WO2024007364A1

WO2024007364A1 - Wearable-device-based light environment and posture detection method, apparatus and system

Info

Publication number: WO2024007364A1
Application number: PCT/CN2022/106272
Authority: WO
Inventors: 林波荣; 曾云一; 孙弘历; 余娟
Original assignee: 清华大学
Priority date: 2022-07-05
Filing date: 2022-07-18
Publication date: 2024-01-11
Also published as: CN115177240A

Abstract

Provided are a wearable-device-based light environment and posture detection method, apparatus and system, and a storage medium. The method comprises: receiving illumination data of ambient light collected by a wearable device and motion data of a target object wearing the wearable device, the wearable device being worn near the eyes of the target object (S201); determining a posture angle of the head of the target object according to the motion data (S202); and according to the posture angle and/or the illumination data, detecting a posture of the target object and/or the light environment where the target object is located to obtain a detection result (S203). Long-duration multi-site healthy light environment perception can be realized by means of the wearable device, and the health effects of light can be detected and prompted from the perspectives of both biological rhythm and vision health.

Description

Light environment and attitude detection methods, devices and systems based on wearable devices

This application requests the priority of the Chinese patent application submitted to the China Patent Office on July 5, 2022, with the application number 202210793682.0 and the invention title "Light environment and attitude detection method, device and system based on wearable devices", all of which The contents are incorporated into this application by reference.

Technical field

The present disclosure relates to the field of light environment and attitude detection, and in particular, to a method, device, and system for light environment and attitude detection based on wearable devices.

Background technique

Eyes are the windows to the soul, and the information they receive affects human emotions and even health. More than 70% of the information a person obtains in a day comes from light. In addition to providing vision, light is also an important timing factor for the human body's biological clock, affecting people's circadian rhythm and work status. The influence of light on vision and biological clock is closely related to the illumination and spectral distribution of the human eye. For example, too strong light can damage the retina, and too weak light can easily cause visual fatigue; the light environment in the blue light band is conducive to improving vitality during the day, but exposure to blue light at night can induce sleep disorders.

Therefore, eye health is related to the health of the whole body. Among them, vision health has attracted much attention in recent years. Myopia in my country has shown a trend of getting younger. In 2020, the overall myopia rate among children and adolescents nationwide reached 52.7%. The causes of myopia include substandard lighting environment, substandard sitting posture, and long-term use of eyes at close range.

How to promptly identify and provide prompts for these triggers on people's health, biological rhythms, etc. in daily life is a key issue to be solved.

Contents of the invention

In view of this, the present disclosure proposes a method, device, system and storage medium for light environment and posture detection based on wearable devices.

According to one aspect of the present disclosure, a light environment and attitude detection method is provided, including:

Receive illumination data of ambient light collected by a wearable device and motion data of a target object wearing the wearable device, the wearable device being worn near the eyes of the target object;

Determine the posture angle of the target object's head based on the motion data;

According to the posture angle and/or the illumination data, the posture and/or the light environment of the target object are detected to obtain a detection result.

In a possible implementation, the posture and/or the light environment of the target object are detected according to the posture angle and/or the illumination data, and the detection results are obtained, including:

Determine spectral information based on the illumination data;

It is determined based on the spectral information that the main light source of the light environment is natural lighting or artificial lighting.

Determine illumination based on the illumination data;

When the illumination exceeds the first threshold, first prompt information is generated, and the first prompt information indicates that the illumination is too high or the illumination adjustment method.

According to the posture angle, it is determined that the posture of the target object is computer office work or paper office work, and it is determined whether the target object has a bad sitting posture according to the posture angle.

In a possible implementation, detecting the posture and/or the light environment of the target object according to the posture angle and/or the illumination data, and obtaining the detection results includes:

Determine color temperature based on the lighting data;

When it is determined that the posture of the target object is working with a computer and the color temperature exceeds the second threshold, second prompt information is generated, and the second prompt information indicates that the color temperature is too high or the color temperature adjustment method is too high.

Determine the target period to which the current time belongs;

Determine physiologically equivalent illuminance based on lighting data;

When the physiological equivalent illuminance does not meet the preset conditions corresponding to the target period, third prompt information is generated, and the third prompt information indicates abnormal physiological equivalent illuminance or a physiological equivalent illuminance adjustment method.

In a possible implementation, detecting the posture and/or the light environment of the target object according to the posture angle and/or the illumination data, and obtaining a detection result, further includes:

When it is determined that the posture of the target object is a bad sitting posture, fourth prompt information is generated, and the fourth prompt information indicates a bad sitting posture or a sitting posture adjustment method.

