WEARABLE SENSOR-BASED CLOSED-LOOP GLAUCOMA MONITORING AND VIRTUAL REALITY CONTENT ADAPTATION SYSTEM

Abstract

The invention relates to a wearable sensor-based closed-loop glaucoma monitoring and virtual reality content adaptation system. The system includes a wearable sensor module (1), eye movement tracking sensor (2), head position sensor (3), visual performance measurement unit (4), virtual reality headset (5), central processing unit (6), wireless communication module (7), artificial intelligence analysis module (8), dynamic risk model generator (9), and automatic exercise adaptation unit (10). Data on eye movements, head position, and visual performance are combined in the central processing unit (6) and transmitted via the wireless communication module (7) to the artificial intelligence analysis module (8). The dynamic risk model generator (9) within the artificial intelligence analysis module (8) processes this data and generates a user-specific glaucoma progression risk score.The glaucoma progression risk score is transferred to the automated exercise adaptation unit (10), and at least one of the difficulty level, visual contrast, and target locations of the peripheral vision-focused task content (11) is restructured based on this risk score. The restructured peripheral vision-focused task content (11) is transferred to the virtual reality headset (5); current eye movement, head position, and visual performance data related to these task contents are retrieved and transferred back to the artificial intelligence analysis module (8) via the central processing unit (6) and the wireless communication module (7).

