Touch sensing method and system of LED light source

Abstract

The embodiment of the invention relates to the technical field of light source control, in particular to a touch sensing method and system of an LED light source, initial touch information is obtained through a touch sensing surface, fingerprint authentication is conducted on the initial touch information, and when a fingerprint authentication result meets a preset standard, the LED light source is triggered. Activating an induction control function of the LED light source, analyzing a finger touch posture according to the initial touch information to obtain a finger posture feature when the finger executes the initial touch behavior, obtaining subsequent touch information through the touch induction surface, analyzing the subsequent touch information according to the finger posture feature to generate a touch track feature of the finger, and outputting the touch track feature of the finger. And analyzing the touch track characteristics based on the induction control function, and generating an induction control instruction of the LED light source so as to control the working state of the LED light source.

Description

Technical Field

[0001] The embodiments of this disclosure relate to the technical field of light source control, and more specifically, the embodiments of this disclosure relate to a touch sensing method and system for an LED light source. Background Technology

[0002] Traditional LED light source control methods, such as using mechanical switches or remote controls, are relatively cumbersome to operate. Mechanical switches require manual pressing, have fixed positions, and are not flexible enough in certain situations. Summary of the Invention

[0003] In view of this, the present disclosure provides a touch sensing method and system for LED light sources to achieve flexible control of LED light sources.

[0004] According to a first aspect of this disclosure, a touch sensing method for an LED light source is provided, comprising: Initial touch information is obtained through the touch sensing surface, and fingerprint authentication is performed on the initial touch information. When the fingerprint authentication result meets the preset standard, the sensing and control function of the LED light source is activated. The finger touch posture is analyzed based on the initial touch information to obtain the finger posture features when the finger performs the initial touch behavior; Subsequent touch information is acquired through the touch sensing surface, and the subsequent touch information is analyzed based on the finger posture characteristics to generate the touch trajectory characteristics of the finger; Based on the aforementioned sensing and control function, the touch trajectory features are analyzed to generate sensing and control commands for the LED light source, thereby controlling the working state of the LED light source.

[0005] According to a second aspect of this disclosure, a touch sensing system for an LED light source is provided for implementing the touch sensing method for an LED light source as described in any one of the first aspects, comprising: The touch sensing module is used to acquire initial touch information through the touch sensing surface and perform fingerprint authentication on the initial touch information. When the fingerprint authentication result meets the preset standard, the sensing and control function of the LED light source is activated. The touch parsing module is used to parse the finger touch posture based on the initial touch information to obtain the finger posture features when the finger performs the initial touch behavior; The trajectory analysis module is used to acquire subsequent touch information through the touch sensing surface, and analyze the subsequent touch information according to the finger posture characteristics to generate the touch trajectory characteristics of the finger. The sensing control module is used to analyze the touch trajectory features based on the sensing control function, generate sensing control commands for the LED light source, and control the working state of the LED light source.

[0006] The technical solution disclosed herein has the following beneficial effects: ① The system determines the user's desired control command by using finger touch. Different finger touch trajectories are used to send different control commands to the light source, making the operation more flexible and eliminating the need to fumble for the corresponding button in the dark.

[0007] ② Before recognizing the movement trajectory of a finger touch, the initial touch posture of the finger is first identified. Then, based on the initial touch posture, the subsequent movement trajectory of the finger is determined. In other words, when the user's body is in different relative positions to the touch-sensitive surface, the form of the finger's sliding movement trajectory on the touch-sensitive surface is different. By analyzing the initial posture of the finger through fingerprint recognition and then determining the finger movement trajectory fed back by the subsequent touch movement, users can directly slide the finger trajectory corresponding to the desired command from any angle, without having to draw a fixed trajectory on the touch-sensitive surface, making the operation more flexible.

[0008] ③ The fingerprint recognition results are used to schedule the corresponding parsing algorithm to analyze the touch trajectory features and generate corresponding control commands. This allows each user to set their own personalized command set and control the light source according to their own suitable touch trajectory. Attached Figure Description

[0009] Figure 1 A schematic diagram illustrating the steps of a touch sensing method for an LED light source in this exemplary embodiment is shown. Figure 2 A schematic diagram of the structure of a touch sensing system for an LED light source in this exemplary embodiment is shown. Detailed Implementation

[0010] To make the objectives, technical solutions, and advantages of this disclosure clearer, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure. Unless otherwise specified, the embodiments and features in the embodiments of this disclosure can be arbitrarily combined with each other. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown here.

[0011] The term "comprising" and any variations thereof in the specification and claims of this disclosure are intended to cover non-exclusive protection. For example, a process, method, system, product, or apparatus that comprises a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.

[0012] In this disclosure, there are one or more embodiments; "multiple" refers to two or more. "And / or" describes the relationship between the associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following associated objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0013] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order, sequence, size, or priority. For example, the terms "first dialogue information" and "second dialogue information" in the embodiments of this disclosure are merely used to distinguish different dialogue information. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0014] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, which are schematic illustrations of this disclosure and are not necessarily drawn to scale. Some block diagrams shown in the drawings may be functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in hardware modules or integrated circuits, or in networks, processors, or microcontrollers. Implementations can be carried out in various forms and should not be construed as limited to the examples set forth herein. The features, structures, or characteristics described in this disclosure can be combined in any suitable manner in one or more implementations. In the following description, numerous specific details are provided to give a thorough description of the embodiments of this disclosure. However, those skilled in the art will recognize that one or more specific details may be omitted when implementing the technical solutions of this disclosure, or other methods, components, devices, steps, etc., may be used to replace one or more specific details. It should be noted that in the embodiments of this disclosure, the dissemination and use of data comply with relevant national laws and regulations. Please see Figure 1 As shown, this disclosure provides a touch sensing method for an LED light source, including: S1: Initial touch information is obtained through the touch sensing surface, and fingerprint authentication is performed on the initial touch information. When the fingerprint authentication result meets the preset standard, the sensing and control function of the LED light source is activated. S2: Analyze the finger touch posture based on the initial touch information to obtain the finger posture features when the finger performs the initial touch behavior; S3: Acquire subsequent touch information through the touch sensing surface, and analyze the subsequent touch information according to the finger posture characteristics to generate the touch trajectory characteristics of the finger; S4: Based on the aforementioned sensing and control function, the touch trajectory features are analyzed to generate sensing and control commands for the LED light source, thereby controlling the working state of the LED light source.