In a possible implementation, the method further includes:

Store the illumination data, motion data and detection results;

Determine the statistical information for light environment and posture detection based on the detection results within the preset time period;

According to the statistical information, fifth prompt information is generated.

In a possible implementation, the statistical information includes:

Natural light lighting time; and/or

The proportion of the target time of any one or more of the illumination, color temperature, physiologically equivalent illumination and the posture of the target object to the preset time period.

In a possible implementation, fifth prompt information is generated based on the statistical information, including:

When the natural light illumination time is insufficient, the fifth prompt message indicates receiving more sufficient natural light;

When the illumination and/or the target object's attitude compliance rate is low, the fifth prompt information indicates a risk of myopia;

When the physiological equivalent illumination compliance rate is low, the fifth prompt information indicates that there is a circadian rhythm health risk.

According to another aspect of the present disclosure, a light environment and attitude detection device based on wearable devices is proposed, including:

processor;

Memory used to store instructions executable by the processor;

Wherein, the processor is configured to implement the above method when executing instructions stored in the memory.

According to another aspect of the present disclosure, a non-volatile computer-readable storage medium is proposed, on which computer program instructions are stored, characterized in that the above method is implemented when the computer program instructions are executed by a processor.

According to another aspect of the present disclosure, a light environment and attitude detection system based on wearable devices is proposed, including:

A wearable device configured to collect illumination data of ambient light and movement data of a target object wearing the wearable device, where the wearable device is worn near the eyes of the target object;

According to the above-mentioned light environment and attitude detection device;

Communication equipment, used to transmit the illumination data and motion data to the light environment and attitude detection device.

According to another aspect of the present disclosure, a computer program product is provided, including computer readable code, or a non-volatile computer readable storage medium carrying the computer readable code, when the computer readable code is stored in an electronic device When running in the processor, the processor in the electronic device executes the above method.

Based on this, the present disclosure detects the posture and/or the light environment of the target object based on the illumination data and motion data collected by the wearable device. Therefore, long-term and multi-location healthy light environment perception can be achieved through the wearable device. Moreover, based on illumination data and motion data, the health effects of light can be detected and prompted from the biological rhythm and vision health levels at the same time. The wearable device is small in size and easy to wear. It can be worn near the eyes of the target object to evaluate the light environment of the target object's eyes and the posture of the target object itself over a long period of time and in multiple locations. It is independent of time and Space restrictions can be applied to daytime work activities and nighttime living.

Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments with reference to the accompanying drawings.

Description of the drawings

The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate exemplary embodiments, features, and aspects of the disclosure and together with the description serve to explain the principles of the disclosure.

FIG. 1 shows a schematic diagram of a light environment and attitude detection system according to an embodiment of the present disclosure.

Figure 2a shows a flow chart of a light environment and attitude detection method according to an embodiment of the present disclosure.

Figure 2b shows a flow chart of a light environment and attitude detection method according to an embodiment of the present disclosure.

Figure 3 shows the spectral diagram of a spectral sensor with 8 spectral response bands.

Figure 4 shows a schematic diagram of a three-axis acceleration sensor.

Figure 5 shows a schematic diagram of the posture of the target object.

Figure 6 shows a schematic diagram of wired data transmission according to an embodiment of the present disclosure.

Figure 7 shows a schematic diagram of data wireless transmission according to an embodiment of the present disclosure.

FIG. 8 shows a schematic diagram of wearing a wearable device according to an embodiment of the present disclosure.

FIG. 9 shows a block diagram of a device 1900 for light environment and posture detection according to an exemplary embodiment.

Detailed ways

Various exemplary embodiments, features, and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numbers in the drawings identify functionally identical or similar elements. Although various aspects of the embodiments are illustrated in the drawings, the drawings are not necessarily drawn to scale unless otherwise indicated.

The word "exemplary" as used herein means "serving as an example, example, or illustrative." Any embodiment described herein as "exemplary" is not necessarily to be construed as superior or superior to other embodiments.

In addition, in order to better explain the present disclosure, numerous specific details are given in the following detailed description. It will be understood by those skilled in the art that the present disclosure may be practiced without certain specific details. In some instances, methods, means, components and circuits that are well known to those skilled in the art are not described in detail in order to emphasize the subject matter of the disclosure.

