CN115444685A - Over-long-leaving-bed reminding control method and system, intelligent bed and storage medium - Google Patents
Over-long-leaving-bed reminding control method and system, intelligent bed and storage medium Download PDFInfo
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G7/00—Beds specially adapted for nursing; Devices for lifting patients or disabled persons
- A61G7/05—Parts, details or accessories of beds
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/24—Reminder alarms, e.g. anti-loss alarms
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- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
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Abstract
The invention relates to a method and a system for reminding and controlling over-long leaving of a bed, an intelligent bed and a storage medium. The existing reminding function of the bed which is too long adopts a fixed threshold value of the bed which is too long, and the use experience is influenced. The method comprises the steps of obtaining an over-long bed leaving threshold according to a prediction algorithm, monitoring the bed leaving state of a user, obtaining bed leaving duration data, updating and correcting the over-long bed leaving threshold according to the obtained bed leaving duration data by the prediction algorithm, and carrying out early warning operation when the bed leaving duration is monitored to reach the over-long bed leaving threshold. Through monitoring when leaving the bed to the user and updating the threshold value of leaving the bed for a long time, triggering when leaving the bed for a long time surpassing the threshold value of leaving the bed for a long time and reminding the operation, through gathering the user and leaving the bed for a long time to the threshold value of leaving the bed for a long time carry out real-time calculation update, laminating user habit, the accuracy of judging of the event of leaving the bed for a long time of existing effect promotion, the condition of taking place the spurious triggering warning is avoided in addition in effect, promote to use and experience.
Description
Technical Field
The invention relates to the field of bedding, in particular to a method and a system for reminding and controlling a bed to be too long, an intelligent bed and a storage medium.
Background
The accelerating of the social aging process can stimulate the industrial demand of the intelligent mattress to increase, and the development of the aging market becomes a new growth point of the industry. Present intelligent mattress mainly is applied to monitoring user's physiological signal, and the old man who uses the sleep monitoring mattress probably has the activity demand of getting up in the use, and often leaves the bed after, especially at night, takes place to collide with easily, unexpected circumstances such as tumbleing cause the user injured. Particularly, for solitary old people with children not around, how to timely and effectively remotely inform guardians of the children when abnormal leaving the bed occurs at night, the social attention and the attention are more and more paid.
The existing monitoring scheme for the bed leaving state of the old is mainly applied to monitoring the bed leaving state or the bed leaving state in real time of a hospital or a professional nursing institution, equipment such as a breathing machine and a heartbeat is generally adopted, a professional manages nearby a console, the technology is complex, the cost is high, and the monitoring scheme is not suitable for abnormal bed leaving scenes in normal living states of the old living alone.
Also some have appeared in the market and taken the bed pad system of reminding the function of leaving the bed for a long time, through setting up fixed the bed threshold value of leaving the bed for a long time of leaving the old man and judging when leaving the bed, when exceeding this fixed time from the bed, then start the function of reminding of leaving the bed for a long time, this type of solution has following problem: the threshold value of leaving the bed for too long is a fixed value, so that the condition that the system is easily inconsistent with the actual habits of the old due to the fact that the threshold value of leaving the bed for too long is set, if the set threshold value of leaving the bed for too long is too small, remote reminding can be frequently triggered, the daily life of guardians is influenced, the vigilance of the guardians is reduced due to frequent reminding, if the set threshold value of leaving the bed for too long is too large, remote reminding notification is not timely enough, the system reaction is delayed, the optimal rescue opportunity is easily mistakenly delayed, and the use experience is influenced.
Disclosure of Invention
In order to solve the defects of the prior art, the invention provides the too-long-bed-leaving reminding control method, the system using the same, the intelligent bed and the storage medium.
The invention is realized by the following modes: a too-long bed leaving reminding control method comprises the steps of obtaining a too-long bed leaving threshold according to a prediction algorithm, monitoring a bed leaving state of a user, obtaining bed leaving duration data, updating and correcting the too-long bed leaving threshold according to the obtained bed leaving duration data through the prediction algorithm, and performing early warning operation when the monitored bed leaving duration reaches the too-long bed leaving threshold. Through monitoring the long time of leaving the bed to the user and updating the bed threshold value of leaving for a long time, trigger when leaving the bed for a long time and exceed the bed threshold value of leaving for a long time and remind the operation, it is long to leave the bed threshold value to calculate in real time and update to leave for a long time to leave for the long time leaves the bed threshold value and the user is actually leaves the bed for a long time and is correlated with each other, laminating user habit, the accuracy of the event judgement of leaving the bed for a long time has been effectively promoted, guarantee user safety through in time triggering the warning accurately, the condition of mistakenly triggering the warning is effectively avoided taking place in addition, promote the use and experience.
