Method and system for attention training

Abstract

The present invention relates to attention training systems and methods, particularly for treating individuals with Attention-Deficit / Hyperactivity Disorder (ADHD). Specifically, the present invention is related to employing biofeedback and virtual reality technologies to enhance gaze control and attention measures. The claimed invention represents a system and method for attention training that improve the relevant technological field by providing and utilizing a highly informative real-time biofeedback reliably representing the user's ability to sustain attention.

Description

YEDA-P-058-PCTMETHOD AND SYSTEM FOR ATTENTION TRAININGCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of priority of U.S. Provisional Patent Application No. 63 / 695,947, filed September 18, 2024, the contents of which are all incorporated herein by reference in their entirety.FIELD OF THE INVENTION

[0002] The present invention relates to attention training systems and methods, particularly for treating individuals with Attention-Deficit / Hyperactivity Disorder (ADHD). Specifically, the present invention is related to employing biofeedback and virtual reality technologies to enhance gaze control and attention measures.BACKGROUND OF THE INVENTION

[0003] As known, individuals with attention-deficit-related conditions (e.g., Attention- Deficit / Hyperactivity Disorder (ADHD)) commonly exhibit difficulties with response inhibition, which manifest as scattered thinking, motor restlessness, and distinct patterns in how they visually scan their environment. These challenges are often accompanied by an inability to suppress eye blinks and micro saccades, leading to a broader and less focused distribution of gaze. Such erratic visual scanning behavior is a hallmark of ADHD and can significantly impair an individual's ability to concentrate and perform tasks that require sustained attention.

[0004] Research consistently demonstrates that, under the influence of attention-enhancing medications, many of these irregularities in eye movement and gaze distribution normalize, aligning more closely with the patterns seen in typically developing individuals. This suggests that the visual scanning and attentional processes in individuals with ADHD are part of a closed-loop system that, in the absence of intervention, stabilizes in a non-optimal regime. The interconnection between motor control and visual focus is crucial in this context, as everyday life naturally involves motion and requires the recruitment of attention capabilities in combination with motor function. Accordingly, disruptions in one adversely affect the other.

[0005] Existing therapeutic solutions for ADHD often fail to adequately address this dynamic interconnection. Similar to continuous performance tests (CPTs) like the Test of Variables of Attention (TOVA) and the MOXO-CPT, which are traditionally used to assessYEDA-P-058-PCT attention and diagnose ADHD, these therapeutic solutions tend to be monotonous and not very engaging, limiting their effectiveness. Furthermore, they typically do not incorporate real-time feedback mechanisms that can help individuals learn to control their gaze and improve their attention dynamically.SUMMARY OF THE INVENTION

[0006] Accordingly, there is a need for a system and method for attention training that would improve the relevant technological field by providing and utilizing a highly informative real-time biofeedback to reliably monitor the user’s ability to sustain attention. Such a solution would enable a more personalized and dynamically adaptive training regimen compared to conventional, monotonous approaches, thereby enhancing both the effectiveness of the training and the overall performance of the system and method. Furthermore, this solution could potentially serve as a powerful instrument for treating ADHD.

[0007] To address the aforementioned needs, the following is suggested.

[0008] In the general aspect, the present invention may be directed to a system for attention training, including: an input means that include at least one eye-tracking sensor configured to detect gaze points each representing a data sample indicating where a user is looking at a specific moment in time; an output means, configured to provide sensory stimuli to the user, said sensory stimuli being characterized by at least one parameter; at least one non-transitory memory device, wherein modules of instruction code are stored; and at least one processor associated with said at least one memory device, the input means and the output means. The at least one processor may be configured to execute the modules of instruction code, whereupon execution of said modules of instruction code, the at least one processor may be configured to: based on the detected gaze points, continuously calculate a gaze point dispersion; and dynamically alter a value of said at least one parameter, based on the calculated gaze point dispersion.

[0009] In another general aspect, the present invention may be directed to a method of attention training by at least one processor. The method may include: detecting, using at least one eye-tracking sensor, a plurality of gaze points each representing a data sample indicating where a user is looking at a specific moment in time; based on the detected plurality of gaze points, continuously calculating a gaze point dispersion; and providing, using output means, sensory stimuli to the user, said sensory stimuli being characterized by at least oneYEDA-P-058-PCT parameter, while dynamically altering a value of said at least one parameter, based on the calculated gaze point dispersion.

[0010] In some embodiments, the gaze point dispersion may represent an extent of a distribution of the detected gaze points around a target area of a predetermined size during a period of observation defined by a sliding time window of a predetermined duration.

[0011] In some embodiments, said target area may be characterized by a fixed position in spatial coordinates within the 360-degree field of view, so that said fixed position remains constant regardless of user’s head movement.

[0012] In some embodiments, said calculating the gaze point dispersion may include: defining a set of the gaze points determined within the sliding time window; for each of the gaze points of the defined set, calculating a distance from a respective gaze point to said area or to a specific region thereof; and determining the extent of the distribution, based on the calculated distance.

[0013] Accordingly, in some embodiments, said at least one processor may be further configured to calculate the gaze point dispersion by: defining a set of the gaze points determined within the sliding time window; for each of the gaze points of the defined set, calculating a distance from a respective gaze point to said area or to a specific region thereof; and determining the extent of the distribution, based on the calculated distance.

[0014] In some embodiments, said extent of the distribution may be represented by at least one of (i) an average distance from the gaze points of the defined set to said area or to a specific region thereof; and (ii) a standard deviation of the distance from the gaze points of the defined set to said area or to a specific region thereof.

[0015] In some embodiments, said dynamically altering the value of said at least one parameter may be performed correlatively to the determined extent of the distribution.

[0016] Accordingly, in some embodiments, said at least one processor may be further configured to dynamically alter the value of said at least one parameter correlatively to the determined extent of the distribution.

[0017] In some embodiments, said dynamically altering the value of said at least one parameter may be performed provided that the determined extent of the distribution exceeds a predefined threshold value.YEDA-P-058-PCT

[0018] Accordingly, in some embodiments, said at least one processor may be further configured to dynamically alter the value of said at least one parameter, provided that the determined extent of the distribution exceeds a predefined threshold value.

[0019] In some embodiments, the method may further include gradually adjusting at least one of (i) said predetermined size of the target area; and (ii) said predetermined duration of the sliding time window, correlatively to the determined extent of the distribution.

[0020] Accordingly, in some embodiments, said at least one processor may be further configured to gradually adjust at least one of (i) said predetermined size of the target area; and (ii) said predetermined duration of the sliding time window, correlatively to the determined extent of the distribution.

[0021] In some embodiments, said sensory stimuli may include visual stimuli. In some embodiments, said at least one parameter may be blurriness.

[0022] In some embodiments, said visual stimuli may include a stereoscopic video content. Such visual stimuli may be provided to the user via a Virtual-Reality (VR) headset configured to track user’s head movement to adjust the stereoscopic video content based thereon.

