System for automatically identifying left eye and right eye of detector and applied to ophthalmology equipment

Abstract

The invention discloses a system for automatically identifying the left eye and the right eye of a detector applied to ophthalmology equipment, which can realize quick and accurate double-eye measurement switching on the premise of not increasing the size and the cost of the equipment and improve the measurement efficiency and the experience of the detector. According to the technical scheme, the system comprises a left proximity sensor module, a right proximity sensor module and an upper-layer application, and the left proximity sensor module and the right proximity sensor module are arranged on the left side and the right side of the detection position of the ophthalmic equipment; wherein the left proximity sensor module and the right proximity sensor module are used for reading sensor original values when eyes of a detector are placed at detection positions of ophthalmologic equipment, respectively processing the read sensor original values to obtain sensor effective values and reporting the sensor effective values to an upper-layer application; and the upper layer application automatically judges whether the person currently placed at the detection position of the ophthalmic equipment by the detector is the left eye or the right eye according to the sensor effective values reported by the left proximity sensor module and the right proximity sensor module.

Description

Technical Field

[0001] The present invention relates to an application technology in ophthalmic equipment, and in particular to a system for automatically identifying the left and right eyes of a tester applied to ophthalmic equipment. Background Art

[0002] When using ophthalmic equipment, it is crucial to accurately obtain physiological parameters, images, or characteristics of the tester's eyes. Traditional ophthalmic equipment generally uses the following two main methods to measure both eyes:

[0003] 1. Manual operation

[0004] A common method involves an operator (such as a nurse) manually operating a joystick or other mechanical device to align the ophthalmic device's measuring components with the tester's left and right eyes. The operator needs to precisely adjust the device's alignment based on the tester's facial features and eye position, and then record measurement data for each eye. While this method can meet measurement needs to a certain extent, its reliance on manual operation has the following drawbacks:

[0005] (1) The operator's skills and experience are high, and unskilled operation may lead to measurement errors or inaccurate alignment.

[0006] (2) The measurement process is rather cumbersome and requires manual alignment and recording one by one, which is inefficient and cannot achieve automated measurement, making it difficult to match the high-efficiency requirements of modern ophthalmic diagnosis.

[0007] 2. Mechanical mobile platform method

[0008] Another traditional method uses a machine's lateral motion platform (such as a lead screw slider) to switch between left and right eye measurements. After measuring one eye, the ophthalmic device drives the motion platform to move the measuring component from one eye to the other, and then continues measuring. However, this method also has many problems:

[0009] (1) The device is large in size: Since it needs to move significantly in the lateral direction to cover the range of the left and right eyes, the overall size of the ophthalmic device is limited, especially the lateral width is large, which takes up more space and is not convenient for use in medical environments with limited space.

[0010] (2) Increased costs: In order to achieve the lateral movement function, ophthalmic equipment needs to be equipped with additional structural parts, control parts and electronic parts, such as complex transmission mechanisms, drive motors, sensors, etc., which undoubtedly increases the manufacturing cost and maintenance cost of ophthalmic equipment.

[0011] (3) Low measurement efficiency: After measuring one eye, the ophthalmic equipment needs to spend a certain amount of time to control the mobile platform to move to the position of the other eye and realign it with the center of the eye. This process increases the waiting time for measurement and reduces the overall measurement efficiency. This problem is particularly prominent in scenarios where a large number of testers need to be screened quickly.

[0012] In summary, existing ophthalmic equipment, whether manually operated or using a mechanical mobile platform, has problems such as large size, high cost, and low efficiency when measuring both eyes, making it difficult to meet the needs of modern ophthalmic diagnosis for efficient, accurate, and automated measurement. Summary of the Invention

[0013] The following is a brief summary of one or more aspects to provide a basic understanding of these aspects. This summary is not an exhaustive overview of all conceivable aspects and is neither intended to identify key or critical elements of all aspects nor to define the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that will be provided later.

