Treatment parameters for acoustic stimulation

Abstract

The present invention relates to the field of cell stimulation by mechanical energy, in particular by acoustic energy, for example by ultrasound stimulation such as focused ultrasound (FUS). It relates to a method for determining a set of subject-specific treatment parameters for acoustic stimulation and a method for verifying a set of treatment parameters for acoustic stimulation. The method for determining a set of subject-specific treatment parameters comprises the steps of generating subject-specific data and determining a target field distribution in a body part, wherein the step of generating subject-specific data comprises measuring geometrical properties of the body part. It also comprises the step of selecting a set of treatment parameters from at least two different sets of treatment parameters, wherein the selection is performed before the step of applying any set of treatment parameters to the body part. The method for verifying a set of treatment parameters for acoustic stimulation comprises the steps of determining a target field distribution of an acoustic field in a body part, receiving a set of relevant treatment parameters for at least one transducer, generating a subject-specific 3D model of the body part, and determining the difference between the target field distribution and the field distribution determined in the subject-specific 3D model.

Description

Technical Field

[0001] The present invention relates to the field of cell stimulation by mechanical energy, in particular by acoustic energy, for example by ultrasound stimulation such as focused ultrasound (FUS). It relates to a method for determining treatment parameters, a method for verifying and (if necessary) adjusting treatment parameters, an apparatus associated with a computer-implemented method for determining a set of subject-specific treatment parameters for acoustic stimulation and an apparatus associated with a method for verifying a set of treatment parameters for acoustic stimulation. Background Art

[0002] US2017 / 0291044 A1 discloses an ultrasonic deep brain stimulation method and an ultrasonic deep brain stimulation system. The disclosed method is a time reversal method, comprising the following steps: creating a 3D digital model of the head from image data of the head of an animal or a person requiring ultrasonic deep brain stimulation, creating a 3D digital model of an ultrasonic transducer array, and determining the voltage signal to be applied to the "real" ultrasonic transducer array for generating a specific ultrasonic field in the brain by placing a virtual sound source at one or more positions that need to be focused, simulating the propagation behavior of ultrasonic waves emitted from the virtual sound source in the 3D digital model of the head, and simulating the voltage signal of the ultrasonic transducer array when the ultrasonic wave propagates to the virtual spatial position where the ultrasonic transducer array is located. In one embodiment, a skull model is printed, a "real" sound source is placed at one or more positions that need to be focused, and the voltage generated by the ultrasonic transducer array arranged on the printed skull is measured to determine the voltage signal to be applied to the ultrasonic transducer array.

[0003] Independent of the embodiment of the ultrasonic deep brain stimulation method disclosed in US2017 / 0291044 A1, the head of an animal or a human is placed in a magnetic resonance imaging (MRI) system during ultrasound transmission to observe and adjust the position displacement and shape change of the focus.

[0004] The prior art method for stimulating cells by sound waves disclosed in US2017 / 0291044 A1 has various disadvantages. In particular, the determination of the treatment parameters involves complex simulations and / or complex measurements, which can only be configured and performed by experts. Furthermore, the need to place the head of an animal or a person in an MRI system in this prior art method prevents the method from being used outside specialized medical institutions and for medical cases that are generally rated as less severe, such as those related to muscle tension, migraines, tension / relaxation, learning problems, sleep problems, etc. Furthermore, the system components for performing the prior art method for stimulating cells by sound waves have a very specific design, can only be adapted to the medical case in a limited way, and have very limited user-friendliness.

[0005] In other words, the prior art methods and devices are too complex, too expensive, and too limited in design and implementation to be used by the wider public and / or for a wide range of applications, meaning a wide range of medical and non-medical cases.

[0006] Applications in the field of brain therapy, trauma therapy (e.g. bone stimulation, muscle stimulation), pain therapy (e.g. chronic pain, back pain, migraine) or drug delivery (e.g. local drug delivery, gene therapy) are examples of applications related to medical use cases. Applications in the field of health (e.g. relaxation, less severe insomnia, migraine and muscle tension, etc.) or in the field of learning are examples of applications related to non-medical use cases. Summary of the invention

[0007] It is an object of the present invention to overcome the disadvantages of prior art methods and devices.