[0023] Accordingly, in some embodiments, said output means may include a Virtual- Reality (VR) headset configured to display a stereoscopic video content to the user and to track user’s head movement to adjust the stereoscopic video content based thereon.

[0024] In some embodiments, the method may further include receiving, via at least one motion controller, a motion input data element corresponding to the movement thereof, enabling interaction with the stereoscopic video content.

[0025] Accordingly, in some embodiments, said input means may include at least one motion controller configured to provide a motion input data element corresponding to the movement thereof, enabling interaction with the stereoscopic video content.

[0026] In some embodiments, said stereoscopic video content may include interactive tasks to be performed using said motion input data element, said interactive tasks requiring the user to retain visual focus within the target area in order to successfully complete said interactive tasks.

[0027] In some embodiments, said sensory stimuli may include auditory stimuli. In some embodiments, said at least one parameter may be loudness.YEDA-P-058-PCT

[0028] In some embodiments, said sensory stimuli may include haptic feedback. In some embodiments, said at least one parameter may be an intensity of the haptic feedback.BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The subject matter regarded as the invention is particularly pointed out and distinctly claimed in the concluding portion of the specification. The invention, however, both as to organization and method of operation, together with objects, features, and advantages thereof, may best be understood by reference to the following detailed description when read with the accompanying drawings in which:

[0030] Fig. 1 is a schematic representation of a concept of the present invention, according to some embodiments;

[0031] Fig. 2 is a block diagram providing a general representation of a system for attention training, according to some embodiments;

[0032] Fig. 3 is a block diagram providing a detailed representation of the system for attention training, according to some embodiments; and

[0033] Fig. 4 is a flow diagram, depicting a method for attention training, according to some embodiments.

[0034] Fig. 5 is a schematic illustration of clinical research stages, according to some embodiments;

[0035] Fig. 6 is a set of bar charts showing gaze concentration measured during stages 3-5 of the clinical research, according to some embodiments;

[0036] Fig. 7 is a bar chart showing the difference in gaze concentration between stages 3 and 5 of the clinical research, measured during these stages, according to some embodiments;

[0037] Fig. 8 is a bar chart showing the difference in gaze concentration between stages 3 and 5 of the clinical research, measured during fixation tests following these stages, according to some embodiments; and

[0038] Fig. 9 is a bar chart showing the improvement in MOXO score (a common ADHD symptoms measure) between stages 1 and 6 of the clinical research, according to some embodiments.

[0039] It will be appreciated that for simplicity and clarity of illustration, elements shown in the figures have not necessarily been drawn to scale. For example, the dimensions of some of the elements may be exaggerated relative to other elements for clarity. Further, whereYEDA-P-058-PCT considered appropriate, reference numerals may be repeated among the figures to indicate corresponding or analogous elements.DETAILED DESCRIPTION OF THE PRESENT INVENTION

[0040] One skilled in the art will realize the invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The foregoing embodiments are therefore to be considered in all respects illustrative rather than limiting of the invention described herein. Scope of the invention is thus indicated by the appended claims, rather than by the foregoing description, and all changes that come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.

[0041] In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be understood by those skilled in the art that the present invention may be practiced without these specific details. In other instances, well-known methods, procedures, and components have not been described in detail so as not to obscure the present invention. Some features or elements described with respect to one embodiment may be combined with features or elements described with respect to other embodiments. For the sake of clarity, discussion of same or similar features or elements may not be repeated.

[0042] Although embodiments of the invention are not limited in this regard, discussions utilizing terms such as, for example, “processing,” “computing,” “calculating,” “determining,” “establishing”, “analyzing”, “checking”, “choosing”, “selecting”, “omitting”, “training”, “applying”, “forming” or the like, may refer to operation(s) and / or process(es) of a computer, a computing platform, a computing system, or other electronic computing device, that manipulates and / or transforms data represented as physical (e.g., electronic) quantities within the computer’s registers and / or memories into other data similarly represented as physical quantities within the computer’s registers and / or memories or other information non-transitory storage medium that may store instructions to perform operations and / or processes.

[0043] Although embodiments of the invention are not limited in this regard, the terms “plurality” and “a plurality” as used herein may include, for example, “multiple” or “two or more”. The terms “plurality” or “a plurality” may be used throughout the specification toYEDA-P-058-PCT describe two or more components, devices, elements, units, parameters, or the like. The term “set” when used herein may include one or more items.

[0044] In relation to certain aspects of the invention, the present disclosure may refer to terms such as ‘environment’, ‘VR environment’, ‘video content’, ‘stereoscopic video content’, or similar. Within the context of this disclosure, these terms pertain to specific information provided to the user via sensory stimuli (visual stimuli, auditory stimuli, tactile stimuli etc.) - for example, specific gameplay of a VR attention training game, content of a video shown to the user, audio content etc. Therefore, in this context, these terms shall be considered equivalent.

[0045] Unless explicitly stated, the method embodiments described herein are not constrained to a particular order or sequence. Additionally, some of the described method embodiments or elements thereof can occur or be performed simultaneously, at the same point in time, concurrently, or iteratively and repeatedly.

[0046] The advent of advanced technologies, particularly in the field of biofeedback, presents a unique opportunity to develop more effective and engaging therapeutic interventions for attention training, and, in particular, for treating ADHD. Biofeedback involves monitoring physiological signals and providing real-time feedback to the individual to help them learn to regulate these signals. When combined with various techniques of providing sensory stimuli to the user (e.g., with Virtual Reality (VR) technologies), biofeedback enables the creation of immersive and interactive training environments that are both engaging and effective.

[0047] The suggested invention leverages these advancements to provide a personalized attention training approach. It is suggested herein to adjust the sensory input in real-time based on each patient's motor output, in particular, based on specific metric of their eye movement pattern - a gaze point dispersion - which is highly representative of the user’s ability to sustain attention.

[0048] According to some embodiments of the present invention, the gaze point dispersion may represent an extent of a distribution of the detected gaze points around a target area of a predetermined size during a period of observation defined by a sliding time window of a predetermined duration. The gaze points may be detected using an eye tracking sensor and may indicate, in spatial coordinates, where a user is looking at a specific moment in time. Through an algorithm that continuously analyzes the gaze point dispersion (e.g., based on aYEDA-P-058-PCT distance from detected gaze points to the target area or to a specific region thereof), the suggested system makes the patient experience changes in at least one parameter of the sensory stimuli (e.g., for visual stimuli - blurriness, for auditory stimuli - loudness). In some embodiments, while experiencing the abovementioned effect, the user may be asked to perform various interactive tasks, e.g., within the VR environment.

[0049] This algorithm integrates missing feedback into the attentional-eye scanning system (also referred herein as Oculomotor Biofeedback (OBF)). It provides real-time details of eye movement, facilitating the stabilization of the visual system towards more focused gaze behavior and potentially leading to improved attention and reduced symptoms of ADHD. This method offers a more personalized and adaptive training regimen compared to conventional continuous performance tests, which are often monotonous and less effective.

