CN112716449A - Method and system for monitoring human sleep state based on mobile device - Google Patents
Method and system for monitoring human sleep state based on mobile device Download PDFInfo
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Abstract
The invention discloses a method for monitoring a human sleep state based on mobile equipment, which belongs to the technical field of intelligent detection and comprises the following steps: acquiring basic movement information of a first object, and restoring the detection equipment to an initial state before acquisition; judging whether to start the sonar system according to the basic movement information of the first object: if the sonar system is started, the sonar system detects an environmental noise variable; and outputting sleep report information in combination with REM sleep according to the basic movement information and the ambient noise variable of the first object. According to the method and the system for monitoring the human body sleep state based on the mobile equipment, the sleep state information is determined according to the human body state information of the first object and the preset standard information, the state of the first object is automatically calculated and analyzed according to data, the sleep state information is deduced, only basic data need to be acquired through the mobile equipment, other hardware support is not needed, and the problems that in the prior art, the hardware support cost is high and the use threshold is high are solved.
Description
Technical Field
The invention relates to the technical field of intelligent detection, in particular to a method and a system for monitoring a human sleep state based on mobile equipment.
Background
With the improvement of living standard, people pay more and more attention to their health. Among them, the quality of sleep is becoming a topic of increasing concern. Modern people are influenced by work pressure and diversification of entertainment projects, and the bad life habits of sleeping at night and staying up to night are the largest.
In the prior art, people need to turn to medical equipment or medical medicines for improving the sleep quality. The medical equipment is bulky and needs an external circuit to be attached to a human body when in use, and the medicine is difficult to persist for a long time. So that the proportion of people who really would like to resort to medical guidance is small.
Along with the popularization of intelligent mobile equipment, the mobile information of a human body is simply and conveniently acquired through the intelligent mobile equipment, the sonar system can effectively identify the variable size of the environmental noise, and the acquisition of the sleep state can become more active, simpler and more convenient by combining the data of the intelligent mobile equipment and the sleep scientific data.
Disclosure of Invention
Aiming at the problems, the invention provides a method for monitoring the sleep state of a human body based on mobile equipment.
The invention provides a method for monitoring a human sleep state based on mobile equipment, which comprises the following steps:
acquiring basic movement information of a first object, and restoring detection equipment to an initialization state before acquisition;
judging whether to start the sonar system according to the basic movement information of the first object:
if the sonar system is started, the sonar system detects an environmental noise variable;
and outputting sleep report information in combination with REM sleep according to the basic movement information and the ambient noise variable of the first object.
Further, the basic movement information of the first object includes: displacement data;
the displacement data includes: acceleration data, gyroscope data, distance data of a device held by the first object.
Further, the obtaining of the displacement data:
moving the detection object in the X-axis direction, and obtaining a set of data (X1, X2, X3 … Xn) within n seconds or n minutes of moving, wherein the displacement difference in the X-axis direction is an array M (M1 ═ X1-X2|, M2 ═ X2-X3|, … Mn-1 ═ Xn-1-Xn |), and the value in the X-axis direction is MAX or AVERGAE (M1, M2 … Mn), the larger of the two;
meanwhile, obtaining a corresponding number sequence N and a corresponding number sequence P in the Y-axis direction and the Z-axis direction by using the same calculation method;
the number sequence N (N1 ═ Y1-Y2|, N2 ═ Y2-Y3| … Nn-1 ═ Yn-1-Yn |), the value in the final Y direction being MAX or AVERGAE (N1, N2 … Nn), the larger of the two;
the numerical sequence P (P1 ═ Z1-Z2|, P2 ═ Z2-Z3| … Pn-1 ═ Zn-1-Zn |), and finally the value in the Z axis direction is MAX or AVERGAE (M1, M2 … Mn), whichever is larger.
Further, the sonar system is started; the displacement difference of the first object in the three directions of the coordinates X-axis, Y-axis and Z-axis for the previous second and the next second is less than 0.05m-1 m.
Further, when the displacement difference of the first object in the three directions of the X axis, the Y axis and the Z axis of the coordinate in the previous second and the next second is more than 0.05m-1 m; the sonar system is not activated.
Furthermore, before collecting the basic movement information of the first object, preset information is carried out;
the preset information includes: the magnitude of the displacement of the first object and the ambient noise variation in which the first object is located.
Further, the displacement is preset to be-15 m/s2To 15m/s2And the preset size of the environmental noise is 0db-90 db.