[0015] In step S1 of the embodiments provided in this disclosure, the touch sensing surface performs a self-check of the pressure path and the photoelectric path to obtain the initial contact information of the finger touching the touch sensing surface. The touch sensing surface has both pressure sensing and photoelectric sensing paths. Before the user touches it, the system will perform a self-check of the working status of these two sensing paths to ensure that they can work normally. For example, it checks whether the pressure sensor can accurately sense pressure changes and whether the photoelectric sensor can normally receive and process light signals. When the user's finger touches the touch sensing surface, the pressure path will sense the pressure applied by the finger, and the photoelectric path will detect the finger's blocking or reflection of light. The system integrates the information obtained from these two paths to obtain the initial contact information of the finger touching the touch sensing surface.

[0016] Pressure and photoelectric approaches are key means of acquiring initial touch information. Their proper functioning is crucial for subsequent fingerprint authentication and sensor control. Through status self-checking, potential faults in the sensing approach can be detected and eliminated in a timely manner, ensuring accurate acquisition of the initial contact information of the finger contact. Performing status self-checking before each touch operation can avoid misjudgments or operation failures caused by sensing approach faults, thereby improving the stability and reliability of the system.

[0017] The system uses a pre-deployed fingerprint recognition model to identify fingerprint features from initial contact information. This results in matching data between the initial touch information and several pre-recorded fingerprint accounts. This matching data is then used as the fingerprint authentication result. The system employs a pre-deployed fingerprint recognition model trained on a large amount of fingerprint data, enabling it to accurately identify fingerprint features. Upon receiving initial contact information, the system inputs it into the fingerprint recognition model, which extracts and analyzes the fingerprint features. Several pre-recorded fingerprint accounts, each corresponding to an authorized user's fingerprint information, are used to compare the extracted fingerprint features with the pre-recorded fingerprint accounts. The model calculates the matching degree between the initial touch information and each fingerprint account, obtaining matching data. This matching data is then used as the fingerprint authentication result. If the matching data meets preset standards, such as a matching degree reaching a certain threshold, fingerprint authentication is considered successful; otherwise, it is considered a failure.

[0018] Fingerprints are unique biometric features of the human body, possessing high specificity and stability. Fingerprint authentication ensures that only authorized users can control the LED light source, effectively preventing unauthorized operation and enhancing system security. Each authorized user's fingerprint is unique, and by matching it with a pre-recorded fingerprint account, the specific user's identity can be identified. In this way, the system can provide personalized sensing and control services based on different users' preferences and settings.

[0019] When the fingerprint authentication result meets the preset standard, the LED light source's sensing and control function is activated. The system compares the fingerprint authentication result with the preset standard, which can be set according to actual needs. For example, the matching threshold can be set to 80%. If the matching data reaches or exceeds this threshold, the result is considered to meet the preset standard. When the fingerprint authentication result meets the preset standard, the system activates the LED light source's sensing and control function. This means that users can perform further operations on the LED light source by touching the sensor, such as adjusting brightness and color. The LED light source's sensing and control function is only activated when fingerprint authentication is successful. This effectively controls operation permissions, ensuring that only authorized users can operate the light source. For authorized users, sensing and control can be performed directly after fingerprint authentication without additional identity verification, improving the convenience of operation and user experience.

[0020] In step S2 of the embodiments provided in this disclosure, the initial touch information is decomposed into fingerprint blocks and spatially located to obtain several unit fingerprint blocks and spatial positioning data of each unit fingerprint block relative to the touch sensing surface. The initial touch information includes the overall fingerprint information when the finger contacts the touch sensing surface. This overall fingerprint information is decomposed into multiple smaller unit fingerprint blocks according to certain rules. For example, it can be divided into small square or rectangular blocks according to a grid pattern. The specific position of each unit fingerprint block on the touch sensing surface is determined, and their spatial positioning data relative to the touch sensing surface is obtained. This can be achieved through the coordinate system of the touch sensing surface itself. Each unit fingerprint block has a corresponding coordinate value, thereby clarifying its accurate position on the sensing surface.

[0021] The initial touch information contains a large amount of detail and complex fingerprint patterns. If the entire fingerprint information is analyzed directly, the analysis results will be inaccurate due to the excessive complexity of the information. After breaking it down into unit fingerprint blocks, each small area can be analyzed in more detail, which improves the accuracy of finger touch posture analysis. Spatial positioning data provides the foundation for subsequent digital reproduction. By clarifying the position of each unit fingerprint block, the finger touch situation can be accurately reproduced in the digital model, making subsequent analysis and processing more convenient and accurate.

[0022] Based on spatial positioning data, each unit fingerprint block is digitally reproduced to obtain finger posture features composed of the finger touch position and finger touch posture when performing the initial touch behavior. Using spatial positioning data, the positional relationship of each unit fingerprint block is reconstructed in the digital model. Through computer programs or algorithms, each unit fingerprint block is placed in a virtual digital space according to its corresponding spatial coordinates to form a digital model corresponding to the actual touch situation. After the digital reproduction is completed, this digital model can reflect the specific situation when the finger performs the initial touch behavior, including the contact position between the finger and the touch sensing surface (i.e., the finger touch position) and the posture information such as the angle and bending degree of the finger (i.e., the finger touch posture). Combining this information yields the finger posture features.

[0023] Digital reproduction can transform abstract spatial positioning data into intuitive digital models, allowing for clearer observation and analysis of finger touch positions and postures. This visual presentation facilitates further interpretation and processing of touch behavior. Finger posture characteristics are crucial information in the entire touch sensing method, providing a reference for the initial state of finger touch trajectory characteristics analysis. Only by accurately acquiring the initial finger posture characteristics can subsequent touch information be better combined to analyze the finger's movement direction, distance, and other trajectory information, thereby achieving precise control of the LED light source.

[0024] In step S3 of the embodiments provided in this disclosure, the movement operation of the finger after performing the initial touch behavior is acquired by the touch sensing surface and recorded as subsequent touch information. After the user completes the initial touch behavior, the touch sensing surface continuously monitors the finger's movement. The touch sensing surface uses its pressure sensing, photoelectric sensing and other technologies to capture information such as the position change and pressure change of the finger on the sensing surface in real time, and records this information reflecting the finger movement operation to form subsequent touch information. For example, if the user slides his finger on the touch sensing surface, the touch sensing surface will record the position coordinates of the finger at different times and the amount of pressure applied.

[0025] After the initial touch, the user's subsequent movement often contains a specific intention to control the LED light source, such as adjusting brightness or switching colors. By acquiring subsequent touch information, the system can capture these operations in a timely manner, providing a data basis for subsequent analysis and instruction generation. The control of the LED light source usually needs to be adjusted in real time according to the user's dynamic operations. Continuously acquiring subsequent touch information allows the system to continuously update the user's operation status, thereby achieving dynamic and precise control of the light source.

