding the user to fall asleep at a sleep reminding time before the recommended sleep time.
2. The method of claim 1, wherein the step of obtaining the recommended sleep duration of the user comprises:
acquiring a recommended sleep time corresponding to the age of the user.
3. The method of claim 1, wherein the step of obtaining the recommended sleep duration of the user comprises:
determining recommended sleep duration according to the user sleep information and the user fatigue value; the user sleep information comprises a previous-day falling sleep time length, a previous-day light sleep time length and a previous-day deep sleep time length.
4. The method of claim 3, wherein the obtaining the recommended sleep duration of the user further comprises:
acquiring recommended sleep time of preset days;
and averaging the recommended sleep time of the preset days to be used as the recommended sleep time of the user.
5. The method of claim 3, wherein the step of determining the recommended sleep duration based on the user sleep information and the user fatigue value comprises:
obtaining the sleep duration of the previous day according to the sleep information of the user;
acquiring a user fatigue value;
and correcting the sleep duration of the previous day based on the user fatigue value to obtain the recommended sleep duration.
6. The method of claim 5, wherein the obtaining the user fatigue value comprises:
acquiring a feedback fatigue value, a user bed-staying time length and a detection fatigue value;
calculating a user fatigue value by adopting a first calculation formula; the first calculation formula is: p ═ i + j + k)/3;
wherein p represents a user fatigue value, i represents a feedback fatigue value, j represents a user bed-staying duration, and k represents a detection fatigue value.
7. The method of claim 5, wherein the obtaining the user fatigue value comprises:
and acquiring a feedback fatigue value sent by a user through a terminal.
8. The method of claim 5, wherein the step of modifying the previous day sleep duration based on the user fatigue value comprises:
s10, calculating the deep sleep ratio through a deep sleep ratio calculation formula;
the deep sleep proportion calculation formula is as follows: v ═ S/(S + Q);
wherein v is the deep sleep proportion, S is the deep sleep time length of the previous day, and Q is the light sleep time length of the previous day;
s11, if the deep sleep proportion is larger than or equal to a first proportion value and the sleep time length of the previous day is larger than or equal to the recommended sleep time length corresponding to the age of the user, correcting the deep sleep proportion through a first correction formula;
the first correction formula is as follows: z ═ T + (Q + S) (1+ p);
wherein Z is recommended sleep time, T is sleep time of the previous day, and p is a user fatigue value;
s12, if the deep sleep proportion is larger than or equal to the first proportion value and the sleep time length of the previous day is smaller than the recommended sleep time length corresponding to the age of the user, correcting the deep sleep proportion through a second correction formula;
the second correction formula is as follows: z is A;
wherein A is the recommended sleep duration corresponding to the age of the user;
s13, if the deep sleep proportion is smaller than the first proportion value and the previous day sleep time length is larger than or equal to the recommended sleep time length corresponding to the age of the user, correcting the user through a third correction formula;
the third correction formula is as follows: z ═ a (1+ p);
s14, if the deep sleep proportion is smaller than the first proportion value and the sleep time length of the previous day is smaller than the recommended sleep time length corresponding to the age of the user, correcting the user by a fourth correction formula;
the fourth correction formula is as follows: z ═ T + (Q + S) (1+ p)) (1+ (0.2-v) × 5).
9. The method of claim 1, further comprising:
monitoring whether the user falls asleep or not after the recommended sleep-falling time;
if the user does not fall asleep, reminding the user to fall asleep, and executing the step of monitoring whether the user falls asleep again after a first preset time.
10. The method according to claim 1, wherein the sleep onset reminding time is a second preset time period, a third preset time period, and/or a fourth preset time period before the sleep onset recommended time.
11. The method of claim 1, wherein the step of reminding the user to fall asleep at a sleep alert time prior to the recommended sleep time comprises:
and when the sensor detects that the user is influencing the sleep action, reminding the user to fall asleep every fifth preset time.
12. The method according to claim 1, wherein the preset content is played while the user is reminded to fall asleep at the sleep reminding moment.
13. A sleep alert device, comprising:
the device comprises an acquisition unit, a processing unit and a control unit, wherein the acquisition unit is used for acquiring the recommended sleep time of a user;
the recommending unit is used for acquiring a preset alarm clock time and obtaining a recommended sleep-in time based on a difference value between the preset alarm clock time and the recommended sleep duration;
and the reminding unit is used for reminding the user of falling asleep at the sleep-falling reminding time before the recommended sleep-falling time.
14. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method of any one of claims 1 to 12.
15. A computer device comprising a processor and a memory, wherein the memory has stored thereon a computer program which, when executed by the processor, implements the method of any of claims 1 to 12.
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