[0014] The purpose of the present invention is to solve the above problems and provide a system for automatically identifying the left and right eyes of the examinee applied to ophthalmic equipment. It can achieve fast and accurate binocular measurement switching without increasing the size and cost of the equipment, thereby improving measurement efficiency and the examinee's experience.

[0015] The technical solution of the present invention is as follows: The present invention discloses a system for automatically identifying the left and right eyes of a person being detected in an ophthalmic device, comprising a left proximity sensor module, a right proximity sensor module, and an upper-layer application. The left proximity sensor module and the right proximity sensor module are arranged on the left and right sides of a detection position of the ophthalmic device, wherein:

[0016] The left proximity sensor module and the right proximity sensor module are used to read the sensor raw value when the examinee's eyes are placed in the detection position of the ophthalmic equipment, and each module processes the read sensor raw value to obtain the sensor valid value and reports it to the upper layer application;

[0017] The upper-layer application automatically determines whether the examinee's current eye is the left eye or the right eye placed in the ophthalmic device's detection position based on the sensor valid values ​​reported by the left proximity sensor module and the right proximity sensor module.

[0018] According to an embodiment of the system for automatically identifying the left and right eyes of a person applied to ophthalmic equipment of the present invention, a filter is respectively provided on the left proximity sensor module and the right proximity sensor module.

[0019] According to an embodiment of the system for automatically identifying and detecting the left and right eyes of a person applied to an ophthalmic device of the present invention, the process for converting the read raw sensor values ​​by the left proximity sensor module and the right proximity sensor module into effective sensor values ​​is as follows:

[0020] Filter and reduce noise on the original sensor value;

[0021] Perform weighted processing on specific targets, calculate the limit range, and obtain the sensor effective value based on the limit range.

[0022] According to an embodiment of the system for automatically identifying the left and right eyes of a subject in ophthalmic equipment of the present invention, the filtering and noise reduction process adopts a sliding average filtering method.

[0023] According to an embodiment of the system for automatically identifying the left and right eyes of a subject applied to ophthalmologic equipment of the present invention, the filtering magnification of the sliding average filter is 16 times.

[0024] According to an embodiment of the system for automatically identifying the left and right eyes of a person being detected in ophthalmic equipment of the present invention, specific targets are divided into valid targets and invalid targets, and weighted processing is to perform directional enhancement of the effective value of the valid targets and weaken the invalid targets.

[0025] According to an embodiment of the system for automatically identifying the left and right eyes of a subject in an ophthalmic device of the present invention, the upper layer application automatically identifies whether the subject is the left eye or the right eye based on the distance between the left proximity sensor module and the right proximity sensor module and the target object:

[0026] When the examinee's left eye is positioned correctly, the right proximity sensor module detects a target at a closer distance than the left proximity sensor module. The upper-layer application automatically identifies that the examinee is testing the left eye based on the data reported by the underlying sensor.

[0027] When the examinee's right eye is correctly positioned, the left proximity sensor module detects a target at a closer distance than the right proximity sensor module. The upper-layer application automatically identifies that the examinee is testing the right eye based on the data reported by the underlying sensor.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] 1) Since the machine does not need to move significantly left and right to actively cover the left and right eyes of the examinee, the size of the ophthalmic equipment can be greatly reduced;

[0030] 2) Because ophthalmic devices no longer require additional structural components, control components, or electronic components to support their large lateral movement, only two low-cost sensor modules and their processing algorithms can replace these components, thus reducing product manufacturing costs.

[0031] 3) After measuring one eye, the machine no longer needs to be controlled to move to the range of the other eye and then realign the eye center, thus improving detection efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The above features and advantages of the present invention will be better understood after reading the detailed description of the embodiments of the present disclosure in conjunction with the following drawings. In the drawings, the components are not necessarily drawn to scale, and components with similar related properties or characteristics may have the same or similar reference numerals.