[0026] Based on the finger posture characteristics, the subsequent touch information is analyzed to determine the finger movement direction and distance. Using the previously obtained finger posture characteristics as a reference, the finger position at different times in the subsequent touch information is compared. By calculating the changes in position coordinates, the direction of finger movement is determined, such as upward, downward, leftward, rightward, or more complex diagonal movement. For example, if the horizontal coordinate of the finger increases while the vertical coordinate remains unchanged in a later time, it can be determined that the finger is moving to the right. Similarly, based on the finger posture characteristics and subsequent touch information, the distance between the finger positions at different times is calculated. Mathematical formulas, such as the distance formula between two points, can be used to accurately calculate the distance traveled by the finger from one position to another.

[0027] The direction and distance of finger movement are key factors in determining the specific type of user operation. Different directions and distances of movement may correspond to different control commands. For example, sliding to the left indicates decreasing brightness, while sliding to the right indicates increasing brightness. The length of the slide determines the magnitude of brightness adjustment. By accurately analyzing this information, the system can correctly identify the user's operational intent. Precise analysis of movement direction and distance helps improve the accuracy of LED light source control. Based on the analysis results, the system can more accurately adjust the working state of the light source to meet the user's personalized needs for light source effects.

[0028] Based on finger posture characteristics, the touch position and posture of the finger at each moment of subsequent touch behavior are simulated according to the finger movement direction and distance. This yields the subsequent posture characteristics of the finger at each moment of subsequent touch behavior. Given the initial posture characteristics, movement direction, and movement distance of the finger, the state of the finger at each subsequent moment is simulated. Assuming that the finger is initially flat and the fingertip is in a certain position, the new position of the fingertip and possible posture changes such as bending and tilting of the finger can be predicted based on the movement direction and distance. Through this simulation, the specific posture characteristics of the finger at each moment of subsequent touch behavior are obtained, including touch position and posture information.

[0029] Knowing only the direction and distance of finger movement is insufficient to fully understand the finger's touch behavior. Simulating subsequent posture features can take into account the changes in finger posture during movement, such as bending and rotation, thus presenting a more complete picture of the actual state of the finger at each moment. These changes in finger posture contain information about the user's operational intent. For example, a slight bend in the finger during a slide indicates a specific operational command. By simulating subsequent posture features, the system can more accurately identify these operational intents contained in the posture changes, improving the accuracy of operation recognition.

[0030] The subsequent posture features at each moment are sequentially arranged with the finger posture features to obtain the finger touch trajectory features. According to the time order, the initial finger posture features and the subsequent posture features at each subsequent moment are arranged in sequence, thus forming a complete sequence that clearly shows the changes in posture and position of the finger from the initial touch to the subsequent movement. This sequence is the finger touch trajectory feature, which comprehensively reflects the entire movement trajectory of the finger on the touch sensing surface.

[0031] Arranging the posture characteristics at each moment in chronological order can intuitively display the entire movement process of the finger from the start of the touch to the end. This visualized trajectory feature facilitates comprehensive analysis by the system, enabling a better understanding of the user's operating patterns and habits. The touch trajectory feature is an important basis for generating LED light source sensing control commands. Based on this complete trajectory information, combined with preset rules and algorithms, the system can accurately generate control commands that conform to the user's operating intentions, thereby achieving effective control of the light source's working state.

[0032] In step S4 of the embodiments provided in this disclosure, the sensing control parsing algorithm corresponding to the fingerprint account performing the touch behavior is scheduled based on the sensing control function. The system pre-sets corresponding sensing control parsing algorithms for different fingerprint accounts, and each algorithm is personalized according to the user's usage habits and preferences. After fingerprint authentication is completed and touch trajectory features are obtained, the system will schedule the corresponding sensing control parsing algorithm from the stored algorithm library based on the fingerprint account performing the touch behavior. For example, if user A's fingerprint authentication is successful, the sensing control parsing algorithm specifically customized for user A will be invoked.

[0033] Different users have different usage habits and preferences. By configuring a dedicated sensing and control analysis algorithm for each fingerprint account, a personalized control experience can be achieved. For example, some users are used to moving left to increase brightness, while others are used to moving right. Personalized algorithms can meet the needs of different users. Personalized algorithms can better adapt to the touch behavior characteristics of specific users, thereby improving the accuracy of touch trajectory feature analysis and more accurately identifying the user's control intentions.

[0034] By analyzing the touch trajectory features using a sensor-based control parsing algorithm, the algorithm obtains information on the user's control tendencies in performing touch actions. The algorithm analyzes the direction of finger movement in the touch trajectory features and determines the control type corresponding to this movement direction. For example, moving to the left corresponds to decreasing the brightness of the LED light source, moving to the right corresponds to increasing the brightness, moving upward corresponds to switching to a warmer color, and moving downward corresponds to switching to a cooler color.

[0035] At the same time, the algorithm also analyzes the distance the finger moves to determine the degree of control. For example, the longer the finger moves to the right, the more the brightness of the LED light source needs to be increased; the shorter the distance, the smaller the increase in brightness. By combining the control type information of the finger movement direction and the control degree information of the finger movement distance, the algorithm generates control tendency information of the user's touch behavior. For example, if the finger moves a long distance to the right, the control tendency information is "significantly increase the brightness of the LED light source".

[0036] Touch trajectory features are simply a series of finger movement information. They need to be converted into meaningful control information through tendency analysis. By analyzing the direction and distance of finger movement, the system can deeply understand the user's operation intention, determine what kind of control the user wants to perform on the LED light source and the degree of control. The control tendency information is the direct basis for generating inductive control commands. Only by accurately parsing the user's control tendency can control commands that meet the user's needs be generated, thus achieving effective control of the LED light source.

[0037] Based on the control tendency information, the system generates corresponding sensing control commands for the LED light source. According to the obtained control tendency information, the system converts it into specific sensing control commands according to the preset rules. For example, if the control tendency information is "significantly increase the brightness of the LED light source", the system will generate a specific command, such as "increase the brightness of the LED light source to 80%" (assuming the brightness range is 0-100%). The generated sensing control command will be sent to the control system of the LED light source to control the working state of the LED light source.

