Intelligent lighting system and working method thereof

Abstract

The invention provides an intelligent lighting system and a working method thereof. The method comprises the following steps: acquiring a heart rate variability signal and a skin electrical activity signal from a wearable device; calculating to obtain a heart rate variability time sequence curve by using the heart rate variability signal, calculating to obtain a skin electrical activity time sequence curve by using the skin electrical activity signal, and determining the emotional state of the user based on the heart rate variability time sequence curve and the skin electrical activity time sequence curve; and adjusting the light emitting state of the lighting lamp according to the determined emotional state of the user. The invention further provides an intelligent lighting system for implementing the method. According to the invention, the emotional state of the user can be accurately identified, so that the light emitting state of the lighting lamp can be accurately adjusted.

Description

Technical Field

[0001] This invention relates to the technical field of intelligent lighting systems, specifically to the working method of intelligent lighting systems and intelligent luminaires that implement this method. Background Technology

[0002] With the widespread application of smart home technology, smart lighting fixtures have become the main type of lighting in homes. As technology advances, smart lighting fixtures, in addition to fulfilling traditional lighting functions, are also used to regulate users' emotions. Research shows that the lighting environment has a significant impact on people's emotions and psychology; different color temperatures and brightness levels can evoke different physiological and psychological responses. For example, high color temperature (cool) bright light often makes people alert and focused, while low color temperature (warm) dimmer light helps to relax and soothe emotions.

[0003] Currently, some existing smart lighting systems allow users to manually adjust the color temperature and brightness of lights via mobile apps or voice assistants, or automatically adjust them based on time and ambient light, thereby helping users improve their mood. For example, smart lighting systems support changing the color and brightness of lights through applications or voice commands to create different atmospheres. In addition, research and patents have explored methods for using physiological signals for environmental control.

[0004] However, existing smart lighting systems primarily focus on basic on / off control or simple scene modes, lacking proactive perception and targeted adjustment based on the user's psychological state. For example, one existing smart lighting system uses wearable devices to detect user movements or sleep patterns to control light switches, but it lacks the ability to dynamically adjust light color temperature and brightness based on the user's stress, anxiety, or other psychological states. Similarly, while some emotional lighting systems can adjust lighting based on user emotions, most rely on voice recognition or camera-captured facial expressions, which are highly intrusive and have limited accuracy. In contrast, sensing stress and emotions through wearable devices by monitoring physiological signals such as heart rate variability (HRV) and electrical skin activity (EDA) is a more direct, objective, and continuous method. HRV reflects the balance of the autonomic nervous system and is an important indicator of psychological stress; EDA reflects the degree of emotional arousal through changes in skin conductivity. When a person is under stress or tension, HRV typically decreases while EDA increases, and these changes can be captured in real time by wearable sensors.

[0005] An existing multimodal data fusion-based emotion recognition and treatment system collects a user's heart rate variability (HRV) and electrodermal activity (EDA) signals to analyze the user's current emotional state and controls lighting based on these two signals. However, this approach simply analyzes the HRV and EDA signals independently without combining their temporal sequences for comprehensive analysis, leading to inaccurate judgments of the user's emotional state. Summary of the Invention

[0006] The first objective of this invention is to provide a method for operating an intelligent lighting system that improves the accuracy of recognizing users' emotional states.

[0007] A second objective of this invention is to provide an intelligent lighting system that implements the above-described method for operating the intelligent lighting system.

[0008] To achieve the first objective of this invention, the working method of the intelligent lighting system provided by this invention includes acquiring heart rate variability signals and electrodermal activity signals from a wearable device; calculating a heart rate variability time-series curve using the heart rate variability signals and calculating an electrodermal activity time-series curve using the electrodermal activity signals; determining the user's emotional state based on the heart rate variability time-series curve and the electrodermal activity time-series curve; and adjusting the luminous state of the lighting fixtures according to the determined user's emotional state.

[0009] As can be seen from the above scheme, after acquiring the user's heart rate variability signal and electrodermal activity signal through wearable devices, it is necessary to convert them into heart rate variability time-series curves and electrodermal activity time-series curves. The intelligent lighting system determines the user's emotional state based on the heart rate variability time-series curve and electrodermal activity time-series curve, that is, it determines the user's emotional state by combining the time-series relationship of heart rate variability signal and electrodermal activity signal. Compared with the method of analyzing heart rate variability signal and electrodermal activity signal separately to determine the user's emotional state, this invention can more accurately determine the user's emotional state, and thus can accurately adjust the light emission state of the lighting fixtures.