[0033] Figure 1 The figure shows a hardware structure diagram of an embodiment of the system for automatically identifying the left and right eyes of a person to be examined in ophthalmic equipment according to the present invention.

[0034] Figure 2 A flowchart showing the system operation of an embodiment of the system for automatically identifying the left and right eyes of an examinee applied to ophthalmologic equipment according to the present invention.

[0035] Figure 3 Shown Figure 2 A detailed flowchart of the local processing steps in the system operation process is shown. DETAILED DESCRIPTION

[0036] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. Note that the various aspects described below with reference to the accompanying drawings and specific embodiments are merely exemplary and should not be construed as limiting the scope of protection of the present invention.

[0037] Figure 1 The hardware structure of an embodiment of the system for automatically identifying the left and right eyes of a person using ophthalmic equipment according to the present invention is shown. Figure 1 The hardware of the system in this embodiment includes two proximity sensor modules, namely, a left proximity sensor module 1 and a right proximity sensor module 2. Each of the left proximity sensor module 1 and the right proximity sensor module 2 is provided with a filter. The left proximity sensor module 1 and the right proximity sensor module 2 are provided on the left and right sides of the detection position 3 of the ophthalmic device.

[0038] This design is based on ergonomic principles:

[0039] 1) For more than 99% of people, the tip of the nose is the highest point of the skin near the eyes;

[0040] 2) The tip of the nose is to the right of the left eye and to the left of the right eye.

[0041] The operating principle of a proximity sensor is that light is emitted from a transmitter at a specific wavelength (usually in the infrared band) at a conical emission angle. Upon striking an object that reflects that wavelength, it is reflected back and received by a receiver, where it is converted into an analog electrical signal. This signal is then filtered and converted to a digital signal using an ADC. Different media have different reflectivities and signal frequencies for the emitted energy. Filters are typically located in the optical path of a proximity sensor, installed between the transmitter and receiver, or directly covering the sensor's optical window. These filters enable wavelength selection, improve the signal-to-noise ratio, protect the sensor, and enhance measurement accuracy. This effectively improves the sensor's measurement performance in ophthalmic equipment, ensuring more accurate and reliable data when measuring both eyes.

[0042] Figure 2 The system operation flow of an embodiment of the system for automatically identifying the left and right eyes of a person detected by an ophthalmic device according to the present invention is shown. Figure 2 As shown, the following is a detailed description of each step in the system operation process.

[0043] Step 1: When the eyes of the examinee are placed at the detection position of the ophthalmic device, the left proximity sensor module 1 and the right proximity sensor module 2 read the sensor raw values.

[0044] Step 2: The left proximity sensor module 1 and the right proximity sensor module 2 each process the read sensor raw values ​​to obtain sensor effective values.

[0045] The specific processing of step 2 is as follows Figure 3 As shown, the following is a detailed description of step 2.

[0046] Step 2-1: Filter and reduce noise on the raw sensor values: Filter the signal noise in the raw sensor values ​​to reduce the impact of sensor background noise and environmental noise on the effective sensor value.

[0047] Sliding average filtering is usually used for noise reduction: if the number of input sampling points is N, assuming an 8-fold sliding average filter is used, the filtering principle is as follows: first, average the data of the first 8 cycles:

[0048] = ( X0 + X1 + X2 + X3 + X4 + X5 + X6 + X7) / 8

[0049] Represents the average value of group 0; X0 represents the 0th data sampled, and so on;

[0050] After 8 cycles, the sliding input of data is realized:

[0051] = ( 7 + X n ) / 8,i=1,2,3...N-8; N>8; n=i+7;

[0052] represents the mean value of group i; X n Indicates the nth data sampled; N represents the total number of sampling points.

[0053] The above formula shows that the smaller the sliding filter multiplier is, the worse the filtering effect is, but the better the real-time response to signal changes is; the larger the sliding filter multiplier is, the better the filtering effect is, but the real-time response to signal changes is worse. Optimally, a filter multiplier of 16 can be used.

