Daytime short-term sleep evaluation method based on multi-dimensional lighting factors

Abstract

The invention relates to a daytime short-term sleep evaluation method based on multi-dimensional lighting factors, and belongs to the technical field of sleep monitoring. The method comprises the following steps: obtaining individual characteristics, afternoon nap behavior characteristics and a sleep quality evaluation result of a research object, and carrying out code conversion to obtain a correlation analysis result of the afternoon nap characteristics and an afternoon nap light environment; setting a physiological rhythm test according to a correlation analysis result, and performing a light intervention experiment on the research object through the physiological rhythm test to obtain experimental effect data; staged regression analysis is carried out on test indexes in experimental effect data along with non-visual effect illumination changes by establishing an illumination adjustment model based on the afternoon nap rhythm and moment, and a health rhythm illumination parameter standard table is established according to a staged regression analysis result. Sleep quality is effectively optimized according to a health rhythm illumination parameter standard table, emotion and alertness are adjusted, and sleep disorders are reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of sleep monitoring, and in particular relates to a daytime short-term sleep evaluation method based on multi-dimensional lighting factors. Background Art

[0002] Light exposure is one of the important factors that affect sleep. Studies have shown that adequate daylight exposure can improve sleep quality, reduce sleep disturbances, and have a positive impact on mood and mental health. Lighting operations at different time periods have significant effects on objective indicators of sleep (such as duration and efficiency) and subjective indicators (such as sleep quality); with the discovery of retinal photosensitive ganglion cells (ipRGC), the evaluation of light environment has transitioned from the single visual effect in the past to the dual evaluation of visual and non-visual effects. The close relationship between light and health has been further confirmed and refined. Light physical properties such as spectrum, light intensity, light history, and exposure time will affect biological indicators such as human hormone secretion, body temperature, and heart rate, thereby affecting daily routines closely related to health, such as alertness, work efficiency, mood, and sleep.

[0003] The lighting conditions used in the studies are highly heterogeneous, including light intensity, color temperature (CCT), exposure time, duration, etc. The inconsistency of these factors leads to inconsistent results on the effects on sleep and cognitive performance. In addition, many studies were conducted in laboratory environments, without fully considering the general credibility of the research results in the real-world environment; in field studies, although some studies adopted randomized controlled trial designs, there are challenges in implementing certain objective assessment techniques (such as electroencephalograms (EEGs)), and requiring participants to use equipment (such as activity recorders) for a long time increases the complexity of the research. In addition, current studies lack systematic examination of the dynamic relationship between daytime light, emotion, and sleep, indicating that this possible path of action still needs further empirical research to prove.

[0004] Overall, although existing studies have explored the effects of light on sleep and adopted a variety of subjective and objective assessment methods, these methods still face many challenges in practical application, such as inconsistent lighting conditions, limitations of research environments, and complexity of assessment techniques. Summary of the invention

[0005] In order to solve the above problems existing in the prior art, the present invention provides a method for evaluating daytime short-term sleep based on multi-dimensional lighting factors. The purpose of the present invention can be achieved through the following technical solutions:

[0006] A method for evaluating daytime short-term sleep based on multi-dimensional lighting factors, including:

[0007] S1: Obtain the individual characteristics, nap behavior characteristics, and sleep quality assessment results of the research subjects, and perform coding conversion to obtain the correlation analysis results between nap characteristics and nap light environment;

[0008] S2: setting a physiological rhythm test according to the correlation analysis result, and performing a light intervention experiment on the research subject through the physiological rhythm test to obtain experimental effect data;

[0009] S3: By establishing a lighting regulation model based on nap rhythm and time, a staged regression analysis is performed on the test indicators in the experimental effect data as the non-visual effect illumination changes, and a standard table of healthy rhythm lighting parameters is established according to the staged regression analysis results.

[0010] Specifically, the individual characteristics are gender and age for controlling individual differences, the nap behavior characteristics include nap time, location, frequency, and duration, and the sleep quality assessment result is the quantitative assessment result of the research subject on the brightness, color, temperature, and softness of the nap light environment.