Preferably, the updating and correcting the bed overdue threshold includes: acquiring the time length data of the previous bed leaving time to form a data sequence; calculating the data sequence through a prediction algorithm to obtain a threshold value of the bed which is too long to leave; acquiring current bed leaving time length data, replacing the earliest acquired bed leaving time length data in the data sequence with the current bed leaving time length data, and updating the data sequence; and calculating the updated data sequence through a prediction algorithm and updating and correcting the bed-over-long threshold. The data sequence calculates a corresponding too-long bed leaving threshold through a prediction algorithm, the recently obtained time length of the user leaving the bed is stored in the data sequence and replaces the original time length data of the user leaving the bed, and the too-long bed leaving threshold is adjusted, so that the too-long bed leaving threshold can be updated in real time after the user leaves the bed and is associated with the actual time length of the user leaving the bed, errors are effectively reduced, and triggering accuracy is improved. And sequencing and recording the user bed leaving duration obtained by monitoring the monitoring component according to an acquisition sequence to form a data sequence, and calculating the data sequence by a prediction algorithm to obtain the over-long bed leaving threshold.
Preferably, the prediction algorithm comprises: acquiring the variance of the data sequence; setting a deviation coefficient, and acquiring a deviation range of the variance; setting newly-added bed leaving time length data in the data sequence, setting the maximum value of the variance deviation range as the variance of the data sequence, and calculating the newly-added bed leaving time length data; and taking the newly added bed leaving time length data as an over-long bed leaving threshold value. The variance is amplified to provide a proper bed leaving time range for the user, so that the user can timely send a reminding signal to the associated person when a long-time bed leaving event occurs, the associated person can rescue the user conveniently, the condition of false triggering can be effectively reduced, and the reminding accuracy is improved.
Preferably, the update of the data sequence is implemented by replacing the newly acquired time length data of leaving bed with the earliest acquired time length data of leaving bed in the data sequence. The bed leaving time length data obtained continuously is replaced by the bed leaving time length data obtained earliest in the data sequence, so that the bed leaving time length data in the data sequence are close to the current time and are matched with the bed leaving habit of the user in the nearest time period, and the situation that the calculated and obtained threshold value of the bed leaving time of the user for too long time is greatly deviated from the bed leaving habit of the user is effectively prevented.
Preferably, if the newly acquired bed leaving time length data reaches the bed leaving threshold value, the data sequence is not added, and in addition, the bed leaving time length data in the data sequence can be automatically generated or set by the user. When the time length data of leaving the bed reaches and exceeds the time length data of leaving the bed for too long, the time length data of leaving the bed is not matched with the daily habit of the user, and the data sequence is not recorded to ensure that the calculated time length data of leaving the bed for too long is matched with the daily habit of the user.
Preferably, the control method realizes the function of reminding the user of leaving the bed too long by the following steps: monitoring the out-of-bed or in-bed state of a user to obtain the state of the user; starting timing when monitoring that the user is in a bed leaving state, and stopping timing when monitoring that the user is in the bed leaving state so as to obtain bed leaving duration data; when the obtained bed leaving time length data is more than or equal to the over-long bed leaving threshold value, sending an early warning message, wherein the bed leaving time length data is not used for updating the data sequence; and when the obtained bed leaving time length data is smaller than the over-long bed leaving threshold, transmitting the bed leaving time length data to the data sequence, and updating the over-long bed leaving threshold through a prediction algorithm after the data sequence is updated. Whether the bed leaving event belongs to a normal event or not is judged by monitoring the bed leaving time of the user, and a reminding signal is sent out when the bed leaving time reaches a bed leaving threshold for a long time, so that the associated person set by the user can know the user condition conveniently, and the associated person can implement rescue measures conveniently.
A system using the control method comprises a supporting module, a monitoring module, a processing module, a storage module and a reminding module. Specifically, a holding module for holding a user; the monitoring module is used for monitoring the out-of-bed or in-bed state of a user to acquire the user state; the processing module is used for calculating an over-long bed leaving threshold value by utilizing a prediction algorithm, acquiring the time length of the user leaving the bed according to the state of the user, and sending a trigger signal to the reminding module when the time length of the user leaving the bed reaches the over-long bed leaving threshold value; the storage module is used for storing the time length data of the user leaving the bed in the past and providing a data sequence required by calculating the threshold value of the user leaving the bed for the processing module; and the reminding module receives the trigger signal from the processing module and sends out a reminding signal by starting a reminding operation, so that associated people can know the user condition in time.
