CN112120670B - Sleep quality monitoring system based on big data - Google Patents
Sleep quality monitoring system based on big data Download PDFInfo
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- CN112120670B CN112120670B CN202011002021.9A CN202011002021A CN112120670B CN 112120670 B CN112120670 B CN 112120670B CN 202011002021 A CN202011002021 A CN 202011002021A CN 112120670 B CN112120670 B CN 112120670B
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4815—Sleep quality
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/01—Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
- A61B5/02055—Simultaneously evaluating both cardiovascular condition and temperature
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
Abstract
The invention discloses a sleep quality monitoring system based on big data, which comprises: the monitored data is transmitted to the central processing unit through the monitoring end, the central processing unit processes the data and then transmits the monitoring information to the control module through the WIFI module, meanwhile, the data is transmitted to a voice recognition broadcasting module, the voice recognition broadcasting module broadcasts corresponding information, a control module transmits the received information to a big data server, the big data server stores the information when the user is in normal sleep, the big data server compares the received data with the stored data and transmits the result to the control module, the control module judges the sleep quality of the user according to the comparison result, and the quality of the sleep quality of the user is displayed by controlling the on and off of the light emitting diodes with different colors, meanwhile, the control module also transmits the compared result to the display module for display.
Description
Technical Field
The invention relates to the field of intelligent testing, in particular to a sleep quality monitoring system based on big data.
Background
Modern society rhythm is faster and faster, and people's operating pressure is also bigger and bigger, and too big can influence people's healthy, receives operating pressure's puzzlement for a long time and makes people can't be relieved sleep, and the sleep quality at night is more and more poor, and then can influence the work efficiency on the next day, and in the long run, people can become more and more anxious, fidgety, can form vicious circle.
People often neglect the quality of their sleep, generally can not find out the problem in time when the quality state of their sleep is not good, some existing sleep quality monitoring methods monitor people's sleep quality, but there are following problems in the monitoring process:
1. the sleep quality monitoring data is too complex, the user is not clear the sleep quality, and the judgment of the sleep quality of the user has errors;
2. in the motion monitoring link, the position is moved, so that the accuracy and timeliness of data for monitoring the sleep quality of the user are low, and the monitoring difficulty is increased.
Therefore, a sleep quality monitoring system based on big data is needed to solve the above problems.
Disclosure of Invention
The present invention aims to provide a sleep quality monitoring system based on big data to solve the problems proposed in the above background art.
In order to solve the technical problems, the invention provides the following technical scheme: a big data based sleep quality monitoring system, the sleep quality monitoring system comprising: the system comprises a monitoring end, a central processing unit, a voice recognition broadcasting module, a WIFI module, a control module, a big data server, a light emitting diode and a display module;
the output of monitoring end with central processing unit's input is connected, central processing unit's output with speech recognition reports the input of module and passes through the IO mouth and connect, another output of central processing unit with the input of WIFI module is connected, the output of WIFI module with control module's input is connected, control module's output with big data server the emitting diode with display module's input is connected, big data server's output with control module's input is connected, control module with big data server establishes two-way communication and connects.
Furthermore, the monitoring end comprises an infrared body temperature monitoring module, a heart rate monitoring module, a blood pressure monitoring module, a respiratory rate monitoring module, a motion monitoring module and a blood oxygen monitoring module, wherein the infrared body temperature monitoring module is used for detecting the body temperature of the user during sleeping, the heart rate monitoring module is used for detecting the heart beating frequency of the user during sleeping, the blood pressure monitoring module is used for detecting the blood pressure condition of the user during sleeping, the respiratory rate monitoring module is used for detecting the respiratory frequency of the user during sleeping, the motion monitoring module is used for detecting the turnover frequency of the user during sleeping and maintaining the time of a sleeping posture, the blood oxygen monitoring module is used for detecting the oxygen content in blood of the user during sleeping, the sleep quality of the user is monitored from multiple aspects, the monitored data is more comprehensive, and the accuracy of the sleep quality monitoring data of the user is improved, the sleep quality of the user can be judged more clearly and accurately.