[0050] The concept of the present invention is further explained with reference to Fig.l.

[0051] According to the concept, the system may provide various sensory stimuli to the user: e.g., visual stimuli 301 (e.g., a stereoscopic video content) and auditory stimuli 302 (e.g., spatial sound). Stimuli 301 and 302 may be provided as a VR environment, e.g., in the form of a VR game. In some embodiments, stereoscopic video content (VR environment) may include interactive tasks to be performed using motion input data provided via motion controllers. For example, to win the game, the user may be required to hit objects 303 that continuously move towards them in a random order and frequency pattern, using virtual tools 304 controlled via motion controllers.

[0052] While performing interactive tasks (e.g., while playing the VR game), user’s ocular motoric may be continuously monitored using at least one eye-tracking sensor (e.g., built into VR headset or a stand-alone one) configured to detect gaze points (e.g., gaze points 202) each representing a data sample indicating where a user is looking at a specific moment in time.

[0053] Detected gaze points 202 may be further used to continuously calculate the gaze point dispersion. As indicated above, in some embodiments, the gaze point dispersion may represent an extent of a distribution of detected gaze points 202 around a target area of a predetermined size (e.g., target area 201) during a period of observation defined by a sliding time window of a predetermined duration. In some embodiments, target area 201 may be characterized by a fixed position in spatial coordinates within the field of view (e.g., 360- degree field of view), so that said fixed position remains constant regardless of user’s headYEDA-P-058-PCT movement. For example, target area 201 could be an area around the farthest point of the visual perspective in the VR environment, such as point 305 where objects 303 appear from.

[0054] In some embodiments, the gaze point dispersion may be calculated by: defining a set of the gaze points determined within the sliding time window; for each of the gaze points of the defined set (e.g., for each of gaze points 202), calculating a distance from a respective gaze point to area 201 or to a specific region thereof (e.g., to the center of area 201); and determining the extent of the distribution, based on the calculated distance. Depending on a specific embodiment, said extent of the distribution may be represented by, e.g., (i) an average distance from the gaze points (e.g., gaze points 202) of the defined set to said area (e.g., area 210) or to a specific region thereof (e.g., an average distance from points 202 to the center of area 210, or from points 202 to the border of area 210); and (ii) a standard deviation of the distance from the gaze points (e.g., gaze points 202) of the defined set to said area (e.g., area 210) or to a specific region thereof (e.g., a standard deviation of the distance from points 202 to the center of area 210, or from points 202 to the border of area 210).

[0055] According to the concept of the present invention, the calculated gaze point dispersion may be further used as a biofeedback metric to dynamically alter a value of at least one parameter of the sensory stimuli. In particular, in some embodiments, at least one parameter of the sensory stimuli may be further dynamically altered correlatively to the determined extent of the distribution of detected gaze points 202 around a target area 201, or specific region thereof.

[0056] For example, if the averaged distance to the center of area 201 is shorter than predefined radius 203 of area 201, no stimuli alteration is needed, as such a scenario indicates that user successfully sustains attention by keeping the gaze within the desired area (e.g., area 201). However, if the averaged distance to the center of area 201 is longer than predefined radius 203 but shorter than predefined radius 204 (e.g., if the averaged position of points 202 is within ring-shaped area 205), parameters of the visual and auditory stimuli, such as blurriness and loudness, may be altered to interactively communicate to the users that their attention is not focused enough and to stimulate them towards more focused behavior. To make this stimulation even more effective, these parameters may be altered correlatively to the extent of distribution. For example, the longer the averaged distance to the center of area 201 (i.e., the greater the difference between the averaged distance andYEDA-P-058-PCT radius 203), the stronger the alteration in blurriness and loudness levels. In some embodiments, the value of said at least one parameter (e.g., blurriness and loudness levels) may be altered proportionally, dynamically proportionally, exponentially, or according to another similar function, with respect to the calculated extent of the distribution (e.g., to the average distance).

[0057] Fig. 1 schematically demonstrates the abovementioned aspects. As shown in the upper left part, when the extent of the distribution is within the acceptable range, e.g., when the averaged distance from points 202 to the center of area 210 is shorter than radius 203, no visual stimuli alteration is applied: the stereoscopic video content (represented by image 301) is sharp (the ‘blurriness’ is set to zero), and auditory stimuli 302 (the background music and sound effects that are provided to the user) are comparatively loud (the ‘loudness’ remains in its normal range).

[0058] However, when the extent of the distribution falls outside the acceptable range - such as when the average distance from points 202 to the center of area 210 exceeds radius 203 (and, in some embodiments, is shorter than radius 204) - the visual stimuli may be altered accordingly. As shown in the lower left part of Fig. 1, the stereoscopic video content (represented by image 401) becomes blurred (with the ‘blurriness’ level increasing in proportion to the average distance), and the auditory stimuli 402 (including background music and sound effects) become comparatively quiet (with the ‘loudness’ level reduced).

[0059] To return to the ‘normal’ content representation, the user must control their gaze and maintain visual focus within the target area 210. This effort will gradually restore the ‘blurriness’ and ‘loudness’ parameters to their initial (normal) state, as shown by image 301 and auditory stimuli 302. Thereby, this process creates a closed ocular biofeedback loop, providing for effective attention training.

[0060] Additionally, the actual content provided to the user (e.g., the gameplay of the VR game) may be configured so that the interactive tasks thereof require the user to retain visual focus within target area 201 in order to successfully complete these tasks. For example, in the type of VR game shown in Fig. 1, to successfully hit objects 303 without missing, the best strategy would be to look at the farthest point of the visual perspective in the VR environment, such as point 305 where objects 303 appear from. The user should use peripheral vision to hit the closest objects 303 without directly looking at each one, which would cause the gaze point to constantly switch from one object 303 to another.YEDA-P-058-PCTAccordingly, by using such type of the content, further improvement of system efficiency may be achieved, providing synergic effect and accelerating attention training.

[0061] It should be understood that although the system configuration using the abovedescribed type of VR environment has demonstrated high efficiency, this specific type of VR environment is provided as a non-exclusive example only, and the present invention shall not be considered limited to this configuration. Furthermore, in some embodiments, sensory stimuli may not include visual stimuli. For example, the user may look at real objects and perform various interactive tasks using them, while receiving ocular biofeedback through other types of sensory stimuli, such as auditory or haptic feedback.

[0062] Reference is now made to Fig. 2, which is a block diagram providing a general representation of system 100 for attention training, according to some embodiments.

[0063] In some embodiments, system 100 may include computing device 1.

[0064] Computing device 1 may include a processor or controller 2 that may be, for example, a central processing unit (CPU) processor, a chip or any suitable computing or computational device, an operating system 3, a memory device 4, instruction code 5, a storage system 6, input devices 7 and output devices 8. Processor 2 (or one or more controllers or processors, possibly across multiple units or devices) may be configured to carry out methods described herein, and / or to execute or act as the various modules, units, etc. More than one computing device 1 may be included in, and one or more computing devices 1 may act as the components of, system 100 according to embodiments of the invention.

