System for migraine treatment

Abstract

There is provided a system for migraine treatment by transcutaneous electrical stimulation of a trigeminal nerve of a user, the system comprising: a stimulation device for attachment to a forehead of a user, wherein the stimulation device comprises an electrical stimulation means for transcutaneous electrical stimulation of the trigeminal nerve; and a processor configured to: receive one or more input parameters specific to the user, determine one or more user-specific treatment parameters depending on the received one or more input parameters, and transmitting the user-specific treatment parameters to the device.

Description

[0001] SYSTE M FOR M IG RAI N E TREATM ENT

[0002] TECH N ICAL FI ELD

[0003] The present invention relates to a system for medical treatment, and more particularly to a system for treatment of migraine, as well as to methods of operating the same.

[0004] BACKG ROU N D

[0005] Migraine is a complex neurological disorder characterized by recurrent attacks of moderate to severe headaches, often accompanied by symptoms such as nausea, vomiting, and sensitivity to light and sound. It represents a significant burden on patients' quality of life and healthcare systems worldwide.

[0006] Current therapeutic approaches for migraine management include pharmacological treatments (e.g., triptans, CGRP antagonists, and preventive medications). Despite the availability of these treatments, many patients experience incomplete relief, side effects, or variability in treatment response.

[0007] Known approaches also include non-pharmacological strategies, such as lifestyle modifications and neuromodulation therapies. These approaches have garnered increasing interest as alternatives or adjuncts to pharmacological options. Among these, transcutaneous electrical nerve stimulation (TENS) has been identified as a promising approach for both abortive and preventive migraine treatment. TENS involves the application of low-intensity electrical pulses, for example to the trigeminal nerve branches (which may be referred to as external trigeminal nerve stimulation, eTNS), through electrodes placed on the skin. The trigeminal nerve is a major cranial nerve involved in the sensory innervation of the face and plays a role in the pathophysiology of migraine, particularly through its involvement in the trigeminovascular system. The primary mechanism of TENS is thought to involve neuromodulation of cortical and subcortical areas implicated in pain processing, reducing hyperexcitability in these regions and restoring neurological homeostasis.

[0008] Known TENS treatment methods include the use of devices capable of delivering stimulation to the trigeminal nerve. They involve the application of transcutaneous electrical stimulation using consecutive pre-programmed pulses delivered via electrodes placed on the skin, and have been shown to modulate neural pathways associated with migraine pathophysiology, providing relief to patients. In particular, the stimulation leads to changes in neural activity within the trigeminal pathways and associated brain regions, ultimately reducing migraine frequency, severity, or duration. However, the efficacy of such methods is relatively poor, and are only effective for a subset of patients. Embodiments of the present invention seek to provide enhanced treatment systems, methods and other implementations that improve the scope of migraine treatment to address aspects of efficacy as well as providing new functionality and methods.

[0009] SU M MARY

[0010] The invention is defined by the appended independent claims. Additional features and advantages of the concepts disclosed herein are set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the described technologies. The features and advantages of the concepts may be realized and obtained by means of the instruments and combinations particularly pointed out in the appended claims. These and other features of the described technologies will become more fully apparent from the following description and appended claims, or may be learned by the practice of the disclosed concepts as set forth herein.

[0011] It is an objective of the present invention to provide effective and individualized treatment approaches, particularly for patients who do not respond well to medication or experience adverse effects.

[0012] It is a further objective to provide systems and methods that account for individual variability in migraine triggers, severity, or response to stimulation.

[0013] It is a still further objective to provide systems and methods for migraine treatment that are tailored to the specific needs and conditions of individual users.

[0014] In a first aspect, there is provided a system for migraine treatment by transcutaneous electrical stimulation of a trigeminal nerve of a user, the system comprising: a stimulation device for attachment to a forehead of a user, wherein the stimulation device comprises an electrical stimulation means for transcutaneous electrical stimulation of the trigeminal nerve; and a processor configured to: receive one or more input parameter values specific to the user, determine one or more user-specific treatment parameters depending on the received one or more input parameter values, and transmitting the user-specific treatment parameters to the device.

[0015] The input parameter values may be received over a first predetermined time period. The input parameter values relating to one or more input parameters. At least one of the input parameters may be a result parameter of a visual perception test performed by the user.

[0016] The system may further be configured to determine, in dependence on the received input parameter values, a risk score of a migraine attack occurring within a second predetermined time period. The system may compare said risk score to a threshold, and in response to the risk score exceeding a threshold, transmit a signal to a user device notifying the user that treatment is to be performed. The system may further be configured to receive feedback from the user, wherein the feedback comprises data relating to the occurrence of a migraine attack during the second predetermined time period and / or data relating to a perceived efficacy of performed treatment. The system may determine the risk score and the user-specific treatment parameters, using machine learning, in dependence on previously received feedback from the user.

[0017] The system according to the first aspect offers personalized migraine treatment by adjusting the electrical stimulation based on individual user characteristics, potentially increasing the efficacy of the therapy. By receiving input parameters specific to the user, the system can tailor the treatment to the user's unique physiological condition, which can increase the efficacy and reduce the risk of side effects commonly associated with one-size-fits-all treatments. The integration of a processor with the capability to determine and transmit user-specific treatment parameters to the device enhances the convenience and usability of the system, promoting consistent and correct use by the patient.

[0018] Optionally, the input parameters include one or more (i) demographic parameters, (ii) one or more physiological parameters, (iii) one or more lifestyle parameters,

[0019] (iv) one or more environmental parameters relating to a current location of the user,

[0020] (v) one or more parameters relating to historical migraine attacks, or any combination thereof. In some embodiments, the input parameters comprises parameters from at least two, optionally at least three, optionally at least four, optionally all of the above-defined different parameter categories (i) to (v).

[0021] By incorporating a wide range of different inputs, a comprehensive understanding of the user's health status can be obtained, which can lead to more precise and effective treatment customization. The inclusion of at least some different parameters enables the system to identify and respond to potential triggers or patterns in migraine occurrences, potentially improving preventative care.

[0022] Optionally, the user-specific treatment parameters include one or more intertreatment parameters, and / or one or more intra-treatment parameters. Optionally, the one or more intra-treatment parameters include one or more parameters relating to a waveform signal of the electrical stimulation, optionally wherein the one or more intra-treatment parameters include a pulse amplitude, a pulse amplitude increase rate, a pulse repetition frequency, a pulse duration, a pulse width, a pulse shape, a treatment duration, or any combination thereof. Optionally, the inter-treatment parameters include one or more parameters relating to a time period between consecutive treatments, a time of day for a treatment, or any combination thereof. Customizing such parameters of the electrical stimulation signal allows for precise control over the therapy, which can maximize therapeutic benefits while minimizing discomfort. Furthermore, the system's ability to adjust inter-treatment parameters ensures that the user receives the optimal frequency of therapy, which can prevent overstimulation and contribute to the safety of the treatment, as well as helping users avoid potential migraine triggers by timing the therapy in anticipation of known high-risk periods, thereby acting as a preventative measure.