[0038] Control intention information is only an abstract description and needs to be transformed into specific instructions in order to be recognized and executed by the LED light source control system. Generating inductive control instructions is a key step in translating the user's operating intentions into actual control actions, ensuring that the LED light source can change its working state according to the user's wishes. Inductive control instructions are a standardized signal that facilitates interface and communication with the LED light source control system. Through a unified instruction format, the stability and compatibility of the system can be ensured, and the efficiency and accuracy of control can be improved.

[0039] In one possible implementation, the steps of acquiring initial touch information via a touch-sensing surface and performing fingerprint authentication on the initial touch information include: S11: Perform a self-check of the pressure path and photoelectric path states on the touch sensing surface to obtain the initial contact information of the finger touching the touch sensing surface; S12: Based on the pre-deployed fingerprint recognition model, the initial contact information is identified by fingerprint features to obtain matching data of the initial touch information relative to a number of pre-recorded fingerprint accounts, and the matching data is used as the result of fingerprint authentication.

[0040] The system sends a self-test signal to the pressure sensor on the touch-sensitive surface. After receiving the signal, the pressure sensor checks whether its circuit connection is normal, including whether there is any looseness or short circuit between the sensor and the circuit board. The pressure sensor will check whether its sensitivity is within the normal range. It will simulate a standard pressure value and then compare the detected output signal with the preset standard output signal. If the deviation is within the allowable error range, the pressure sensor sensitivity is considered to be normal. When the user's finger touches the touch-sensitive surface, the pressure sensor starts to work, converting the pressure applied by the finger into an electrical signal. This electrical signal is converted from analog to digital and recorded by the system as pressure-related initial contact information.

[0041] The system checks whether the light-emitting element of the photoelectric sensor can emit light normally and whether the receiving element can receive light normally. By sending a test signal to the light-emitting element, it observes whether it emits light and detects whether the light intensity received by the receiving element meets expectations. It also checks whether the optical path of the photoelectric sensor is unobstructed and not blocked or contaminated. If there is a problem with the optical path, it will cause the received light signal to be inaccurate. When a finger touches the touch-sensitive surface, the finger will reflect or block the light emitted by the photoelectric sensor. The photoelectric sensor converts the received light changes into electrical signals, which are then processed to obtain photoelectric related initial contact information. The system integrates the initial contact information obtained through the pressure path and the photoelectric path to form complete initial touch information.

[0042] Pressure and photoelectric approaches are important ways for touch-sensitive surfaces to acquire information. Self-checking can promptly detect sensor malfunctions or anomalies, ensuring accurate acquisition of initial contact information when a user touches the surface. If a sensor malfunction goes undetected, the acquired information will be inaccurate, affecting subsequent fingerprint authentication results. Pressure and photoelectric approaches complement each other, providing more comprehensive and accurate initial contact information. Pressure information reflects the force applied by the finger and the contact area, while photoelectric information reflects the texture and shape of the fingerprint. Combining the two allows for a more accurate description of the finger's touch, providing a more reliable basis for fingerprint authentication.

[0043] A pre-deployed fingerprint recognition model preprocesses the integrated initial contact information to remove noise and interference signals, thereby improving the accuracy of fingerprint feature extraction. The model then uses specific algorithms to extract key fingerprint features, such as breakpoints, bifurcation points, and ridge patterns, from the preprocessed information. These features are unique identifiers for each person's fingerprint.

[0044] The system pre-registers several fingerprint accounts, each corresponding to an authorized user's fingerprint feature template. The fingerprint recognition model compares the extracted current fingerprint features with the feature templates of each pre-registered fingerprint account to calculate their similarity. The similarity calculation can be done using various methods, such as feature point matching algorithms and texture matching algorithms.

[0045] After comparison, the model generates a matching score for each pre-entered fingerprint account. This score represents the similarity between the current fingerprint and the fingerprint of that account. The system uses these matching scores as matching data and judges whether the matching score reaches or exceeds the set threshold according to preset rules. If so, the fingerprint authentication is considered successful; otherwise, the fingerprint authentication is considered to have failed.

[0046] Fingerprints are unique biometric features of the human body. Fingerprint authentication ensures that only authorized users can activate the LED light source's sensing and control functions. Matching the current fingerprint with a pre-registered fingerprint account effectively prevents unauthorized operation and ensures system security. Since different users have different fingerprints, fingerprint authentication can identify specific user identities. This allows the system to provide personalized sensing and control services based on different user preferences and settings, improving user experience. Utilizing a pre-deployed fingerprint recognition model for feature identification and matching automates fingerprint authentication. This automated authentication method not only improves efficiency but also reduces human interference, ensuring the objectivity and accuracy of the authentication results.

[0047] In one possible implementation, the step of parsing the finger touch posture based on the initial touch information to obtain the finger posture features when the finger performs the initial touch behavior includes: S21: The initial touch information is decomposed into fingerprint blocks and spatially located to obtain several unit fingerprint blocks and spatial positioning data of each unit fingerprint block relative to the touch sensing surface. S22: Digitally reproduce the fingerprint blocks of each unit according to the spatial positioning data to obtain the finger posture features composed of the finger touch position and finger touch posture when performing the initial touch behavior.

[0048] According to the preset grid division method, the entire fingerprint area corresponding to the initial touch information is divided into multiple units of equal size and regularity, such as a square grid with fixed side length. According to the determined rules, the fingerprint data in the initial touch information is divided into independent unit fingerprint blocks, and each unit fingerprint block contains the fingerprint pattern feature information in that area.

[0049] A two-dimensional rectangular coordinate system is established with a fixed angle of the touch-sensing surface as the origin. This coordinate system covers the entire touch-sensing surface and is used to determine the position of each unit fingerprint block. By analyzing the relative position of each unit fingerprint block on the touch-sensing surface and combining it with the established coordinate system, its specific coordinate value in the coordinate system is determined. These coordinate values ​​are the spatial positioning data of each unit fingerprint block relative to the touch-sensing surface.

[0050] The fingerprint data in the initial touch information is usually quite complex, containing a large amount of detail and overall information. By breaking it down into unit fingerprint blocks, each small area can be analyzed in more detail, avoiding inaccurate analysis results due to the large size and complexity of the overall data. By studying each unit fingerprint block separately, the local features of the fingerprint can be captured more accurately, providing more detailed information for subsequent posture analysis. Spatial positioning data provides the foundation for subsequent digital reproduction. By clarifying the specific position of each unit fingerprint block on the touch sensing surface, the touch situation of the finger can be accurately reproduced in the digital model. Moreover, this coordinate system-based positioning method makes data processing more standardized and regulated, facilitating subsequent analysis and calculation by the computer system.