The information received by the eyes affects the human body's mood and health. The light it receives not only provides vision but also affects the body's biological clock. Not only that, but the biorhythmic effects of light and vision health are interconnected. On the one hand, they all need to obtain the lighting data of the human eye. For example, excessive light during the day can damage the retina, and exposure to blue light at night can induce sleep disorders; on the other hand, they are all related to the person's working status, such as the light environment. It can affect people's working status, and substandard light environment and posture can affect people's visual health. Vision health is an important part of national health and involves the entire life span of people of all ages. Visual impairment will affect people's physical and mental health and quality of life, and is a serious social problem.

Based on this, the present disclosure provides a light environment and posture detection method and device. The illumination data and motion data collected by the wearable device can detect the posture of the target object and/or the light environment in which it is located. Therefore, the wearable device can Realize long-term and multi-location healthy light environment perception, and based on lighting data and motion data, the health effects of light can be detected and prompted from the biological rhythm and vision health levels at the same time. The wearable device is small in size and easy to wear. It can be worn near the eyes of the target object to evaluate the light environment of the target object's eyes and the posture of the target object itself over a long period of time and in multiple locations. It is independent of time and Space restrictions can be applied to daytime work activities and nighttime living.

FIG. 1 shows a schematic diagram of a wearable device-based light environment and attitude detection system according to an embodiment of the present disclosure. As shown in Figure 1, the system includes:

The wearable device 11 is used to collect illumination data of ambient light and movement data of a target object wearing the wearable device. The wearable device is worn near the eyes of the target object. The wearable device 11 may include a spectral sensor and a motion sensor. The spectral sensor may output response values in different spectral bands by collecting ambient light irradiating the wearable device, and the response values may be used as illumination data. The motion sensor can obtain motion data of the head of the target subject wearing the wearable device. These sensors can be miniaturized, so the diameter of the wearable device 11 can be controlled within 1 cm and can be worn near the user's eyes. Figure 8 shows a schematic diagram of wearing a wearable device according to an embodiment of the present disclosure. , the wearable device can be fixed near the eyes, and the light sensor probe in the spectrum sensor can face the direction of the incoming light. "Near the eyes" can mean any position within the area of the head, such as the forehead, earlobes, etc. near the eyes. Ways of wearing wearable devices include but are not limited to: 1. Fixing on the glasses frame with a clip; 2. Fixing on the earlobe with a clip; 3. Fixing on the front of the forehead with an elastic band. Among them, the wearable device can be provided with a switch button. When the user chooses to turn on the wearable device, the wearable device starts and starts collecting illumination data and motion data through the wearable device.

Communication device 12 is used to transmit the illumination data and motion data to the light environment and attitude detection device. The communication device 12 and the wearable device 11 may be connected through a wired connection or a wireless connection, and the communication device 12 may also be integrated into the wearable device 11 . The communication device 12 obtains the illumination data and motion data collected by the wearable device 11 and transmits them to the light environment and attitude detection device 13, which may be wired transmission or wireless transmission such as Bluetooth or WIFI. The light environment and attitude detection device 13 can be an electronic device such as a smart phone, a tablet, or a computer.

Figure 6 shows a schematic diagram of wired data transmission according to an embodiment of the present disclosure, including a wearable device 11, a communication device 12, a light environment and attitude detection device 13. Among them, the communication device 12 is a data line, and the light environment and attitude detection device 13 is a smart phone. The white dot in the picture is the light sensor probe. When worn, it faces the direction of the incoming light and collects the ambient light that hits the wearable device. The data line supplies power to the wearable device and at the same time transmits the data monitored by the wearable device to the light environment and attitude detection device, where it is calculated, stored and displayed in the light environment and attitude detection device.

Figure 7 shows a schematic diagram of wireless data transmission according to an embodiment of the present disclosure, including a wearable device 11, a communication device 12, a light environment and attitude detection device 13. Among them, the communication device 12 includes a data line and a Bluetooth module, and the light environment and attitude detection device 13 is a smart phone. The white dot in the picture is the light sensor probe. When worn, it faces the direction of the incoming light and collects the ambient light that hits the wearable device. The data line supplies power to the wearable device and at the same time transmits the data monitored by the wearable device to the Bluetooth module in the communication device. The Bluetooth module transmits the data to the light environment and attitude detection device, where it is calculated, stored and displayed.

The light environment and attitude detection device 13 may include a computing unit, a real-time prompting unit, a storage module, and a historical data prompting unit.

The computing unit can process lighting data and motion data to obtain detection results. For example, it can be completed on mobile phones, tablets, computers and other electronic devices. According to the illumination data output by the spectrum sensor in the wearable device 11, the spectral information is determined to determine whether the main light source of the current light environment is natural light or artificial lighting, and then the illumination, color temperature, and physiological illumination of the current ambient light are calculated through the illumination data. to determine whether the light environment meets the standard. According to the motion data of the target object's head output by the motion sensor in the wearable device 11, the posture angle of the target object's head can be determined to determine whether the posture meets the standard.