Further, the system for monitoring the sleep state of the human body by the mobile device comprises: collecting equipment;
the acquisition device includes: the system comprises a mobile APP, a hardware sensor, a central processing unit and an output device;
the mobile APP is used for collecting displacement data;
the hardware sensor is used for detecting environmental decibel data;
the central processing unit is used for processing the relevant information transmitted by the mobile APP and the hardware sensor;
and the output equipment is used for outputting the data processed by the central processing unit.
The invention has the advantages that:
1. according to the method and the system for monitoring the human body sleep state based on the mobile equipment, the sleep state information is determined according to the human body state information of the first object and the preset standard information, the state of the first object is automatically calculated and analyzed according to data, the sleep state information is deduced, only basic data need to be acquired through the mobile equipment, other hardware support is not needed, and the problems that in the prior art, the hardware support cost is high and the use threshold is high are solved.
2. The invention does not need special or expensive information acquisition hardware, and mobile equipment such as smart phones, bracelets and other daily equipment can be used, thus having no manufacturing cost of a user side.
3. The invention adopts the mobile equipment to obtain the original data and directly carries out modeling training, has low manufacturing cost and greatly improves the flexibility, the adaptability and the popularity.
4. The invention is an attempt made in the field of sleep health, which feeds back the sleep track of a user in real time, assists the user to adjust the sleep habit in time and ensures the sleep health.
5. According to the invention, the sleep behavior of the user can be analyzed and evaluated by measuring data, and great improvement and continuous tracking in the aspect of functionality are realized.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention.
FIG. 1 is a flow chart of the operation of the present invention;
FIG. 2 is a flow chart of the present invention for detecting wake-up of a subject
FIG. 3 is a flow chart of the present invention for detecting that a subject has slept.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The terms "first" and the like in the description and in the claims, and in the preceding drawings, if any, 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 invention described herein are, for example, 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.
Example one
Referring to fig. 1 to 3, as shown in fig. 1 to 3, a method for monitoring a sleep state of a human body based on a mobile device includes: acquiring basic movement information of a first object, and restoring the detection equipment to an initial state before acquisition;
judging whether to start the sonar system according to the basic movement information of the first object:
if the sonar system is started, the sonar system detects an environmental noise variable;
and outputting sleep report information in combination with REM sleep according to the basic movement information and the ambient noise variable of the first object.
It should be noted that REM sleep, also called heterogeneous sleep (Para-sleep) or fast phase sleep, heterogeneous sleep or fast wave sleep, is a rapid eye movement. The eyeball is a sleep stage, and the eyeball can rapidly move involuntarily at the sleep stage. At this stage, the brain neurons are active as they were awake. Most lifelike dreams that can be recalled after waking up occur at REM sleep. It is the shallowest of all sleep stages, and people who wake up while REM sleeps will be different from those in other sleep stages, but full of alertness and mental fullness.
In addition, REM sleep usually occurs at the part of the transition from the deep sleep period to the shallow sleep period, so we adopt different calculation methods according to different data situations:
when the first object passes a longer deep sleep period and enters a shorter light sleep period, marking the time length of the second half of the deep sleep period which is less than 50 percent as first REM sleep, and the time length of single REM sleep is not more than 15 minutes;
when the first subject enters a longer light sleep period after a shorter deep sleep period, the first half of the light sleep period < 50% is marked as the second REM sleep, and the single REM sleep time length does not exceed 15 minutes.
It should be noted that REM sleep refers to the existing REM analysis system to output the sleep report in the present solution, and the specific process of analyzing data is not described herein again, and the analysis principle refers to the introduction of the prior art.
In an embodiment of the present invention, the basic mobility information includes: displacement data;
the displacement data includes: acceleration data, gyroscope data, distance data of a device held by the first object.
In an embodiment of the present invention, the basic movement information of the first object includes: displacement data;
the displacement data includes: acceleration data, gyroscope data, distance data of a device held by the first object.
In an embodiment of the present invention, the obtaining of the displacement data:
it should be noted that both the displacement data and the sonar system data are acquired at a frequency not lower than every second, and in some special cases, at a millisecond frequency. The moving device tests show that the displacement difference is not obvious on the premise that the moving speed of the first object is accurate to the second, so that training data are measured in a unit of every n seconds and every n minutes in the model respectively, and the difference value of all detection data in the n seconds or n minutes is obtained by taking a MAX function or an AVERAGE function to obtain a determined value. After repeated pre-verification, the finally obtained modeling training formula is as follows:
moving the detection object in the X-axis direction, and obtaining a set of data (X1, X2, X3 … Xn) within n seconds or n minutes of moving, wherein the displacement difference in the X-axis direction is an array M (M1 ═ X1-X2|, M2 ═ X2-X3|, … Mn-1 ═ Xn-1-Xn |), and the value in the X-axis direction is MAX or AVERGAE (M1, M2 … Mn), the larger of the two;
meanwhile, obtaining a corresponding number sequence N and a corresponding number sequence P in the Y-axis direction and the Z-axis direction by using the same calculation method;
the number sequence N (N1 ═ Y1-Y2|, N2 ═ Y2-Y3| … Nn-1 ═ Yn-1-Yn |), the value in the final Y direction being MAX or AVERGAE (N1, N2 … Nn), the larger of the two;
the numerical sequence P (P1 ═ Z1-Z2|, P2 ═ Z2-Z3| … Pn-1 ═ Zn-1-Zn |), and finally the value in the Z axis direction is MAX or AVERGAE (M1, M2 … Mn), whichever is larger.