[0065] Operating system 3 may be or may include any code segment (e.g., one similar to instruction code 5 described herein) designed and / or configured to perform tasks involving coordination, scheduling, arbitration, supervising, controlling or otherwise managing operation of computing device 1, for example, scheduling execution of software programs or tasks or enabling software programs or other modules or units to communicate. Operating system 3 may be a commercial operating system. It is noted that an operating system 3 may be an optional component, e.g., in some embodiments, a system may include a computing device that does not require or include an operating system 3.

[0066] Memory device 4 may be or may include, for example, a Random- Access Memory (RAM), a read only memory (ROM), a Dynamic RAM (DRAM), a Synchronous DRAM (SD-RAM), a double data rate (DDR) memory chip, a Flash memory, a volatile memory, aYEDA-P-058-PCT non-volatile memory, a cache memory, a buffer, a short-term memory unit, a long-term memory unit, or other suitable memory units or storage units. Memory device 4 may be or may include a plurality of possibly different memory units. Memory device 4 may be a computer or processor non-transitory readable medium, or a computer non-transitory storage medium, e.g., a RAM. In one embodiment, a non-transitory storage medium such as memory device 4, a hard disk drive, another storage device, etc. may store instructions or code which when executed by a processor may cause the processor to carry out methods as described herein.

[0067] Instruction code 5 may be any executable code, e.g., an application, a program, a process, task, or script. Instruction code 5 may be executed by processor or controller 2 possibly under control of operating system 3. For example, instruction code 5 may be a standalone application or an API module that may be configured to receive a plurality of gaze points each representing a data sample indicating where a user is looking at a specific moment in time, said gaze points detected using at least one eye-tracking sensor; based on the detected plurality of gaze points, continuously calculating a gaze point dispersion; and provide, using output means, sensory stimuli to the user, said sensory stimuli being characterized by at least one parameter, while dynamically altering a value of said at least one parameter, based on the calculated gaze point dispersion, as described herein. Although, for the sake of clarity, a single item of instruction code 5 is shown in Fig. 2, a system according to some embodiments of the invention may include a plurality of executable code segments or modules similar to instruction code 5 that may be loaded into memory device 4 and cause processor 2 to carry out methods described herein.

[0068] Storage system 6 may be or may include, for example, a flash memory as known in the art, a memory that is internal to, or embedded in, a micro controller or chip as known in the art, a hard disk drive, a CD-Recordable (CD-R) drive, a Blu-ray disk (BD), a universal serial bus (USB) device or other suitable removable and / or fixed storage unit. Various types of input and output data may be stored in storage system 6 and may be loaded from storage system 6 into memory device 4 where it may be processed by processor or controller 2. In some embodiments, some of the components shown in Fig. 2 may be omitted. For example, memory device 4 may be a non-volatile memory having the storage capacity of storage system 6. Accordingly, although shown as a separate component, storage system 6 may be embedded or included in memory device 4.YEDA-P-058-PCT

[0069] Input devices 7 may be or may include any suitable input devices, components, or systems, e.g., eye-tracking sensors, motion controllers etc. In some embodiments, input devices 7 may further include additional physiological sensors, such as heart rate monitors and skin conductance sensors, to provide more comprehensive biofeedback and to further alter at least one parameter of sensory stimuli based on signals therefrom. Input devices 7 may also include, e.g., a detachable keyboard or keypad, a mouse and the like. Output devices 8 may include one or more (possibly detachable) displays or monitors, headphones, speakers and / or any other suitable output devices. Various input and output devices (7 and 8) may be integrated into a single device, such as a Virtual-Reality (VR) headset. This headset may be configured to display stereoscopic video content and play sounds (acting as output device 8), while also tracking the user's head movements (acting as input device 7) to adjust the video content based thereon. Any applicable input / output (I / O) devices may be connected to computing device 1 as shown by blocks 7 and 8. For example, a wired or wireless network interface card (NIC), a universal serial bus (USB) device or external hard drive may be included in input devices 7 and / or output devices 8. It will be recognized that any suitable number of input devices 7 and output device 8 may be operatively connected to computing device 1 as shown by blocks 7 and 8.

[0070] A system according to some embodiments of the invention may include components such as, but not limited to, a plurality of central processing units (CPU) or any other suitable multi-purpose or specific processors or controllers (e.g., similar to element 2), a plurality of input units, a plurality of output units, a plurality of memory units, and a plurality of storage units.

[0071] Reference is now made to Fig. 3, which is a block diagram providing a detailed representation of system 100 for attention training, according to some embodiments.

[0072] According to some embodiments of the invention, system 100 may be implemented as a combination of software and hardware modules. For example, system 100 may be or may include computing devices such as element 1 of Fig. 2. Furthermore, system 100 may be adapted to execute one or more modules of instruction code (e.g., element 5 of Fig. 2) to request, receive, analyze, calculate and produce various data.

[0073] As further described in detail herein, system 100 may be adapted to execute one or more modules of instruction code (e.g., element 5 of Fig. 1) in order to perform steps of the claimed method.YEDA-P-058-PCT

[0074] As shown in Fig. 3, arrows may represent the flow of one or more data elements to and from system 100 and / or among modules or elements of system 100. Some arrows have been omitted in Fig. 3 for the purpose of clarity.

[0075] As shown in Fig. 3, in some embodiments, system 100 may include eye-tracking sensor 10. Eye-tracking sensor 10 may be configured to detect gaze points 10A (such as gaze points 202, discussed with reference to Fig. 1) each representing a data sample indicating where a user is looking at a specific moment in time.

[0076] Eye-tracking sensor 10 may, e.g., include infrared camera that capture reflections from the user's eyes or electrooculography (EOG) sensor that measure the electrical activity of the eye muscles. Sensor 10 may be embedded within the VR headset or attached externally, and may communicate wirelessly with computing device 1 (as shown in Fig. 2) to ensure seamless integration.

[0077] It should be understood that the present invention is not limited to a specific eyetracking sensor (sensor 10). Any known eye-tracking sensor suitable for the purposes of this invention (e.g., configured to detect gaze points) may be used herein. A person skilled in the art will recognize which known eye-tracking sensors are applicable and how to implement them.

[0078] In some embodiments, system 100 may further include motion controller 11.

[0079] Motion controller 11 may be utilized with a Virtual Reality (VR) headset to enhance user interaction and immersion. Various types of motion controllers may be used herein. These controllers may include handheld devices equipped with sensors to detect position and orientation, allowing for precise tracking of hand movements. Additionally, motion controllers can incorporate haptic feedback mechanisms to provide tactile sensations, that may be used as sensory stimuli for the attention training approach suggested herein, further enriching the VR experience. Other types of motion controllers may include wearable devices, such as gloves or suits, embedded with sensors to capture full-body movements. These controllers can communicate wirelessly with the VR headset, ensuring seamless integration and real-time response to user actions. The versatility of these motion controllers allows for a wide range of attention training applications.