[0023] Optionally, at least one of the input parameters are received from an external device, optionally from a user device configured to measure the at least one input parameter. The ability to receive input parameters from external devices such as smartphones or smartwatches streamlines the data collection process, making it more convenient for users to provide necessary information for personalized treatment, without the need for a complex stimulation device with a large number of sensors.

[0024] Optionally, the system further comprises input means for receiving input from the user. Optionally, at least one of the input parameters is received by the system via the input means. Hence, the user can easily input data relating to e.g. previous migraine attacks, lifestyle activities and the like.

[0025] Optionally, the processor is further configured to receive feedback data from the user, optionally wherein the feedback data relates to a perceived efficiency of a performed treatment, a perceived comfort level of a performed treatment, whether and / or when a migraine attack has occurred, a severity of a migraine attack, or any combination thereof. Such tuning of the machine learning algorithms based on user feedback or treatment outcomes can lead to continuous improvement in therapy effectiveness, contributing to better long-term management of migraine symptoms.

[0026] Optionally, the processor is further configured to determine, in dependence on the received input parameters, a risk of a future migraine attack. Optionally, the user-specific treatment parameters are determined in dependence on the determined risk. The capability to generate migraine risk warnings enables proactive health management, allowing users to take preventative measures before the onset of a migraine. The provision of timely warnings can improve the user's quality of life by reducing the frequency and severity of migraine attacks through early intervention.

[0027] Optionally, the system further comprises notification means configured to notify the user of the determined risk. The integration of notification means encourages user engagement and interaction with the treatment system, which may lead to increased awareness of their health status and a more active role in managing their migraine condition.

[0028] Optionally, the processor is configured to use one or more machine learning algorithms to determine the user-specific treatment parameters, optionally wherein the processor is configured to train the one or more machine learning algorithms on received feedback data. In a second aspect, there is provided a method of adapting a migraine treatment to a specific user, the method comprising: receiving one or more input parameters specific to the user, determining one or more user-specific treatment parameters depending on the received one or more input parameters, and transmitting the user specific treatment parameters to a device for attachment to a forehead of a user, wherein the device comprises an electrical stimulation means for transcutaneous electrical stimulation of a trigeminal nerve of the user.

[0029] BRI EF DESCRIPTION OF TH E DRAWINGS

[0030] In order to best describe the manner in which the above-described embodiments are implemented, as well as define other advantages and features of the disclosure, a more particular description is provided below and is illustrated in the appended drawings. Understanding that these drawings depict only exemplary embodiments of the invention and are not therefore to be considered to be limiting in scope, the examples will be described and explained with additional specificity and detail through the use of the accompanying drawings in which:

[0031] Fig. 1 is a schematic block diagram of a migraine treatment system according to embodiments;

[0032] Fig. 2a is a schematic view of a stimulation device according to embodiments;

[0033] Fig. 2b is a block diagram of a stimulation device according to embodiments;

[0034] Fig. 3a is a schematic diagram of an exemplary electrical stimulation signal;

[0035] Fig. 3b is a schematic diagram of an exemplary electrical stimulation signal;

[0036] Fig. 3c is a schematic diagram of an exemplary electrical stimulation signal;

[0037] Fig. 3 is a schematic diagram of an exemplary electrical stimulation signal; and

[0038] Fig. 4 is a flowchart of a method of operating the migraine treatment system according to embodiments; and

[0039] Fig. 5 is a flowchart of a method of operating the migraine treatment system according to embodiments.

[0040] Further, in the figures like reference characters designate like or corresponding parts throughout the several figures. The first digit in the reference character denotes the first figure in which the corresponding element or part appears.

[0041] DETAI LED DESCRIPTION

[0042] Various embodiments of the disclosed methods and arrangements are discussed in detail below. While specific implementations are discussed, it should be understood that this is done for illustration purposes only. A person skilled in the relevant art will recognize that other components, configurations, and steps may be used without parting from the spirit and scope of the claimed invention. Hereinafter, certain embodiments will be described more fully with reference to the accompanying drawings. It will be apparent to those skilled in the art that various modifications and variations can be made without departing from the inventive concept. Other embodiments will be apparent to those skilled in the art from consideration of the specification and practice disclosed herein. It is to be understood that elements and materials may be substituted for those illustrated and described herein, parts and processes may be reversed or omitted, certain features may be utilized independently, and embodiments or features of embodiments may be combined, all as would be apparent to the skilled person in the art.

[0043] The embodiments herein are provided by way of example so that this disclosure will be thorough and complete, and will fully convey the scope of the inventive concept, and that the claims be construed as encompassing all modifications, equivalents and alternatives of the present inventive concept which are apparent to those skilled in the art to which the inventive concept pertains. If nothing else is stated, different embodiments may be combined with each other.

[0044] Although reference may be made to directions (e.g. left, right, up, down, upper, lower) as shown in the figures, it will be appreciated that these references are purely for illustrative purposes, and that embodiments are not limited to such directions.

[0045] The application provides systems and methods for migraine treatment based on external trigeminal nerve stimulation, e-TNS. It is noted that e-TNS has previously been shown to be effective for treatment of migraines and other headaches. The systems and methods encompassed herein, effect the e-TNS treatment via non-in- vasive transcutaneous electrical nerve stimulation (TENS) which, as opposed to percutaneous methods requiring electrode insertion, can be effected entirely in a non- invasive way, i.e. without surgery.

[0046] In particular, the application provides systems and methods for such migraine treatment that account for the variability in migraine triggers and responses to treatment among individuals. By incorporating user-specific input parameters, including demographics, health metrics, physiological metrics, historical migraine data, lifestyle data, as well as other forms of user-specific input data, the system aims to tailor neuromodulation treatments to the unique needs of each user. This personalized approach seeks to enhance the efficacy of migraine management by adapting treatment parameters based on user-specific data and user feedback, thereby addressing the limitations of conventional migraine therapies that often fail to account for individual differences.

[0047] Fig. 1 shows a system 100 for migraine treatment according to embodiments. The system 100 is configured to perform acute and / or preventive treatment of migraine and migraine attacks. The system 100 is further configured to predict the occurrence of potential future migraine attacks as will be described later. The system 100 comprises a stimulation device 101 and a processor 102. The stimulation device 101 is configured to provide neuromodulation by electrical stimulation of one or more nerves, while the processor 102 is configured to determine user-specific treatment parameters which are used by the stimulation device 101 when performing electrical stimulation. The stimulation device 101 will be described in more detail in relation to Fig. 2.