In one embodiment of the invention, a sonar system is started; the displacement difference of the first object in the three directions of the coordinates X-axis, Y-axis and Z-axis for the previous second and the next second is less than 0.05m-1 m.
In one embodiment of the invention, when the displacement difference of the first object in the three directions of the coordinate X axis, the coordinate Y axis and the coordinate Z axis in the previous second and the next second is more than 0.05m-1 m; the sonar system is not activated.
In one embodiment of the invention, the preset information is carried out before the basic movement information of the first object is collected; the preset information includes: the magnitude of the displacement of the first object and the ambient noise variation in which the first object is located.
In one embodiment of the present invention, the preset displacement is-15 m/s2To 15m/s2And the preset size of the environmental noise is 0db-90 db.
In one embodiment of the present invention, the method includes: collecting equipment;
the acquisition device includes: the system comprises a mobile APP, a hardware sensor, a central processing unit and an output device;
the mobile APP is used for collecting displacement data;
the hardware sensor is used for detecting environmental decibel data;
the central processing unit is used for processing the relevant information transmitted by the mobile APP and the hardware sensor;
and the output equipment is used for outputting the data processed by the central processing unit.
Example two
A method for monitoring the sleep state of a human body based on a mobile device can be as follows:
in this embodiment, displacement and ambient noise decibel change data can be collected through the mobile device and the hardware sensor.
S101, starting sleep monitoring through mobile terminal apps to ensure that data can be acquired in the running process of the equipment.
S102, acquiring displacement data, and acquiring acceleration data, gyroscope data and distance data of equipment held by a first object through detection equipment;
determining basic movement information of the first object according to the displacement, namely X-axis, Y-axis and Z-axis information data during the equipment held by the first object;
determining sonar system starting time node information according to the basic movement information of the first object;
s103, deducing the human body state of the first object according to the displacement data: whether to fall asleep;
specifically, the method comprises the steps of calculating the displacement difference of the X axis, the Y axis and the Z axis of the mobile equipment according to the displacement data, namely the X axis, the Y axis and the Z axis information of the equipment period held by the first object, obtaining the range value of the displacement difference, and judging whether the human body state is 'still/asleep' or 'clear/not asleep' according to whether the displacement data reach the standard or not "
S104, if the first object does not carry the mobile equipment or the human body state is 'still/asleep', acquiring an environmental noise variable by using a sonar system; wherein the ambient noise variation is collected by a device microphone
And according to the environment noise variable, calculating the noise variable difference of the area where the mobile equipment is located to obtain the range value of the variable difference.
S105, according to the obtained noise variation difference, and in combination with the basic law that a basic model during sleep is supposed to be deep sleep, light sleep and clear-headed, presetting the sleep state of the first object as deep sleep, light sleep and clear-headed; and continuously correcting the variation difference in the monitoring process to enable the sleep state of the first object to continuously approach to the real sleep state.
And S106, graphically marking the sleep state 'dream' of the first object according to the sleep state of the first object in the previous step and by combining REM sleep, namely the stage and trigger of the dream during the sleep process.
And S107, combining the steps, deducing the acquired data of the first object, the environmental noise variable data and the REM sleep, drawing a sleep track of the first object in the sleep monitoring process and presenting the sleep track to the first object.
It should be noted that, in this embodiment, it is ensured that the sleep state of the first subject conforms to the basic rule of sleep, and conforms to the sleep cycle, deep sleep, and light sleep time ratio corresponding to the first subject, and the calculation is continuously corrected.
It should be noted that, in order to more accurately detect the sleep state of the first object, a basic preview of the first object may be performed, that is, the basic data frame is made by combining various states of human body movement, including the displacement numbers reflected by the static, slight movement, and violent movement, wherein the larger the data amount of the object, the more accurate the data.