The real-time prompt unit gives prompts or suggestions based on the data obtained by the computing unit. For example, visual display can be performed through applications on electronic devices such as mobile phones, tablets, and computers. It can clearly provide the impact of light environment on vision and biological rhythms, as well as multi-dimensional real-time evaluation of eye habits.

The storage module stores the data collected by the wearable device 11 and the detection results of the computing unit. For example, it can be stored locally on the electronic device or in the cloud.

The historical data prompt unit provides health prompts to the user based on the data and detection results stored in the storage module in the past period. For example, it can be visually displayed through applications on mobile phones, tablets, computers and other electronic devices to provide multi-dimensional long-term evaluation of eye habits.

In a possible implementation, Figure 2a shows a flow chart of a wearable device-based light environment and attitude detection method according to an embodiment of the present disclosure. This method can be implemented through the light environment and attitude detection device 13 in Figure 1 accomplish. As shown in Figure 2a, the method includes:

S201. Receive illumination data of ambient light collected by a wearable device and motion data of a target object wearing the wearable device. The wearable device is worn near the eyes of the target object.

Among them, wearable devices may include spectrum sensors and motion sensors. The illumination data may be the response values of different spectral bands output by the spectral sensor by collecting the ambient light irradiated to the wearable device (for example, the ambient light near the eyes), where the response value refers to the size of the signal. The motion data may be the motion acceleration of the head of the target object wearing the wearable device obtained by the motion sensor. Taking the three-axis acceleration sensor shown in Figure 4 as an example, the three-axis acceleration sensor is a sensor used to measure spatial acceleration, that is, Measures how fast an object changes speed in space. The motion data collected by the motion sensor can be the acceleration x, y, and z in the three-axis directions of the three-axis rectangular coordinate system. This disclosure uses a miniaturized wearable device to realize wearable monitoring of multiple parameters such as illumination, spectral distribution, work type, posture, etc. At the same time, the wearable device is worn near the eyes of the target object, which can achieve long-term, multi-location perception and has a wider range of application scenarios.

S202: Determine the posture angle of the target object's head according to the motion data.

Among them, take the three-axis acceleration sensor shown in Figure 4 as an example: a three-axis rectangular coordinate system is established, and the motion sensor collects motion data, that is, the acceleration components in the three-axis directions, which are (x, y, z). The angle between the current direction a and the xz plane is φ, and the angle between the current direction a and the yz plane is ω. The calculation formulas corresponding to the two angles are:

Thus, the posture angle of the target object's head is calculated.

S203: Detect the posture and/or the light environment of the target object according to the posture angle and/or the illumination data, and obtain a detection result.

Among them, since the wearable device is worn near the eyes of the target object, the measured data can be considered to represent the illumination data received by the human eye and the movement data of the head. Therefore, by detecting the calculated posture angle and illumination data, we can obtain The pose of the target object and the lighting environment.

The following describes several exemplary ways of detecting the posture and/or the light environment of the target object according to the posture angle and/or the lighting data in step S203 to obtain the detection results.

In a possible implementation, step S203 may include: determining spectral information according to the illumination data; determining whether the main light source of the light environment is natural lighting or artificial lighting according to the spectral information.

The illumination data may include response values of different spectral bands output by the spectral sensor by collecting ambient light irradiated to the wearable device. Spectral information can then be obtained by fitting multiple response values.

Among them, Figure 3 shows the spectrum diagram of a spectral sensor with 8 spectral response bands. By smoothly connecting the response values of different bands, the spectral distribution can be obtained. Generally, the electromagnetic wave wavelength of visible light that the human eye can perceive is between 380 and 780 nanometers, so the horizontal axis of this graph represents the wavelength range of 400-700 nanometers, and the vertical axis represents the relative sensitivity (response value). It can be observed from Figure 3 that the spectral distributions of natural light and artificial lighting are quite different: the natural light spectrum presents continuous characteristics, while the artificial lighting spectrum has peaks and peaks and valleys; in addition, the eye illumination provided by natural light Significantly higher than artificial lighting, there will be a larger spectral response value under natural light. These characteristics can distinguish whether ambient light is natural light or artificial lighting. In a possible situation, natural lighting and artificial lighting exist at the same time. At this time, if the spectral distribution is closer to the continuous spectrum, it is mainly natural lighting; if the spectral distribution is closer to the peak-valley distribution spectrum, it is mainly artificial lighting. .