Further, the voice recognition broadcasting module is used for broadcasting the data information monitored by the monitoring end, firstly, the voice recognition broadcasting module is initialized, after the voice recognition broadcasting module receives the data information monitored by the monitoring end and transmitted by the central processing unit, whether the serial port of the voice recognition broadcasting module receives voice is detected, after the serial port receives the voice, the user speaks a wake-up word, the wake-up word is recognized by the serial port, the voice recognition broadcasting module starts to work, after the voice recognition broadcasting module starts to work, the user sends a second-level voice instruction, after the second-level voice instruction is received by the serial port, the voice recognition broadcasting module broadcasts corresponding voice, namely the data information monitored by the monitoring end, the sleep quality monitoring information of the user is displayed and simultaneously is broadcasted, the user can accurately know the sleep condition of the user without looking up the monitoring data of the user, and the difficulty of the user in recognizing the sleep quality of the user is reduced.
Furthermore, the awakening words are self-defined, the secondary voice instruction is set to be sleep monitoring information of last night (the sleep monitoring information can be changed according to actual conditions), and after the secondary voice instruction is sent out, the voice recognition broadcasting module can broadcast the corresponding monitored data information.
Further, when the voice broadcasting module broadcasts the monitored data information, the big data server stores normal sleep monitoring information of the user, the normal sleep monitoring information is compared with the monitoring information received by the control module, and the comparison result is displayed through the display module.
Furthermore, the movement monitoring module is used for detecting the number of times of turning over the user during sleeping and the time for maintaining a sleeping posture, a movement monitoring tool is needed by the movement monitoring module, the movement monitoring tool is used for scanning the user after the user enters the sleeping, after the movement monitoring tool is fixed, the movement monitoring tool scans the user and identifies the position coordinates of the appointed point (such as a nose, a point on an arm and the like), and the movement monitoring tool simultaneously observes the coordinate change of the appointed point in real time.
Furthermore, when the motion monitoring tool observes the coordinate change of the designated point in real time, if the position coordinate of the designated point does not change, the motion monitoring tool calculates the time for keeping the position coordinate of the designated point unchanged, if the position coordinate of the designated point changes, the motion monitoring tool counts the times of the coordinate change of the designated point and describes the motion track of the designated point by using a moving point space-time model, the motion monitoring tool is also used for identifying the latest position coordinate of the designated point, the sleeping posture change of the whole body of the user during sleeping can be inferred from the local position change, the whole body can be observed through the local part, and the working difficulty of the motion monitoring tool is reduced.
Furthermore, the moving point space-time model represents the future position of the moving point by using a time function, the position attribute is the dynamic attribute of the moving point, the value of the dynamic attribute is determined by time, a position updating system is triggered when the deviation between the moved position of the specified point and the initial position exceeds a certain threshold value, the position updating system is used for updating the position coordinate of the specified point, and the accuracy of the sleeping posture change data of the user during sleeping is improved by updating and identifying the position coordinate of the specified point in real time.
Further, the motion trajectory of the specified point is composed of a seven-element group sequence (x)i，yi，zi，ti，di，viΔ t), wherein x isi、yi、ziIs represented as the specified point tiTime of day spatial position, diRepresents tiDirection of time trace, said viRepresents said tiThe time speed, the delta t represents a time updating threshold value, the motion track of the designated point is determined by the value of the delta t, and if the designated point is at the time tiHas a position coordinate of Pi(xi，yi，zi) The specified point is in the time interval [ t ]i，ti+1]Upper slave point Pi(xi，yi，zi) To point Pi+1(xi+1，yi+1，zi+1) At said velocity viCarry out uniform linear motion, then
In said time interval ti，ti+1]The specified point is on the motion trail Pi(xi，yi，zi) And point Pi+1(xi+1，yi+1，zi+1) The position between v and v is obtained by linear interpolation, and the user can have slight movement besides turning over when sleeping, and the v isiIs set to vmaxWhen said v isiLess than said vmaxWhen the user is sleeping, the user is judged to have slight movement but not turn over, and when v is in the stateiIs greater than or equal to vmaxWhen the user turns over during sleeping, the user can clearly know the sleeping posture change of the user in the sleeping state through the display of the movement track, and then the sleeping quality is judged.
Further, the light emitting diode has three colors, which are respectively: the three colors are used for judging the sleep quality of the user, the green light represents that the sleep quality of the user is good, the yellow light represents that the sleep quality of the user is general, the red light represents that the sleep quality of the user is poor, the user often does not know the sleep quality of the user when facing a group of data, and the color change of the light emitting diode enables the user to understand the sleep quality of the user more easily.