[0008] In particular, a first object of the present invention is to provide a method and related apparatus for determining a set of subject-specific treatment parameters for acoustic wave stimulation, which can be used by the wider public for a wide range of applications.

[0009] A second object of the present invention is to provide a method and associated apparatus for verifying and (if necessary) adjusting a set of treatment parameters for acoustic wave stimulation that can be used by the wider public for a wide range of applications.

[0010] These objects are achieved by a computer-implemented method and associated apparatus for determining a set of subject-specific treatment parameters for acoustic wave stimulation and a method and associated apparatus for validating a set of treatment parameters for acoustic wave stimulation.

[0011] Independently of the aspects of the present invention and embodiments thereof, if not explicitly stated otherwise, the following terms have the following meanings:

[0012] A goal (eg, a set of treatment parameters or a body part) is "subject-specific" if it is relevant to an individual (human or animal) subject (eg, a patient). For example, steps may be taken to ensure that the goal is relevant or adapted to the individual patient.

[0013] A "set of treatment parameters for acoustic stimulation" ("treatment parameters" for short) comprises operating parameters of a transducer for generating a sound field in the body part to be stimulated and information about the arrangement of the transducer relative to the body part (relative to its physical 3D model, as the case may be). The latter may comprise, for example, information about at least one of the orientation of the transducer relative to the body part, the contact pressure between the transducer and the body part and the type of transducer to be used. For example, the orientation of the transducer may be given by the angle between the axis of the transducer (in particular the oscillation axis) and the surface normal of the body part at the location where the transducer is arranged. Frequency, intensity, pulse duration, pulse length, pulse repetition rate are examples of operating parameters.

[0014] If more than one transducer is used, the treatment parameters may also include information about the arrangement of the transducers relative to each other.

[0015] A "body part" may be any body part, such as the head, neck, limbs or a portion thereof.

[0016] A "wearable device" is a device that can be placed and secured to a body part, for example by being tightened around the body part. A hood, a cuff or any other garment that can be placed around a body part are examples of wearable devices.

[0017] The wearable device may include a rigid portion. The rigid portion may include a surface that forms a negative side of the surface of the body part to be stimulated. In many embodiments, the body part to be stimulated and therefore the surface is subject specific.

[0018] According to a first aspect of the invention, a method for determining a set of subject-specific treatment parameters for acoustic wave stimulation is provided as described below. According to a second aspect, such a method can be implemented in conjunction with a method for verifying and (if necessary) adjusting a set of treatment parameters for acoustic wave stimulation. This means that the treatment parameters determined by the method according to the first aspect of the invention can be verified and adjusted (if necessary) by the method according to the second aspect of the invention.

[0019] The method according to the first aspect enables determination of a set of subject specific treatment parameters for acoustic wave stimulation, which means acoustic wave therapy. The method comprises the following steps:

[0020] - Generating subject specific data, wherein the step of generating subject specific data comprises measuring at least one geometrical property of the body part.

[0021] The body part whose geometrical properties are measured is the body part to which the sound waves will be applied.

[0022] In an embodiment, a plurality of geometrical properties are measured.

[0023] • Determining a target field distribution of the sound field in the body part, wherein the step of determining the target field distribution comprises selecting an application, meaning a medical or non-medical case to be treated.

[0024] The target field distribution may be a target intensity distribution.

[0025] - Selecting a set of treatment parameters from at least two different sets of treatment parameters, wherein the step of selecting is performed before the step of applying any set of treatment parameters to the body part.

[0026] In the step of selecting a set of treatment parameters from at least two different sets of treatment parameters, a criterion for selecting the set of treatment parameters may be an expected field distribution in the body part when applied to the body part.

[0027] In particular, a set of treatment parameters may be selected that is expected to most closely approximate the target field distribution when applied to the body part.