[0051] Based on the previously established coordinate system, a virtual two-dimensional space is created in the computer system. This space corresponds to the actual size and proportion of the touch-sensing surface. In this virtual space, the basic framework of the digital model is determined according to the origin and coordinate axis direction of the coordinate system. Based on the spatial positioning data of each unit fingerprint block, each unit fingerprint block is accurately placed in the corresponding position of the digital model. The position of each unit fingerprint block in the digital model corresponds one-to-one with its actual position on the touch-sensing surface.

[0052] After the unit fingerprint blocks are placed, the entire digital model presents the fingerprint distribution when the finger performs the initial touch behavior. By analyzing the overall fingerprint distribution, the relative positional relationship between each unit fingerprint block, and the direction of the fingerprint pattern in the digital model, the touch position and touch posture of the finger are inferred, thus obtaining the finger posture features composed of the finger touch position and the finger touch posture.

[0053] Digital reproduction can transform abstract spatial positioning data into intuitive digital models, allowing for clearer observation and analysis of finger touch positions and postures. Through visualized digital models, the contact pattern between the finger and the touch-sensing surface, the distribution of fingerprints, and other information can be directly observed, thus more accurately inferring the finger's posture characteristics. Finger posture characteristics are crucial information in the entire touch sensing method, providing a reference for the initial state of subsequent analysis of the finger's touch trajectory characteristics. Only by accurately acquiring the initial finger posture characteristics can subsequent touch information be better combined to analyze the finger's movement direction, distance, and other trajectory information, thereby achieving precise control of the LED light source.

[0054] In one possible implementation, the steps of acquiring subsequent touch information through a touch-sensing surface and analyzing the subsequent touch information based on the finger posture characteristics to generate touch trajectory features of the finger include: S31: The movement of the finger after the initial touch action is obtained through the touch sensing surface and recorded as subsequent touch information; S32: Based on the finger posture characteristics, analyze the finger movement direction and finger movement distance of the subsequent touch information to obtain the finger movement direction and finger movement distance fed back by the subsequent touch information; S33: Based on the finger posture characteristics, simulate the finger touch position and finger touch posture at each moment of the subsequent touch behavior according to the finger movement direction and the finger movement distance, and obtain the subsequent posture characteristics of the finger at each moment of the subsequent touch behavior. S34: Arrange the subsequent posture features at each moment with the finger posture features in a temporal sequence to obtain the touch trajectory features of the finger.

[0055] The touch-sensing surface captures finger movements after the initial touch action, recording them as subsequent touch information. After acquiring the initial touch information, the surface maintains real-time monitoring of the sensing area. Utilizing internal pressure sensors and photoelectric sensors, it continuously senses the physical interaction between the finger and the surface. As the finger moves on the surface, the sensors convert detected physical signals such as pressure changes, light obstruction, or reflection changes into electrical signals. These electrical signals undergo analog-to-digital conversion and signal processing circuitry to convert them into digital data, such as the finger's coordinate position at different times and the magnitude of applied pressure. The system records the collected digital data chronologically to form subsequent touch information. This information includes a series of state data related to the finger's movement.

[0056] After the initial touch, subsequent movement operations often include specific instructions to control the LED light source, such as adjusting brightness or switching colors. By acquiring subsequent touch information, the system can promptly capture these operational intentions, providing a data basis for generating subsequent instructions. The control of the LED light source usually needs to be dynamically adjusted according to the user's real-time operations. Continuously acquiring subsequent touch information allows the system to track finger movements in real time, thereby achieving real-time and precise control of the light source's working status.

[0057] Based on finger posture characteristics, subsequent touch information is analyzed to determine the direction and distance of finger movement, using the initial touch position and posture recorded in the finger posture characteristics as a reference point. This reference point provides a benchmark for subsequent movement analysis. By comparing the coordinates of the finger at different times in subsequent touch information with the coordinates of the reference point, the displacement of the finger in the horizontal (X-axis) and vertical (Y-axis) directions is determined by calculating the difference in coordinates. The direction of finger movement is determined based on the sign of the coordinate difference; for example, if the X-coordinate increases, the finger moves to the right; if the Y-coordinate decreases, the finger moves upward. Combining the changes in the X and Y directions, the specific direction of finger movement can be determined, such as upper right, lower left, etc. Using the coordinate difference, the straight-line distance from the reference point to the current position is calculated using the Pythagorean theorem, which is taken as the distance the finger has moved.

[0058] The direction and distance of finger movement are key factors in determining the specific type of user operation. Different combinations of movement direction and distance correspond to different control commands. For example, sliding to the left decreases brightness, while sliding to the right increases brightness. The length of the slide determines the magnitude of brightness adjustment. By accurately analyzing this information, the system can correctly identify the user's operational intent. Precise analysis of movement direction and distance helps improve the accuracy of LED light source control. Based on the analysis results, the system can more accurately adjust the working state of the light source to meet the user's personalized needs for light source effects.

[0059] Based on finger posture characteristics, the model simulates the finger touch position and posture at each moment of subsequent touch actions according to the finger movement direction and distance. Based on the finger posture characteristics, a simulation model that can describe the movement of the finger on the sensing surface is constructed. This model considers factors such as finger shape and joint movement to more accurately simulate the changes in finger posture. According to the finger movement direction and distance, combined with the simulation model, the touch position and posture of the finger at each moment of subsequent touch actions are predicted. For example, if the finger moves a certain distance to the upper right, the model will calculate the degree of bending and tilt angle of the finger at the new position according to the initial posture and movement law of the finger. The predicted finger touch position and posture information at each moment are organized to form the subsequent posture characteristics of the finger at each moment of subsequent touch actions.

[0060] Knowing only the direction and distance of finger movement is insufficient to fully understand the finger's touch behavior. Simulating subsequent posture features can take into account the changes in finger posture during movement, such as bending and rotation, thus presenting a more complete picture of the actual state of the finger at each moment. These changes in finger posture may also contain information about the user's operational intent. For example, a slight bend in the finger during a slide may indicate a specific operational command. By simulating subsequent posture features, the system can more accurately identify these operational intents implied in the changes in posture, improving the accuracy of operation recognition.

[0061] The subsequent posture features at each moment are sequentially arranged with the finger posture features to obtain the finger touch trajectory features. The finger posture features (initial posture) and the subsequent posture features at each moment are arranged in chronological order to ensure that each posture feature corresponds to an accurate timestamp to reflect the order of finger movement. The arranged posture feature sequence constitutes the finger touch trajectory features. This feature completely describes the position and posture changes of the finger from the initial touch to the subsequent movement, presenting a continuous motion trajectory.