In a possible implementation, step S203 may include: determining the illumination according to the illumination data; when the illumination exceeds the first threshold, generating first prompt information, the first prompt information indicating that the illumination is too high or the illumination is too high. Adjustment method.

Among them, the illumination of the current ambient light can be calculated through the lighting data. Illumination refers to the luminous flux of visible light received per unit area, which is used to indicate the intensity of light and the degree of illumination of the surface area of an object. If you are in a strong light environment, the function of the eye lens will be affected, and the damage may lead to cataracts; too high illumination will also cause uncomfortable glare and cause damage to the retina. Therefore, when the illumination is too high, real-time first prompt information is generated to reduce damage in time and avoid long-term damage. For example, it is recommended to lower the current light or take sunshade measures. Among them, the first threshold can be flexibly set according to personal conditions and actual detection scenarios, as long as it meets human physiological and health standards.

In a possible implementation, step S203 may include: determining, based on the posture angle, that the posture of the target object is computer office work or paper office work, and determining whether the target object has a bad sitting posture based on the posture angle. .

Among them, as shown in Figure 5, after obtaining the posture angle of the target object's head, it can be judged whether the target object's work type and posture are standard. In one possible judgment method, first determine the type of work based on the posture angle of the target's head. If the vertical direction of the head is close to parallel, it is computer work; if there is a downward inclination, it is paper work; Then judge the posture. If the downward angle is too large, it means poor sitting posture.

In a possible implementation, step S203 may include: determining the color temperature according to the illumination data; and generating second prompt information when it is determined that the posture of the target object is computer office work and the color temperature exceeds the second threshold, The second prompt information indicates that the color temperature is too high or the color temperature is adjusted.

Among them, the color temperature of the current ambient light can be calculated through the lighting data. Blue has the highest color temperature and is present in a large amount of light in computer monitors, digital products, LEDs, etc. If the color temperature is too high, it will increase the amount of toxins in the macular area of the eyes. Staring for a long time will cause visual fatigue and irreversible damage, and too high a color temperature will cause visual fatigue and irreversible damage. The color temperature will affect the positive emotions of workers. Therefore, when it is judged that the computer is working and the color temperature is too high, real-time second prompt information is generated to reduce damage in time and avoid long-term damage, such as recommending timely rest or using anti-blue light products. Among them, the second threshold can be flexibly set according to personal conditions and actual detection scenarios, as long as it meets human physiological and health standards.

In a possible implementation, step S203 may include: determining the target period to which the current time belongs; determining the physiological equivalent illuminance according to the illumination data; when the physiological equivalent illuminance does not meet the preset conditions corresponding to the target period , generating third prompt information, the third prompt information indicating abnormal physiological equivalent illuminance or a physiological equivalent illuminance adjustment method.

Among them, the physiological equivalent illuminance of the current ambient light can be calculated through the illumination data. Physiologically equivalent illuminance is a luminosity derived based on the effect of irradiance on human non-visual systems. Non-visual systems include life rhythms, neuroendocrine and neurological behaviors. Simply put, light affects the biological clock. There are different physiologically equivalent illumination standards during the day and at night, and the specific time period can be determined according to work requirements. This method does not limit the specific time period. In one possible implementation, the physiological equivalent illuminance of residential buildings at night refers to the data measured after 20:00 at night, and the physiological equivalent illuminance of long-term work refers to the data measured during work from 10:00 to 17:00. The data. In one possible implementation method, the physiological equivalent illuminance at 1.2 meters in the main line of sight direction of places where people work for a long time in public buildings is not less than 200lx, and the physiological equivalent illuminance at night in residential buildings is not higher than 50lx. It can be determined that 10:00-17:00 is the first target period, and its corresponding preset condition is that the physiological equivalent illumination is not lower than the threshold A, and 20:00 to 6:00 the next day is the second target period, and its corresponding preset condition is The preset condition is that the physiological equivalent illumination is not higher than threshold B. Threshold A and threshold B can be set according to actual needs with reference to the above standards. In order to ensure a suitable and good rest environment and a comfortable and efficient working environment, when the physiological equivalent illumination is not When the preset conditions corresponding to the target time period are met, real-time third prompt information is generated to reduce discomfort in time and avoid long-term adverse effects on the biological clock, such as suggesting adjusting the lighting.

In a possible implementation, step S203 may include: when it is determined that the posture of the target object is a bad sitting posture, generating fourth prompt information, the fourth prompt information indicating a bad sitting posture or a sitting posture adjustment method.