When the system runs, the processing module calculates the over-long bed leaving threshold value through the past bed leaving duration data provided by the storage module, and updates the over-long bed leaving threshold value by using the bed leaving duration data obtained by the monitoring module; the processing module monitors the state of the user through the monitoring module, and when the time length of leaving the bed of the user reaches a threshold value of leaving the bed for too long, a reminding signal is sent out through the reminding module. The processing module updates the bed threshold value after the user leaves for a long time and monitors the time length when the user leaves the bed, so that the triggering condition of the reminding module and the habit of the user are synchronously changed, the condition of mistaken touch is effectively reduced, the triggering module is ensured to send a reminding signal in time when the user takes a bed event after the user leaves for a long time, and the use experience is further improved.
The utility model provides an use control method's intelligent bed, includes fills up the body, be equipped with the monitoring subassembly of transversely laying in filling up the body, the monitoring subassembly is timed the user leave the bed time to it reminds the operation to go out after exceeding the bed threshold value of leaving for a long time. The position of a user is monitored by the monitoring component arranged in the middle of the top surface of the cushion body, so that the user can be informed of the in-bed state or out-of-bed state. The monitoring component corresponds to the chest body of the user, can accurately monitor the out-of-bed state of the user, and can improve the monitoring precision of the physiological data of the user by shortening the horizontal distance between the monitoring component and the heart and lung of the user. The installation position of the monitoring assembly can be set according to actual conditions, and the monitoring assembly can be arranged in the middle of the top surface of the cushion body and can also be arranged in the cushion body.
Preferably, the reminding operation includes sending a reminding signal to the outside, and the reminding signal can provide a warning for a guardian, so that a danger may exist when the duration of the user leaving the bed exceeds a threshold value of leaving the bed for too long, the guardian can be ensured to perform timely treatment on the user, and the safety of the user is ensured.
Preferably, the monitoring component is a piezoelectric sleep monitoring band or an optical fiber sleep monitoring band, and can accurately monitor whether a user leaves the bed, so that multiple options are provided for assembling and forming the intelligent bed for realizing the control method.
Preferably, a control box is arranged in the cushion body and can send a reminding signal outwards, the control box can monitor the state of a user through the monitoring assembly, can compare the counted bed leaving time with a threshold value of the bed leaving time for too long time, and sends the reminding signal outwards when the triggering condition is met.
A storage medium storing a computer program, the storage medium executing the control method when executed by at least one processing module. The storage medium forms a storage module, provides programs and data required by operation for the operation of the processing module, ensures that the system can continuously operate, and ensures that the threshold value of the bed which is too long is associated with the daily habit of the user.
The invention has the beneficial effects that: through monitoring the long time of leaving the bed to the user and updating the bed threshold value of leaving for a long time, trigger when leaving the bed for a long time and exceed the bed threshold value of leaving for a long time and remind the operation, it is long to leave the bed threshold value to calculate in real time and update to leave for a long time to leave for the long time leaves the bed threshold value and the user is actually leaves the bed for a long time and is correlated with each other, laminating user habit, the accuracy of the event judgement of leaving the bed for a long time has been effectively promoted, guarantee user safety through in time triggering the warning accurately, the condition of mistakenly triggering the warning is effectively avoided taking place in addition, promote the use and experience.
Drawings
FIG. 1 is a schematic diagram of the structure of the decision tree;
FIG. 2 is a schematic structural diagram of the intelligent bed;
in the figure: 1. the monitoring device comprises a pad body, 2, a monitoring component, 3, a mobile terminal, 4 and a control box.
Detailed Description
The essential features of the invention will be further explained below with reference to the drawings and the detailed description of the specification.
The first embodiment is as follows:
the embodiment provides a method for reminding and controlling bed leaving too long.
As shown in fig. 1, in the method for controlling the too-long-out-of-bed reminder, by monitoring the time length of the user leaving the bed and updating the threshold value of the too-long-out-of-bed, the reminding operation is triggered when the time length of the user leaving the bed exceeds the threshold value of the too-long-out-of-bed. Specifically, an over-long bed leaving threshold is obtained according to a prediction algorithm, the bed leaving state of the user is monitored, bed leaving duration data is obtained, the prediction algorithm updates and corrects the over-long bed leaving threshold according to the obtained bed leaving duration data, and early warning operation is performed when the monitored bed leaving duration reaches the over-long bed leaving threshold. The long-time bed leaving threshold value and the actual bed leaving time of the user are correlated with each other, the accuracy of the long-time bed leaving event judgment is effectively improved, the user safety is ensured by timely and accurately triggering the reminding, the situation of mistakenly triggering the reminding is effectively avoided, and the use experience is improved.