[0011] In this embodiment, Figure 2 As shown, through actual questionnaire survey, the relationship between nap characteristics and lighting factors was analyzed. Through literature research and actual plans, the survey content covering multiple aspects of individual naps was designed. The main contents include: Basic individual information: including basic background information such as gender, age, occupation / major, so as to control individual differences when analyzing data; Description of nap behavior characteristics: covering aspects such as nap time, location, frequency, duration, etc., to obtain the basic characteristics of individual nap behavior; Nap light environment evaluation: explore the respondents' subjective feelings about the nap light environment, including evaluation of light brightness, color, temperature, light softness, etc.; Nap effect evaluation: through the respondents' self-evaluation of nap effects, examine the potential impact of the light environment on nap quality. As shown in the figure, through actual questionnaire survey, the relationship between nap characteristics and lighting factors was analyzed. Figure 3 As shown, each original categorical question, including the answers to “nap duration”, “nap quality”, “actual light environment for nap” and “mental state after nap”, was coded and converted in ascending order of 1234 to represent the increasing quality of nap.

[0012] Specifically, the test indicators of the physiological rhythm test include electroencephalogram, KSS sleepiness scale, body temperature, heart rate, and lighting parameters of lighting conditions are preset according to illumination and color temperature data.

[0013] Specifically, the EEG is used to record brain wave band data of alpha waves, beta waves, theta waves, and delta waves under lighting parameters, the alpha waves are used to indicate that the brain is in a relaxed state, the beta waves are used to indicate wakefulness and rapid eye movement sleep, the theta waves are used to indicate shallow sleep stages and rapid eye movement sleep stages, and the delta waves are used to indicate deep sleep stages.

[0014] Specifically, the KSS sleepiness scale is an influence factor of illumination and color temperature on alertness during nap.

[0015] Specifically, the illumination adjustment model is used to calculate the non-visual equivalent illumination according to the illumination parameters of the illumination conditions. The non-visual equivalent illumination adopts the melanopic equivalent daylight illumination, and the calculation formula is:

[0016]

[0017] Among them, S mel (λ) is the spectral energy distribution, E e,λ (λ) is the spectral response curve of melanopsin, λ is the wavelength in the spectrum, is the melanopsin equivalent daylight illuminance, The scaling factor that equalizes the equivalent illuminance value of non-visual photoreceptor cells (ipRGC) to the illuminance value of photopic vision.

[0018] Specifically, the staged regression analysis selects the melanopsin equivalent daylight illumination as the independent variable, and takes the body temperature change rate and heart rate change rate at the sampling time as the dependent variables, and constructs a body temperature light parameter regression model and a heart rate light parameter regression model respectively.

[0019] Specifically, the standard table of healthy rhythmic lighting parameters uses electroencephalogram, KSS sleepiness scale, body temperature, and heart rate as horizontal indicators, and takes falling asleep, steady-state sleep, deep sleep, and awakening during the nap stage as sampling moments to construct standard reference values ​​for color temperature and melanopsin EDI.

[0020] Specifically, the lighting conditions include desktop illumination, color temperature, 45° eye illumination, and non-visual irradiance of photoreceptor cells.

[0021] Specifically, the duration and intensity of the light stimulation in the light intervention experiment are controlled by a programmable microcontroller to match the sleep pattern of the research subject, and the experimental effect data are quantified by the standard deviation between the experimental group and the control group.

[0022] The beneficial effects of the present invention are:

[0023] Based on the actual nap light environment survey and preference research, a practical nap experiment under different nap light environments was designed, and the nap rhythm and sleepiness scale were used to comprehensively evaluate the nap quality itself and the nap sleep inertia, which has practical significance in terms of experimental design and evaluation methods; the lighting system was converted from visual to non-visual, and then the nap was divided into stages, and then the melanopsin EDI and color temperature were given for each stage according to the nap rhythm, which provided theoretical guidance and scientific basis for the dynamic lighting control of the nap light environment and the creation of a healthy nap light environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0025] Figure 1 It is a flow chart of a method for evaluating daytime short-term sleep based on multi-dimensional lighting factors of the present invention;

[0026] Figure 2 It is a flowchart of the questionnaire-based nap habit and benefit evaluation study in the present invention;

[0027] Figure 3 This is a coding distribution diagram based on the nap light environment preference analysis category;

[0028] Figure 4 It is a schematic diagram of the flow of the experimental effect analysis of the lighting conditions on the nap rhythm in the present invention;

[0029] Figure 5 It is a flow chart of the light regulation model based on nap rhythm and time in the present invention;

[0030] Figure 6 This is a standard table of healthy rhythm lighting parameters in the present invention. DETAILED DESCRIPTION

[0031] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0032] See also Figure 1 , a method for evaluating short-term daytime sleep based on multi-dimensional lighting factors, including:

[0033] S1: Obtain the individual characteristics, nap behavior characteristics, and sleep quality assessment results of the research subjects, and perform coding conversion to obtain the correlation analysis results between nap characteristics and nap light environment;

[0034] S2: setting a physiological rhythm test according to the correlation analysis result, and performing a light intervention experiment on the research subject through the physiological rhythm test to obtain experimental effect data;

[0035] S3: By establishing a lighting regulation model based on nap rhythm and time, a staged regression analysis is performed on the test indicators in the experimental effect data as the non-visual effect illumination changes, and a standard table of healthy rhythm lighting parameters is established according to the staged regression analysis results.