[0062] Arranging the posture characteristics at each moment in chronological order can intuitively display the entire movement process of the finger from the start of the touch to the end. This visualized trajectory feature facilitates comprehensive analysis by the system, enabling a better understanding of the user's operating patterns and habits. The touch trajectory feature is an important basis for generating LED light source sensing control commands. Based on this complete trajectory information, combined with preset rules and algorithms, the system can accurately generate control commands that conform to the user's operating intentions, thereby achieving effective control of the light source's working state.

[0063] In one possible implementation, the step of parsing the touch trajectory features based on the sensing control function to generate sensing control commands for the LED light source includes: S41: A sensor control parsing algorithm that schedules the fingerprint account corresponding to the touch behavior based on the sensor control function; S42: The touch trajectory features are analyzed using the aforementioned sensing control analysis algorithm to determine the user's touch behavior tendency, thereby obtaining control tendency information for the user to perform touch actions. S43: Generate corresponding sensing control commands for the LED light source based on the control tendency information.

[0064] Based on the sensing control function, the system schedules the sensing control parsing algorithm corresponding to the fingerprint account that performs the touch behavior. After completing fingerprint authentication, the system records the fingerprint account information that performs the touch behavior. When it is necessary to analyze the touch trajectory features, the system first extracts the fingerprint account identifier from the stored authentication record. The system pre-stores multiple sensing control parsing algorithms for different fingerprint accounts. Based on the identified fingerprint account identifier, the system searches for the corresponding sensing control parsing algorithm in the algorithm library and schedules it to the system's parsing module for execution.

[0065] Different users have different usage habits and preferences. By configuring a dedicated sensing control analysis algorithm for each fingerprint account, a personalized control experience can be achieved. For example, some users are used to using specific gestures to adjust the light source color, while other users have different operating habits. Personalized algorithms can better adapt to these differences and improve user satisfaction. Personalized algorithms can be optimized and adjusted based on the historical touch behavior data of a specific user, and more accurately identify the user's control intention. Compared with general algorithms, it can reduce misjudgments and improve the accuracy of touch trajectory feature analysis.

[0066] The sensor-controlled analysis algorithm analyzes the touch trajectory features to interpret the user's touch behavior tendencies, thereby obtaining information on the user's control tendencies in performing touch actions. The sensor-controlled analysis algorithm extracts the finger movement direction information at different time periods from the touch trajectory features, including horizontal (left, right) and vertical (up, down) movement. According to preset rules, the algorithm maps the extracted movement direction information to specific control types. For example, it specifies that moving the finger to the left corresponds to the "decrease brightness" control type, and moving it to the right corresponds to the "increase brightness" control type, etc.

[0067] The algorithm calculates the distance the finger travels in each phase of movement. By comparing the coordinate positions at different time points, it uses mathematical formulas (such as the distance formula between two points) to derive the specific distance value. Based on the calculated distance, the degree of control is graded. For example, a shorter distance corresponds to "small adjustment" and a longer distance corresponds to "large adjustment". The algorithm integrates the control type information of the finger movement direction and the control degree information of the finger movement distance to generate control tendency information for the user's touch behavior. For example, if the finger moves a long distance to the right, the generated control tendency information is "significantly increase brightness".

[0068] Touch trajectory features are simply a series of finger movement information. They need to be converted into meaningful control information through tendency analysis. By analyzing the direction and distance of finger movement, the system can deeply understand the user's operation intention, determine what kind of control the user wants to perform on the LED light source and the degree of control. The control tendency information is the direct basis for generating inductive control commands. Only by accurately parsing the user's control tendency can control commands that meet the user's needs be generated, thus achieving effective control of the LED light source.

[0069] Based on the control tendency information, the system generates corresponding sensing control commands for the LED light source. A series of rules for converting control tendency information into sensing control commands are pre-set in the system. Based on the generated control tendency information, the system searches for matching rules and converts the control tendency information into specific sensing control commands according to the matching rules. For example, if the control tendency information is "significantly increase brightness", the command generated according to the rules is "increase the brightness of the LED light source to 80% (assuming the current brightness is 30% and the brightness range is 0-100%)". The generated sensing control command is sent to the control system of the LED light source to realize the control of the working state of the LED light source.

[0070] Control intention information is only an abstract description and needs to be transformed into specific instructions in order to be recognized and executed by the LED light source control system. Generating inductive control instructions is a key step in translating the user's operating intentions into actual control actions, ensuring that the LED light source can change its working state according to the user's wishes. Inductive control instructions are a standardized signal that facilitates interface and communication with the LED light source control system. Through a unified instruction format, the stability and compatibility of the system can be ensured, and the efficiency and accuracy of control can be improved.

[0071] In one possible implementation, the step of analyzing the touch trajectory features using the sensor-based control parsing algorithm to obtain user touch behavior tendency information includes: S421: The touch trajectory features are analyzed by the sensor control analysis algorithm to determine the control type of finger movement direction, and the control type information fed back by the touch trajectory features is obtained. S422: The touch trajectory features are analyzed by the sensor control analysis algorithm to determine the degree of control of finger movement distance, and the control degree information fed back by the touch trajectory features is obtained. S423: Combine the control type information with the control degree information to generate control tendency information for performing touch behavior.

[0072] The sensor-controlled analysis algorithm extracts the coordinate data of the finger at different time periods from the touch trajectory features. This coordinate data records the position change of the finger on the touch sensing surface. By comparing the coordinates of adjacent time points, the direction of finger movement can be determined. Based on the calculated coordinate difference, the direction of finger movement can be judged.

[0073] The algorithm maps the direction of finger movement to specific control types according to pre-set rules. For example, moving the finger to the left corresponds to "decreasing brightness", moving it to the right corresponds to "increasing brightness", moving it up corresponds to "switching to warm colors", and moving it down corresponds to "switching to cool colors".

[0074] The direction of finger movement is a key indicator of the user's intent. Different movement directions correspond to different control operations on the LED light source, such as adjusting brightness or changing color. By analyzing the movement direction and mapping it to the control type, the system can accurately identify the specific operation the user wants to perform, providing a foundation for generating subsequent control commands. Supporting multiple movement directions and different control types allows users to achieve diverse control of the LED light source through simple finger swipes, improving user convenience and system usability.

[0075] By analyzing the touch trajectory features using a sensor-based control analysis algorithm, the degree of control is determined by the distance the finger moves. The control level information fed back by the touch trajectory features is obtained, and the distance the finger moves in each movement stage is calculated using coordinate data. Based on the calculated distance, the degree of control is classified.