In this embodiment, the control method implements the too-long bed leaving reminding function through the following decision tree:
and at the first node, N pieces of bed leaving time length data are obtained in a forward tracing mode, the bed leaving time length data are sequentially arranged to form the data sequence DT, and the data sequence DT is transferred to the second node. The method includes the steps that the duration of the user leaving events of the past times is counted and recorded, N pieces of leaving duration data traced forward are combined to form a data sequence DT for calculation of a prediction algorithm, it is guaranteed that data in the data sequence DT are matched with the recent leaving habits of the user all the time, it is guaranteed that the calculated too-long leaving threshold value and the leaving habits of the user change synchronously, and it is guaranteed that high reminding triggering accuracy can be provided. Specifically, the method comprises the following steps:
when the recorded bed leaving time length data are more than N, combining the latest N bed leaving time length data to form a data sequence DT which is arranged from front to back along the time sequence;
when the recorded bed leaving time length data are less than N, the bed leaving time length data are randomly set in the range of the normal bed leaving time length and are pushed and replaced from back to front by the obtained real-time bed leaving time length Current-T in later-period use. When the stored bed leaving time length data are less and the data sequence DT cannot be formed, the bed leaving time length data meeting the quantity required by the data sequence DT are randomly set in the normal bed leaving time length range, so that the current over-long bed leaving threshold value cannot be triggered when a bed leaving event in the normal bed leaving time length range occurs by a user, the condition of false triggering is prevented, and the bed leaving time length data randomly generated in the data sequence DT can be replaced by the time length of the over-long bed leaving time through successive statistics, so that the over-long bed leaving threshold value is gradually changed and matched with the user bed leaving habit. Randomly generated bed leaving time length data are placed at the front position of the data sequence DT, the collected real-time bed leaving time length can be placed at the tail end of the data sequence DT, data at the head end of the data sequence DT are pushed and replaced, and finally the data sequence DT formed by the real-time bed leaving time length is obtained.
The user inputs a normal bed leaving duration range through the mobile terminal 3, wherein the normal bed leaving duration range comprises a lower limit value Tmin and an upper limit value Tmax. The user sets the normal bed leaving time range including the lower limit value Tmin and the upper limit value Tmax according to the self bed leaving habit, and inputs and collects the time range through the mobile terminal 3, so that the recorded real-time bed leaving time data can be generated randomly when the number of the recorded real-time bed leaving time data is insufficient, and the prediction algorithm can be ensured to calculate normally and obtain the threshold value of the over-long bed leaving time.
And calculating the average value AVG _ DT and the variance VAR _ DT corresponding to the data sequence DT by using the data sequence DT at the second node, obtaining the over-long bed leaving threshold value OV _ DT through a prediction algorithm, and transferring to a third node. The too-long bed exit threshold value OV _ DT, which changes synchronously with the user's bed exit habit, is obtained by calculating the data sequence DT updated in real time. In particular, the predictive algorithm obtains the overlength bed threshold value OV _ DT by:
first, the variance of the data sequence is obtained. Acquiring a data sequence DT, DT = (X) as a basis for calculation 1 ，X 2 ，X 3 ，…，X N ) The leaving-bed time length data in the data sequence DT are arranged in the order of the acquisition time from the first to the last, and the average value AVG _ DT and the variance VAR _ DT of the data sequence DT are calculated, specifically:
substituting equation 1 into equation 2 yields:
the dispersion degree of each bed-leaving duration data in the data sequence DT is reflected by calculating the average value AVG _ DT and the variance VAR _ DT of the data sequence DT, and the average value AVG _ DT and the variance VAR _ DT can be matched and linked with the most recent bed-leaving duration of the user.
And secondly, setting a deviation coefficient and acquiring a variance deviation range. Setting the range coefficient of the allowable deviation of the variance VAR _ DT to K, and calculating the allowable deviation range VAR _ DT of the obtained variance VAR _ DT X K is more than or equal to 3 and less than or equal to 10, specifically:
VAR_DT X = K × VAR _ DT (formula 4)
The variance VAR _ DT is amplified by setting the parameter K, thereby forming an allowable deviation range VAR _ DT X The method is used for accommodating the situation that reasonable deviation occurs when the user leaves the bed once, effectively adapting to the change of the time when the user leaves the bed due to self reasons, improving the triggering accuracy and effectively preventing the situation of false triggering reminding.
Third, a new addition is set in the data sequenceAnd (4) the bed leaving time length data sets the maximum value of the variance deviation range as the variance of the data sequence, and calculates the newly added bed leaving time length data. Assuming that the newly added bed leaving time length is X _ DT, storing the X _ DT as the last data record of the data sequence DT and deleting the first data of the data sequence DT so as to obtain a new data sequence DT X ，DT X ＝(X 2 ，X 3 ，…，X N X _ DT), new data sequence DT X Substituting equation 1 to obtain:
new data sequence DT X And formula 3 are simultaneously substituted into formula 4 to obtain:
and calculating to obtain X _ DT according to the formula 5 and the formula 6, and taking the newly added bed leaving time length data X _ DT as a currently preset over-bed leaving threshold value OV _ DT.