Compared with the prior art, the invention has the following beneficial effects:
1. the movement monitoring module in the monitoring end conjectures the turn-over times of the user during sleeping and the time for maintaining a constant sleeping posture by monitoring the change times of the position coordinates of the body part of the user, so as to judge the sleeping quality of the user, the whole body can be observed through the part, the working difficulty of the movement monitoring tool is reduced, the movement locus of the body part of the user is described by using a moving point space-time model, and the user can be helped to see the movement locus of the user in the sleeping state more clearly;
2. the central processing unit is connected with the voice recognition broadcasting module through the IO port after receiving the monitoring data transmitted by the monitoring end, and transmits the data to the voice recognition broadcasting module, and the voice recognition broadcasting module broadcasts the monitoring data, so that if a user does not hear own sleep monitoring information in time, the user can check the own sleep condition through the monitoring data displayed by the display module, the user can accurately know the own sleep condition without checking the own monitoring data, the difficulty of the user in recognizing the own sleep quality is reduced, and the user is helped to take corresponding measures to improve the own sleep quality, so that the working efficiency in the daytime is improved;
3. when a pile of data is faced, a user often cannot comprehensively know and accurately judge the sleep quality of the user, the control module controls the light emitting diode to emit light with different colors, the light with different colors represents different sleep qualities, the user can know the sleep condition of the user in a simpler mode, and the user is helped to comprehensively know and judge the sleep quality of the user by combining the comparison result of the monitoring information displayed by the display module and the normal monitoring information of the big data server.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a basic block diagram of a big data based sleep quality monitoring system of the present invention;
FIG. 2 is a software flow diagram of the voice recognition broadcast module of the present invention;
FIG. 3 is a diagram of the components of the monitoring end of the present invention;
FIG. 4 is a monitoring flow diagram of the motion monitoring module in the monitoring end of the present invention;
FIG. 5 is a schematic diagram of the sleep quality of the light emitting diode of the present invention represented by different lights;
FIG. 6 is a diagram of the trajectory of the specified point motion of the moving point spatiotemporal model of the present invention;
in the figure: 1. a monitoring end; 2. a central processing unit; 3. a voice recognition broadcasting module; 4. a WIFI module; 5. a control module; 6. a big data server; 7. a light emitting diode; 8. a display module; 9. an infrared body temperature monitoring module; 10. a heart rate monitoring module; 11. a blood pressure monitoring module; 12. a respiratory frequency monitoring module; 13. a motion monitoring module; 14. a blood oxygen monitoring module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-6, the present invention provides the following technical solutions: a big data based sleep quality monitoring system, the sleep quality monitoring system comprising: the system comprises a monitoring end 1, a central processing unit 2, a voice recognition broadcasting module 3, a WIFI module 4, a control module 5, a big data server 6, a light emitting diode 7 and a display module 8;
the output of monitoring end 1 is connected with central processing unit 2's input, central processing unit 2's output passes through the IO mouth with voice recognition reports the input of module and is connected, another output of central processing unit 2 is connected with WIFI module 4's input, WIFI module 4's output is connected with control module 5's input, control module 5's output and big data server 6, emitting diode 7 and display module 8's input are connected, big data server 6's output is connected with control module 5's input, control module 5 establishes two-way communication with big data server 6 and is connected, the information when being used for the user normal sleep of storage in big data server 6 makes the comparison with the information that control module 5 received from monitoring end 1, thereby can reachd the judged result of user sleep quality.
Voice recognition reports module 3 and is used for broadcasting the data message that monitoring end 1 monitored, at first, initialize voice recognition reports module 3, treat behind voice recognition reports module 3 received the data message that central processing unit 2 transmitted through monitoring end 1 monitoring, detect whether voice recognition reports module 3's serial ports received pronunciation, treat behind the serial ports received pronunciation, the user speaks the word of awakening up, after the word of awakening up was discerned by the serial ports, voice recognition reports module 3 and begins work after, the user sends second grade voice command, treat that second grade voice command is received by the serial ports after, voice recognition reports module 3 can broadcast corresponding pronunciation, the data message that monitoring end 1 monitored promptly.
The awakening words are self-defined, the secondary voice instruction is set as 'sleep monitoring information last and night' (can be changed according to actual conditions), and after the secondary voice instruction is sent out, the voice recognition broadcasting module 3 can broadcast the corresponding monitored data information so that a user can know the sleep condition of the user more conveniently.