[0076] The distance a finger moves reflects the user's desired level of control. Different distances correspond to different adjustment ranges. For example, small adjustments allow for fine-tuning of brightness or color, while large adjustments can quickly change the light source status. By classifying the degree of movement distance, the system can more accurately control the working state of the LED light source, meeting the user's personalized needs. Differentiating the degree of control based on the movement distance allows users to flexibly adjust the control range according to their needs, avoiding inconvenience caused by overly simplistic control and improving the user experience.

[0077] By combining control type information with control degree information, control tendency information for performing touch behavior is generated. The control type information obtained through direction analysis and the control degree information obtained through distance analysis are integrated. For example, if the control type information is "increase brightness" and the control degree information is "significantly adjust", then the integrated control tendency information is "significantly increase brightness".

[0078] Individual control type information or control degree information cannot fully express the user's operating intention. Only by combining the two can a complete control tendency information be formed, accurately reflecting the user's specific requirements for controlling the LED light source. For example, "significantly increase brightness" indicates both the control type and the degree of control. Control tendency information is the direct basis for generating LED light source sensing control commands. Complete and accurate control tendency information ensures that the generated control commands meet the user's actual needs, achieving precise control of the LED light source.

[0079] In one possible implementation, the sensor-controlled parsing algorithm has an adaptive adjustment function, and its steps include: S401: Record the touch trajectory features of the fingerprint account corresponding to the sensing control parsing algorithm, and combine the touch trajectory features within a predetermined time range as touch adjustment combinations according to the time relationship. S402: Mark the sequence of each touch trajectory feature in the touch adjustment combination, and adjust the control tendency information of the touch trajectory features in the previous sequence according to the touch trajectory features in the later sequence to obtain the actual tendency information of the touch trajectory features in the previous sequence. S403: Adjust the parameters of the sensing control parsing algorithm according to the actual tendency information of each group of touch adjustment combinations, so that the parsing mode of the sensing control parsing algorithm for touch trajectory features is adapted to the actual tendency information of the touch trajectory features.

[0080] The system records the touch trajectory characteristics of each fingerprint account corresponding to the sensing control analysis algorithm. Touch trajectory characteristics within a predetermined time range are then combined into touch adjustment combinations based on temporal relationships. Whenever a specific fingerprint account is used for touch operation, the system automatically records the corresponding touch trajectory characteristics. These characteristics include information such as the direction, distance, and posture of the finger on the touch-sensitive surface. The system stores these touch trajectory characteristics in a database and associates them with the corresponding fingerprint account, while also recording the timestamp of each touch operation within a predetermined time range, such as the past week or month. This time range can be adjusted according to actual needs to select a suitable period for analyzing changes in user touch behavior. The system then filters all touch trajectory characteristics corresponding to a specific fingerprint account within the predetermined time range from the database and arranges these characteristics in chronological order to form a touch adjustment combination.

[0081] Users' touch behavior habits may change over time. By recording touch trajectory characteristics within a predetermined time range, the system can capture these changes, providing a data basis for the adaptive adjustment of the algorithm. A single touch trajectory feature cannot accurately reflect the user's true intention, but by combining and analyzing multiple touch trajectory features, a more comprehensive understanding of the user's operating habits and preferences can be obtained, thereby enabling more accurate algorithm adjustments.

[0082] Each touch trajectory feature in the touch adjustment combination is numbered and marked sequentially according to time. The control tendency information of the touch trajectory features in the earlier sequence is adjusted with reference to the touch trajectory features in the later sequence. For example, if the user frequently uses a certain operation mode to achieve the same control purpose in subsequent touch operations, then this operation mode can be considered to better reflect the user's true intention. The specific adjustment method can be to modify the control tendency information of the earlier operation based on the control tendency that appears more frequently in the subsequent touch trajectory features. For example, if a previous operation is interpreted as "significantly increase brightness", but a subsequent operation is interpreted as "slightly increase brightness", then the control tendency information of the previous operation is adjusted to "medium increase brightness". This yields the actual tendency information of the touch trajectory features in the earlier sequence. This actual tendency information can more accurately reflect the user's true operation intention throughout the predetermined time range.

[0083] In some cases, due to various factors (such as non-standard touch operation, environmental interference, etc.), the sensor control parsing algorithm may not accurately interpret the control tendency information of touch trajectory features. By referring to subsequent touch trajectory features for adjustment, the previous parsing error can be corrected, and more accurate actual tendency information can be obtained. The user's operating habits will gradually become clear and stable, and subsequent touch operations can better reflect their true control intentions. Therefore, adjusting the previous control tendency information based on subsequent operations can enable the system to more accurately grasp the user's true needs.

[0084] The parameters of the sensing control analysis algorithm are adjusted according to the actual tendency information of each group of touch adjustment combinations, so that the analysis mode of the sensing control analysis algorithm for touch trajectory features is adapted to the actual tendency information of touch trajectory features. The parameters related to control tendency analysis in the sensing control analysis algorithm are analyzed, such as the mapping relationship between movement direction and control type, and the grading standard of movement distance and control degree.

[0085] Based on the actual preference information of touch adjustment combinations, the parameters of the sensor control analysis algorithm are adjusted. For example, if the actual preference information shows that the user prefers to adjust the brightness by making larger movements, the grading standard of movement distance and control intensity can be adjusted so that larger movement distances correspond to more obvious brightness adjustments. The adjusted parameters are then applied to the sensor control analysis algorithm to complete the algorithm update. The updated algorithm can better adapt to the touch behavior habits of specific fingerprint account users and improve the accuracy of touch trajectory feature analysis.

[0086] Different users have different touch behavior habits, and even the same user's habits may change. By adjusting the parameters of the sensing and control analysis algorithm based on actual preference information, the algorithm can better adapt to the current operating habits of a specific user, improve the accuracy and adaptability of the algorithm in analyzing touch trajectory features, and when the algorithm can more accurately analyze the user's touch operation intentions, the system can more precisely control the working state of the LED light source, provide users with services that better meet their needs, and thus optimize the user experience.

[0087] Please see Figure 2 As shown, this disclosure provides a touch sensing system for an LED light source, used to implement the touch sensing method for an LED light source as described in any one of the first aspects, including: The touch sensing module is used to acquire initial touch information through the touch sensing surface and perform fingerprint authentication on the initial touch information. When the fingerprint authentication result meets the preset standard, the sensing and control function of the LED light source is activated. The touch parsing module is used to parse the finger touch posture based on the initial touch information to obtain the finger posture features when the finger performs the initial touch behavior; The trajectory analysis module is used to acquire subsequent touch information through the touch sensing surface, and analyze the subsequent touch information according to the finger posture characteristics to generate the touch trajectory characteristics of the finger. The sensing control module is used to analyze the touch trajectory features based on the sensing control function, generate sensing control commands for the LED light source, and control the working state of the LED light source.