[0080] In some embodiments, system 100 may include stereoscopic displays 12.

[0081] Stereoscopic displays can be integrated with the Virtual Reality (VR) headset to provide a more immersive and realistic visual experience. As known, these displays workYEDA-P-058-PCT by presenting two slightly different images to each eye, mimicking the way human binocular vision perceives depth. This technique creates a three-dimensional effect, allowing users to perceive depth and spatial relationships in the virtual environment. Stereoscopic displays typically use dual lenses or screens to achieve this effect, ensuring that each eye receives the appropriate image. The use of stereoscopic technology enhances the sense of presence in VR environment, making it ideal for attention training purposes. By accurately replicating the way human see the real world, stereoscopic displays significantly improve the realism and engagement of VR content, which, when combined with the suggested Oculomotor Biofeedback (OBF) and the integration of interactive tasks (that may be performed using motion controllers (such as motion controller 11)), may provide further improvement to the relevant technological field. This improvement is achieved by increasing the efficiency of system 100, accelerating the attention training process, and providing sustained fixation of training results, as, by using such immersive VR technology, training is conducted through the interconnection between motor control and visual focus, mirroring everyday life needs.

[0082] In some embodiments, system 100 may further include headphones 13.

[0083] Various types of headphones 13 may be used in system 100. In some embodiments, headphones 13 can be integrated with the VR headset to enhance the auditory experience and provide immersive soundscapes. These headphones may include over-ear, on-ear, or in- ear designs, each offering different levels of sound isolation and comfort. Some headphones may feature spatial audio technology, which simulates 3D sound by adjusting the audio output based on the user's head movements. This technology enhances the sense of presence and realism in VR attention training applications. Furthermore, noise-canceling features can be incorporated to minimize external distractions, allowing users to fully immerse themselves in the virtual world.

[0084] Accordingly, in some embodiments, system 100 may include a VR headset (comprising stereoscopic displays 12 and headphones 13 and having motion controller 11 connected thereto).

[0085] In some embodiments, system 100 may include gaze point analysis module 20. In some embodiments, gaze point analysis module 20 may be configured to continuously receive gaze points 10A from eye-tracking sensor 10. Gaze point analysis module 20 may be further configured to receive preset parameters, defining a target area in spatial coordinates, with respect to which the gaze point dispersion may be calculated (e.g., such asYEDA-P-058-PCT area 201, discussed with reference to Fig. 1). These preset parameters may, e.g., include target area size 60A and target area location 61 A. In some nonlimiting embodiments, target area may be characterized by a fixed position in spatial coordinates within the field of view, so that said fixed position remains constant regardless of user’s head movement.

[0086] In some embodiments, said preset parameters may further include sliding time window duration 62A, defining the period of observation for further gaze point dispersion evaluation.

[0087] Gaze point analysis module 20 may be further configured to continuously define set 20A of the gaze points 10A that were determined within the sliding time window of the preset duration 62A. Module 20 may be further configured to calculate, for each of gaze points 10A of set 20A, distance 21 A from a respective gaze point 10A to the target area (or to a specific region thereof, e.g., the center of the target area, as discussed with reference to Fig. 1).

[0088] In some embodiments, system 100 may further include AVG / STD calculation module 30. Module 30 may be configured to receive distances 21A to the target area, Module 30 may be configured to evaluate the gaze point dispersion represented as extent 30A of the distribution of detected gaze points 10A around the target area of a predetermined size during a period of observation defined by a sliding time window of a predetermined duration. In particular, module 30 may be configured to determine extent 30A of a distribution of the detected gaze points 10A around the target area during the period of observation (e.g., for set 20A of gaze points 10A), using the calculated distances 21 A. For example, module 30 may be configured to calculate extent 30A of distribution as represented by an average (AVG) distance 30 A’ from gaze points 10A of set 20A to said target area or to a specific region thereof (e.g., to the center of the target area, as discussed with reference to Fig. 1). Additionally or alternatively, module 30 may be configured to calculate the extent 30A of distribution as a standard deviation (STD) 30A” of the distance 21A from gaze points 10A of set 20A to the target area or to a specific region thereof. In some embodiments, said AVG distance 30A’ or STD 30A” may be considered as a radius of an area of gaze point distribution (representing extent 30A of the distribution), said area having the same center as the target area.

[0089] It should be understood that the calculation of the ‘extent of the distribution’ is not limited to any specific function of the calculated distances 21A. E.g., in some embodiments,YEDA-P-058-PCT it may various mathematical transformations of distance 21A values (e.g., normalization). Furthermore, depending on embodiments, it may be represented both in absolute and relative units of measurements. E.g., in some embodiments, the extent of the distribution may be expressed as a percentage, e.g., a percentage of gaze points 10A (detected within the period of observation) that are located within the target area.

[0090] In some embodiments, system 100 may further include biofeedback-based content alteration module 40. Biofeedback-based content alteration module 40 may be configured to receive calculated extent 30A of the distribution (e.g., average distance 30A’, STD 30A” of the distance, or radius of the area of gaze point distribution). Module 40 may be further configured to dynamically alter a value of at least one parameter of sensory stimuli provided to the user, e.g., via stereoscopic displays 12 and headphones 13, based on the calculated gaze point dispersion (e.g., extent 30A of the distribution of gaze points 10A). E.g., module 40 may be further configured to alter the value of said at least one parameter correlatively to the extent 30A of the distribution. For example, module 40 may store a specific predefined function from the value of extent 30A of gaze point distribution to the value of the desired parameter. E.g., module 40 may alter the desired parameter proportionally, dynamically proportionally, exponentially etc. to the value of extent 30A. In some embodiments, said parameter may include blurriness level 40A (for the visual stimuli provided via stereoscopic displays 12) and / or loudness level 41A (for the auditory stimuli provided via headphones 13).

[0091] In some embodiments, said sensory stimuli may also include tactile stimuli (haptic feedback provided by motion controller 11), and the parameters of the sensory stimuli may accordingly include intensity of the haptic feedback.

[0092] In some embodiments, the parameters of the auditory stimuli may also include the Head-Related Transfer Function (HRTF) adjustment. HRTF is the parameter of spatial audio that can be adjusted to control the extent to which the audio panorama changes in response to the user's head movements. By adjusting the HRTF, system 100 can either maintain a stable audio environment or create a dynamic soundscape that shifts dramatically with head motion away and to the target area. This capability may enhance the user's concentration on the target area radiating sound within the 3D environment, thereby improving the overall immersive experience and effectiveness of attention training system 100.YEDA-P-058-PCT

[0093] Module 40 may be configured to perform the alteration of the at least one parameter of the sensory stimuli, e.g., as discussed with reference to Fig. 1.