[0010] A preferred approach is to determine the user's emotional state based on the heart rate variability time series curve and the skin conductance activity time series curve. This includes: if the skin conductance activity time series curve shows a steep peak and then falls rapidly, and the heart rate variability time series curve shows a lag with a wide valley, then the user's emotional state is confirmed to be a high-pressure state.

[0011] Therefore, it can be seen that the above method can accurately determine whether the user is in a high-pressure state, and then alleviate the user's high-pressure state by adjusting the smart lights.

[0012] A further approach is to determine the user's emotional state based on the heart rate variability time series curve and the skin conductance activity time series curve. For example, if the skin conductance activity time series curve shows a continuous plateau-like rise and the heart rate variability time series curve decreases synchronously, then the user's emotional state is confirmed to be a focused state.

[0013] Therefore, it is evident that the above method can accurately determine whether a user is in a focused state, and then adjust the smart lighting fixtures to provide the user with more suitable illumination.

[0014] A further approach is to adjust the lighting status of the lighting fixtures based on the determined user's emotional state, including adjusting the color temperature and / or brightness of the lighting fixtures.

[0015] A further solution involves adjusting the color temperature and / or brightness of the lighting fixtures, including: if the user is confirmed to be under high pressure, adjusting the color temperature to 2700K to 3500K and the brightness to 30% to 50% of the maximum brightness of the lighting fixtures; if the user is confirmed to be in a focused state, adjusting the color temperature to 5000K to 6000K and the brightness to 70% to 100% of the maximum brightness of the lighting fixtures; if the user is confirmed to be in a drowsy state, adjusting the color temperature to 4000K to 5000K and the brightness to 60% to 80% of the maximum brightness of the lighting fixtures.

[0016] Therefore, adjusting the color temperature and brightness of lighting fixtures according to the user's different emotional state can provide the user with more suitable lighting conditions.

[0017] A further approach is to obtain the user's exercise intensity data. If the user's exercise intensity data exceeds a preset exercise intensity threshold, the determination of the user's emotional state is paused until the user's physiological indicators return to the resting baseline level before the user's emotional state is determined.

[0018] Therefore, by excluding the emotional state judgment information when the user's exercise intensity data is too large, the present invention can more accurately identify the user's true emotional state, thereby further improving the accuracy of emotional state recognition.

[0019] A further approach is to obtain user preference data on the illumination state of lighting fixtures under various emotional states; when adjusting the illumination state of lighting fixtures based on the determined user emotional state, the illumination state of the lighting fixtures is set based on the user's emotional state and the user's preference data.

[0020] Since different users have different preferences for the color temperature and brightness of lighting fixtures under different emotional states, obtaining user preference data and determining the user's current emotional state, and then applying the user preference data to set the lighting status of the lighting fixtures, can help alleviate the user's emotional stress.

[0021] A further approach is to obtain user preference data on the lighting status of lighting fixtures under various emotional states, including: obtaining user setting data on the lighting status of lighting fixtures under various emotional states, and determining user preference data on the lighting status of lighting fixtures under the corresponding emotional states based on the setting data.

[0022] Therefore, by acquiring user preference data on the lighting status of lamps under various emotional states, it is equivalent to continuously refining the preference data through self-learning, thereby setting better preference data.

[0023] To achieve the second objective mentioned above, the intelligent lighting system provided by the present invention includes a controller and a lighting fixture. The controller receives heart rate variability signals and skin conductance signals sent by a wearable device, and sends control signals to the lighting fixture. Furthermore, the controller is capable of operating the aforementioned intelligent lighting system.

[0024] A further approach is to have the wearable device communicate wirelessly with the controller. Attached Figure Description

[0025] Figure 1 This is a structural block diagram of the intelligent lighting system and wearable device of the present invention.

[0026] Figure 2 This is a flowchart of an embodiment of the working method of the intelligent lighting system of the present invention.

[0027] Figure 3 This is a timing diagram confirming that the user is in a high-voltage state in an embodiment of the working method of the intelligent lighting system of the present invention.

[0028] Figure 4 The timing diagram for confirming that the user is in a focused state is shown in the embodiment of the working method of the intelligent lighting system of the present invention.

[0029] Figure 5 This is a flowchart illustrating the self-learning preference data in an embodiment of the working method of the intelligent lighting system of the present invention.

[0030] The present invention will be further described below with reference to the accompanying drawings and embodiments. Detailed Implementation

[0031] The intelligent lighting system of the present invention has intelligent lamps. The intelligent lighting system can acquire the user's physiological parameter information and judge the user's emotional state. Based on the user's emotional state, it intelligently adjusts the light emission state of the intelligent lamps, such as adjusting the color temperature and light emission brightness, to alleviate the user's emotional stress.