[0048] The processor 102 may be arranged separately from the stimulation device 101. For example, the processor 102 may be arranged at a remote server, in a cloud environment, or at another back-end device of the system. In some embodiments, the processor 102 runs on a user device 103, such as a user’s computer 104, smartphone 105 and / or smartwatch 106, e.g. as part of an application installed on said user device 103.

[0049] Alternatively, the processor 102 may form part of the stimulation device 101. For example, the stimulation device 101 may comprise one or more electronic circuits (e.g. located within a housing of the stimulation device 101) and forming the processor 102.

[0050] The processor 102 is configured to determine treatment parameters that are to be used by the stimulation device 101 when providing electrical stimulation to a user. That is, a processing module 107 of the processor 102 is configured to receive user-specific input parameters and determine appropriate treatment parameters in response thereto, as will be explained in more detail later. In some embodiments, the processor 102 is further configured to control the electrical stimulation provided by the stimulation device 101.

[0051] In addition to the processing module 107, the processor 102 may comprise a communication module 108 to allow the processor to communicate with the stimulation device 101 and / or any other devices with which the processor 102 interacts, including the user device(s) 103. The communication module 108 preferably comprises means for wirelessly connecting to a network, such as via WiFi or Bluetooth, to allow wireless communication with the stimulation device 101 and / or any other device.

[0052] However, it will be appreciated that embodiments also include wired communication means for communication between the processor 102 and the stimulation device 101.

[0053] The system 100, and in particular the processor 102 and / or the stimulation device 101 , may further be configured to communicate with one or more other devices, such as one or more user devices 103 or other external devices. The user device(s) 103 may be almost any kind of electronic device such as a smartphone 105, tablet, laptop or desktop computer 104, or even a television. Other examples of user devices 103 include wearable user devices or user devices provided with sensors and able to communicate with the system 100, such as smart watches 106, smart rings, fitness tracking bands or bracelets, smart scales, smart blood pressure monitors, smart heart rate monitors, headphones provided with bio-sensors, or the like. For example, the system 100 may communicate with an app or other program installed on such a user device 103 allowing the user to interact with the system 100 through said app. As another example, the system 100 may communicate with a back-end server or cloud associated with the user device 103 (such as a server used by the user device provider to store or log data relating to the user), e.g. via an API.

[0054] The system 100 may further comprise input means 109 allowing a user to interact with the system 100 and to enter data into the system 100. The input means 109 may comprise one or more buttons, a keyboard, a touchscreen, or the like. The input means 109 may, for example, be part of a user device 103 and utilise the user interface of said user device 103.

[0055] The system 100 may also comprise notification means 110 for notifying a user. The notification means 110 may be audio notification means (e.g. configured to emit a chime, a beep, or a ping), haptic notification means (e.g. notifying the user via vibration) and / or visual notification means such as a display or one or more lights (e.g. LEDs). In some embodiments, the notification means 110 are part of the user device 103, for example in the form of push notifications in an app on the user device 103.

[0056] Fig. 2 shows the stimulation device 101 in more detail. In particular, Fig. 2a shows a schematic view of the stimulation device 101 , while Fig. 2b shows a block diagram of the stimulation device 101.

[0057] The stimulation device 101 is a wearable device configured to be attached to a forehead of the user. Preferably, the simulation device 101 is configured easy and manual application to the user’s forehead in the supraorbital or supratrochlear region, thereby covering the afferent paths of the supratrochlear and supraorbital nerves of the ophthalmic branch of the trigeminal nerve.

[0058] The stimulation device 101 includes electrical stimulation means 201 that targets the trigeminal nerve. The electrical stimulation means 201 are configured to deliver transcutaneous electrical impulses to alleviate migraine symptoms. In particular, the stimulation device 101 may target the supraorbital and / or supratrochlear nerves of the ophthalmic branch of the trigeminal nerve. This is particularly advantageous because these nerves can easily be stimulated via non-invasive TENS through the skin of the user at the user’s forehead. The supraorbital and / or supratrochlear region is often preferred because it is typically hairless or comprises only a small amount of hair, thus facilitating application and removal of the stimulation device and the electrical stimulation means.

[0059] The electrical stimulation means 201 may include a plurality (e.g. one or more pairs) of strategically placed electrodes 202 that makes contact with the skin when the stimulation device 101 is worn by the user. These electrodes 202, possibly arranged in an array formation, ensure coverage and effective stimulation across the area associated with the trigeminal nerve. In particular, the electrodes 202 are effectively positioned near the trigeminal nerve for optimal therapeutic impact.

[0060] The electrode material, likely a conductive silicone or similar compound, provides durable conductivity while minimizing skin irritation. Additionally, the electrodes 202 may employ a self-adhesive conductive gel (e.g. a hydrogel) or self-adhesive conductive pads for application to the user’s forehead so as to enhance contact quality and reduce impedance during the treatment so as to provide consistent electrical delivery.

[0061] The electrical stimulation means 201 further comprise a signal generating means 203 (which may also be referred to as a pulse generator) comprising electronics for generating the required electrical signals used for the electrical stimulation and for supplying the electrodes by means of low-voltage electric pulses. Such electronics may include a microcontroller or a circuit board (e.g. a printed circuit board), a current pulse generator, and / or a voltage generator, and the design of such electronics will be well within the capabilities of the skilled person.

[0062] The stimulation device 101 may comprise, in addition to or as an alternative to the self-adhesive conductive gel provided on the electrodes 202, attachment means 204 to ensure that the stimulation device 101 stays attached to the forehead of the user during treatment. These attachment means 204 may comprise an adjustable head- band, elastic straps and / or adhesive pads, or the like.

[0063] The stimulation device 101 may further include an integrated power source 205 (e.g. a one or more batteries), which may be rechargeable, either wirelessly (e.g. inductively or capacitively) or via a cabled connection. It will be appreciated that in some embodiments, the stimulation device 101 may be powered via a wired connection to an external power source, such as the mains. Of course, the stimulation device 101 may further comprise a memory or the like for storing the required settings for stimulation and the like. In some embodiments, the stimulation device 101 may comprise a user interface (e.g. in the form of buttons and / or a touchscreen display) allowing the user to interact with the stimulation device 101 , for example to start and or end stimulation. In other embodiments, the user interface may alternatively or additionally be provided as part of the user device, and in particular in an app installed thereon. The stimulation device 101 may, of course, also have communication means 206 corresponding to the communication module 108 of the processor 102 to allow the previously described communication with the processor 102.