[0028] In one embodiment, the step of selecting includes comparing a first expected field distribution associated with a first set of treatment parameters to a target field distribution, and comparing a second expected field distribution associated with a second set of treatment parameters.

[0029] Each comparison may produce a value indicative of a difference between an expected field distribution and a target field distribution, wherein a set of treatment parameters associated with the expected field distribution having a smaller value is selected.

[0030] In one embodiment, the step of determining the target field distribution may include the sub-step of consulting an electronic library (hereinafter referred to as "the library").

[0031] The library may include entries relating an application, in particular the effect that the acoustic stimulation should produce, to a target field distribution.

[0032] The entry may further relate object specific data to the target field distribution.The object specific data may include information as given above.

[0033] Entries can further relate target field distributions to multiple sets of treatment parameters.

[0034] Each set of treatment parameters can be associated with at least one of the measured or calculated field distributions. The operator of the library can provide a basic number of data sets. Users uploading their measurements and calculations (e.g., the results of numerical simulations described below) can provide more data sets.

[0035] The library may also include entries on:

[0036] o The number of successful and unsuccessful uses of a set of treatment parameters.

[0037] o Measurement of neural and / or electrical activity.

[0038] The library, or more precisely a computerized device, such as a computer, hosting and / or communicating with the library, may be configured to perform the step of determining a target field distribution.

[0039] In one embodiment, the method comprises the step of transferring the subject specific data to a library, wherein the library (computerized means) is configured to perform the step of determining the target field distribution.

[0040] The selected application may also be transmitted to the library. Alternatively, the library (computerized device) may be configured to provide a user interface. The user interface may be configured to allow a user to select possible applications.

[0041] The list of selectable applications may be user dependent.The list of selectable applications presented to an expert, such as a practitioner, may include applications, particularly medical applications, which are not selectable in the list presented to a non-expert user.

[0042] The step of determining a target field distribution may comprise the sub-step of determining a target field distribution that best fits the object specific data transmitted to the library. In particular, the determined target field distribution best fits the target field distributions stored in the library.

[0043] In one embodiment, the step of determining the target field distribution does not include the sub-step of consulting a library. In this embodiment, a practitioner or user, such as supported by materials accompanying the acoustic wave stimulation device or otherwise provided (such as on a web page), can determine the target field distribution.

[0044] In embodiments that include the sub-step of consulting a library, the library, or rather a computerized device hosting and / or communicating with the library, may be further configured to perform the step of selecting a set of treatment parameters.

[0045] In this embodiment, the step of selecting may include the sub-steps of identifying multiple stored sets of treatment parameters having measured and / or calculated field distributions that best fit the target field distribution, and selecting a set of treatment parameters predicted to produce the field distribution best suited for the application.

[0046] The forecast may consider at least one of the following:

[0047] o The difference between the measured geometrical properties of the body part to be stimulated and the geometrical properties of the body part associated with the determined target field distribution.

[0048] o A difference in at least one of the other object-specific data transmitted.

[0049] o The difference between tissue characteristics measured on the body part to be stimulated and tissue characteristics measured or estimated on the body part associated with the determined target field distribution.

[0050] o Observation of deformations of geometrical properties of a body part caused by a wearable device and / or at least one transducer for stimulation, as described below.

[0051] o The measured position of at least one transducer used for stimulation, as described below.

[0052] In particular, the field distribution that is most suitable for the application is predicted in comparison with other stored field distributions.

[0053] The step of generating subject-specific data may include the step of collecting subject-specific information, such as gender, age, weight, height, BMI, body fat content, fat percentage, muscle percentage, etc.

[0054] In one embodiment, at least one of the geometrical properties measured in the steps of generating subject specific data and subject specific information as exemplarily given above is taken into account in the step of selecting a set of treatment parameters.

[0055] In other words, a set of treatment parameters is selected taking into account the characteristics of the body and / or body part to be treated.

[0056] Optionally, the selected application is also taken into account in the step of selecting a set of treatment parameters.