[0054] Step 2-2: Perform weighted processing on specific targets in the application scenario, calculate the limit range, and obtain the sensor effective value based on the limit range.

[0055] Specific targets are divided into valid targets and invalid targets. Valid targets are enhanced with their effective values, while invalid targets are weakened. For example, in the application scenario of ophthalmology testing, valid targets include skin and masks, while invalid targets include hair and ambient light.

[0056] In this embodiment, the proximity sensor uses infrared light at a wavelength of 940nm, which is relatively bright in actual use scenarios. Overall, the sensor's readings do not fluctuate significantly, remaining relatively stable. However, to accommodate the varying conditions of different users, special processing has been implemented for each of the following situations.

[0057] 1. Skin effects:

[0058] The reflectivity of light-colored skin (such as yellow and white) is close to 50%.

[0059] Dark skin (such as black) may have a slightly lower reflectivity (about 30%-40%) due to the absorption of visible light by melanin, but lower absorption of near-infrared light.

[0060] 2. Impact of masks:

[0061] Blue medical mask: The blue outer layer is thinner, and 940nm infrared light can easily penetrate the surface to reach the white inner layer, resulting in a reflectivity of 40%-70%.

[0062] White N95 mask: Most masks are made of non-woven fabric, which has a strong scattering effect on 940nm infrared light and a reflectivity of 60%-80%.

[0063] In actual applications, the object detected by the sensor is either human skin or a mask, so only one of the above two situations will occur at a time. The overall reflectivity range is 30%-80%. Taking the majority of users as yellow people who do not wear masks as the data basis, superimposing the above 30%-80% data range, the dynamic range becomes [-20%, 30%] of the basic value. Assuming that the basic data is X0, the limit range is: [0.8X0, 1.3X0].

[0064] Based on the theoretical limits described above, extensive real-world testing has revealed that the practical limits are in the range [0.79 x 0, 1.28 x 0]. If the raw sensor value, after filtering and noise reduction, falls within this practical limit, it is considered the sensor's effective value.

[0065] After processing in steps 2-1 and 2-2, the sensor data becomes highly resistant to noise. Whether it's ambient light or non-target objects, the impact on the sensor's effective value is minimal, making the reported sensor value and subsequent judgment results more accurate. Furthermore, after processing in these steps, the proximity sensor converts analog values ​​into simple numerical values ​​and reports them to the upper-level application, allowing subsequent applications to quickly and easily determine the left or right eye of the subject, improving automation.

[0066] Step 3: The left proximity sensor module 1 and the right proximity sensor module 2 each report the sensor effective value to the upper layer application.

[0067] Step 4: The upper-layer application automatically determines whether the person is currently placing their left eye or right eye in the ophthalmic device detection position based on the sensor valid values ​​reported by the left proximity sensor module 1 and the right proximity sensor module 2.

[0068] Specifically, the upper layer application automatically identifies whether the detector is the left eye or the right eye based on the distance between the left proximity sensor module 1 and the right proximity sensor module 2 and the target object:

[0069] When the subject's left eye is positioned correctly, the right proximity sensor module 2 detects a target object (usually the tip of the nose) at a closer distance than the left proximity sensor module 1. The upper-layer application automatically recognizes that the subject is testing their left eye based on the data reported by the underlying sensors.

[0070] When the subject's right eye is positioned correctly, the left proximity sensor module 1 detects a target object (usually the tip of the nose) at a closer distance than the right proximity sensor module 2. The upper-layer application automatically recognizes that the subject is testing the right eye based on the data reported by the underlying sensors.

[0071] Although the above methods are illustrated and described as a series of acts for simplicity of explanation, it is to be understood and appreciated that these methods are not limited by the order of the acts, as some acts may occur in a different order and / or concurrently with other acts from those illustrated and described herein or not illustrated and described herein but understandable to those skilled in the art according to one or more embodiments.