[0064] As already mentioned, the main purpose of the stimulation device 101 is to provide transcutaneous electrical stimulation of the trigeminal nerve of a user. The stimulation device 101 is accordingly configured to generate electrical signals with consecutive electrical pulses using treatment parameters that are particularly suitable for migraine treatment (or at least alleviation of migraine symptoms). “Treatment parameters” as used herein, comprise both intra-treatment properties or parameters and inter-treatment properties or parameters. Intra-treatment parameters may be defined as parameters defining (or at least partly defining) a single treatment session ans / or parameters used during a treatment session, and may include properties or parameters of the electrical stimulation, the consecutive electrical pulses, as well as the waveform formed by the pulses, such as pulse shape, pulse repetition frequency, pulse repetition period (i.e. a temporal period), pulse amplitude, pulse amplitude increase rate, pulse width, treatment session duration, and the like. Inter-treatment properties relate to properties associated with several consecutive treatment sessions, and may be defined as parameters defining (or at least partly defining) the interplay between several consecutive treatment sessions, such as inter-treatment time period (i.e. the time lapsed between two consecutive treatments), inter-treatment frequency, the time of day during which treatment is performed, or the like. As will be described later, these treatment parameters are in embodiments adjusted in dependence on user-specific input data to improve the treatment efficacy for users.

[0065] The pulse shape refers to the shape of a single pulse within the electrical signal which typically comprises a plurality of consecutive pulses. The pulses may have any shape suitable for migraine treatment. However, individual users may have different sensitivity levels to different waveforms and the pulse shape may accordingly be tailored to the specific user so as to increase efficacy while reducing discomfort during treatment. Studies have shown that biphasic pulses (and in particular symmetrical biphasic pulses such as rectangular symmetrical biphasic pulses and / or asymmetrical biphasic pulses such as rectangular asymmetrical biphasic pulses) and / or mo- nophasic waveforms are particularly suitable for migraine treatment. However, embodiments include other pulse shapes as well, including but not limited to polyphasic pulses, balanced asymmetrical pulses, unbalanced asymmetrical pulses, square wave pulses, triangular wave pulses, burst or impulse pulses, sine wave pulses, or the like. Here it is noted that in a biphasic waveform, current flows in both directions, and each electrode 202 therefore acts as a cathode (negative) during some part of the waveform as opposed to in monophasic waveforms where the same electrode 202acts as the cathode during the entire waveform signal.

[0066] The amplitude refers to the intensity level of the electrical signal, typically measured in terms of electrical current. A higher amplitude results in stronger stimulation, but a high intensity may also bring some discomfort to the user during treatment. Furthermore, the intensity may need to be adjusted in dependence on how good contact (i.e. conductivity) there is between the electrodes and the skin of the user. The amplitude may accordingly be adjusted to balance perceived discomfort with efficacy. In some embodiments, the amplitude may be between 0.1 milliampere and 200 milliampere, optionally between 0.5 milliampere and 128 milliampere, optionally between 1 milliampere and 50 milliampere, optionally between 2 milliampere and 40 milliampere, optionally between 3 milliampere and 30 milliampere, optionally between 4 milliampere and 28 milliampere, optionally between 5 and 25 milliampere, optionally around 16 milliampere.

[0067] The pulse amplitude may be increased over time (e.g. over several consecutive pulses) to reduce the discomfort experienced by the user as the user will become gradually accustomed to the intensity of the electrical stimulation. The rate at which the pulse amplitude increases (e.g. from zero amplitude to the above-described amplitudes) may be less than 480 microampere per second, optionally less than 240 microampere per second, optionally less than 120 microampere per second, optionally less than 60 microampere per second, optionally less than 30 microampere per second, optionally less than 20 microampere per second.

[0068] The pulse repetition frequency refers to how many pulses are delivered per second. The choice of pulse repetition frequency can affect the nerve fibre activation resulting in different perceived sensations and therapeutic effects. In embodiments, the pulse repetition frequency may be between 10 and 300Hz, optionally between 20 and 200Hz, optionally between 30 and 150Hz, optionally around 60 Hz or 120Hz.

[0069] The pulse width refers to the duration of a single pulse, and in particular to the duration of a single pulse’s on-phase. Studies have shown that narrow pulses may target specific nerve fibres, while wider pulses affect a broader range of nerve activity. The perceived efficacy of the treatment method may therefore be increased by tailoring the pulse width to specific users. In embodiments, the pulse width may be between 1 microsecond and 500 microseconds, optionally between 4 microseconds and 240 microseconds, optionally between 8 microseconds and 120 microseconds, optionally between 12 microseconds and 60 microseconds, optionally between 16 microseconds and 50 microseconds, optionally between 20 microseconds and 40 microseconds, optionally between 25 microseconds and 35 microseconds.

[0070] The duration of treatment refers to the length of time for which a stimulation cycle (comprising several consecutive pulses) is applied. Shorter durations may prevent overstimulation, while longer periods might be necessary for more pronounced effects. In embodiments, the treatment duration may be at least 5 minutes, optionally at least 10 minutes, optionally at least 15 minutes, optionally at least 20 minutes, optionally at least 25 minutes, optionally at least 30 minutes, optionally at least 45 minutes, optionally at least 60 minutes, optionally at least 90 minutes. In some embodiments, the treatment duration may be between 10 and 30 minutes, optionally between 15 and 25 minutes. In some embodiments, the treatment duration may be between 40 and 80 minutes, optionally between 50 and 70 minutes.

[0071] In some embodiments, a biphasic pulse shape (e.g. a symmetrical biphasic pulse shape, a rectangular symmetrical biphasic pulse shape, an asymmetrical biphasic pulse shape, or a rectangular asymmetrical biphasic pulse shape) is used together with a pulse width of between 12 microseconds and 60 microseconds, a pulse amplitude between 5 milliampere and 16 milliampere, and a treatment duration of at least 10 minutes.

[0072] It will be appreciated that embodiments are not limited to the above parameter values and ranges, but include any system or method using the inventive concept and falling within the spirit and scope of the claims.

[0073] Exemplary electrical stimulation signals are shown in Figs. 3a to 3d. In particular, Fig. 3a shows a first stimulation signal using monophasic pulses, Fig. 3b shows a second stimulation signal using biphasic pulses (rectangular or balanced symmetrical, balanced asymmetrical, and / or unbalanced asymmetrical) as, Fig. 3c shows a third stimulation signal using polyphasic pulses, and Fig. 3d shows a fourth stimulation signal using asymmetrical biphasic pulses.

[0074] By setting these waveform parameters appropriately, in dependence on user-specific input data, the system 100 achieves customizable treatment regimens that can adapt to the user's unique physiological and therapeutic requirements.

[0075] Fig. 4 shows a method of determining or setting the treatment parameters in dependence on user-specific input data.