[0057] Thus, the step of selecting a set of treatment parameters may be based on historical treatment data, wherein a set of treatment parameters that was successfully used for a stored treatment that is closest to the selected application and subject to be treated is selected.

[0058] Historical treatment data may be stored in a repository.

[0059] At least some of the subject-specific information may be generated by a correspondingly equipped wearable device.

[0060] In an embodiment, the measurement of the geometric property of the body part comprises the measurement of the shape of the body part. The shape may be measured by a method comprising at least one of the following steps, for example:

[0061] o Taking at least two photographs of the body part, wherein the two photographs are taken from different positions relative to the body part.

[0062] o Providing a wearable device including an arrangement of positioning points and / or lines, and determining the relative positions of the positioning points and / or the orientation of the lines after the wearable device is arranged on a body part.

[0063] The wearable device may be the same wearable device equipped to generate object specific information other than geometric properties.

[0064] o Applying sound waves to a body part and measuring the transmitted and / or scattered sound waves.

[0065] The acoustic waves may be generated and measured by a transducer disposed in a wearable device. The wearable device may be a wearable device including an arrangement of anchor points and / or lines, a wearable device configured to generate object specific information other than geometric properties, a wearable device including an arrangement of anchor points and / or lines and configured to generate object specific information other than geometric properties, or other wearable devices.

[0066] o Using at least one of an MRI system, a CT system, and a body scanner.

[0067] This embodiment of the step of measuring geometrical properties may be performed during a consultation in a medical setting, whereas the other steps of the method as well as the body part and applied acoustic stimulation determined by the subject (e.g., patient) may be performed without the presence of a medical professional, e.g., at home.

[0068] The step of measuring a geometric property of the body part may also comprise measuring or at least estimating the shape of a part of the body part, for example measuring the shape of a bone such as the skull or a long bone.

[0069] The step of measuring geometrical properties of the body part may generate data representing 3D geometrical properties, in particular the 3D shape of the body part and optionally parts of the measured body part.

[0070] In the step of determining a target field distribution of an acoustic field in a body part, the target field distribution may be one of a target field distribution in a body corresponding to the measured geometric characteristic, a target field distribution in a body approximating the measured geometric characteristic, and a stored target field distribution in a body similar to the body corresponding to the measured geometric characteristic.

[0071] Independent of the embodiment, the target field distribution may include information about the sound field over an extended area of ​​the body. In particular, the target field distribution may include information about the sound field at multiple locations in the body, such as more than 10, more than 50 or more than 100 locations.

[0072] Independently of the specific embodiment, the method may include the steps of measuring neuronal activity of the body part and / or measuring electrical activity of the body part.

[0073] This step can be performed by a method comprising at least one of the following:

[0074] ○ Perform an electroencephalogram (EEG).

[0075] ○Perform functional magnetic resonance imaging (fMRI).

[0076] ○Measure the Doppler effect.

[0077] ○ Perform electrocorticography (ECoG).

[0078] The step of measuring neuronal and / or electrical activity of a body part can be performed during a consultation in a medical institution, while the other steps of the method and the acoustic stimulation of the body part and application determined by the subject (e.g., a patient) can be performed without the presence of a medical professional, such as at home.

[0079] The step of measuring the neuronal and / or electrical activity of the body part may be used to generate a subject specific target field distribution by taking into account the neuronal condition of the subject.

[0080] The step of measuring neuronal and / or electrical activity of the body part may be used in a feedback loop for verifying that the field distribution applied to the body part ("applied field distribution") has the required field distribution for the desired application, meaning that the desired effect is achieved.

[0081] The step of measuring the neuronal and / or electrical activity of the body part can be used in a feedback loop for adjusting the field distribution applied to the body part ("applied field distribution"). For example, it can be used to better align the applied field distribution with the target field distribution and / or maximize the desired effect of the stimulation.

[0082] The library, a computerized device hosting the library and / or communicating with the library, a wearable device, or a separate device capable of connecting to at least one of the library, the computerized device, and the wearable device may include a user interface designed to guide the subject to a target field distribution that best suits the desired application.