Description

1 TARIFF WEARABLE SENSOR-BASED CLOSED-LOOP GLAUCOMA MONITORING AND VIRTUAL REALITY CONTENT ADAPTATION SYSTEM TECHNICAL AREA 5 The invention relates to digital health systems, wearable sensor technologies, and virtual reality. technology-based visual applications and AI-powered data processing systems It is related to their fields. The invention specifically targets a user's eye movements, head position, and visual cues. data regarding its performance is obtained through wearable sensors, said 10 the subject is the integration of data into a centralized processing structure based on artificial intelligence. virtual reality is processed in the analysis structure and depends on the data output obtained. closed-loop feedback structure of visual task content presented in the environment a glaucoma monitoring and virtual system in which it is automatically reconfigured. The reality relates to the content adaptation system. 15 STATE OF THE ART In known technical applications for monitoring glaucoma, intraocular pressure is measured. data regarding the visual field and optic nerve structure are obtained at specific time intervals. It is common to evaluate patients by doing so. In addition, remote patient monitoring 20 systems, wearable sensors, machine learning-based risk assessment systems and visual applications carried out in a virtual reality environment In the current state of the art, these exist as separate technical solutions. WO2021258004A1 publication number, included in the known state of the art. The document states that remote monitoring of intraocular pressure data obtained in a home environment is permitted. A system for this purpose is being described. In this system, home-based intraocular pressure (IOP) testing is performed. Data obtained from the measuring device together with additional clinical information about the user. It is being evaluated and is a patient health indicator related to eye health. is being generated. The generated indicator is transmitted to the healthcare professional remotely. It is used in the monitoring process. 30 WO2022173872A1 publication number, included in the known state of the art. The document includes health data obtained from clinical visits and remote patient monitoring. based on the evaluation of data using artificial intelligence and machine learning techniques 2 A digital therapeutic platform is being described. On this platform, the results obtained... By processing health data, disease patterns are identified, and these patterns are used... It is used in generating personalized recommendations. Systems in known technology provide clinically or remotely obtained information about the patient. 5 includes solutions for monitoring, processing and evaluating data. together; regarding the user's eye movements, head position and visual performance The continuous acquisition of functional data from a wearable sensor structure, The subject data is processed by a dynamic risk model generator and customized for the user. converting it into a glaucoma progression risk score and the resulting risk score 10 visual task contents presented in a virtual reality environment within the same system closed systems that perform feedback processes on their technical parameters together. There is no technical structure for the loop. Specifically, content used in virtual reality-based visual applications. They are usually offered with fixed or predefined parameters. This in structures, with the user's real-time functional data in a virtual reality environment 15 a continuously functioning feedback link between the visual task content presented not available; current data obtained from sensors makes the task content difficult. real technical parameters such as level, visual contrast and target locations There is no closed-loop adaptation structure that is reflected in a timely manner. THE TECHNICAL PROBLEM THAT IS INTENDED TO BE SOLVED The fundamental technical problem that the invention aims to solve is the user's eye. functional data relating to movements, head position and visual performance the continuous acquisition of the data created as a result of processing that data Technical aspects of visual task content presented in a virtual reality environment as data output. 25 real-time feedback to its parameters and these processes are carried out within the same system. an integrated and closed-loop data processing architecture that enables its execution. Its structure is not found in known techniques. In current technical infrastructures, user data is mostly collected at specific times. obtained from measurement sources at intervals or independently of each other; word 30 the subject is virtual reality, the data output created as a result of data processing. The difficulty level, visual contrast, and of the visual task content presented in the environment 3 continuous and automatic reflection of technical parameters such as target locations There is no integrated adaptation mechanism that provides this. Another related technical problem is the data obtained from wearable sensors. Eye movement, head position, and visual performance data are all part of the same data processing chain. By combining them, a user-specific glaucoma progression risk score of 5 transformation and the said risk score presented in the virtual reality heading (5) in the restructuring of the technical parameters of visual task content a real-time feedback architecture that enables its use in the known technique It is the absence of it. The invention also enables the acquisition of sensor data and the central processing of that data. 10 integrating in the processing unit (6), artificial intelligence via wireless communication module (7) Transfer to the analysis module (8) by the dynamic risk model generator (9) creation of a user-specific glaucoma progression risk score and assessment of that risk by transferring the score to the automatic exercise adaptation unit (10) virtual reality The technical parameters of the visual task content presented in the environment have been revised to 15. its use in structuring processes within a single system architecture The aim is to integrate them. The technical problem that is intended to be solved within this scope is related to the user's current situation. functional data is continuously obtained, and said data is processed. The resulting glaucoma progression risk score is 20 in a virtual reality environment. Technical parameters of the presented visual task content should be revised. used in its structuring and related to the restructured task contents. By re-entering the current user data into the system, it returns to the same data processing cycle. It is the creation of an integrated closed-loop system structure from which it is fed. A BRIEF DESCRIPTION OF THE INVENTION The invention involves the continuous acquisition of functional data belonging to the user, verbally. the subject is virtual reality, the data output created as a result of data processing. Technical parameters of visual task content presented in the environment are being revised. A closed-loop glaucoma monitoring and virtual reality system used in its configuration 30 It relates to the content adaptation system. 