[0076] In step 401 , the system 100 receives one or more input parameters specific to the user who is to undergo treatment. In other words, the system 100 gathers comprehensive user-specific data that may be relevant for the treatment of migraine. In particular, the input parameters may include one or more demographic parameters, one or more physiological parameters, one or more lifestyle parameters, one or more environmental parameters (associated with the present location of the user), one or more historical migraine parameters relating to historical migraine attacks or episodes experienced by the user, one or more measured physiological parameters, one or more metrological parameters, one or more self-evaluation parameters, one or more test-based parameters, or any combination thereof.

[0077] The input parameters may be measured by one or more sensors and / or received from one or more external devices (such as the one or more user devices 103 and / or one or more servers or clouds used to store data measured or otherwise recorded by the user devices). For example, one or more input parameters may be measured by a smart watch 106 and transmitted to the system 100. Additionally, or alternatively, one or more of the input parameters may be input into the system 100 by the user via the input means 109 (e.g. by a user logging migraine history and / or food intake into an app on a user device 103 such as a smartphone 105). Yet additionally, or alternatively, one or more of the input parameters may be determined in dependence on a location of the user, where the location may be determined independence on GPS data associated with a user device 103 (and / or the stimulation device 101) and transmitted to the system 100. Based on the location, the system 100 may, for example, determine a weather condition or an air pressure using current metrological data or the like.

[0078] The input parameters may include one or more demographic parameters. The demographic parameters may include any one or more of the user’s height, weight, age, gender, ethnicity, or the like. These may be recorded by the user via the input means 109 and stored in the system 100 for use in determination of the user-specific treatment parameters.

[0079] The input parameters may additionally or alternatively include one or more physiological parameters, including but not limited to heart rate, blood pressure, blood oxygen levels, stress level, skin temperature, or any combination thereof. Such parameters may be measured by a user device 103 (e.g. a smart watch 106) or any other suitable external device or sensor. Although, the stress level may not be measured directly, it may be deduced from other physiological parameters, lifestyle parameters, or the like.

[0080] The input parameters may additionally or alternatively include one or more lifestyle parameters such as an activity level of the user, dietary routines of the user, sleep patterns of the user, whether the user has skipped any meals or food intake (or conversely whether the user has eaten breakfast, lunch, and / or dinner), coffee and / or alcohol consumption of the user, or any combination thereof. Some of these parameters (such as activity level and / or sleep pattern) may be measured by, for example, a smart watch 106, while other parameters may be recorded by the user via the input means 109.

[0081] The input parameters may additionally or alternatively include one or more environmental parameters such as one or more metrological parameters including but not limited to air temperature, air pressure, weather condition, or the like, at the location where the user is currently present. Such environmental or metrological parameters may be determined in dependence on the location of the user, which location may be determined independence on GPS data associated with a user device 103 (and / or the stimulation device 101) and transmitted to the system 100. Based on the location, the system 100 may, for example, determine a weather condition or an air pressure using current metrological data or the like. Alternatively, the system 100 may comprise and / or interact with one or more sensors for measuring the relevant environmental or metrological parameters.

[0082] The input parameters may additionally or alternatively include one or more parameters relating to a user’s previous migraine attack(s). Such parameters may include migraine characteristics, severity, start time of the migraine attack(s), duration of the migraine attack(s), pain intensity, type of headache (e.g. if it is unilateral, throbbing, if an aura is present or not), if vomiting and / or nausea occurred, if phonophobia and / or photophobia was present, or any combination thereof. These parameters may be in the form of self-evaluation parameters where the user is instructed to self-evaluate one or more of the above-mentioned characteristics of one or more previous migraine attacks.

[0083] The one or more input parameters may additionally or alternatively comprise one or more test-based input parameters, wherein the test-based input parameters are one or more result parameters from a test which the user has undertaken.

[0084] To this effect, the system may provide the user with a test, e.g. at a user interface of a user device, which the user is instructed to perform. The result(s) from said test is received (e.g. recorded by the user device as the user interacts with the user interface), and may be transmitted to the system for analysis. In some embodiments, the system may prompt a user to perform the test, e.g. by transmitting a notification to the user device.

[0085] The test may be, or comprise, a visual perception test. Studies have shown that visual perception capabilities can be an indicator for migraine onset. Hence, the inventors have realised that visual perception tests may be used to objectively assess and predict the risk of migraine onset in a user. In embodiments, the visual perception test may be displayed (i.e. visually provided) at the user device.

[0086] In a general sense, visual perception tests measure a user’s ability to correctly interpret and process complex or subtle visual stimuli, often pushing the limits of their sensory integration capacities. For the purposes of migraine prediction according to embodiments, these tests are designed to probe inhibitory and excitatory balances within the visual system by quantifying responses to stimuli that rely heavily on functional inhibitory circuits. Abnormal processing may serve as a predictive biomarker for an individual's susceptibility to migraine attacks, and a high degree of visual hyperexcitability, as measured by a visual perception test (e.g., a heightened perceptual response and / or a broadened temporal window of summation) may correlate directly with an elevated risk profile for migraine onset.

[0087] In preferred embodiments, the visual perception test(s) may be contrast-based visual perception test(s). Contrast processing is a fundamental operation of the visual cortex, and disruptions in the inhibitory mechanisms responsible for separating and defining visual boundaries are a key marker of cortical hyperexcitability in mi- graineurs.

[0088] The measurements or results derived from these tests quantify the degree to which a user’s visual system exhibits impaired spatial or temporal inhibition. These quantitative results, such as a statistically significant reduction in performance (e.g. in surround suppression magnitude and / or an enhanced contrast perception threshold), therefore provide non-invasive, objective data points that may be integrated into a risk prediction algorithm for a migraine episode.

[0089] In some embodiments, the contrast-based visual perception test may be a Chubb illusion test. This test, also known as the contrast-contrast illusion test, measures a subject’s perception of a low-contrast target's contrast when it is placed against a background that varies in local contrast (luminance or texture). In particular, the test measures the user’s perceived contrast of a low-contrast target stimulus (e.g. a Gabor patch) when it is presented against two or more different backgrounds: such as a (e.g. uniform) low-contrast field and a (e.g. highly textured) high-contrast field.

[0090] The Chubb illusion test involves presenting a low-contrast target stimulus (e.g. a small Gabor patch or simple sine-wave grating) that is embedded within two different backgrounds: a uniform, low-contrast background and a highly textured, high-con- trast background (e.g., a high-contrast pattern of random dots, static noise, or checkerboard pattern). The physical contrast of the target remains constant in both conditions. The user is tasked with comparing the perceived contrast of the target in the textured environment versus the uniform environment.