Among them, if the downward tilt of the head posture angle is too large, it is a sign of poor sitting posture. Poor sitting posture not only causes visual fatigue due to writing too close to each other, but also affects vision for a long time. It can also cause scoliosis of the spine, which affects breathing and digestion. In the long term, it will show slight displacement and affect other functions, such as causing posterior thoracic spine. Bursts can also affect circulatory function. Therefore, real-time fourth prompt information is generated to reduce damage in time and avoid long-term adverse effects on the eyes and body, such as suggesting adjusting the sitting posture or performing relaxing exercises.

The above-mentioned illuminance, color temperature, physiological equivalent illuminance, etc. can be obtained based on lighting data through relevant technologies.

In a possible implementation, the method may further include: storing the illumination data, motion data and detection results. Based on the detection results within a preset time period, statistical information for light environment and posture detection is determined. According to the statistical information, fifth prompt information is generated.

Among them, all illumination data and motion data can be stored, as well as all calculation results such as calculated illuminance, color temperature, physiologically equivalent illuminance, posture angle, etc., as well as all judgment results such as light source type, work type, posture, and whether it meets the standards. , whether it meets the standard or not, can be stored, and the timestamp information corresponding to the data can also be recorded at the same time.

Among them, all information, including lighting data, motion data, calculation results, detection results and preset time periods, can be counted from the time the device starts to the end of detection or within any preset time period.

Among them, based on the stored lighting data, motion data, calculation results, detection results and preset time periods, the detection results of the light environment and posture can be summarized to provide an overall risk warning.

In a possible implementation, the statistical information may include: natural light illumination time; and/or the time to reach the standard for any one or more of illumination, color temperature, physiologically equivalent illumination, and the posture of the target object. proportion to the preset time period.

For example, if the preset time period is 24 hours, the total duration of natural light illumination time within the preset time period can be counted, or the ratio of the total duration of illumination below the first threshold (that is, the illumination meets the standard) to 24 hours can be counted. etc.

In a possible implementation, according to the statistical information, the fifth prompt information includes: when the natural light illumination time is insufficient, the fifth prompt information indicates accepting more sufficient natural light; when the illumination and /or When the target object's posture compliance rate is low, the fifth prompt information indicates a risk of myopia; when the physiologically equivalent illumination compliance rate is low, the fifth prompt information indicates a circadian health risk.

Among them, the compliance rate of the light environment and attitude can be calculated based on the proportion of the compliance time to the total monitoring time. Based on the sum of the natural light exposure times, the natural light exposure duration can be calculated. Then analyze the user's historical data to generate macro-level fifth prompt information.

In one possible implementation, if the natural light exposure duration is low, it indicates the need to receive more sufficient natural light to maintain health and good mood; if the illumination and posture compliance rate is low, it indicates the risk of myopia; if the physiological The equivalent illuminance compliance rate is low, indicating the risk of unhealthy circadian rhythm. This content can be visually displayed through applications on mobile phones, tablets, computers and other electronic devices, allowing a clear understanding of the impact of the light environment on vision and biological rhythms, as well as a multi-dimensional long-term evaluation of eye habits. Multi-dimensional evaluations and tips simultaneously help users maintain a healthy circadian rhythm and protect users' visual health.

Figure 2b shows a flow chart of a light environment and attitude detection method according to an embodiment of the present disclosure. As shown in Figure 2b, after the wearable device is turned on, the collected illumination data and motion data can be transmitted to the light environment and attitude detection device. After the light environment and attitude detection device receives the illumination data and motion data, it can Spectral information is obtained from the data, and the main light source of the light environment is determined to be natural lighting or artificial lighting based on the spectral information. The posture angle can be obtained based on the motion data, the posture of the target object can be determined based on the posture angle, and the illuminance and color temperature can be obtained based on the lighting data. , Physiologically equivalent illumination, combined with time and the posture of the target object, determine whether the illumination, color temperature, and physiologically equivalent illumination meet the standards. Real-time reminders can be provided based on the various non-compliance situations mentioned above, such as reminders through light environment and attitude detection devices or wearable devices. Various detection results, data and their timestamps mentioned above can also be stored. And obtain statistical information based on the stored data, and provide reminders based on the statistical information.

It should be noted that although a light environment and attitude detection method is introduced as above using FIG. 2a and FIG. 2b as an example, those skilled in the art can understand that the present disclosure should not be limited thereto. In fact, users can flexibly set the threshold according to personal circumstances and/or actual application scenarios, as long as it meets human physiological and health standards. Lighting data and motion data can also be flexibly used according to personal circumstances and/or actual application scenarios, and are not limited to the detection content given in this example.

