A System for Assessing Neurological Functions Using Digital Markers Derived from Keyboard Interactions

Abstract

The invention is a neurological function assessment system that processes user interaction with keys not only through timing but also integrating physical pressure force and content analysis to detect impairments in neurological functions.

Description

1 TARIFF Neurological Detection with Digital Tokens Derived from Keyboard Interactions Functions Assessment System TECHNICAL FIELD The invention relates to neurological methods using digital tokens derived from keyboard interactions in general. It is related to the functions evaluation system. The invention specifically utilizes the force it receives from keys that have integrated pressure sensors. By analyzing the data, it creates a user's muscle control and finger strength profile. Errors such as missing keystrokes, duplicate characters, or characters entered in the wrong order. a keyboard that automatically detects and classifies interaction types By analyzing the digital tokens obtained from their interactions using time metrics, it provides a detailed analysis. 15 neurological that detects motor control differences and neurological disorders It is related to the functions evaluation system. STATE OF THE ART Individuals' motor and neurological development can be assessed through the dynamics of using elements such as keyboards. Digital markers that analyze health are used as passive monitoring in modern medicine. This is one of the most important pillars of the revolution called [name of revolution]. These systems allow the user By detecting changes in micro-movements that the individual is not even aware of, neurological... It plays a critical role in the early diagnosis of diseases. 25 Current technology uses time-based metrics to monitor neurological functions. Analyses can be performed based on this. For example, when one button is released and another is pressed... By analyzing the time elapsed or the length of time a key has been held down, conditions like Parkinson's disease can be diagnosed. Diseases can be detected. However, only time-based (temporal) metrics are available. 30 Analyses conducted on this subject measure only one "output" of the neurological condition, while It can miss the depth of the complex neuromotor mechanism that produces the output. "The button The "push-and-release" measurement is just the tip of the iceberg. The nature of motor control... 2 Understanding is a multidimensional process that combines time, force, kinematics, and linguistic context. This is possible with (multimodal) data analysis. Based on research conducted under the known state of the art, US20150272504A1 Application number [number] was encountered. This application is from a user requesting a standard 5. By analyzing their interactions with the computer keyboard, Parkinson's, Alzheimer's or It is designed for the early diagnosis and monitoring of neurological diseases such as Huntington's. It describes the system. The patent application in question describes standard equipment. It aims to reach a wide audience through this platform. Therefore, physical It lacks advanced data layers that measure the depth of interaction. For example, 10 keys a sensor that can analyze applied physical pressure and force data It does not have integration. Also, when your finger moves from one key to another... a device that will track its trajectory in the air, its movements such as acceleration and deceleration It does not incorporate image processing or deep sensor mechanisms. The system, External factors such as the user's current emotional state or cognitive load affect motor 15 a multimodal approach that will isolate the "noise" effect on performance Instead of presenting an analytical framework, it focuses largely on temporal statistics. It remains limited to superficial modeling. In conclusion, improvements in neurological function assessment systems are needed. This is being done to eliminate the disadvantages mentioned above and New structures are needed to provide solutions to the existing systems. THE PURPOSE OF THE INVENTION The present invention meets the aforementioned requirements and overcomes all the disadvantages. neurological functions that eliminate and bring some additional advantages It is related to the evaluation system. The main purpose of the invention is to receive 30 signals from buttons with integrated pressure sensors. By analyzing force data, the user's muscle control and finger strength profile can be determined. errors, missing keystrokes, duplicate characters, or characters entered in the wrong order It automatically detects and classifies types of erroneous interactions, such as those found on the keyboard. It analyzes the digital tokens it obtains from these interactions using time metrics. 3 neurological that detects motor control differences and neurological disorders Its function is to provide an evaluation system. One aim of the invention is to expand the range of data obtained from keyboard interactions. The aim is to offer an analytical approach that goes beyond time-based metrics. 5 Another purpose of the invention is to detect force from buttons with integrated pressure sensors. By analyzing the data, the user's muscle control and finger strength profile to remove. Another purpose of the invention is to correct missing keystrokes, duplicate character formation, and characters in the wrong order. The goal is to enable the automatic detection and classification of events such as unauthorized entry. Another aim of the invention is to create new digital tokens along with time-based metrics. By analyzing the user's motor control skills, a multidimensional 15 The goal is to enable modeling. Another aim of the invention is to obtain multidimensional data through the developed algorithms. The dataset can be used for various purposes such as early detection of neurological disorders and monitoring motor performance. The goal is to make it available for use in applications. 20 The structural and characteristic features and all the advantages of the invention are given in the figures below. And thanks to the detailed explanation written with references to these figures, it becomes clearer. This will be understood as such. Therefore, the evaluation should also be based on these forms and details. This should be done taking the explanation into consideration. 25 BRIEF DESCRIPTION OF THE FIGURES The best way to utilize the advantages of the existing invention, together with its structure and additional elements. For understanding, it should be evaluated together with the figures explained below. It is necessary. 30 Figure 1 Block diagram of the neurological function assessment system that is the subject of the invention. It is the appearance. 4 REFERENCE NUMBERS 1. Keyboard 2. Matching module 3. Error detection module 5 4. Text analysis module 5. Analysis engine DETAILED EXPLANATION OF THE INVENTION This detailed explanation describes the invention's assessment of neurological functions. The preferred structures of the system contribute not only to a better understanding of the subject. This is explained in a way that is geared towards and does not create any limiting effects. The invention, whose block diagram view is given in Figure 1, integrates pressure sensors into 15 By analyzing the force data received from the pressed keys, it determines the user's muscle control and The finger force profile reveals missed presses, double character formation, or incorrect presses. automatically detects types of erroneous interactions, such as entering characters in a queue. classifying, the digital tokens obtained from keyboard (1) interactions over time By analyzing metrics, differences in fine motor control and neurological disorders can be identified. 