At the third node, the monitoring component 2 monitors the user by the interval unit duration Tsample1, and transfers the monitoring result to the fourth node. Specifically, the monitoring assembly 2 takes the interval unit duration Tsample1 as a monitoring period, and the monitoring assembly 2 monitors the user once in each monitoring period, so that the timeliness of finding the user bed leaving event is ensured, the energy consumption can be reduced by controlling the monitoring frequency, and the requirement on the monitoring equipment is further reduced.
And judging the state of the user at the fourth node, switching to the third node and continuously monitoring the user when the user is in the bed state, and switching to the fifth node when the user is in the out-of-bed state. Specifically, the monitoring component 2 senses that the user leaves the bed and classifies the bed-leaving event, so that the user state can be monitored in real time, and the user can respond in time after the bed-leaving event occurs.
And in the fifth node, the monitoring component 2 monitors the user by the interval unit time length Tsample2, accumulates and counts the duration of the bed leaving state of the user at this time, obtains the real-time bed leaving time length Current-T, and switches to the sixth node. Specifically, when the user has a bed exit event, the monitoring cycle duration of the monitoring assembly 2 is set to Tsample2, which ensures that the monitoring assembly 2 can accurately time the bed exit duration of the user. And the real-time bed leaving time duration Current-T carries out time duration accumulation statistics according to the number of monitoring periods that the user is continuously in the bed leaving state after the user has a bed leaving event, and provides real-time updated data for the sixth node.
And comparing the real-time bed leaving time Current-T with the over-time bed leaving threshold value OV _ DT at the sixth node, switching to the seventh node when the Current-T is less than OV _ DT, and switching to the ninth node when the Current-T is more than or equal to OV _ DT. Specifically, the continuously updated real-time bed leaving time duration Current-T is compared with the too-long bed leaving threshold value OV _ DT, and differentiated operation is performed on different comparison results, so that not only can the user bed leaving event be continuously and timely tracked, but also reminding operation can be performed when the real-time bed leaving time duration Current-T is greater than the too-long bed leaving threshold value OV _ DT.
And judging the user state at the seventh node, switching to the fifth node and continuously monitoring the user when the user is in the out-of-bed state, ensuring that the real-time out-of-bed time Current-T can be continuously accumulated and timed, and switching to the eighth node when the user is in the in-bed state, recording the continuous time of the out-of-bed event and updating the data sequence DT.
And at the eighth node, storing a record of the corresponding real-time bed leaving time duration Current-T, storing the real-time bed leaving time duration Current-T as a last data record of the data sequence DT, deleting the first data of the data sequence DT, transmitting the newly obtained data sequence DT to the second node, updating the data sequence to ensure that the data in the data sequence is the latest and latest bed leaving time duration data of the user, providing basic data for calculation for a prediction algorithm of the second node, and always changing along with the bed leaving habit of the user by using the over-long bed leaving threshold value so as to keep the accuracy of the triggering reminding operation.
And triggering a reminding operation at the ninth node, and transmitting the non-updated data sequence DT to the second node, specifically, when the reminding operation is triggered by the bed leaving event, the bed leaving time corresponding to the bed leaving event is not recorded into the data sequence DT, so that the situation that the long bed leaving threshold value and the user bed leaving habit have large deviation due to the fact that the data sequence DT is recorded into the long bed leaving time with large single deviation is prevented, and the influence of the long bed leaving time with large single deviation on the long bed leaving threshold value is effectively eliminated.
In the prediction algorithm, the unknown number X _ DT is set and compared with X 2 、X 3 、…、X N Used in combination with the allowable deviation range VAR _ DT X Calculating the unknown number X _ DT by using the known allowable deviation range VAR _ DT X And X 2 、X 3 、…、X N The unknown number X _ DT is used as a threshold value of the user leaving the bed for too long time and is used as a basis for judging whether the reminding is triggered or not, so that a deviation space is provided for reasonable deviation of the user leaving the bed for a single time, the threshold value of the user leaving the bed for too long time can be matched with the previous time of the user leaving the bed, the situation that the threshold value of the user leaving the bed for too long time cannot be matched with the change of the user leaving the bed due to the fixed threshold value of the user leaving the bed is prevented, the triggering accuracy is guaranteed not to be reduced due to the change of the user leaving the bed, and the use experience is guaranteed.