In a possible implementation, the present disclosure also provides a light environment and attitude detection device based on a wearable device, including:

A receiving module configured to receive illumination data of ambient light collected by a wearable device and motion data of a target object wearing the wearable device, where the wearable device is worn near the eyes of the target object;

A determination module configured to determine the posture angle of the target object's head according to the motion data;

A detection module, configured to detect the posture and/or the light environment of the target object according to the posture angle and/or the illumination data, and obtain a detection result.

In some embodiments, the functions or modules provided by the device provided by the embodiments of the present disclosure can be used to execute the methods described in the above method embodiments. For specific implementation, refer to the description of the above method embodiments. For the sake of brevity, here No longer.

Embodiments of the present disclosure also provide a computer-readable storage medium on which computer program instructions are stored, and when the computer program instructions are executed by a processor, the above method is implemented. Computer-readable storage media may be volatile or non-volatile computer-readable storage media.

An embodiment of the present disclosure also proposes a light environment and attitude detection device based on a wearable device, including: a processor; a memory for storing instructions executable by the processor; wherein the processor is configured to execute the memory When storing instructions, implement the above method.

Embodiments of the present disclosure also provide a computer program product, including computer readable code, or a non-volatile computer readable storage medium carrying the computer readable code. When the computer readable code is stored in a processor of an electronic device, When running, the processor in the electronic device executes the above method.

FIG. 9 shows a block diagram of a device 1900 for light environment and posture detection according to an exemplary embodiment. For example, the device 1900 may be provided as a server or terminal device. Referring to FIG. 9 , apparatus 1900 includes a processing component 1922 , which further includes one or more processors, and memory resources represented by memory 1932 for storing instructions, such as application programs, executable by processing component 1922 . The application program stored in memory 1932 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 1922 is configured to execute instructions to perform the above-described method.

Device 1900 may also include a power supply component 1926 configured to perform power management of device 1900, a wired or wireless network interface 1950 configured to connect device 1900 to a network, and an input-output (I/O) interface 1958. Device 1900 may operate based on an operating system stored in memory 1932, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™ or the like.

In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions, which can be executed by the processing component 1922 of the apparatus 1900 to complete the above method.

The present disclosure may be a system, method, and/or computer program product. A computer program product may include a computer-readable storage medium having thereon computer-readable program instructions for causing a processor to implement aspects of the present disclosure.

Computer-readable storage media may be tangible devices that can retain and store instructions for use by an instruction execution device. The computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) or Flash memory), Static Random Access Memory (SRAM), Compact Disk Read Only Memory (CD-ROM), Digital Versatile Disk (DVD), Memory Stick, Floppy Disk, Mechanical Coding Device, such as a printer with instructions stored on it. Protruding structures in hole cards or grooves, and any suitable combination of the above. As used herein, computer-readable storage media are not to be construed as transient signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or through electrical wires. transmitted electrical signals.

Computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to various computing/processing devices, or to an external computer or external storage device over a network, such as the Internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage on a computer-readable storage medium in the respective computing/processing device .

Computer program instructions for performing operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or instructions in one or more programming languages. Source code or object code written in any combination of object-oriented programming languages - such as Smalltalk, C++, etc., and conventional procedural programming languages - such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server implement. In situations involving remote computers, the remote computer can be connected to the user's computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (such as an Internet service provider through the Internet). connect). In some embodiments, by utilizing state information of computer-readable program instructions to personalize an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), the electronic circuit can Computer readable program instructions are executed to implement various aspects of the disclosure.

Aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.

These computer-readable program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus, thereby producing a machine that, when executed by the processor of the computer or other programmable data processing apparatus, , resulting in an apparatus that implements the functions/actions specified in one or more blocks in the flowchart and/or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium. These instructions cause the computer, programmable data processing device and/or other equipment to work in a specific manner. Therefore, the computer-readable medium storing the instructions includes An article of manufacture that includes instructions that implement aspects of the functions/acts specified in one or more blocks of the flowcharts and/or block diagrams.

Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other equipment, causing a series of operating steps to be performed on the computer, other programmable data processing apparatus, or other equipment to produce a computer-implemented process , thereby causing instructions executed on a computer, other programmable data processing apparatus, or other equipment to implement the functions/actions specified in one or more blocks in the flowcharts and/or block diagrams.