[0036] Specifically, the individual characteristics are gender and age for controlling individual differences, the nap behavior characteristics include nap time, location, frequency, and duration, and the sleep quality assessment result is the quantitative assessment result of the research subject on the brightness, color, temperature, and softness of the nap light environment.

[0037] Specifically, the test indicators of the physiological rhythm test include electroencephalogram, KSS sleepiness scale, body temperature, heart rate, and lighting parameters of lighting conditions are preset according to illumination and color temperature data.

[0038] In this embodiment, Figure 4 As shown, since the basic survey questionnaire failed to clearly draw out the lighting factors that affect naps, a specific nap lighting experiment is needed to explore the effects of different lighting parameters on the physiological rhythm of naps and the degree of sleepiness before and after naps. Lighting parameters - This study set four illumination levels (0LX, 60LX, 300LX, 600LX) and two color temperature levels (2800K, 5800K), forming 7 nap lighting conditions: L0 (darkness), L1 (60LX, 2800k), L2 (300LX, 2800K), L3 (600LX, 2800K), L4 (60LX, 5800K), L5 (300LX ,5800k), L6 (600LX, 5800K); the dark environment is used to simulate the light environment of wearing an eye mask during a nap. 60lx is set to low illumination, and 300lx is used to simulate the desktop illumination set according to national standards for drawing curtains during a nap; 600lx is calculated based on the CIE and WELL proposal that the daytime bedroom illumination should not be less than 250EML; 2800K and 5800K are designed to be soft and bright based on the survey.

[0039] Specifically, the EEG is used to record brain wave band data of alpha waves, beta waves, theta waves, and delta waves under lighting parameters, the alpha waves are used to indicate that the brain is in a relaxed state, the beta waves are used to indicate wakefulness and rapid eye movement sleep, the theta waves are used to indicate shallow sleep stages and rapid eye movement sleep stages, and the delta waves are used to indicate deep sleep stages.

[0040] Specifically, the KSS sleepiness scale is an influence factor of illumination and color temperature on alertness during nap.

[0041] Specifically, the illumination adjustment model is used to calculate the non-visual equivalent illumination according to the illumination parameters of the illumination conditions. The non-visual equivalent illumination adopts the melanopic equivalent daylight illumination, and the calculation formula is:

[0042]

[0043] Among them, S mel (λ) is the spectral energy distribution, Ee,λ (λ) is the spectral response curve of melanopsin, λ is the wavelength in the spectrum, is the melanopsin equivalent daylight illuminance, The scaling factor that equalizes the equivalent illuminance value of non-visual photoreceptor cells (ipRGC) to the illuminance value of photopic vision.

[0044] Specifically, the staged regression analysis selects the melanopsin equivalent daylight illumination as the independent variable, and takes the body temperature change rate and heart rate change rate at the sampling time as the dependent variables, and constructs a body temperature light parameter regression model and a heart rate light parameter regression model respectively.

[0045] Specifically, the standard table of healthy rhythmic lighting parameters uses electroencephalogram, KSS sleepiness scale, body temperature, and heart rate as horizontal indicators, and takes falling asleep, steady-state sleep, deep sleep, and awakening during the nap stage as sampling moments to construct standard reference values ​​for color temperature and melanopsin EDI.

[0046] Specifically, the lighting conditions include desktop illumination, color temperature, 45° eye illumination, and non-visual irradiance of photoreceptor cells.

[0047] Specifically, the duration and intensity of the light stimulation in the light intervention experiment are controlled by a programmable microcontroller to match the sleep pattern of the research subject, and the experimental effect data are quantified by the standard deviation between the experimental group and the control group.

[0048] In this embodiment, Figure 5 As shown, the functional law of each test index changing with the non-visual effect illumination was explored, and regression analysis was performed to find the more appropriate non-visual illumination in different time periods (every five minutes) during naps, and a lighting regulation model based on nap rhythm and time was established.

[0049] The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device.