[0094] Additionally, in some embodiments, module 40 may be further configured to receive a predefined threshold value, defining situations where extent 30A is within the acceptable region, meaning that no alteration of the at least one parameter of the sensory stimuli is necessary, and situation where extent 30A is within the abnormal region, meaning that said alteration is necessary. Accordingly, in some embodiments, module 40 may be further configured to dynamically alter the value of said at least one parameter, provided that the determined extent of the distribution exceeds the predefined threshold value. E.g., in the embodiments where extent 30A may be represented as averaged distance 30A’, said predefined threshold value may be defined corresponding to the value of the radius of the target area (e.g., radius 203, as discussed with reference to Fig. 1).

[0095] In some embodiments, module 40 may be configured to alter the value of said at least one parameter (e.g., blurriness level 40A and loudness level 41A) according to the following formula:

[0096] where MF(r) is a function form radius r of the area of the gaze point distribution to the value of said at least one parameter, rthreshis a radius of the target area (e.g., radius 203, as shown in Fig. 1) and rmaxis a radius of the area of gradual adjustment of the parameter (e.g., radius 203 + radius 204 (width of the ring-shaped area), as shown in Fig. 1).

[0097] In some embodiments, system 100 may further include VR content generation / processing module 50.

[0098] VR content generation / processing module 50 may be configured to generate stereoscopic video content 50A and audio content 51 A, to provide an immersive VR attention training environment to the user (same as explained with reference to Fig. 1), e.g., using stereoscopic displays 12 and headphones 13, which may be, for example, integrated in the VR headset. Accordingly, the VR headset may be configured to display stereoscopic video content 50A to the user and to track user’ s head movement to adjust stereoscopic video content 50A based thereon, as well as providing auditory stimuli (audio content 51 A).YEDA-P-058-PCT

[0099] Accordingly, in some embodiments, motion controller 11 may be configured to provide, to VR content generation / processing module 50, motion input data elements 11A corresponding to the movement of the motion controller 11 (e.g., coordinates of movement, signals from gyroscope sensors integrated in the controller 11 etc.), enabling interaction with stereoscopic video content 50A.

[0100] In some embodiments, module 50 may be further configured to generate stereoscopic video content 50A including interactive tasks to be performed using motion controller 11, i.e., based on motion input data elements 11 A. Such interactive tasks may require the user to retain visual focus within the target area in order to successfully complete said interactive tasks (as explained with reference to Fig. 1).

[0101] In some embodiments, system 100 may further include dynamic difficulty level adjustment module 60. Module 60 may be configured to receive extent 30A of distribution. Using extent 30A of the distribution, module 60 may evaluate how well a specific user retains attention within a predefined area. In some embodiments, if the user continuously keeps their gaze within the target area, it indicates that their attention is properly trained for the task. To further train the user's attention, module 60 can gradually adjust at least one of the following correlatively to extent 30A of the distribution: (i) predetermined size 60A of the target area; and (ii) predetermined duration 62 A of the sliding time window. For example, the size 60A of the target area may be decreased, and the duration 62A of the sliding time window may be increased. The same may apply to opposite scenarios. When extent 30A of the distribution is too high, it may indicate that the current settings for size 60A and duration 62A are too difficult for the user. In such cases, module 60 may be configured to gradually increase size 60A and decrease duration 62A. Module 60 may continue these adjustments until the desired condition for effective attention training is achieved (e.g., until at least 20% of gaze points 10A of set 20A are within the target area).

[0102] Such dynamic difficulty adjustment may further contribute to the abovementioned improvement of the technological field, by further improving system 100 efficiency. It creates a more personalized training approach, accelerating the attention training process for individuals with varying levels of attention disorder and ensuring sustained fixation of training results for each case.

[0103] In some embodiments, system 100 may further include, or configured to receive input from additional physiological sensors (not shown), such as heart rate monitors and skinYEDA-P-058-PCT conductance sensors, to provide more comprehensive biofeedback and to further alter at least one parameter of sensory stimuli based on signals therefrom.

[0104] In some embodiments, system 100 may include therapist control module 14. Module 14 may be configured to output information to a stand-alone display, such as the same video content 50A that the user is currently seeing (including any alterations to the visual stimuli parameters). It may also output information about the current gaze point dispersion, the user's attention training progress (e.g., how quickly the user improves extent 30A of the gaze point distribution), and additional data from various physiological sensors (e.g., heart rate monitors and skin conductance sensors). This output information can be reviewed by a therapist. Module 14 can also receive manual adjustments to the difficulty level parameters, allowing the therapist to intervene in the attention training process if necessary.

[0105] Referring now to Fig. 4, a flow diagram is presented, depicting a method for attention training, by at least one processor (e.g., processor 2 of Fig. 2), according to some embodiments.

[0106] As shown in step S1005, the at least one processor (e.g., such as processor 2 of Fig. 2) may detect, using at least one eye-tracking sensor (e.g., sensor 10 as shown in Fig. 3), a plurality of gaze points (e.g., gaze points 10A as shown in Fig. 3) each representing a data sample indicating where a user is looking at a specific moment in time. Step S1005 may be carried out by eye-tracking sensor 10 (as described with reference to Fig. 3).

[0107] As shown in step S1010, the at least one processor (e.g., such as processor 2 of Fig. 2) may continuously calculate, based on the detected plurality of gaze points (e.g., gaze points 10A as shown in Fig. 3), a gaze point dispersion (e.g., represented by extent 30A of gaze point distribution as shown in Fig. 3). Step S1010 may be carried out by gaze point analysis module 20 and AVG / STD calculation module 30 (as described with reference to Fig. 3).

[0108] As shown in step S1015, the at least one processor (e.g., such as processor 2 of Fig. 2) may provide, using output means (e.g., headphones 13 and stereoscopic displays 12 as shown in Fig. 3), sensory stimuli to the user (e.g., stereoscopic video content 50A and audio content 51A as shown in Fig. 3), said sensory stimuli being characterized by at least one parameter (blurriness level 40A and loudness level 41A as shown in Fig. 3), while dynamically altering a value of said at least one parameter, based on the calculated gazeYEDA-P-058-PCT point dispersion (e.g., represented by extent 30A of gaze point distribution as shown in Fig. 3). Step S 1015 may be carried out by biofeedback-based content alteration module 40 and VR content generation / processing module 50 (as described with reference to Fig. 3).

[0109] Initial clinical research has shown promising results. For the experiment, 32 participants, all officially diagnosed with ADHD, were selected. The participants were divided into two equal groups: an experimental group, whose participants underwent, during the research, the attention training using OBF as suggested herein (also referred to as the ‘biofeedback group’), and a control group, whose participants did not undergo the suggested attention training. The research demonstrates that participants who underwent a single training session using the system and method according to the present invention exhibited significant improvements in gaze distribution, number of saccades, fixation abilities, and attention scores on a standard test (MOXO, Neurotech-solutions LTD). These improvements were not observed in the control group, highlighting the potential efficacy of our approach.