For example, the ambient noise variance of the first subject is poor and the pre-performance of the sleep state, the collected ambient noise variance belongs to one of deep sleep, light sleep or awake in the personal behavior of the first subject. The thresholds for deep and light sleep are set in conjunction with the basic ambient noise, and the calculations are corrected for each complete monitoring of the first subject.
The specific process comprises the following steps:
the method comprises the following steps of firstly, dividing test objects into N groups, and respectively carrying out complete data acquisition for more than 24 hours on each group of test objects by adopting mobile equipment to match with personal records of the test objects. Obtaining different displacement variables of the test object in the processes of walking, running, sleeping and daily using the mobile phone, and dividing a rough living and activating interval.
The second step is that: the accuracy correction data is marked by the N groups of test subjects according to the coarse liveness interval markers.
The third step: and releasing the correction data model to the line, and repeatedly verifying the model for multiple times by combining with the feedback of the real object.
The fourth step: in combination with scientific sleep data, deep sleep accounts for about 25%, light sleep accounts for about 55%, and data during sleep are corrected.
In this example, the sleep trajectory is recorded graphically, including as a histogram, a waveform, and the like.
Continuous monitoring of the first subject can result in effective historical data that, when analyzed, results in a sleep quality improvement program, but is not limited to helping fall asleep, foster regular sleep, abstain from behavioral or other factors that affect sleep, and the like.
It should be noted that, as can be understood by those skilled in the art: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (8)
1. A method for monitoring a sleep state of a human body based on a mobile device is characterized by comprising the following steps:
acquiring basic movement information of a first object, and restoring the detection equipment to an initial state before acquisition;
judging whether to start the sonar system according to the basic movement information of the first object:
if the sonar system is started, the sonar system detects an environmental noise variable;
and outputting sleep report information in combination with REM sleep according to the basic movement information and the ambient noise variable of the first object.
2. The mobile device-based human sleep state monitoring method of claim 1, wherein the basic movement information of the first object comprises: displacement data;
the displacement data includes: acceleration data, gyroscope data, distance data of a device held by the first object.
3. The method for monitoring the sleep state of a human body based on a mobile device according to claim 2, wherein the obtaining of the displacement data comprises:
moving the detection object in the X-axis direction, and obtaining a set of data (X1, X2, X3 … Xn) within n seconds or n minutes of moving, wherein the displacement difference in the X-axis direction is an array M (M1 ═ X1-X2|, M2 ═ X2-X3|, … Mn-1 ═ | X n-1-Xn |), and the value in the X-axis direction is MAX or AVERGAE (M1, M2 … Mn), the larger of the two;
meanwhile, obtaining a corresponding number sequence N and a corresponding number sequence P in the Y-axis direction and the Z-axis direction by using the same calculation method;
the numerical sequence N (N1 ═ Y1-Y2|, N2 ═ Y2-Y3| … N N-1 ═ Y N-1-Yn |), the value in the final Y direction is MAX or AVERGAE (N1, N2 … Nn), the larger of the two;
the numerical sequence P (P1 ═ Z1-Z2|, P2 ═ Z2-Z3| … P n-1 ═ Zn-1-Zn |), and finally the value in the Z axis direction is MAX or AVERGAE (M1, M2 … Mn), the larger of the two.
4. The method for monitoring the sleep state of the human body based on the mobile equipment according to the claim 3, characterized in that the sonar system is started; the displacement difference of the first object in the three directions of the coordinates X-axis, Y-axis and Z-axis for the previous second and the next second is less than 0.05m-1 m.
5. The method for monitoring the sleep state of the human body based on the mobile device according to claim 4, wherein when the displacement difference of the first object in the three directions of the coordinate X-axis, the coordinate Y-axis and the coordinate Z-axis in the previous second and the next second is more than 0.05m-1 m; the sonar system is not activated.
6. The method for monitoring the sleep state of the human body based on the mobile device as claimed in claim 1, wherein the preset information is performed before the basic movement information of the first object is acquired;
the preset information includes: the magnitude of the displacement of the first object and the ambient noise variation in which the first object is located.
7. The method for monitoring sleep states of a human body based on a mobile device according to claim 1, wherein the displacement is preset to be-15 m/s2To 15m/s2And the preset size of the environmental noise is 0db-90 db.
8. The system for monitoring the sleep state of a human body based on a mobile device according to claim 1, which comprises: collecting equipment;
the acquisition device includes: the system comprises a mobile APP, a hardware sensor, a central processing unit and an output device;
the mobile APP is used for collecting displacement data;
the hardware sensor is used for detecting environmental decibel data;
the central processing unit is used for processing the relevant information transmitted by the mobile APP and the hardware sensor;
and the output equipment is used for outputting the data processed by the central processing unit.
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