[0032] Intelligent lighting system examples: See Figure 1 The intelligent lighting system of this embodiment includes a controller 12 and a lighting fixture 13. The controller 12 can communicate with a wearable device 11. For example, the wearable device 11 can be a smart bracelet, a smartwatch, or clothing equipped with sensors. The wearable device 11 is equipped with a Bluetooth module, and the controller 12 is also equipped with a Bluetooth module. The wearable device 11 and the controller 12 communicate via Bluetooth. Of course, the wearable device 11 and the controller 12 can also communicate via other wireless methods, such as via NFD (Near Field Communication) or via WIFI.

[0033] Wearable device 11 is used to collect the user's heart rate variability (HRV) signal and electric skin activity (EDA) signal, and send the collected HRV signal and EDA signal to controller 12. Controller 12 identifies the user's emotional state based on the HRV signal and EDA signal, such as identifying whether the user is currently in a high-pressure state, a focused state, or a drowsy state.

[0034] The controller 12 can send control signals to the lighting fixture 13 to control the light emission state of the lighting fixture 13, such as controlling the color temperature and brightness of the lighting fixture 13. Since the controller 12 can recognize the user's current emotional state, the controller 12 will adjust the light emission state of the lighting fixture 13 according to the currently recognized emotional state of the user, that is, adjust at least one of the color temperature and brightness to alleviate the user's emotional stress.

[0035] Example of how an intelligent lighting system works: The following is combined with Figure 2 The working method of the intelligent lighting system is described below. First, step S1 is executed, whereby the wearable device acquires the user's heart rate variability (HRV) and electrodermal activity (EDA) signals. Preferably, the wearable device continuously and periodically acquires the user's HRV and EDA signals, for example, every 0.5 seconds. The wearable device then sends the acquired HRV and EDA signals to the controller, which subsequently uses the received HRV and EDA signals to identify the user's emotional state.

[0036] Then, step S2 is executed to acquire the user's current exercise intensity data. Preferably, the wearable device is also equipped with motion sensors such as a triaxial sensor or an accelerometer, and sends the motion speed data detected by the motion sensors to the controller. The controller also calculates the user's current exercise intensity data based on the received motion speed data. For example, the user's current exercise intensity data can be directly represented by the speed collected by the accelerometer. Furthermore, the controller determines whether the user's current exercise intensity data exceeds an exercise intensity threshold. The exercise intensity threshold is a preset threshold, such as 150 steps / minute. If the user's current exercise intensity data exceeds the exercise intensity threshold, it can be considered that the user is currently in a state of vigorous exercise. At this time, the heart rate variability signal and skin conductance signal collected often cannot accurately reflect the user's true emotional state. Therefore, during the period when the user's current exercise intensity data exceeds the exercise intensity threshold, the identification of the user's emotional state will be stopped until the user's physiological parameters (such as heart rate variability signal) return to the preset resting baseline level value, and then emotion regulation will be reactivated. Therefore, step S6 needs to be executed to determine whether the user's current physiological indicators have dropped to the preset resting baseline level. If not, continue to wait. If they have dropped below the resting baseline level, then step S3 is executed.

[0037] If the user's current exercise intensity data does not exceed the exercise intensity threshold, or if the physiological parameters have dropped to a pre-set resting baseline level, it indicates that the user is not currently in a state of strenuous exercise. Therefore, step S3 needs to be executed to identify the user's current emotional state based on heart rate variability signals and skin conductance activity signals. Specifically, the controller will calculate a skin conductance activity time-series curve based on skin conductance activity signals acquired over a period of time, such as... Figure 3 , Figure 4 As shown, by acquiring skin conductance activity signals at multiple time points, a skin conductance activity time-series curve can be obtained, for example... Figure 3 or Figure 4 The black line. Correspondingly, by acquiring heart rate variability signals at multiple time points, a heart rate variability time-series curve can be obtained, such as... Figure 3 or Figure 4 As shown by the red line in the middle.

[0038] After acquiring the time-series curves of electroskin activity (ESA) and heart rate variability (HRV), this embodiment will identify the user's current emotional state based on these curves. Specifically, the user's emotional state can be identified according to a pre-set model. For example, when the ESA curve shows a steep peak followed by a rapid decline, and the HSV curve lags behind with a trough, i.e. Figure 3The curve pattern shown confirms that the user's emotional state is under high pressure. For example, if the skin conductance activity time-series curve shows a sustained plateau-like rise, and the heart rate variability time-series curve declines synchronously, such as... Figure 4 The curve pattern shown confirms that the user's emotional state is focused. Of course, curve models for other emotional states can also be set. Step S3 compares the similarity between the currently acquired skin conductance activity time-series curve and heart rate variability time-series curve and the pre-set curve model to identify the user's current emotional state. In this embodiment, the user's emotional state can be set to three types: high stress, focused, and drowsy, each with a corresponding curve model.