[0110] Referring to Fig. 5, the sequence of stages of the clinical research is schematically illustrated.

[0111] The research included six stages. At Stage 1 (shown by element 501), the initial MOXO test was conducted (denoted MOXO #1), and the initial MOXO scores of the participants were calculated.

[0112] At Stage 2 (shown by element 502), participants of both groups were subjected to visual and auditory stimuli (similar to stimuli 301 and 302, discussed with reference to Fig. 1) using a VR headset. At this stage, no motion controllers were used, and no interactive tasks were included. The participants were asked to sustain their visual focus on the target area (around the farthest point of the visual perspective in the VR environment, such as point 305 discussed with reference to Fig. 1) and not to be distracted by objects that continuously moved towards them in a random order and frequency pattern (same as objects 303 discussed with reference to Fig. 1). This stage was used to help participants adapt to the VR environment, making subsequent measurements more informative.

[0113] At Stage 3 (shown by element 503), interactive tasks using motion controllers were added. The participants were asked to hit objects (same as objects 303 of Fig. 1) that continuously moved towards them in a random order and frequency pattern, using virtual tools (such as tools 304, shown in Fig. 1) controlled via motion controllers (such as motionYEDA-P-058-PCT controller 11 of Fig. 3). As in the previous stage, participants were asked to keep their visual focus on the target area while performing these interactive tasks.

[0114] At Stage 4 (shown by element 504), for the ‘biofeedback’ group of the participants, Oculomotor Biofeedback (OBF) loop was added, as suggested by the present invention. Eye-tracking sensors configured to detect gaze points (such as sensor 10 of Fig. 3) and the gaze point dispersion calculation based on the detected gaze points were used at each stage of the research that involved VR. However, Stage 4 also included the dynamic alteration of a value of sensory stimuli parameters (blurriness level and loudness level, such as elements 40A and 41A of Fig. 3, respectively), based on the calculated gaze point dispersion, according to the concept of the present invention. The ‘control’ group continued using the VR environment without the OBF loop, same as at the previous stage.

[0115] At Stage 5 (shown by element 505), OBF loop was removed, and both groups of the participants continued using the VR environment, same as at the Stage 3.

[0116] At Stage 6 (shown by element 506), the MOXO test was conducted again (denoted MOXO #2), and the updated MOXO scores of all the participants were calculated.

[0117] Immediately after each of Stages 2-5, a 30-second fixation test was performed. Participants were asked to keep their visual focus on an indicated area (or point) without any sensory stimuli (i.e., without using the VR headset), while their gaze point dispersion was measured. This test aimed to assess how well the attention training results were maintained outside the VR environment.

[0118] The clinical research results are shown in Figs. 6-9 and are discussed below.

[0119] Fig. 6 is a set of bar charts showing gaze concentration (also referred herein as ‘gaze dispersion’ or ‘gaze point dispersion’) measured during stages 3-5 of the clinical research.

[0120] In the embodiment of the present invention used for the clinical research, gaze point dispersion was defined as the standard deviation from its mean value within a sliding time window, measured in degrees. The desired outcome was a decrease in gaze point dispersion at Stages 4 and 5 compared to Stage 3. The chart on the left shows measurements from the ‘biofeedback’ group, while the chart on the right shows measurements from the ‘control’ group. As seen in the left chart, the ‘biofeedback’ group experienced a significant reduction in gaze point dispersion at Stage 4, which was almost completely sustained whenYEDA-P-058-PCT the OBF loop was turned off at Stage 5. This effect was not observed in the ‘control’ group, as shown in the right chart.

[0121] Fig. 7 is a bar chart illustrating the difference in gaze concentration (gaze point dispersion) between stages 3 and 5 of the clinical research for both participant groups. The parameter shown is the gaze point dispersion at stage 5 minus the gaze point dispersion at stage 3, for each group, respectively. Therefore, the desired outcome is a negative value, with larger absolute values indicating better results. Although the ‘control’ group shows some improvement in gaze point dispersion, the ‘biofeedback’ group demonstrates a much stronger effect, despite high variance between participants (each participant's measurement is represented by a circle).

[0122] Fig. 8 is a bar chart illustrating the difference in gaze concentration (gaze point dispersion) between stages 3 and 5 of the clinical research, measured during fixation tests conducted after these stages. When comparing the results of the fixation tests following Stages 3 and 5, a significant improvement in the ‘biofeedback’ group compared to the ‘control’ group is observed. Therefore, participants who experienced OBF loop demonstrated an improvement in their ability to focus their gaze outside the suggested attention training system, during fixation tests.

[0123] Fig. 9 is a bar chart illustrating the improvement in MOXO scores between stages 1 and 6 of the clinical research. It compares the results of MOXO #1 and MOXO #2 tests for the ‘biofeedback’ group. In particular, the chart shows the average score derived from the four sub-scores in each participant’s report. The score value of -1.65, marked by a dashed line, represents a predefined threshold for the MOXO test - individuals scoring below this value are considered to have a high potential for an ADHD diagnosis. Despite considerable variability between participants, a significant average improvement in MOXO scores was observed in the ‘biofeedback’ group. Moreover, the average score, which was below the threshold in MOXO #1, surpassed the threshold in MOXO #2. In contrast, the ‘control’ group showed no significant improvement in MOXO scores.

[0124] Therefore, the clinical research demonstrated the high efficiency of the suggested method and system for attention training.

[0125] Specifically, it was verified that gaze point dispersion can be enhanced by the suggested OBF-based training, according to the proposed method and system. Furthermore, it was confirmed that the positive effect can generalize to later retesting without using theYEDA-P-058-PCTOBF loop. Additionally, it was verified that the effect can generalize to later fixation tests without using sensory stimuli and the OBF loop of the suggested system. Moreover, the clinical research demonstrated promising results in improving standardized ADHD indicators using the suggested system and method, providing a potentially highly effective tool for treating ADHD.

[0126] It should be understood that although the efficiency of the present invention is discussed in relation to ADHD, its scope is not limited to this specific application. For example, in some embodiments, the proposed method and system for attention training can be applied to shooting training (e.g., for snipers), helping them maintain focus on a specific target. In such applications, the target area (e.g., target area 201 in Fig. 1) may be movable and may 'jump' to a different virtual object once the previous one is hit. Additionally or alternatively, the virtual object may appear or disappear in a random or predefined pattern. The dynamic difficulty level adjustment module 60 may also be configured to adjust the velocity of movable virtual targets (along with other settings, as explained in Fig. 3) to further enhance training efficiency.

[0127] As can be seen from the provided description, the claimed invention represents a system and method for attention training that improve the relevant technological field by providing and utilizing a highly informative real-time biofeedback reliably representing the user’s ability to sustain attention. The suggested solution enables a more personalized and dynamically adaptive training regimen compared to conventional, monotonous approaches, thereby enhancing both the effectiveness of the training and the overall performance of the system and method. Furthermore, this solution represents a powerful instrument for treating ADHD.