[0091] For a normal user, the high-contrast, textured background induces strong surround suppression via lateral inhibition, causing the perceived contrast of the target to be significantly reduced (i.e., the target appears less salient). A user with migraine onset, on the other hand, often exhibit a failure or reduction of surround suppression. This means that when the migraine-prone user views the target against the textured background, they perceive the target's contrast as higher than or equal to its perception against the uniform background (a reduced or inverted illusion magnitude).

[0092] Based on the results of the visual perception test, and in particular based on changes in the results from a baseline or the like, the system can quantify the risk of migraine onset. For example, if the results to the test get progressively further away from the baseline (which may correspond to the result of a normal user, or the result of the user when migraine is not imminent), the system may deduce that a migraine attack is approaching and calculate a risk score for a migraine attack occurring within a predetermined time period.

[0093] Returning to the input parameters more generally, the one or more input parameters comprise at least two different types of parameters selected from a group of parameter types comprising: measured physiological parameters, metrological parameters, self-evaluation parameters, and test-based parameters. Hence, the performance of the system may be improved, for instance in relation to a predictability accuracy and / or a treatment efficacy. The system 100 may use instantaneous input parameter values or the most recent input parameters values available. For example, the system 100 may request updated input parameter values (e.g. from the one or more user devices) prior to commencement of a treatment.

[0094] Alternatively, the system 100 may use input parameters recorded over a recent period of time, such as input parameter values recorded / measured / received during the last 6 hours, 12 hours, 24 hours, 48 hours, or the like. For example, the time period may be a sliding time period, e.g. immediately preceding the time of evaluation or analysis. Hence, the system 100 can see if and how the input parameter values have changed over the recent period of time which may influence how the user-specific treatment parameters should be determined and defined. In step 403, the processor 102 uses the input parameters, that were received by the processor 102 or otherwise obtained in step 401 , to customize treatment settings. In particular, the processor 102 determines or adjusts one or more user-specific treatment parameters in dependence on the received one or more user-specific input parameters. Hence, by integrating the user-specific input data, the processor 102 can determine more optimal treatment parameters to improve the efficacy of the treatment for the specific user.

[0095] In particular, the processor 102 uses machine algorithms (and in particular random forest algorithms), potentially in combination with standard statistical analysis, predictive analytics, Al, ranking algorithms, deep learning, big data techniques, and / or other rule-based algorithms to select or determine appropriate treatment parameters or adjusts the stimulation regime to improve the efficacy of treatment and / or reduce the discomfort experienced by the user. In other words, the input parameters are input to a model or algorithm that analyses and adjusts treatment parameters according to the data of the user.

[0096] The one or more treatment parameters that may be determined by the processor 102 in dependence on the received input parameters may comprise one or more in- tra-treatment parameters and / or one or more inter-treatment parameters. The one or more intra-treatment parameters may include parameters of a single electrical stimulation treatment session, such as pulse shape, pulse repetition frequency, pulse repetition period, pulse amplitude, pulse amplitude increase rate, pulse width, treatment duration, or any combination thereof. The one or more inter-treatment parameters may include parameters relating to several consecutive treatment sessions, such as inter-treatment time period, inter-treatment frequency, the time of day during which treatment is performed, or any combination thereof.

[0097] For example, the processor 102 may, in dependence on the input parameters, select a pulse shape from a set of pulse shapes (including e.g. biphasic pulses, symmetrical biphasic pulses, rectangular symmetrical biphasic pulses, asymmetrical biphasic pulses, rectangular asymmetrical biphasic pulses, monophasic pulses, poly- phasic pulses, balanced asymmetrical pulses, unbalanced asymmetrical pulses, square wave pulses, triangular wave pulses, burst or impulse pulses, and / or sine wave pulses). For example, the processor 102 may, in dependence on the input parameters, additionally, or alternatively, determine the pulse amplitude, e.g. by increasing or decreasing the pulse amplitude from a default or reference value or from a previous value used in treatment of the specific user. For example, the processor 102 may, in dependence on the input parameters, yet alternatively or additionally, determine the pulse width and / or pulse repetition frequency, e.g. by increasing or decreasing the pulse width and / or pulse repetition frequency from a default or reference value or from a previous value used in treatment of the specific user.

[0098] Using the above-mentioned algorithms, and in particular machine learning algorithms, the system 100 may accordingly correlate the success of various stimulation parameters to outcomes across a population of users. Based upon sensed data, measurements made by a user, or feedback provided by users (as will be explained later), the system 100 may thus recommend certain stimulation parameters that are more likely to work best for individual users. In particular, the system 100 and the machine learning algorithms can recognise patterns in the data to allow it to determine appropriate treatment parameters and treatment parameter values.

[0099] Furthermore, by employing machine learning, the system 100 can adjust over time, providing increasingly more precise and effective treatments that considers the unique response and conditions of each user. This adaptive capability ensures treatment efficacy while enhancing user satisfaction.

[0100] The machine learning algorithms may be based on neural networks, or any other suitable machine learning algorithm including but not limited to linear regression, decision trees, random forest, K-means clustering, K-nearest neighbors, and / or support vector machines. In particular, the machine learning algorithm utilizing neural networks is particularly effective at recognizing patterns between certain user-specific input parameter values and the efficacy of the treatment, and making decisions in dependence on the recognized patterns.

[0101] Embodiments of the system 100 can be trained on (i) data from group studies of TENS migraine treatments, (ii) data recorded by healthcare officials and / or patients undergoing TENS or e-TNS treatments using non-personalised or predefined treatment parameters, (iii) data collected during patients’ stimulation session and / or (iv) the efficacy associated with selected amplitudes and measured impedances during each session as indicated by user feedback after each treatment session.

[0102] In particular, the system may receive feedback from the user. Such user feedback may comprise information about (i) if a migraine attack occurred, (ii) one or more characteristics of the migraine attack, such as the severity and / or duration of the migraine attack, (iii) how well the treatment worked, or the like. The feedback may be received via the user interface at the user device. For example, the system may, after a treatment session has been completed, send a notification to the user device prompting the user to give feedback. Embodiments may therefore be continuously improved and further trained by taking feedback from users into account.

[0103] Step 403 may further comprise issuing a notification to the user, e.g. via the notification means 110. The notification may instruct or advise the user to initiate a treatment session (e.g. at a given time and / or day) in accordance with determined userspecific inter-treatment parameters. In step 405, the determined user-specific treatment parameters are transmitted to the stimulation device 101.

[0104] In step 407, the stimulation device 101 performs electrical stimulation according to the determined treatment parameters.

[0105] In step 409, the system 101 receives feedback from the user about the performed treatment. In particular, the system 101 may prompt the user, e.g. via the notification means 110, to provide feedback, e.g. via the input means 109, after a treatment session has been completed. The feedback may include data about whether a migraine attack has occurred (e.g. between two preventive treatment sessions), when any migraine attack occurred, the severity of any migraine attack, how effective an acute treatment session was in alleviating migraine symptoms, how comfortable / discom- fortable the treatment session was, or the like. Said feedback may be stored in combination with the relevant treatment parameters, allowing the machine learning algorithms to continuously improve their performance based on said feedback data.