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions that embody one or more elements for implementing the specified logical function(s). Executable instructions. In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two consecutive blocks may actually execute substantially in parallel, or they may sometimes execute in the reverse order, depending on the functionality involved. It will also be noted that each block of the block diagram and/or flowchart illustration, and combinations of blocks in the block diagram and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts. , or can be implemented using a combination of specialized hardware and computer instructions.

The embodiments of the present disclosure have been described above. The above description is illustrative, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical applications, or technical improvements in the market of the embodiments, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

A light environment and posture detection method based on wearable devices, which is characterized by including:

Receive illumination data of ambient light collected by a wearable device and motion data of a target object wearing the wearable device, the wearable device being worn near the eyes of the target object;

Determine the posture angle of the target object's head based on the motion data;

According to the posture angle and/or the illumination data, the posture and/or the light environment of the target object are detected to obtain a detection result.
The method according to claim 1, characterized in that: detecting the posture and/or the light environment of the target object according to the posture angle and/or the illumination data, and obtaining a detection result, including:

Determine spectral information based on the illumination data;

It is determined based on the spectral information that the main light source of the light environment is natural lighting or artificial lighting.
The method according to claim 1, characterized in that, based on the posture angle and/or the illumination data, the posture and/or the light environment of the target object are detected, and the detection result is obtained, including:

Determine illumination based on the illumination data;

When the illumination exceeds the first threshold, first prompt information is generated, and the first prompt information indicates that the illumination is too high or the illumination adjustment method.
The method according to claim 1, characterized in that, based on the posture angle and/or the illumination data, the posture and/or the light environment of the target object are detected, and the detection result is obtained, including:

According to the posture angle, it is determined that the posture of the target object is computer office work or paper office work, and it is determined whether the target object has a bad sitting posture according to the posture angle.
The method according to claim 4, characterized in that, based on the posture angle and/or the illumination data, detecting the posture and/or the light environment of the target object, and obtaining the detection result, including: include:

Determine color temperature based on the lighting data;

When it is determined that the posture of the target object is working with a computer and the color temperature exceeds the second threshold, second prompt information is generated, and the second prompt information indicates that the color temperature is too high or the color temperature adjustment method is too high.
The method according to claim 1, characterized in that, based on the posture angle and/or the illumination data, the posture and/or the light environment of the target object are detected, and the detection result is obtained, including:

Determine the target period to which the current time belongs;

Determine physiologically equivalent illuminance based on lighting data;

When the physiological equivalent illuminance does not meet the preset conditions corresponding to the target period, third prompt information is generated, and the third prompt information indicates abnormal physiological equivalent illuminance or a physiological equivalent illuminance adjustment method.
The method according to claim 4, characterized in that, based on the posture angle and/or the illumination data, detecting the posture and/or the light environment of the target object to obtain the detection result, further comprising:

When it is determined that the target object's posture is a bad sitting posture, fourth prompt information is generated, and the fourth prompt information indicates a bad sitting posture or a sitting posture adjustment method.
The method of claim 1, further comprising:

Store the illumination data, motion data and detection results;

Determine the statistical information for light environment and posture detection based on the detection results within the preset time period;

According to the statistical information, fifth prompt information is generated.
The method according to claim 8, characterized in that the statistical information includes:

Natural light lighting time; and/or

The proportion of the target time of any one or more of the illumination, color temperature, physiologically equivalent illumination and the posture of the target object to the preset time period.
The method according to claims 8 and 9, characterized in that, according to the statistical information, fifth prompt information is generated, including:

When the natural light illumination time is insufficient, the fifth prompt message indicates receiving more sufficient natural light;

When the illumination and/or the target object's attitude compliance rate is low, the fifth prompt information indicates a risk of myopia;

When the physiological equivalent illumination compliance rate is low, the fifth prompt information indicates that there is a circadian rhythm health risk.
A light environment and attitude detection device based on wearable devices, which is characterized by including:

processor;

Memory used to store instructions executable by the processor;

Wherein, the processor is configured to implement the method described in any one of claims 1 to 10 when executing instructions stored in the memory.
A non-volatile computer-readable storage medium on which computer program instructions are stored, characterized in that when the computer program instructions are executed by a processor, the method described in any one of claims 1 to 10 is implemented.
A light environment and attitude detection system based on wearable devices, which is characterized by including:

A wearable device configured to collect illumination data of ambient light and movement data of a target object wearing the wearable device, where the wearable device is worn near the eyes of the target object;

The light environment and attitude detection device according to claim 11;

Communication equipment, used to transmit the illumination data and motion data to the light environment and attitude detection device.