[0050] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0051] The program code included on the computer readable medium can be transmitted with any appropriate medium, including but not limited to wireless, electric wire, optical cable, RF, etc., or any suitable combination of the above. The computer program code for performing the operation of the present invention can be written in one or more programming languages ​​or their combinations, and the programming language includes object-oriented programming languages-such as Java, Smalltalk, C++, and also includes conventional procedural programming languages-such as "C" language or similar programming languages. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0052] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A method for evaluating daytime short-term sleep based on multi-dimensional lighting factors, characterized in that: include: S1: Obtain the individual characteristics, nap behavior characteristics, and sleep quality assessment results of the research subjects, and perform coding conversion to obtain the correlation analysis results between nap characteristics and nap light environment; S2: setting a physiological rhythm test according to the correlation analysis result, and performing a light intervention experiment on the research subject through the physiological rhythm test to obtain experimental effect data; S3: By establishing a lighting regulation model based on nap rhythm and time, a staged regression analysis is performed on the test indicators in the experimental effect data as the non-visual effect illumination changes, and a standard table of healthy rhythm lighting parameters is established according to the staged regression analysis results.

2. The method for evaluating daytime short-term sleep based on multi-dimensional lighting factors according to claim 1, characterized in that: The individual characteristics are gender and age for controlling individual differences, the nap behavior characteristics include nap time, location, frequency, and duration, and the sleep quality assessment result is the quantitative assessment result of the research subject on the brightness, color, temperature, and softness of the nap light environment.

3. The method for evaluating daytime short-term sleep based on multi-dimensional lighting factors according to claim 1, characterized in that: The test indicators of the physiological rhythm test include electroencephalogram, KSS sleepiness scale, body temperature, heart rate, and lighting parameters of the lighting conditions are preset according to illumination and color temperature data.

4. The method for evaluating daytime short-term sleep based on multi-dimensional lighting factors according to claim 3, characterized in that: The electroencephalogram is used to record the brain wave band data of alpha waves, beta waves, theta waves, and delta waves under lighting parameters, the alpha waves are used to indicate that the brain is in a relaxed state, the beta waves are used to indicate the awake state and rapid eye movement sleep, the theta waves are used to indicate the shallow sleep stage and the rapid eye movement sleep stage, and the delta waves are used to indicate the deep sleep stage.

5. The method for evaluating daytime short-term sleep based on multi-dimensional lighting factors according to claim 3, characterized in that: The KSS sleepiness scale is a factor that measures the impact of illumination and color temperature on alertness during naps.

6. The method for evaluating daytime short-term sleep based on multi-dimensional lighting factors according to claim 1, characterized in that: The illumination adjustment model is used to calculate the non-visual equivalent illumination according to the illumination parameters of the illumination conditions. The non-visual equivalent illumination adopts the melanopsin equivalent daylight illumination, and the calculation formula is: Among them, S mel (λ) is the spectral energy distribution, E e,λ (λ) is the spectral response curve of melanopsin, λ is the wavelength in the spectrum, is the melanopsin equivalent daylight illuminance, The scaling factor that equalizes the equivalent illuminance value of non-visual photoreceptor cells (ipRGC) to the illuminance value of photopic vision.

7. The method according to claim 6, characterized in that The staged regression analysis selects the melanopsin equivalent daylight illumination as the independent variable, and takes the body temperature change rate and heart rate change rate at the sampling time as the dependent variables, and constructs a body temperature light parameter regression model and a heart rate light parameter regression model respectively.

8. The method for evaluating daytime short-term sleep based on multi-dimensional lighting factors according to claim 7, characterized in that: The standard table of healthy rhythmic lighting parameters uses electroencephalogram, KSS sleepiness scale, body temperature, and heart rate as horizontal indicators, and uses falling asleep, steady-state sleep, deep sleep, and waking during the nap stage as sampling moments to construct standard reference values ​​for color temperature and melanopsin EDI.

9. The method for evaluating daytime short-term sleep based on multi-dimensional lighting factors according to claim 3, characterized in that: The lighting conditions include desktop illumination, color temperature, 45° eye illumination, and non-visual irradiance of photoreceptor cells.

10. The method for evaluating daytime short-term sleep based on multi-dimensional lighting factors according to claim 1, characterized in that: The duration and intensity of the light stimulation in the light intervention experiment are controlled by a programmable microcontroller to match the sleep pattern of the research subjects, and the experimental effect data are quantified by the standard deviation between the experimental group and the control group.

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