4 Within the scope of the invention, the user's eye movements, head position, and visual Data regarding its performance is obtained through the wearable sensor structure, and the word The data in question is transferred to a processing and analysis structure. The obtained data... The processing results in a user-specific glaucoma progression risk score. is being generated and the score in question is based on visual task 5 presented in a virtual reality environment. data used in restructuring the technical parameters of their content It produces the output. The system processes current functional data obtained from the user. The resulting glaucoma progression risk score is then simulated in a virtual reality environment. The technical parameters of the visual task content presented have been revised to 10. used in its structuring and related to the restructured task contents. a closed-loop system where current user data is reintroduced into the data processing chain It has a structure. In this context, the difficulty level of the visual task content, visual contrast and at least one of the target locations depends on the risk score in question. It is being restructured. 15 The invention also analyzes sensor data generated by the system, and glaucoma progression. risk scores and data on user interaction with visual task content It includes a remote monitoring panel for viewing. DESCRIPTION OF THE FIGURES 20 Figure 1: Wearable virtual reality headset (5) and the physical within the headset It is a schematic view of the components. Figure 2: Wearable sensor-based closed-loop glaucoma monitoring and virtual reality. This is a schematic view of the overall architecture of the content adaptation system. Figure 3: Artificial intelligence analysis module (8), dynamic risk model generator (9), automatic 25 exercise adaptation unit (10), peripheral vision focused task content (11) and virtual This is a schematic view of the closed-loop data flow between the reality heading (5). Figure 4: Schematic of the deterioration warning system (13) with remote monitoring panel (12). It is the appearance. Explanations of the reference numbers in the figures; 1. Wearable sensor module 2. Eye movement tracking sensor 3. Head position sensor 4. Visual performance measurement unit 5. Virtual reality (VR) headset 6. Central Processing Unit 5 7. Wireless communication module 8. Artificial intelligence analysis module 9. Dynamic risk model generator 10. Automatic exercise adaptation unit 11. Task content focused on peripheral vision 10 12. Remote monitoring panel 13. Deterioration warning system DETAILED DESCRIPTION OF THE INVENTION The invention is based on 15 user eye movements, head position and visual performance. The data in question was obtained through a wearable device, and that this data... processing results in a user-specific glaucoma progression risk score. created and this risk score is applied to the visual task presented in the virtual reality environment. closed systems used in the restructuring of the technical parameters of their content The loop relates to a glaucoma monitoring and virtual reality content adaptation system. 20 The invention describes a system consisting of a wearable sensor module (1), eye movement tracking. sensor (2), head position sensor (3), visual performance measurement unit (4), virtual reality headset (5), central processing unit (6), wireless communication module (7), artificial intelligence analysis module (8), dynamic risk model generator (9), automated exercise adaptation unit (10), peripheral vision focused task content (11), remote monitoring 25 It includes the control panel (12) and the deterioration warning system (13). Figure 1 shows the virtual representation of the physical components of the system that are carried by the user. The layout within the reality heading (5) is shown schematically. The virtual reality headset (5) has a body that can be worn on the user's head. wearable sensor module (1), eye movement tracking sensor (2), head 30 position sensor (3), central processing unit (6) and wireless communication module (7) includes. 6 Wearable sensor module (1) located inside virtual reality headset (5) and obtaining physical, behavioral and functional data relating to the user It is a hardware structure that includes the sensor components used. The eye movement tracking sensor (2) is integrated into the wearable sensor module (1) and On the inner surface of the virtual reality headset (5), there are 5 corresponding to the user's eyes. is located in the region. The eye movement tracking sensor (2) tracks the user's eye It collects data on movements, gaze direction, and focal points. In one application, the eye movement tracking sensor (2) of the virtual reality headset (5) are positioned around the right and left lens frames. The head position sensor (3) detects the user's head movements and the angular movement of the head. It obtains data regarding its position. Head position sensor (3), gyroscope, It includes at least one of the following: an accelerometer or an inertial measurement unit. In one application, the head position sensor (3) is placed in front of the virtual reality headset (5) It is located on the printed circuit board inside the header panel. Central processing unit (6), eye movement tracking sensor (2), head position 15 data obtained from the sensor (3) and the visual performance measurement unit (4) and the processor that combines that data in the data processing chain within the system. or includes microcontroller hardware. Wireless communication module (7), wearable sensor module (1), central processing Data between unit (6), artificial intelligence analysis module (8) and remote monitoring panel (12) 20 It is communication equipment that transmits information wirelessly. Wireless communication module (7) transmits the data in question in real time and encrypted. It is configured to perform this task and is Wi-Fi or Bluetooth based. It is able to provide communication. Central processing unit (6) and wireless communication module (7), virtual reality 25 on at least one of the (5) rear headband or side temple sections of the head It can be positioned. Visual performance measurement unit (4), user's virtual reality headset (5) the responses given during visual tasks presented via the medium and visual stimuli obtaining data on response times and storing that data as digital data 30 It is the unit that transforms it. 7 Figure 2 shows the subject of the invention: closed-loop glaucoma monitoring and virtual reality content. The overall architecture of the adaptation system is shown schematically. Eye movements from the tracking sensor (2), head position sensor (3) and visual performance measurement unit (4) The data obtained is transferred to the central processing unit (6). Central processing unit (6) combines the data that it receives and combines the data 5 from wireless communication module (7) to artificial intelligence analysis module (8) It transmits. Artificial intelligence analysis module (8), via wireless communication module (7) regarding the eye movements, head position and visual performance conveyed to him It includes the analysis structure that processes the data. Artificial intelligence analysis module (8), local 10 It can be run on processing infrastructure or cloud-based processing infrastructure. Dynamic risk model generator (9) within the artificial intelligence analysis module (8) The dynamic risk model generator (9) uses the user's eye movements, head By processing up-to-date data regarding position and visual performance, it provides user-specific solutions. It creates a glaucoma progression risk score. 