[0088] In this embodiment, the specific implementation of each module in the above system embodiment is described in the above method embodiment, and will not be repeated here.

[0089] As can be seen from the above, the technical solutions disclosed herein can be implemented as methods, apparatus, systems, computer program products, storage media, electronic devices, etc. Those skilled in the art will understand that various aspects of this disclosure can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, which may be referred to as "circuit," "module," or "system," respectively.

[0090] It should be understood that this disclosure is not limited to the specific methods, steps, or structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. Those skilled in the art will readily conceive of other embodiments based on the specific implementations provided in this disclosure. Therefore, the specific implementations provided in this disclosure are merely exemplary, and the scope and spirit of this disclosure are indicated by the claims, and should cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary technical means in the art not disclosed in this disclosure.

Claims

1. A touch sensing method for an LED light source, characterized in that, include: Initial touch information is obtained through the touch sensing surface, and fingerprint authentication is performed on the initial touch information. When the fingerprint authentication result meets the preset standard, the sensing and control function of the LED light source is activated. The finger touch posture is analyzed based on the initial touch information to obtain the finger posture features when the finger performs the initial touch behavior; Subsequent touch information is acquired through the touch sensing surface, and the subsequent touch information is analyzed based on the finger posture characteristics to generate the touch trajectory characteristics of the finger; Based on the aforementioned sensing and control function, the touch trajectory features are analyzed to generate sensing and control commands for the LED light source, thereby controlling the working state of the LED light source.

2. The touch sensing method for an LED light source as described in claim 1, characterized in that, The steps of acquiring initial touch information through a touch-sensing surface and performing fingerprint authentication on the initial touch information include: The touch sensing surface undergoes a self-check of the pressure path and photoelectric path states to obtain initial contact information of the finger touching the touch sensing surface. The fingerprint features of the initial contact information are identified according to a pre-deployed fingerprint recognition model to obtain matching data of the initial touch information relative to a number of pre-recorded fingerprint accounts, and the matching data is used as the result of fingerprint authentication.

3. The touch sensing method for an LED light source as described in claim 1, characterized in that, The steps of parsing the finger touch posture based on the initial touch information to obtain the finger posture features when the finger performs the initial touch behavior include: The initial touch information is decomposed into fingerprint blocks and spatially located to obtain several unit fingerprint blocks and spatial positioning data of each unit fingerprint block relative to the touch sensing surface. The fingerprint blocks of each unit are digitally reproduced based on the spatial positioning data to obtain finger posture features composed of the finger touch position and finger touch posture when the initial touch behavior is performed.

4. The touch sensing method for an LED light source as described in claim 1, characterized in that, The steps of acquiring subsequent touch information through a touch-sensing surface and analyzing the subsequent touch information based on the finger posture characteristics to generate the touch trajectory characteristics of the finger include: The movement of a finger after the initial touch action is captured by the touch-sensing surface and recorded as subsequent touch information; Based on the finger posture characteristics, the subsequent touch information is analyzed to determine the finger movement direction and finger movement distance, thereby obtaining the finger movement direction and finger movement distance fed back by the subsequent touch information; Based on the finger posture features, the finger touch position and finger touch posture at each moment of the subsequent touch behavior are simulated according to the finger movement direction and the finger movement distance to obtain the subsequent posture features of the finger at each moment of the subsequent touch behavior. The subsequent posture features at each moment are sequentially arranged with the finger posture features to obtain the touch trajectory features of the finger.

5. The touch sensing method for an LED light source as described in claim 1, characterized in that, The steps of analyzing the touch trajectory features based on the aforementioned sensing and control function to generate sensing and control commands for the LED light source include: The sensor control parsing algorithm is based on the aforementioned sensor control function to schedule the fingerprint account that performs the touch behavior. The touch trajectory features are analyzed using the aforementioned sensing and control parsing algorithm to determine the user's touch behavior tendencies and obtain information on the user's control tendencies in performing touch actions. Based on the control tendency information, corresponding sensing control commands are generated for the LED light source.

6. The touch sensing method for an LED light source as described in claim 5, characterized in that, The steps of analyzing the touch trajectory features using the aforementioned sensing control parsing algorithm to obtain user touch behavior tendency information include: The touch trajectory features are analyzed by the sensor control parsing algorithm to determine the control type of finger movement, thereby obtaining the control type information fed back by the touch trajectory features. The touch trajectory features are analyzed by the aforementioned sensing and control parsing algorithm to determine the degree of control by the finger movement distance, thereby obtaining the degree of control information fed back by the touch trajectory features. The control type information is combined with the control degree information to generate control tendency information for performing touch behavior.

7. The touch sensing method for an LED light source as described in claim 5, characterized in that, The sensor-based control analysis algorithm has an adaptive adjustment function, and its steps include: Record the touch trajectory features of the fingerprint account corresponding to the sensing control parsing algorithm, and use the touch trajectory features within a predetermined time range as touch adjustment combinations according to the time relationship; The touch trajectory features in the touch adjustment combination are marked in sequence, and the touch trajectory features in the previous sequence are adjusted according to the touch trajectory features in the later sequence to obtain the actual tendency information of the touch trajectory features in the previous sequence. The parameters of the sensing control parsing algorithm are adjusted according to the actual tendency information of each group of touch adjustment combinations, so that the parsing mode of the sensing control parsing algorithm for touch trajectory features is adapted to the actual tendency information of the touch trajectory features.

8. A touch sensing system for an LED light source, characterized in that, A touch sensing method for implementing an LED light source according to any one of claims 1-7 includes: The touch sensing module is used to acquire initial touch information through the touch sensing surface and perform fingerprint authentication on the initial touch information. When the fingerprint authentication result meets the preset standard, the sensing and control function of the LED light source is activated. The touch parsing module is used to parse the finger touch posture based on the initial touch information to obtain the finger posture features when the finger performs the initial touch behavior; The trajectory analysis module is used to acquire subsequent touch information through the touch sensing surface, and analyze the subsequent touch information according to the finger posture characteristics to generate the touch trajectory characteristics of the finger. The sensing control module is used to analyze the touch trajectory features based on the sensing control function, generate sensing control commands for the LED light source, and control the working state of the LED light source.

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