When the data information that the play of voice broadcast module 3 was monitored, the big data server 2 in the storage have the normal sleep monitor information of user, normal sleep monitor information and the monitor information that control module 5 received are compared, and the result of comparison shows through display module 8, if the user can find data on the display screen when not hearing the sleep monitor information of oneself clearly, ensures not to have monitoring information's omission.
The movement monitoring module 13 is used for detecting the number of times of turning over a user in sleep and the time for maintaining a sleeping posture, the movement monitoring module 13 needs to use a movement monitoring tool, the movement monitoring tool is used for scanning the user after the user enters sleep, after the movement monitoring tool is fixed, the movement monitoring tool scans the user and identifies the position coordinates of a specified point (such as a nose, a point on an arm and the like), and the movement monitoring tool simultaneously observes the coordinate change of the specified point in real time to ensure the integrity of monitoring records.
When the motion monitoring tool observes the coordinate change of the appointed point in real time, if the position coordinate of the appointed point does not change, the motion monitoring tool calculates the time for keeping the position coordinate of the appointed point unchanged, if the position coordinate of the appointed point changes, the motion monitoring tool counts the times of the coordinate change of the appointed point and describes the motion track of the appointed point by using a moving point space-time model, the motion monitoring tool is also used for identifying the latest position coordinate of the appointed point, when the position coordinate of the appointed point is updated, new position information can be generated, and the new position coordinate can be identified in time, so that the accurate judgment on the change of the appointed point next time can be made.
The moving point space-time model represents the future position of the moving point by using a time function, the position attribute is the dynamic attribute of the moving point, the value of the dynamic attribute is determined by time, a position updating system is triggered when the deviation between the position of the appointed point after moving and the initial position exceeds a certain threshold value, and the position updating system is used for updating the position coordinate of the appointed point.
The motion trajectory of the specified point is composed of a seven-element group sequence (x)i，yi，zi，ti，di，viΔ t), where xi、yi、ziIs represented as a specified point tiTime of day spatial position, diRepresents tiDirection of time trace, viRepresents tiThe time speed, delta t represents the threshold value of time updating, the motion track of the designated point is determined by the value of delta t, if the designated point is at the time tiHas a position coordinate of Pi(xi，yi，zi) The specified point is in the time interval [ t ]i，ti+1]Upper slave point Pi(xi，yi，zi) To point Pi+1(xi+1，yi+1， zi+1) At a velocity viCarry out uniform linear motion, then
In the time interval ti，ti+1]Upper, the specified point is on the motion trail Pi(xi，yi，zi) And point Pi+1(xi+1，yi+1，zi+1) The position between the two is obtained by linear interpolation, and the user can have tiny actions besides turning over when sleeping, viIs set to vmaxWhen v isiLess than vmaxWhen the user is sleeping, the user is judged to have slight movement but not turn over, and when v isiGreater than or equal to vmaxAnd judging that the user turns over during sleeping.
The led 7 has three colors, which are: the green light represents that the sleep quality of the user is good, the yellow light represents that the sleep quality of the user is general, the red light represents that the sleep quality of the user is poor, and the lights with different colors represent different sleep qualities, so that the user can clearly know the sleep condition of the user.
The first embodiment is as follows: as shown in FIG. 6, a specified point P is setiHas initial position coordinates of (1, 1, 2), if the user moves to the point P in the sleeping statei+1(4, 5, 7), the required time Δ t ═ ti+1-tiSet to 3s, viMaximum value v ofmaxSet to 5cm/s according to the formula
Calculating the movement speed of the designated point
Because v isiLess than vmaxTherefore, the user is judged to have only slight movement but not turn over in the time period, and the time is accumulated to the time that the coordinate of the appointed point is kept unchangedAnd counting the time when the coordinates of the total designated point are unchanged before the position of the designated point changes next time.