In the data sequence DT, DT = (X) 1 ，X 2 ，X 3 ，…，X N ) The subscript of the parameter X represents the sequence of obtaining the bed leaving time length, the smaller the numerical value of the subscript is, the earlier the bed leaving time length is obtained, when the data sequence DT is updated in real time, the newly obtained bed leaving time length can be arranged at the tail of the data sequence DT, the first data in the data sequence DT is deleted, the number of the bed leaving time length data in the data sequence DT is guaranteed to be unchanged, the calculated amount is effectively controlled, the bed leaving time length data in the data sequence DT can be guaranteed to be matched with the recent bed leaving habit of a user all the time, and the higher triggering accuracy is further kept.
In the embodiment, tsample1 is not less than 5s and not more than 20s, tsample2 is not less than 5s and not more than 20s, the running energy consumption of the equipment is reduced by reducing the monitoring frequency, and the timing precision can be improved by increasing the monitoring frequency when a user gets out of bed. In general, tsample2 < Tsample1 ensures that the device has lower energy consumption when the user is not getting out of bed, and also ensures that the device can improve the timing accuracy when the user gets out of bed.
For ease of understanding, the invention is illustrated by the following example of the operation of the control method:
obtaining N bed leaving time length data in a forward tracing mode at a first node, arranging the bed leaving time length data in sequence to form a data sequence DT, and transferring the data sequence DT to a second node, specifically:
the user uses for the first time, and the normal sleep time period of each day is set as follows through the mobile terminal 3: 21, 00, wherein the lower limit Tmin =2min and the upper limit Tmax =5min of the normal bed leaving time range of the user;
assuming that the user has 2 out-of-bed states during the sleep period every day, and 5 days are taken as an analysis period of data, N =2 × 5=10 in the present embodiment, and 10 out-of-bed duration data are randomly generated and a data sequence DT = (2, 3,4,2, 5) is formed as a basis for calculating the threshold value of the long-term out-of-bed.
And calculating the average value AVG _ DT and the variance VAR _ DT corresponding to the data sequence DT by using the second node, obtaining the overlength bed threshold value OV _ DT through a prediction algorithm, and transferring to a third node. In particular, the predictive algorithm obtains the overlength bed threshold value OV _ DT by:
in a first step, a data sequence DT, DT = (2, 3,4,2, 5) is obtained as a basis for calculation, each leaving-bed time length data in the data sequence DT is arranged in order of the obtaining time from the first to the last, and an average AVG _ DT and a variance VAR _ DT of the data sequence DT are calculated, specifically:
secondly, setting the range coefficient of the allowable deviation of the variance VAR _ DT to be K, K =5, and calculating the allowable deviation range VAR _ DT of the obtained variance VAR _ DT X Specifically, the method comprises the following steps:
VAR_DT X ＝K*VAR_DT＝0.96*5＝4.8
and thirdly, assuming that the obtained bed leaving time length is X _ DT, storing the X _ DT as the last data record of the data sequence DT and deleting the first data of the data sequence DT so as to obtain a new data sequence DT X ，DT X = (3,4,2,3,4,3,4,2,5,x _DT), new data sequence DT X Substituting equation 1 to obtain:
x _ DT =10min is obtained by calculation and is taken as the currently preset too long bed exit threshold, so that OV _ DT =10min.
At the third node, the monitoring component 2 monitors the user by an interval unit time length Tsample1 and transfers a monitoring result to the fourth node, wherein Tsample1 is more than or equal to 5s and less than or equal to 20s;
judging the state of the user at the fourth node, switching to the third node and continuously monitoring the user when the user is in a bed state, and switching to the fifth node when the user is in a bed leaving state;
at a fifth node, monitoring the user by the monitoring component 2 according to the interval unit time length Tsample2, performing accumulated statistics on the continuous time length of the bed leaving state of the user, obtaining the real-time bed leaving time length Current-T, and switching to a sixth node, wherein the Tsample2 is more than or equal to 5s and less than or equal to 20s;
comparing the real-time bed leaving time Current-T with the over-time bed leaving threshold value OV _ DT at the sixth node, switching to the seventh node when the Current-T is less than 10min, and switching to the ninth node when the Current-T is more than or equal to 10 min;
judging the state of the user at a seventh node, switching to a fifth node and continuously monitoring the user when the user is in a bed leaving state, and switching to an eighth node when the user is in a bed state;
at the eighth node, storing a record of the corresponding real-time bed leaving time length Current-T, storing the real-time bed leaving time length Current-T as a last data record of the data sequence DT and deleting first data of the data sequence DT, transmitting the newly obtained data sequence DT to the second node, and if the duration of the bed leaving event is 7min and does not exceed the bed leaving threshold for 10min, obtaining a new data sequence DT, wherein DT = (3, 4,2,3,4, 2,5, 7) and providing a basis for the second node to update the bed leaving threshold for too long time;
at the ninth node, if the duration of the bed exit event is 11min, the bed exit threshold is not exceeded for 10min, a reminder operation is triggered and the non-updated data sequence DT is transmitted to the second node, DT = (2, 3,4,2, 5), so that the bed exit threshold remains at the original value.