[0106] Fig. 5 shows another method of operating the system 100 according to embodiments in which the system 100 is further configured to predict future migraine attacks and perform treatment in dependence thereon. It will be appreciated that Figs. 4 and 5 may be combined or performed independently.

[0107] The systems 100 and methods according to embodiments may thus not merely be aimed at treating migraines, but also at improving prophylactic measures and risk assessment. In particular, the processor 102 may be configured to determine the risk of a future migraine attack (e.g. if a migraine attack is likely to occur, when a migraine attack is likely to occur, and / or the likely severity of a future migraine attack).

[0108] In step 501 , the system 100 receives one or more input parameters specific to a user. This step substantially corresponds to step 401 in Fig. 4.

[0109] The system 100 may receive input parameters recorded over a recent period of time, such as input parameter values recorded / measured / received during the last 6 hours, 12 hours, 24 hours, 48 hours, or the like.

[0110] In step 503, the processor 102 determines, e.g. using the previously described machine learning algorithms, a migraine attack risk score in dependence on the received input parameters. The risk score may indicate the risk of a migraine attach occurring within a predetermined time period, such as within 36 hours, optionally within 30 hours, optionally 26 hours, optionally within 24 hours, optionally within 22 hours, optionally within 18 hours, optionally within 12 hours. In other words, the system 100 can predict whether a migraine attack is likely to occur. Studies have shown that at least some of the above-discussed input parameters may be used to predict whether a migraine attack will occur. These studies include “Forecasting migraine with machine learning based on mobile phone diary and wearable data" by A. Stub- berud et al, and “Using Sleep Time Data from Wearable Sensors for Early Detection of Migraine Attacks" by P. Siirtola et al, both of which are incorporated herein by reference in their entirety. Hence, the machine learning algorithms according to embodiments may recognise patterns in the input parameter values that indicate or correlate to a high risk of an imminent or impending migraine attack.

[0111] The input parameters used for said prediction and computation of a risk score preferably includes one or more test-based parameters, and in particular one or more results from a visual perception test (such as a contrast-based visual perception test, e.g. a Chubb illusion test).

[0112] Based on the input parameters, and in particular the results of the visual perception test, such as changes in the results from a baseline or the like, the system can quantify the risk score for migraine onset. For example, if the results to the test get progressively further away from the baseline (which may correspond to the result of a normal user, or the result of the user when migraine is not imminent), the system may deduce that a migraine attack is approaching and calculate a risk score for a migraine attack occurring within a predetermined time period following the time of evaluation.

[0113] The risk score may be compared to a threshold score.

[0114] In step 505, the user may notified, e.g. via the notification means 110, of the determined risk level. Step 505 may further comprise, if the risk score exceeds the threshold score, instructing or prompting the user, e.g. as part of the notification, to initiate a treatment session (e.g. immediately, within a couple of hours (say), or at a given time and / or day) in dependence on the determined risk score. For example, if there is a high risk of a migraine attack, the system 100 may instruct the user to perform preventive treatment before any migraine attack starts.

[0115] In step 507, one or more user-specific treatment parameters is determined and / or adjusted in dependence on the determined risk score and / or in dependence on the input parameters as previously discussed in relation to Fig. 4. As an example, if the determined risk is high, the system 100 may use a more intensive (preventive) treatment, e.g. by increasing the pulse amplitude and / or the treatment duration. As another example, the system 100 may adjust one or more inter-treatment parameters such as the inter-treatment time period and / or a time of day for treatment.

[0116] After step 505 and / or step 507, a treatment session may be performed in accordance with step 407 of Fig. 4 and / or feedback may be collected in accordance with step 409 of Fig. 4. Such feedback may additionally, or alternatively, include information relating to the accuracy of the prediction and / or risk score, e.g. if a migraine attack occurred, when it occurred, or the like.

[0117] Although the application has been described in the context of migraine treatment, it will be appreciated that embodiments may also be used to treat other symptoms and disorders involving the central nervous system and in particular the cranial nerves such as the trigeminal nerve, including but not limited to, other headaches (such as tension headache, stress headache, and / or cluster headache), neuropathic pain, facial pain, posttraumatic stress disorder (PTSD), anxiety, epilepsy, sleep disorders or somnipathies such as obstructive sleep apnea, depression, bipolar disorder, postural orthostatic tachycardia syndrome (POTS), fibromyalgia, myalgic encephalomyelitis and chronic fatigue syndrome (ME / CFS), stroke and rehabilitation of motor function, multiple sclerosis (MS), and the like.

[0118] The various embodiments described above are provided by way of illustration only and should not be construed to limit the invention. For example, the principles herein may be applied to any suitable treatment system or method. Those skilled in the art will readily recognize various modifications and changes that may be made to the present invention without following the example embodiments and applications illustrated and described herein, and without departing from the scope of the present disclosure.

[0119] Throughout this specification, the word “may” is used in a permissive sense (i.e. meaning having the potential to), rather than in the mandatory sense (i.e. meaning must).

[0120] Throughout this specification, the words “comprise”, “include”, and variations of the words, such as “comprising” and “comprises”, “including”, “includes”, do not exclude other elements or steps.

[0121] As used throughout this specification, the singular forms “a”, “an”, and “the”, include plural referents unless explicitly indicated otherwise. Thus, for example, reference to “an” element includes a combination of two or more elements, notwithstanding use of other terms and phrases for one or more elements, such as “one or more” or “at least one”.

[0122] The term “or” is, unless indicated otherwise, non-exclusive, i.e. encompassing both “and” and “or”. For example, the feature “A or B” includes feature “A”, feature “B” and feature “A and B”.

[0123] Unless otherwise indicated, statements that one value or action is “based on”, “in response to” and / or “in dependence on” another condition or value or action, encompass both instances in which the condition or value or action is the sole factor and instances where the condition or value or action is one factor among a plurality of factors.

[0124] Unless otherwise indicated, statements that “each” instance of some collection have some property should not be read to exclude cases where some otherwise identical or similar members of a larger collection do not have the property, i.e. each does not necessarily mean each and every.

[0125] Embodiments include the following numbered clauses:

[0126] 1 . A system for migraine treatment by transcutaneous electrical stimulation of a trigeminal nerve of a user, the system comprising: a stimulation device for attachment to a forehead of a user, wherein the stimulation device comprises an electrical stimulation means for transcutaneous electrical stimulation of the trigeminal nerve; and a processor configured to: receive one or more input parameters specific to the user, determine one or more user-specific treatment parameters depending on the received one or more input parameters, and transmitting the user-specific treatment parameters to the device.