[0039] Next, step S4 is executed to obtain the user's preference data under their current emotional state. In this embodiment, it is necessary to establish a preference database for the illumination state of lighting fixtures for each user under different emotional states. For example, this database can be established by the user inputting data, or it can be established by collecting data on the user's adjustments to the illumination state of lighting fixtures. The specific process of establishing a preference database by collecting data on the user's adjustments to the illumination state of lighting fixtures will be described later.

[0040] After acquiring the user's preference data under their current emotional state, step S5 is executed to adjust the lighting status of the lamps based on the acquired preference data, specifically adjusting the color temperature and brightness of the lamps. If the user has not set any preference data in the initial state, the lighting is controlled according to the default parameters for each emotional state. For example, if the user's current emotional state is identified as a high-pressure state, such as when the user suddenly receives a stimulating message and exhibits sudden excitement (one possibility being frightened), the color temperature of the lamps is adjusted to 2700K to 3500K, and the brightness is adjusted to 30% to 50% of the lamps' maximum brightness. If the user's current emotional state is identified as a focused state, such as when the user is engrossed in reading, the color temperature is adjusted to 5000K to 6000K, and the brightness is adjusted to 70% to 100% of the lamps' maximum brightness. If the user's emotional state is identified as a drowsy state, the color temperature is adjusted to 4000K to 5000K, and the brightness is adjusted to 60% to 80% of the lamps' maximum brightness.

[0041] After the controller sends a control signal to the lighting fixtures, the fixtures will operate according to the controller's instructions, such as adjusting the color temperature and brightness. If the user is dissatisfied with the current color temperature and brightness, they can manually adjust them, for example, by manually increasing or decreasing the brightness. At this time, the controller can collect the user's adjustments to the lighting fixtures to build a user preference database. Specifically, it records the color temperature, brightness, and other data set by the user in their current emotional state, and uses this data as the user's preference data for that emotional state. If the user experiences the same emotional state again, the lighting fixture's operating parameters will be set according to the previously recorded preference data for that emotional state. If the user continues to adjust the lighting fixture's operating parameters, the system will continue to record the user's final adjustments to the color temperature, brightness, and other operating parameters, and continue to update the user's preference data for that emotional state, thereby continuously improving the user preference database.

[0042] Of course, this embodiment can also adaptively adjust the luminous parameters of the lighting fixtures by acquiring the user's physiological change parameters, and determine the user's preference data based on the user's physiological change parameters, thereby achieving self-learning of preference data. The following will combine... Figure 5 This section describes the specific process of determining user preference data based on physiological change parameters. First, after identifying the user's emotional state, the operating parameters of the lighting fixtures are set according to the current emotional state. Then, step S11 is executed to acquire the user's physiological change parameters. Specifically, after adjusting the operating parameters of the lighting fixtures, the user's heart rate variability (HRV) and electrodermal activity (EDA) signals are acquired through a wearable device. The HRV and EDA time-series curves are then calculated again after adjusting the lighting fixture operating parameters to determine if the user's emotional state has improved, such as whether the user's high blood pressure or drowsiness has improved. Therefore, step S12 is executed to determine if the user's current physiological change parameters meet the requirements of the preset improvement indicators. If they do, step S13 is executed to maintain the current illumination state of the lighting fixtures. If not, step S15 is executed to adjust the illumination state and then return to step S12 to adjust the lighting fixture operating parameters again until the user's emotional state meets the improvement indicators.

[0043] If the user's physiological parameters meet the requirements of the improvement indicators, step S14 needs to be executed to set the current operating parameters of the lighting fixtures, including color temperature and luminous brightness, to the user's preferred data in this emotional state.

[0044] In this embodiment, the user's preference data under various emotional states is stored in the controller's local memory instead of being uploaded to a cloud server. This method avoids the leakage of the user's personal preference privacy information. Furthermore, the heart rate variability (HRV) and electrodermal activity (EDA) signals collected by the user through the wearable device are also stored solely in the controller. After calculating the HRV and EDA time-series curves, the controller does not send these curves to the network, thus effectively preventing the leakage of the user's personal information.