The working principle of the invention is as follows: the monitoring end 1 transmits the monitored body temperature information, heart beating frequency condition, blood pressure condition, breathing frequency, turning frequency, time for maintaining a sleeping posture and oxygen content information in blood of the user during sleeping to the central processing unit 2, wherein, the movement monitoring module 13 monitors the sleeping information by scanning the user through a movement monitoring tool, the movement monitoring tool scans and identifies the position coordinates of the appointed point (such as a point on a nose and an arm), if the position of the appointed point is unchanged, the time for maintaining the coordinates of the appointed point is calculated, if the position of the appointed point is changed, the number of times of the change of the position coordinates of the appointed point is counted, so as to describe the movement track, after the position of the appointed point is changed, the movement monitoring tool updates and identifies the new position coordinates of the appointed point, so as to accurately judge the next position change of the appointed point, the central processing unit 2 is connected with the voice recognition module 3 through an IO port, the central processor 2 transmits the information to the voice recognition broadcasting module 3, the voice recognition broadcasting module is enabled to broadcast corresponding sleep monitoring information by sending a command similar to the sleep state of the user at last night to the voice recognition broadcasting module 3, meanwhile, the output end of the central processor 2 is connected with the input end of the WIFI module 4, the information is also transmitted to the control module 5 through the WIFI module 4, monitoring information of the user in normal sleep is stored in the big data server 6 and is compared with the monitoring information of the control module 5, the comparison result is displayed through the display module 8, meanwhile, the output end of the control module 5 is also connected with the input end of the light emitting diode 7, the light emitting diode 7 is controlled to emit light with different colors to represent different sleep qualities, wherein green light represents good sleep quality of the user, yellow light represents general sleep quality of the user, the red light represents that the sleep quality of the user is poor, so that the user can know the sleep condition of the user in a simple way. The invention is convenient for users to make accurate judgment on the sleep quality of the users, thereby adopting corresponding measures to improve the sleep quality of the users and improving the work efficiency of the users in the next day.
Finally, it should be noted that: it will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein, and any reference signs in the claims are not intended to be construed as limiting the claim concerned.
Claims (6)
1. A sleep quality monitoring system based on big data is characterized in that: the system for sleep quality monitoring comprises: the system comprises a monitoring end (1), a central processing unit (2), a voice recognition broadcasting module (3), a WIFI module (4), a control module (5), a big data server (6), a light emitting diode (7) and a display module (8);
the output end of the monitoring end (1) is connected with the input end of the central processing unit (2), the output end of the central processing unit (2) is connected with the input end of the voice recognition broadcasting module (3) through an IO port, the other output end of the central processing unit (2) is connected with the input end of the WIFI module (4), the output end of the WIFI module (4) is connected with the input end of the control module (5), the output end of the control module (5) is connected with the input end of the big data server (6), the light emitting diode (7) and the display module (8), the output end of the big data server (6) is connected with the input end of the control module (5), and the control module (5) is in bidirectional communication connection with the big data server (6);
the monitoring end (1) comprises an infrared body temperature monitoring module (9), a heart rate monitoring module (10), a blood pressure monitoring module (11), a respiratory rate monitoring module (12), a motion monitoring module (13) and a blood oxygen monitoring module (14), wherein the infrared body temperature monitoring module (9) is used for detecting the body temperature of a user during sleep, the heart rate monitoring module (10) is used for detecting the heart beating frequency of the user during sleep, the blood pressure monitoring module (11) is used for detecting the blood pressure condition of the user during sleep, the respiratory rate monitoring module (12) is used for detecting the respiratory frequency of the user during sleep, the motion monitoring module (13) is used for detecting the turnover frequency of the user during sleep and the time for maintaining a sleeping posture, and the blood oxygen monitoring module (14) is used for detecting the oxygen content in blood of the user during sleep;
the motion monitoring module (13) is used for detecting the number of times of turning over a user during sleeping and the time for maintaining a sleeping posture, a motion monitoring tool is needed by the motion monitoring module (13), the motion monitoring tool is used for scanning the user after the user enters the sleeping, after the motion monitoring tool is fixed, the motion monitoring tool scans the user and identifies the position coordinate of an appointed point, the appointed point is a certain point on the surface of the body of the user scanned by the motion monitoring tool, and the motion monitoring tool simultaneously observes the coordinate change of the appointed point in real time;
when the motion monitoring tool observes the coordinate change of the designated point in real time, if the position coordinate of the designated point does not change, the motion monitoring tool calculates the time for keeping the position coordinate of the designated point unchanged, if the position coordinate of the designated point changes, the motion monitoring tool counts the times of the coordinate change of the designated point and describes the motion track of the designated point by using a moving point space-time model, and the motion monitoring tool is also used for identifying the latest position coordinate of the designated point;
the motion track of the designated point consists of a seven-element group sequence (x)i，yi，zi，ti，di，viΔ t), wherein x isi、yi、ziIs represented as the specified point tiTime of day spatial position, diRepresents tiDirection of time trace, said viRepresents said tiThe time speed, the delta t represents a time updating threshold value, the motion track of the specified point is determined by the value of the delta t, and the delta t is ti+1-tiIf the specified point is at the time tiHas a position coordinate of Pi(xi，yi，zi) The specified point is in the time interval [ t ]i，ti+1]Upper slave point Pi(xi，yi，zi) To point Pi+1(xi+1，yi+1，zi+1) At said velocity viCarry out uniform linear motion, then
In said time interval ti，ti+1]The specified point is on the motion trail Pi(xi，yi，zi) And point Pi+1(xi+1，yi+1，zi+1) The position between v and v is obtained by linear interpolation, and the user can have slight movement besides turning over when sleeping, and the v isiIs set to vmaxWhen said v isiLess than said vmaxWhen the user does not turn over the body, judging that the user has micro motion in the time interval and if the user does not turn over the body, judging that the user has micro motion in the time intervaliIs greater than or equal to vmaxAnd then, judging that the user turns over in the time interval.