In the embodiment, K is more than or equal to 3 and less than or equal to 10, and the user adjusts the parameter K according to the self condition, so as to accommodate the condition that the single bed leaving time of the user has reasonable deviation. The allowable deviation range VAR _ DT obtained when the value of K is larger X The larger the deviation tolerance VAR _ DT and the larger the deviation tolerance VAR _ DT X The smaller. In addition, the parameter K may be 3,4, 7, 10, etc., which should be considered as specific embodiments of the present embodiment.
The second embodiment:
in contrast to the first embodiment, the present embodiment provides a system.
The system comprises a bearing module, a monitoring module, a processing module, a storage module and a reminding module. In particular, the support module, being a mattress or the like, is used for supporting the user; the monitoring module is used for monitoring the bed leaving or in-bed state of the user to obtain the user state, and is used for monitoring the component 2; the processing module is used for calculating an over-long bed leaving threshold value by utilizing a prediction algorithm, acquiring the time length of the user leaving the bed according to the state of the user, and sending a trigger signal to the reminding module when the time length of the user leaving the bed reaches the over-long bed leaving threshold value; the storage module is used for storing the time length data of the user leaving the bed in the past and providing a data sequence required by calculating the threshold value of the user leaving the bed for the processing module; and the reminding module receives the trigger signal from the processing module and sends out a reminding signal by starting reminding operation.
In this embodiment, when the system is in operation, the processing module calculates the threshold value of the bed leaving time of the previous time through the time length data of the bed leaving time provided by the storage module, and updates the threshold value of the bed leaving time of the previous time through the time length data of the bed leaving time of the previous time obtained by the monitoring module; meanwhile, the processing module monitors the state of the user through the monitoring module, and when the time length of the user leaving the bed reaches a threshold value of leaving the bed for too long, a reminding signal is sent out through the reminding module.
The features and effects of the control method described in this embodiment are consistent with those of the embodiment, and are not described again.
Example three:
compared with the second embodiment, the present embodiment provides an intelligent bed.
The intelligent bed as shown in fig. 2 comprises a cushion body 1, wherein a monitoring component 2 which is transversely laid is arranged in the cushion body 1, the monitoring component 2 times the time length of leaving the bed of a user, and the monitoring component starts to remind the user to operate after exceeding a threshold value of leaving the bed for too long. The system collects the time length of the user leaving the bed through the monitoring component 2, and uses the data sequence DT formed by the time length of the user leaving the bed as the basis for calculating the threshold value of the over-long-time leaving the bed, so that the threshold value of the over-long-time leaving the bed and the actual time length of the user leaving the bed are mutually associated, the accuracy of judging the over-long-time leaving event is effectively improved, the safety of the user is ensured by timely and accurately triggering the reminding, the condition of mistaken triggering reminding is effectively avoided, and the use experience is improved.
In this embodiment, fill up and be equipped with control box 4 in the body 1, control box 4 passes through monitoring subassembly 2 monitoring user state and calculates the bed threshold value of leaving for a long time, when leaving the bed for a long time and surpassing the bed threshold value of leaving for a long time, control box 4 outwards sends the warning signal through the trigger subassembly.
In the present embodiment, the monitoring component 2 is disposed on the top surface of the pad body 1 in the area below the chest of the user, and the monitoring component 2 includes, but is not limited to, a piezoelectric sleep monitoring band or an optical fiber sleep monitoring band, which should be regarded as a specific implementation manner of the present embodiment.
In the present embodiment, the mobile terminal 3 includes, but is not limited to, a mobile phone, a tablet, a computer, etc., and the communication between the mobile terminal 3 and the system can be realized in a wireless manner or a wired manner, which should be regarded as a specific implementation manner of the present embodiment.
In this embodiment, the reminding operation includes sending a reminding signal to the outside. The cushion body 1 comprises sound equipment or a signal sending component for transmitting reminding signals outwards, the sound equipment can remind a guardian nearby through sending audio, and the cushion body is suitable for a scene where a user and the guardian live together, and the signal sending component can remotely remind the user through a network and is suitable for a scene where the user and the guardian cannot transmit the reminding signals through the sound equipment.
The features and effects of the system described in this embodiment are the same as those of the second embodiment, and are not described again.
Example four:
compared with the first embodiment, the present embodiment provides a storage medium.
The storage medium stores a computer program, and when executed by at least one processing module, the storage medium executes the control method, and the storage medium stores contents including, but not limited to, the computer program, set parameters, data obtained by monitoring, and the like.