[0128] Unless explicitly stated, the method embodiments described herein are not constrained to a particular order or sequence. Furthermore, all formulas described herein are intended as examples only and other or different formulas may be used. Additionally, some of the described method embodiments or elements thereof may occur or be performed at the same point in time.

[0129] While certain features of the invention have been illustrated and described herein, many modifications, substitutions, changes, and equivalents may occur to those skilled in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of the invention.YEDA-P-058-PCT

[0130] Various embodiments have been presented. Each of these embodiments may of course include features from other embodiments presented, and embodiments not specifically described may include various features described herein.

Claims

YEDA-P-058-PCTCLAIMS1. A system for attention training, comprising: an input means comprising at least one eye-tracking sensor configured to detect gaze points each representing a data sample indicating where a user is looking at a specific moment in time; an output means, configured to provide sensory stimuli to the user, said sensory stimuli being characterized by at least one parameter; at least one non-transitory memory device, wherein modules of instruction code are stored; and at least one processor associated with said at least one memory device, the input means and the output means, and configured to execute the modules of instruction code, whereupon execution of said modules of instruction code, the at least one processor is configured to: based on the detected gaze points, continuously calculate a gaze point dispersion; and dynamically alter a value of said at least one parameter, based on the calculated gaze point dispersion.

2. The system of claim 1, wherein the gaze point dispersion represents an extent of a distribution of the detected gaze points around a target area of a predetermined size during a period of observation defined by a sliding time window of a predetermined duration.

3. The system of claim 2, wherein said target area is characterized by a fixed position in spatial coordinates within the field of view, so that said fixed position remains constant regardless of user’s head movement.

4. The system according to any one of claims 1 and 2, wherein said at least one processor is further configured to calculate the gaze point dispersion by: defining a set of the gaze points determined within the sliding time window; for each of the gaze points of the defined set, calculating a distance from a respective gaze point to said area or to a specific region thereof; and determining the extent of the distribution, based on the calculated distance.YEDA-P-058-PCT5. The system of claim 4, wherein said extent of the distribution is represented by at least one of (i) an average distance from the gaze points of the defined set to said area or to a specific region thereof; and (ii) a standard deviation of the distance from the gaze points of the defined set to said area or to a specific region thereof.

6. The system according to any one of claims 4 and 5, wherein said at least one processor is further configured to dynamically alter the value of said at least one parameter correlatively to the determined extent of the distribution.

7. The system according to any one of claims 4-6, wherein said at least one processor is further configured to dynamically alter the value of said at least one parameter, provided that the determined extent of the distribution exceeds a predefined threshold value.

8. The system according to any one of claims 4-7, wherein said at least one processor is further configured to gradually adjust at least one of (i) said predetermined size of the target area; and (ii) said predetermined duration of the sliding time window, correlatively to the determined extent of the distribution.

9. The system according to any one of claims 2-8, wherein said sensory stimuli comprise visual stimuli.

10. The system of claim 9, wherein said at least one parameter is blurriness.

11. The system according to any one of claims 9 and 10, wherein said output means comprise a Virtual-Reality (VR) headset configured to display a stereoscopic video content to the user and to track user’s head movement to adjust the stereoscopic video content based thereon.

12. The system of claim 11, wherein said input means comprise at least one motion controller configured to provide a motion input data element corresponding to the movement thereof, enabling interaction with the stereoscopic video content.

13. The system of claim 12, wherein said stereoscopic video content comprises interactive tasks to be performed using said motion input data element, said interactiveYEDA-P-058-PCT tasks requiring the user to retain visual focus within the target area in order to successfully complete said interactive tasks.

14. The system according to any one of claims 1-13, wherein said sensory stimuli comprise auditory stimuli.

15. The system of claim 14, wherein said at least one parameter is loudness.

16. The system according to any one of claims 1-15, wherein said sensory stimuli comprise haptic feedback.

17. The system of claim 16, wherein said at least one parameter is an intensity of the haptic feedback.

18. A method of attention training by at least one processor, the method comprising: detecting, using at least one eye-tracking sensor, a plurality of gaze points each representing a data sample indicating where a user is looking at a specific moment in time; based on the detected plurality of gaze points, continuously calculating a gaze point dispersion; providing, using output means, sensory stimuli to the user, said sensory stimuli being characterized by at least one parameter, while dynamically altering a value of said at least one parameter, based on the calculated gaze point dispersion.

19. The method of claim 18, wherein the gaze point dispersion represents an extent of a distribution of the gaze points around a target area of a predetermined size during a period of observation defined by a sliding time window of a predetermined duration.

20. The method of claim 19, wherein said target area is characterized by a fixed position in spatial coordinates within the 360-degree field of view, so that said fixed position remains constant regardless of user’s head movement.

21. The method according to any one of claims 19 and 20, wherein said calculating the gaze point dispersion includes: defining a set of the gaze points determined within the sliding time window;YEDA-P-058-PCT for each of the gaze points of the defined set, calculating a distance from a respective gaze point to said area or to a specific region thereof; and determining the extent of the distribution, based on the calculated distance.

22. The method of claim 21, wherein said extent of the distribution is represented by at least one of (i) an average distance from the gaze points of the defined set to said area or to a specific region thereof; and (ii) a standard deviation of the distance from the gaze points of the defined set to said area or to a specific region thereof.

23. The method according to any one of claims 21 and 22, wherein said dynamically altering the value of said at least one parameter is performed correlatively to the determined extent of the distribution.

24. The method according to any one of claims 21-23, wherein said dynamically altering the value of said at least one parameter is performed provided that the determined extent of the distribution exceeds a predefined threshold value.

25. The method according to any one of claims 21-24, further comprising gradually adjusting at least one of (i) said predetermined size of the target area; and (ii) said predetermined duration of the sliding time window, correlatively to the determined extent of the distribution.

26. The method according to any one of claims 19-25, wherein said sensory stimuli comprise visual stimuli.

27. The method of claim 26, wherein said at least one parameter is blurriness.

28. The method according to any one of claims 26 and 27, wherein said visual stimuli comprise a stereoscopic video content and are provided to the user via a Virtual-Reality (VR) headset configured to track user’s head movement to adjust the stereoscopic video content based thereon.

29. The method of claim 28, further comprising receiving, via at least one motion controller, a motion input data element corresponding to the movement thereof, enabling interaction with the stereoscopic video content.YEDA-P-058-PCT30. The method of claim 29, wherein said stereoscopic video content comprises interactive tasks to be performed using said motion input data element, said interactive tasks requiring the user to retain visual focus within the target area in order to successfully complete said interactive tasks.

31. The method according to any one of claims 18-30, wherein said sensory stimuli comprise auditory stimuli.

32. The method of claim 31, wherein said at least one parameter is loudness.

33. The method according to any one of claims 18-32, wherein said sensory stimuli comprise haptic feedback.

34. The method of claim 33, wherein said at least one parameter is an intensity of the haptic feedback.

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