2. The big-data based sleep quality monitoring system according to claim 1, wherein: the voice recognition broadcasting module (3) is used for broadcasting the data information monitored by the monitoring end (1), firstly, the voice recognition broadcasting module (3) is initialized, after the voice recognition broadcasting module (3) receives the data information monitored by the monitoring end (1) and transmitted by the central processing unit (2), detecting whether the serial port of the voice recognition broadcasting module (3) receives voice, after the serial port receives the voice, a user speaks a wake-up word, after the awakening words are recognized by the serial port, the voice recognition broadcasting module (3) starts to work, after the voice recognition broadcasting module (3) starts working, a user sends a second-level voice instruction, after the second-level voice instruction is received by the serial port, the voice recognition broadcasting module (3) can broadcast corresponding voice, namely, data information monitored by the monitoring end (1).
3. The big-data based sleep quality monitoring system according to claim 2, wherein: awakening words are self-defined, the secondary voice instruction is set to be sleep monitoring information at last night, and after the secondary voice instruction is sent, the voice recognition broadcasting module (3) can broadcast the corresponding monitored data information.
4. The big-data based sleep quality monitoring system according to claim 1, wherein: when the voice broadcasting module (3) plays the monitored data information, the big data server (2) stores normal sleep monitoring information of a user, the normal sleep monitoring information is compared with the monitoring information received by the control module (5), and a comparison result is displayed through the display module (8).
5. The big-data based sleep quality monitoring system according to claim 1, wherein: the moving point space-time model represents the future position of the moving point by using a time function, the position attribute is the dynamic attribute of the moving point, the value of the dynamic attribute is determined by time, a position updating system is triggered when the deviation between the moved position of the appointed point and the initial position exceeds a certain threshold value, and the position updating system is used for updating the position coordinate of the appointed point.
6. The big-data based sleep quality monitoring system according to claim 1, wherein: the light emitting diode (7) has three colors, which are respectively: the system comprises green light, yellow light and red light, wherein the three colors are used for judging the sleep quality of a user, the green light represents that the sleep quality of the user is good, the yellow light represents that the sleep quality of the user is general, and the red light represents that the sleep quality of the user is poor.
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| CN202110502419.7A CN113197552B (en) | 2020-09-22 | 2020-09-22 | Sleep quality monitoring system based on big data |
| CN202011002021.9A CN112120670B (en) | 2020-09-22 | 2020-09-22 | Sleep quality monitoring system based on big data |
| CN202110501397.2A CN113440103B (en) | 2020-09-22 | 2020-09-22 | Sleep quality monitoring system based on big data |
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| CN202011002021.9A CN112120670B (en) | 2020-09-22 | 2020-09-22 | Sleep quality monitoring system based on big data |
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| CN202110502419.7A Division CN113197552B (en) | 2020-09-22 | 2020-09-22 | Sleep quality monitoring system based on big data |
| CN202110501397.2A Division CN113440103B (en) | 2020-09-22 | 2020-09-22 | Sleep quality monitoring system based on big data |
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| CN113197552B (en) | 2023-05-12 |
| CN112120670A (en) | 2020-12-25 |
| CN113440103A (en) | 2021-09-28 |
| CN113440103B (en) | 2023-01-10 |
| CN113197552A (en) | 2021-08-03 |
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