20 It is a neurological function assessment system that detects. Keyboard (1) by expanding the range of data obtained from their interactions, time-based metrics It aims to offer an analytical approach that goes beyond simply allowing users to interact with keys. the interaction is based not only on timing but also on physical pressure force and content. By working in conjunction with analysis, it detects impairments in neurological functions. 25 in order to ensure that;  Each key has at least one pressure sensor underneath it, and the pressure sensors at least collects data on the force applied by the user to the keys via a keyboard (1),  The analysis 30 receives and analyzes the data collected by the mentioned keyboard (1). As a result, the pressure data applied to the keys and the pressure recorded in the system. By aligning the sensor samples to the same time axis, each key event corresponds to the relevant at least one matching module that matches the pressure waveform (2),  The paired pressure wave obtained by the mentioned matching module (2) By analyzing their forms, pressure increase, underpressure, double character formation and at least one fault detection module that detects similar fault conditions (3),  By analyzing the stream of characters entered into the keyboard (1), such as letter order irregularities at least one text analysis module that detects serial text errors (4), 5  Keyboard (1), matching module (2), error detection module (3) and text analysis taking and combining the data obtained by the module (4) and from the combined data by generating digital tokens, the engine uses its included artificial intelligence modules. At least one analysis that generates a control disorder score and alerts the user. engine (5) 10 It includes. The invention concerns a neurological function assessment system and its included analysis engine. (5) thanks to the key interactions on the keyboard (1) multidimensional digital markers by generating and analyzing data, the user controls the motor 15 It provides detailed information about their skills. The invention concerns a keyboard (1) in a neurological function assessment system, each Through micro pressure sensors placed under the keys, pressure is applied to the keys. By collecting force and pressure data, it creates a real-time pressure profile for the user. It measures whether the key has been pressed or not. Data obtained with the keyboard (1) only shows whether the key has been pressed or not. not, but the magnitude of the applied force, the rate of change, and the waveform over time. It also includes the form. The obtained pressure data is processed by the matching module (2), Keyboard functions such as pressing, releasing, and repeated presses are controlled via the operating system it contains. (1) are synchronized with the events on the same time axis. Thus, each physical 25 Sensor data is precisely correlated with its corresponding key event. Matching data set synchronized by module (2), error detection module (3) It is analyzed. For example, when sensor data shows an increase in pressure, the operating system If the keystroke event did not occur on that side, it is detected as a missed press. Similarly In this way, sensor data shows rebound or double peak patterns in the pressure waveform, 30 These are classified as duplicate character occurrences or ghosting situations. Error detection In parallel with the error classification process carried out in module (3), the text The character string entered by the user is analyzed by the analysis module (4), letter It identifies errors such as sequence disruptions. This analysis is independent of time-based events. 6 by examining the organization of the input content, hand coordination and sequence It provides information about planning skills. Keyboard (1), matching module (2), error raw data and detection obtained by the detection module (3) and text analysis module (4) The type of error data obtained is received by an analysis engine (5). The analysis engine (5), By combining time-based metrics and sequential error data, rich digital tokens 5 It produces these markers. These markers can be analyzed using statistical methods or machine learning, such as artificial intelligence. The user's motor control performance is quantitatively analyzed using algorithms. Scores representing neurological disorders or fine motor skills are calculated. to generate alerts for the early diagnosis of anomalies in their skills Available. 10 The system described in the invention differs, in particular, from the timing-based approaches currently employed in technology. In contrast to indirect inferences based on micro pressure sensors integrated into the keyboard (1) By directly measuring the finger force profile and pressure waveform, it allows the muscle It creates a tangible physical data layer on its control. Matching 15 synchronize module (2) physical sensor data with operating system events, The fault detection module (3) detects vibration-related errors via double peak patterns. Distinguishing it from mechanical failures goes beyond the superficial time analyses of current techniques. It provides a diagnostic accuracy that has been passed. In addition, the text analysis module (4) through the examination of character sequencing, motor retardation and cognitive planning 20 It allows for a clear differentiation between the disorders. All By combining these multidimensional data, the analysis engine (5) creates rich digital Converting these into markers, quantitative scores for preclinical diagnosis of neurological anomalies. by enabling its detection, unlike traditional methods that rely solely on time metrics. Much more accurate early diagnosis and engine performance monitoring compared to other systems 25 It offers the opportunity.

Claims

7 REQUESTS 1. User interaction with the keys should be based not only on timing but also on physical interaction. By processing pressure force and content analysis in an integrated manner, neurological neurological functions that enable the detection of impairments in functions 5 It is an evaluation system; its characteristic feature is:  Each key has at least one pressure sensor underneath it, and pressure via sensors, data of the force applied by the user to the keys collecting at least one keyboard (1),  The analysis 10 receives and analyzes the data collected by the mentioned keyboard (1). As a result, the pressure data applied to the keys and the pressure recorded in the system. By aligning the sensor samples to the same time axis, each key event corresponds to the relevant at least one matching module that matches the pressure waveform (2),  The paired pressure obtained by the mentioned matching module (2) By analyzing waveforms, pressure increase, underpressure, and double character 15 detecting at least one error that identifies the occurrence of and similar error conditions. module (3),  By analyzing the stream of characters entered into the keyboard (1), the letter order at least one text that detects serial text errors such as corruptions analysis module (4), 20  Keyboard (1), matching module (2), error detection module (3) and text analysis taking and combining the data obtained by the module (4) and combining it by generating digital tokens from data, the artificial intelligence modules it contains through which a motor control disorder score is generated and the user stimulus at least one analysis engine (5) 25 It includes.

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