[0127] 2. The system according to clause 1 , wherein the input parameters include one or more demographic parameters, one or more physiological parameters, one or more lifestyle parameters, one or more environmental parameters relating to a current location of the user, one or more parameters relating to historical migraine attacks, or any combination thereof.

[0128] 3. The system according to clause 1 or 2, wherein the user-specific treatment parameters include one or more inter-treatment parameters, and / or one or more intra-treatment parameters.

[0129] 4. The system according to clause 3, wherein the one or more intra-treatment parameters include one or more parameters relating to a waveform signal of the electrical stimulation, optionally wherein the one or more intra-treatment parameters include a pulse amplitude, a pulse amplitude increase rate, a pulse repetition frequency, a pulse duration, a pulse width, a pulse shape, a treatment duration, or any combination thereof.

[0130] 5. The system according to clause 3 or 4, wherein the inter-treatment parameters include one or more parameters relating to a time period between consecutive treatments, a time of day for a treatment, or any combination thereof.

[0131] 6. The system according to any preceding clause, wherein at least one of the input parameters are received from an external device, optionally from a user device configured to measure the at least one input parameter.

[0132] 7. The system according to any preceding clause, wherein the system further comprises input means for receiving input from the user.

[0133] 8. The system according to clause 7, wherein at least one of the input parameters is received by the system via the input means.

[0134] 9. The system according to any preceding clause, wherein the processor is further configured to receive feedback data from the user, optionally wherein the feedback data relates to a perceived efficiency of a performed treatment, a perceived comfort level of a performed treatment, whether and / or when a migraine attack has occurred, a severity of a migraine attack, or any combination thereof. 10. The system according to any preceding clause, wherein the processor is further configured to determine, in dependence on the received input parameters, a risk of a future migraine attack.

[0135] 11 . The system according to clause 10, wherein the system further comprises notification means configured to notify the user of the determined risk.

[0136] 12. The system according to clause 10 or 11 , wherein the user-specific treatment parameters are determined in dependence on the determined risk.

[0137] 13. The system according to any preceding clause, wherein the processor is configured to use one or more machine learning algorithms to determine the user-specific treatment parameters, optionally wherein the processor is configured to train the one or more machine learning algorithms on received feedback data.

[0138] 14. A method of adapting a migraine treatment to a specific user, the method comprising: receiving one or more input parameters specific to the user, determining one or more user-specific treatment parameters depending on the received one or more input parameters, and transmitting the user specific treatment parameters to a device for attachment to a forehead of a user, wherein the device comprises an electrical stimulation means for transcutaneous electrical stimulation of a trigeminal nerve of the user.

Claims

23CLAI MS1 . A system for migraine treatment by transcutaneous electrical stimulation of a trigeminal nerve of a user, the system comprising: a stimulation device for attachment to a forehead of a user, wherein the stimulation device comprises an electrical stimulation means for transcutaneous electrical stimulation of the trigeminal nerve; and a processor configured to: receive, over a first predetermined time period, input parameter values associated with the user, wherein the input parameter values relate to one or more input parameters, wherein at least one of the input parameters is a result parameter of a visual perception test performed by the user, determine, in dependence on the received input parameter values, a risk score of a migraine attack occurring within a second predetermined time period, in response to the risk score exceeding a threshold, transmit a signal to a user device notifying the user that treatment is to be performed, determine one or more user-specific treatment parameters depending on the received one or more input parameter values, transmitting the user-specific treatment parameters to the stimulation device, receive feedback from the user, wherein the feedback comprises data relating to the occurrence of a migraine attack during the second predetermined time period and / or data relating to a perceived efficacy of performed treatment, wherein the risk score and the user-specific treatment parameters are determined, using machine learning algorithms, in dependence on previously received feedback from the user.

2. The system according to claim 1 , wherein the visual perception test is a contrast-based visual perception test, optionally a Chubb illusion test.

3. The system according to claim 1 or 2, wherein the system is configured to communicate with the user device, wherein the system is configured to transmit a signal to the user device causing the user device to present, at a user interface or display, the visual perception test to the user at one or more occasions during the first predetermined time period.

4. The system according to any preceding claim, wherein the one or more input parameters comprise at least two different types of parameters selected froma group of parameter types comprising: measured physiological parameters, metrological parameters, self-evaluation parameters, and test-based parameters.

5. The system according to any preceding claim, wherein the processor receives a plurality of input parameter values for each input parameter over the first predetermined time period.

6. The system according to any preceding claim, wherein the first predetermined time period is a sliding time period that precedes the second predetermined time period.

7. The system according to any preceding claim, wherein the first predetermined time period is between 4 and 8 hours, optionally between 5 and 7 hours, optionally around 6 hours, and wherein the second predetermined time period is between 12 and 36 hours, optionally between 18 and 30 hours, optionally between 22 and 26 hours, optionally around 24 hours.

8. The system according to any preceding claim, wherein the user-specific treatment parameters include one or more inter-treatment parameters, and / or one or more intra-treatment parameters, optionally wherein the one or more intra-treatment parameters include one or more parameters relating to a waveform signal of the electrical stimulation, optionally wherein the one or more intra-treatment parameters include a pulse amplitude, a pulse amplitude increase rate, a pulse repetition frequency, a pulse duration, a pulse width, a pulse shape, a treatment duration, or any combination thereof, optionally wherein the inter-treatment parameters include one or more parameters relating to a time period between consecutive treatments, a time of day for a treatment, or any combination thereof.

9. A method of controlling a system comprising a stimulation device for migraine treatment, the method comprising: receiving, over a first predetermined time period, input parameter values associated with the user, wherein the input parameter values relate to one or more input parameters, wherein at least one of the input parameters is a result parameter of a visual perception test performed by the user, determining, in dependence on the received input parameter values, a risk score of a migraine attack occurring within a second predetermined time period,in response to the risk score exceeding a threshold, transmitting a signal to a user device notifying the user that treatment is to be performed, determining one or more user-specific treatment parameters depending on the received one or more input parameter values, and transmitting the user specific treatment parameters to the stimulation device, receiving feedback from the user, wherein the feedback comprises data relating to the occurrence of a migraine attack during the second predetermined time period and / or data relating to a perceived efficacy of performed treatment, wherein the risk score and the user-specific treatment parameters are determined, using machine learning algorithms, in dependence on previously received feedback from the user.

10. The method according to claim 9, wherein the method further comprises: presenting, at a user interface or display, the visual perception test to the user at one or more occasions during the first predetermined time period; receiving one or more responses from the user in response to the visual perception test, computing one or more result parameter values in dependence on the one or more responses.

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