[0045] Furthermore, data transmission between the wearable device and the controller can be encrypted. For example, after acquiring the user's heart rate variability (HRV) and electrodermal activity (EDA) signals, the wearable device encrypts the HRV and EDA signals to be transmitted and sends the encrypted HRV and EDA signals to the controller. Upon receiving the encrypted HRV and EDA signals, the controller first decrypts the received data and then uses the decrypted HRV and EDA signals to calculate the HRV time-series curve and EDA time-series curve.

[0046] This invention, after acquiring the user's heart rate variability (HRV) and electrodermal activity (EDA) signals, does not analyze the user's emotional state independently using these two parameters. Instead, it calculates the HRV and EDA time-series curves and determines the user's emotional state based on these curves. In other words, it combines the temporal relationship between the HRV and EDA signals to determine the user's emotional state. Compared to analyzing HRV and EDA signals separately to determine the user's emotional state, this invention can more accurately determine the user's emotional state, thereby enabling precise adjustment of the lighting fixtures' illumination, more effectively relieving the user's emotional stress, or improving the user's concentration, thus enhancing the user experience.

[0047] Finally, it should be emphasized that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. The working method of an intelligent lighting system, including: Acquire heart rate variability and skin conductance signals from wearable devices; Its features are: The heart rate variability signal is used to calculate the heart rate variability time-series curve, and the skin conductance activity signal is used to calculate the skin conductance activity time-series curve. The user's emotional state is determined based on the heart rate variability time-series curve and the skin conductance activity time-series curve. Adjust the lighting status of the lamps according to the determined emotional state of the user.

2. The working method of the intelligent lighting system according to claim 1, characterized in that: Determining the user's emotional state based on the heart rate variability time-series curve and the skin electroreactivity time-series curve includes: If the skin electrical activity time-series curve shows a steep peak and then falls rapidly, and the heart rate variability time-series curve shows a lag with a wide trough, then the user's emotional state is confirmed to be under high pressure.

3. The working method of the intelligent lighting system according to claim 2, characterized in that: Determining the user's emotional state based on the heart rate variability time-series curve and the skin electroreactivity time-series curve includes: If the skin conductance activity timeline curve shows a sustained plateau-like increase, and the heart rate variability timeline curve decreases synchronously, then the user's emotional state is confirmed to be a focused state.

4. The method of operating the intelligent lighting system according to any one of claims 1 to 3, characterized in that: Adjusting the luminous state of lighting fixtures according to the determined user's emotional state includes adjusting the color temperature and / or luminous brightness of the lighting fixtures.

5. The working method of the intelligent lighting system according to claim 4, characterized in that: Adjusting the color temperature and / or luminous intensity of the lighting fixtures includes: If it is confirmed that the user is in a high-voltage state, the color temperature is adjusted to 2700K to 3500K, and the brightness is adjusted to 30% to 50% of the maximum brightness of the lighting fixture; If the user is confirmed to be in a focused state, the color temperature is adjusted to 5000K to 6000K, and the brightness is adjusted to 70% to 100% of the maximum brightness of the lighting fixture. If the user is confirmed to be drowsy, the color temperature is adjusted to 4000K to 5000K, and the brightness is adjusted to 60% to 80% of the maximum brightness of the lighting fixture.

6. The method of operating the intelligent lighting system according to any one of claims 1 to 3, characterized in that, Also includes: The system acquires the user's exercise intensity data. If the user's exercise intensity data exceeds the preset exercise intensity threshold, the determination of the user's emotional state is paused until the user's physiological indicators return to the resting baseline level before the user's emotional state is determined.

7. The method of operating the intelligent lighting system according to any one of claims 1 to 3, characterized in that, Also includes: Acquire user preference data on the illumination status of lighting fixtures under various emotional states; When adjusting the illumination state of lighting fixtures based on the determined user's emotional state, the illumination state of the lighting fixtures is set based on the user's emotional state and the user's preference data.

8. The method of operating the intelligent lighting system according to claim 7, characterized in that: Obtaining user preference data on the illumination status of lighting fixtures under various emotional states includes: The system acquires user setting data for the illumination state of the lighting fixtures under various emotional states, and determines user preference data for the illumination state of the lighting fixtures under corresponding emotional states based on this setting data.

9. Intelligent lighting systems, including: The controller and the lighting fixture, wherein the controller receives heart rate variability signals and skin conductance signals from the wearable device, and the controller sends control signals to the lighting fixture; Its features are: The controller operates the method of the intelligent lighting system as described in any one of claims 1 to 8.

10. The intelligent lighting system according to claim 9, characterized in that: The wearable device communicates with the controller wirelessly.

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