The features and effects of the control method described in this embodiment are consistent with those of the embodiment, and are not described again.
Claims (10)
1. A reminding control method for over-long leaving bed is characterized in that,
obtaining a threshold value of the bed leaving too long according to a prediction algorithm;
monitoring the bed leaving state of a user, and acquiring bed leaving duration data;
updating and correcting the threshold value of the over-long bed leaving by the prediction algorithm according to the obtained bed leaving duration data;
and when the bed leaving time reaches the threshold value of leaving the bed for too long, performing early warning operation.
2. The method as claimed in claim 1, wherein the updating and modifying the bed-leaving threshold value comprises:
acquiring the time length data of the previous bed leaving time to form a data sequence;
calculating the data sequence through a prediction algorithm to obtain a threshold value of the bed which is too long to leave;
acquiring current bed leaving time length data, replacing the earliest acquired bed leaving time length data in the data sequence with the current bed leaving time length data, and updating the data sequence;
and calculating the updated data sequence through a prediction algorithm and updating and correcting the threshold value of the bed leaving too long.
3. The too-long-out-of-bed reminder control method according to claim 2, wherein the prediction algorithm comprises:
acquiring the variance of the data sequence;
setting a deviation coefficient, and acquiring a deviation range of the variance;
setting newly-added bed leaving time length data in the data sequence, setting the maximum value of the variance deviation range as the variance of the data sequence, and calculating the newly-added bed leaving time length data;
and taking the newly-added bed leaving time length data as an over-long bed leaving threshold value.
4. The method for controlling too long bed leaving reminding according to claim 3, characterized in that the newly acquired bed leaving duration data is used for replacing the earliest acquired bed leaving duration data in the data sequence to realize the update of the data sequence;
if the newly acquired bed leaving time length data reaches the threshold value of too long bed leaving, the data sequence is not added, and in addition, the bed leaving time length data in the data sequence can be automatically generated or set by a user.
5. The too-long-away bed reminder control method according to claim 2,
monitoring the out-of-bed or in-bed state of a user to obtain the state of the user;
starting timing when the user is monitored to be in a bed leaving state, and stopping timing when the user is monitored to be in the bed leaving state so as to obtain bed leaving duration data;
when the obtained bed leaving duration data is larger than or equal to the over-long bed leaving threshold value, sending an early warning message, wherein the bed leaving duration data is not used for updating the data sequence;
and when the obtained bed leaving duration data is smaller than the over-long bed leaving threshold, transmitting the bed leaving duration data to the data sequence, and updating the over-long bed leaving threshold through a prediction algorithm after the data sequence is updated.
6. A system using the control method according to any one of claims 1 to 5, characterized by comprising:
a support module for supporting a user;
the monitoring module is used for monitoring the out-of-bed or in-bed state of a user to acquire the state of the user;
the processing module is used for calculating an over-long bed leaving threshold value by utilizing a prediction algorithm, acquiring the time length of the user leaving the bed according to the state of the user, and sending a trigger signal to the reminding module when the time length of the user leaving the bed reaches the over-long bed leaving threshold value;
the storage module is used for storing the user bed leaving duration data in the past and providing a data sequence required for calculating the over-long bed leaving threshold for the processing module;
and the reminding module receives the trigger signal from the processing module and sends out a reminding signal by starting reminding operation.
7. A system according to claim 6,
the processing module calculates the over-long bed leaving threshold value through the past bed leaving duration data provided by the storage module, and updates the over-long bed leaving threshold value by using the bed leaving duration data obtained by the monitoring module;
the processing module monitors the state of the user through the monitoring module, and the reminding module sends out a reminding signal when the time length of the user leaving the bed reaches a threshold value of leaving the bed for too long.
8. An intelligent bed using the control method of any one of claims 1 to 5, comprising a cushion body (1), wherein a monitoring component (2) laid transversely is arranged in the cushion body (1), the monitoring component (2) times the leaving time of a user, and starts a reminding operation after the threshold value of the leaving time is exceeded.
9. The intelligent bed of claim 8, wherein the alerting action comprises sending an alert signal to the outside; or the monitoring component (2) is a piezoelectric sleep monitoring belt; or the monitoring component (2) is an optical fiber sleep monitoring band; or a control box (4) is arranged in the cushion body, and the control box (4) can send a reminding signal outwards.
10. A storage medium storing a computer program, the storage medium performing the control method of any one of claims 1 to 5 when executed by at least one processing module.
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| CN202211130866.5A CN115444685A (en) | 2022-09-16 | 2022-09-16 | Over-long-leaving-bed reminding control method and system, intelligent bed and storage medium |
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