[0072] Those skilled in the art will further appreciate that the various illustrative logic blocks, modules, circuits, and algorithmic steps described in conjunction with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or a combination of the two. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps are generally described above in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. A skilled person may implement the described functionality in different ways for each specific application, but such implementation decisions should not be interpreted as resulting in a departure from the scope of the present invention.

[0073] The various illustrative logic blocks, modules, and circuits described in conjunction with the embodiments disclosed herein may be implemented or executed using a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

[0074] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor so that the processor can read and write information from / to the storage medium. In an alternative, the storage medium may be integrated into the processor. The processor and storage medium may reside in an ASIC. The ASIC may reside in a detector terminal. In an alternative, the processor and storage medium may reside in a detector terminal as discrete components.

[0075] In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functions may be stored on or transmitted via a computer-readable medium as one or more instructions or code. Computer-readable media includes both computer storage media and communication media, including any medium that facilitates the transfer of a computer program from one location to another. A storage medium may be any available medium that can be accessed by a computer. By way of example and not limitation, such computer-readable media may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Any connection is also properly referred to as a computer-readable medium. For example, if software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. As used herein, disk and disc include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc, where disks typically reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0076] The previous description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be apparent to those skilled in the art, and the general principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the disclosure is not intended to be limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A system for automatically identifying the left and right eyes of an examiner, applied to ophthalmic equipment, characterized in that: The left proximity sensor module and the right proximity sensor module include an upper-layer application. The left proximity sensor module and the right proximity sensor module are arranged on the left and right sides of the detection position of the ophthalmic device, wherein: The left proximity sensor module and the right proximity sensor module are used to read the sensor raw value when the examinee's eyes are placed in the detection position of the ophthalmic equipment, and each module processes the read sensor raw value to obtain the sensor valid value and reports it to the upper layer application; The upper-layer application automatically determines whether the examinee's current eye is the left eye or the right eye placed in the ophthalmic device's detection position based on the sensor valid values ​​reported by the left proximity sensor module and the right proximity sensor module.

2. The system for automatically identifying the left and right eyes of an examiner applied to ophthalmic equipment according to claim 1, characterized in that: A filter is respectively provided on the left proximity sensor module and the right proximity sensor module.

3. The system for automatically identifying the left and right eyes of a person being examined in ophthalmic equipment according to claim 1, characterized in that: The left proximity sensor module and the right proximity sensor module convert the read sensor raw values ​​into sensor effective values ​​in the following process: Filter and reduce noise on the original sensor value; Perform weighted processing on specific targets, calculate the limit range, and obtain the sensor effective value based on the limit range.

4. The system for automatically identifying the left and right eyes of an examiner applied to ophthalmic equipment according to claim 3, characterized in that: The filtering and noise reduction process uses a sliding average filter.

5. The system for automatically identifying the left and right eyes of a person being examined according to claim 4, wherein: The filtering multiple of the sliding average filter is 16 times.

6. The system for automatically identifying the left and right eyes of a person being examined according to claim 3, wherein: Specific targets are divided into valid targets and invalid targets. Weighted processing is to directional enhance the effective value of valid targets and weaken the invalid targets.

7. The system for automatically identifying the left and right eyes of an examiner applied to ophthalmic equipment according to claim 1, characterized in that: The upper layer application automatically identifies whether the detector is the left eye or the right eye based on the distance between the left proximity sensor module and the right proximity sensor module. When the examinee's left eye is positioned correctly, the right proximity sensor module detects a target at a closer distance than the left proximity sensor module. The upper-layer application automatically identifies that the examinee is testing the left eye based on the data reported by the underlying sensor. When the examinee's right eye is correctly positioned, the left proximity sensor module detects a target at a closer distance than the right proximity sensor module. The upper-layer application automatically identifies that the examinee is testing the right eye based on the data reported by the underlying sensor.

Images