15 Glaucoma progression risk score, by dynamic risk model generator (9) numerical data generated and transferred to the automatic exercise adaptation unit (10) It produces the output. Automatic exercise adaptation unit (10), from dynamic risk model generator (9) received the glaucoma progression risk score and the feedback data from the system 20 the peripheral vision focused task presented via the working and virtual reality headset (5) It is the data processing unit that reconstructs the technical parameters of its contents (11). Peripheral vision focused task content (11) via virtual reality headset (5) It consists of visual tasks presented to the user. In Figure 3, the artificial intelligence analysis module (8) and the virtual reality headset (5) 25 The closed-loop data flow between them is shown schematically. Wireless communication Eye movements, head movements transferred from module (7) to the artificial intelligence analysis module (8) Current data on position and visual performance, dynamic risk model User-specific glaucoma progression risk score processed by generator (9) is being created. 30 The generated glaucoma progression risk score is automatically adapted to exercise management. It is transferred to the unit (10). The automatic exercise adaptation unit (10) is the said unit (10). 8 difficulty of peripheral vision focused task content (11) depending on risk score level, visual contrast and at least one of the target locations re-evaluated It is structuring. Reconfigured by the automatic exercise adaptation unit (10) Peripheral vision focused task content (11), virtual reality headset (5) 5 is presented to the user. The user’s restructured task contents (11) eye movement, head position, and visual performance in relation to current responses data from the eye movement tracking sensor (2), head position sensor (3) and visual is obtained again through the performance measurement unit (4). The aforementioned updated data, which was recovered, is in the central processing unit (6) 10 combined with the wireless communication module (7) to the artificial intelligence analysis module (8) is transferred again and re-transmitted by the dynamic risk model generator (9) This process involves obtaining sensor data and assessing the risk of glaucoma progression. the creation of the score, the technical content of the peripheral vision focused tasks (11) Parameter restructuring and restructured task 15 re-integration of updated user data regarding their content into the data processing chain. A closed-loop feedback structure consisting of these processes is created. Glaucoma progression generated by dynamic risk model generator (9) The risk score is transferred as data input to the automatic exercise adaptation unit (10). and depending on the data input in question, 20 through the virtual reality headset (5) Technical parameters of the presented peripheral vision focused task content (11) were revised It is being structured. Figure 4 schematically shows the remote monitoring panel (12) of the system. The physician who monitors the patient's rehabilitation process at home or in the clinic, and Remote monitoring panel (clinical terminal) (12) accessible to nurses User 25 The screen layout of the interface is schematically represented. The main body of the screen is formed by... On the panel, historical risk scores from the AI ​​analysis module (8), sensor data graphs and the patient's daily participation in the rehabilitation program. Percentages are being tracked. The most critical part of the interface is the dynamic risk model. A sudden deviation, progression acceleration or critical 30 in the data from the generator (9) a system that activates when a visual field loss is detected and alerts healthcare professionals The deterioration warning system (13) is positioned with visual / auditory signals. 9 In this way, the clinical team can immediately notice any deterioration in the patient's condition and intervene early. They can create an intervention plan. Deterioration warning system (13) on the remote monitoring panel (12) The deterioration warning system (13) is located in the dynamic risk model generator (9). sudden negative changes identified in the obtained data or the user's peripheral 5 based on inconsistency data regarding interaction with visually focused task content (11) It is configured to generate visual and / or auditory warning output. The system described in the invention monitors user eye movement, head position, and visual information. performance data is obtained through wearable sensors, data is processed and converted into a user-specific glaucoma progression risk score, 10 the risk score created is presented via the virtual reality headset (5) technical parameters of visually focused task content (11) revision used in its structuring and related to the restructured task contents. an integrated closed system where current user data is reintroduced into the data processing chain. It has a loop data processing architecture. 15 In a sample application of the invention, the user wears a virtual reality headset (5) one of the task contents (11) that is placed at the beginning and focused on peripheral vision is virtual reality is presented to the user via the title (5). During the task content, the eye movement tracking sensor (2), head position 20 by the sensor (3) and visual performance measurement unit (4) relating to the user Current functional data is obtained. This data is provided by the central processing unit. (6) and the artificial intelligence analysis module (8) via the wireless communication module (7) is transferred and user-specific by the dynamic risk model generator (9) A glaucoma progression risk score is created. Based on the glaucoma progression risk score created, automated exercise 25 The adaptation unit (10) presents the user with a peripheral vision focused task. (11) revise the visual contrast, target location and / or difficulty level of the content. It is structuring. User feedback regarding the restructured task content has resurfaced. The same data is obtained via sensors and visual performance measurement unit (4) 30 It is being re-entered into the processing cycle. Glaucoma progression risk scores and sensors generated during the procedure. data can be viewed on the remote monitoring panel (12); dynamic risk model sudden negative changes in the data obtained from the generator (9) or task contents Deterioration warning system (13) in case of identification of incompatibility regarding interaction Visual and / or auditory warning outputs can be generated by this. 5 15 25

Claims

11 REQUESTS 1. Wearable sensor module (1), eye movement tracking sensor (2), head position sensor (3), visual performance measurement unit (4), virtual reality headset (5), central processing unit (6), wireless communication module (7), artificial intelligence analysis 5 module (8), dynamic risk model generator (9) and automatic exercise adaptation wearable sensor-based closed-loop glaucoma monitoring unit (10) and It is a virtual reality content adaptation system; its feature is: - The eye movement tracking sensor (2) tracks the user's eye movements, gaze 10 in order to obtain data regarding direction and focal points having a wearable sensor module (1) within it, - head position sensor (3), the user's head movements and angular wearable sensor module (1) to obtain data on its location being within its structure, - visual performance measurement unit (4), virtual reality headset (5) 15 user reactions and responses to visual stimuli presented through the platform structuring the delivery times in a way that will convert them into digital data, - central processing unit (6), eye movement tracking sensor (2), head from the position sensor (3) and the visual performance measurement unit (4) 20 - wireless communication module (7) combined in the central processing unit (6) transferring the data to the artificial intelligence analysis module (8) structuring, - The artificial intelligence analysis module (8) processes the data in question using dynamic risk including the model generator (9), 25 - dynamic risk model generator (9), eye movements, head position and By processing data related to visual performance, user-specific glaucoma solutions are developed. structuring it in a way that will generate a progression risk score, - Dynamic risk model of the automatic exercise adaptation unit (10) 30 based on the glaucoma progression risk score received from the creator (9) Peripheral vision focused presentation via virtual reality headset (5) 12 difficulty level, visual contrast and target of task contents (11) by restructuring at least one of their locations structuring, - Peripheral reconfigured by the automatic exercise adaptation unit (10) visually focused task content (11) virtual reality headset (5) 5 eye movement tracking sensor (2), head position sensor with transmission (3) and the outputs of the visual performance measurement unit (4) are central processing transfer from unit (6) to artificial intelligence analysis module (8) closed-loop feedback structure of data communication links providing It is the creation of. 10 2. The system is as per claim 1 and its feature is; the virtual reality headset (5), wearable sensor module (1), central processing unit (6) and wireless communication It contains module (7).

3. The system according to claim 2, and its feature is the eye movement tracking sensor (2), On the inner surface of the virtual reality headset (5), the right and left lens frames 15 It is positioned around it.

4. The system according to claim 2, and its features are; head position sensor (3), gyroscope, It must include at least one of the following: an accelerometer or an inertial measurement unit, and be virtual. Printed circuit board located inside the front panel of the reality headset (5) It is positioned on it. 20 5. The system according to claim 2, and its features are; central processing unit (6) and wireless communication module (7), virtual reality headset (5) rear headband or It is located in at least one of the lateral temple areas.

6. The system is according to claim 1 and its feature is; wireless communication module (7), Wi-Fi or it must include at least one of the Bluetooth communication interfaces and the central 25 Wireless data between the processing unit (6) and the artificial intelligence analysis module (8) It is the existence of a communication link.

7. The system is according to claim 1 and its feature is; the remote monitoring panel (12), wireless being in data communication link with communication module (7) and artificial intelligence Historical glaucoma progression risk scores obtained from the analysis module (8), 30 Sensor data obtained from the wearable sensor module (1) and the user 13 data on its interaction with peripheral vision-focused task content (11) It has a visualization and data presentation structure.

8. The system is in accordance with Request 7 and its feature is; on the remote monitoring panel (12) the presence of a deterioration warning system (13) and the deterioration warning system (13), sudden negative 5 in the data obtained from the dynamic risk model generator (9). Data regarding changes in the user's peripheral vision-focused task incompatibility data regarding interaction with the content (11) and visual and / or It includes auditory stimulus output.

9. Wearable sensor-based closed-loop data processing and virtual reality content. It is an adaptation method, and its characteristic is; 10 - Eye movements, gaze direction and eye movement tracking sensor (2) Obtaining data regarding focal points, - Head movement and angular position with head position sensor (3) data acquisition, - Visual performance measurement unit (4) and virtual reality headset (5) 15 User reactions and responses to visual stimuli presented through the platform. digitizing delivery times, - from the eye movement tracking sensor (2), from the head position sensor (3) and central data obtained from the visual performance measurement unit (4) combining in the processing unit (6), 20 - Wireless communication module of the data combined in the central processing unit (6) Transfer from (7) to the artificial intelligence analysis module (8), - dynamics within the artificial intelligence analysis module (8) of the data in question glaucoma risk model generator (9) is processed by user-specific glaucoma Generating a progression risk score as a numerical data output, 25 - glaucoma progression risk score to the automated exercise adaptation unit (10) transfer as data input,  The difficulty level of the peripheral vision-focused task content (11), visual contrast and at least one of the target locations in automated exercise The risk of glaucoma progression is 30 by the adaptation unit (10). restructuring based on the score, - restructured peripheral vision-focused task content (11) transfer to virtual reality headset (5), 14 - Regarding the restructured peripheral vision-focused task content (11) current eye movement, head position and visual performance data of the eye motion tracking sensor (2), head position sensor (3) and visual re-obtained via performance measurement unit (4) - The newly received updated data is combined in the central processing unit (6) 5 from wireless communication module (7) to artificial intelligence analysis module (8) It includes the stages of retransfer. 15 25

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