[0083] The wearable device may be any of the wearable devices described above, or may be a wearable device for generating sound waves for stimulation.

[0084] However, the wearable device may be equipped to perform all steps required for acoustic stimulation of a body part, including all steps required by any embodiment of the method for determining a set of subject-specific treatment parameters.

[0085] In one embodiment, the method comprises the step of adding tissue characteristics of the body part to the measured geometrical properties.

[0086] In particular, the acoustic properties of the body parts are added.

[0087] In one embodiment, the method comprises the step of measuring tissue characteristics of the body part. The measuring step may be performed before the adding step.

[0088] The tissue characteristic may be measured by a method comprising at least one of the following steps, for example:

[0089] o Applying sound waves to a body part and measuring the transmitted and / or scattered sound waves.

[0090] For example, scattering properties, attenuation and / or the speed of sound can be determined. In particular, the properties can be determined in a position-dependent manner.

[0091] A wearable device comprising a transducer and configured to generate and measure sound waves may be provided. Any of the wearable devices described above may comprise a transducer and optionally other means for generating and measuring sound waves. However, the wearable device comprising a transducer and configured to generate and measure sound waves may be a separate device.

[0092] ○ Apply optical tomography.

[0093] The steps of measuring and adding tissue features may be performed during a consultation at a medical institution, while the other steps of the method and the body part and applied acoustic stimulation targeted to the subject may be performed without the presence of a medical professional, such as at home.

[0094] In one embodiment, the method includes the step of receiving the tissue signature from a library, such as the electronic library described above.

[0095] Thus, the step of adding a tissue signature may comprise the sub-step of connecting to a library and downloading information related to the tissue signature.

[0096] The step of receiving the tissue signature from the library may include the sub-step of transferring the subject specific data to the library.

[0097] Embodiments comprising the step of adding tissue features may further comprise the step of generating a digital 3D model of the body part based on the measured geometrical properties and the added tissue features.

[0098] The digital 3D model of the body part may include or be data representing a multi-material (multi-tissue) model of the body part.

[0099] The step of generating the digital 3D model may be performed during a consultation at a medical institution, while the other steps of the method as well as the body part and the applied acoustic stimulation determined by the subject may be performed without the presence of a medical professional, for example at home.

[0100] In particular, the embodiment comprising the step of generating a digital 3D model may further comprise the following steps:

[0101] • Determine a first set of treatment parameters.

[0102] - Calculating a calculated field distribution of the acoustic field in the body part using the digital 3D model of the body part and the first set of treatment parameters.

[0103] For example, a numerical simulation is performed using the digital 3D model of the body part and the first set of treatment parameters to calculate a calculated field distribution of the acoustic field in the body part.

[0104] The calculated intensity distribution is calculated in embodiments where the target field distribution is a target intensity distribution.

[0105] Examples of numerical simulation methods that may be used in the step of running the numerical simulation are finite element (FE), finite difference (FD), finite integration (FI), boundary element (BE).

[0106] • Determine the difference between the calculated field distribution and the target field distribution.

[0107] The difference may be a set of values, each of which represents a difference at a point in the digital 3D model. For example, if the calculated field distribution is calculated by numerical simulation, the point may be a node used in the numerical simulation or a selection thereof, and a corresponding point in the target field distribution.

[0108] The set of values ​​may be generated by averaging the calculated field distribution and a target field distribution for the same area.

[0109] Adjusting the first set of treatment parameters to the second set of treatment parameters. The adjustment of the first set of treatment parameters may depend on the satisfaction of a condition. For example, if the set of values ​​is greater than a set of preset values ​​or if a value derived from the set of values ​​is greater than a preset value, the first set of treatment parameters is adjusted to the second set of treatment parameters.

[0110] In particular, based on a difference between the calculated field distribution and the determined target field distribution, the first set of treatment parameters is adjusted to a second set of treatment parameters.

[0111] In one embodiment, the determined difference between the calculated field distribution and the target field distribution is transmitted to a library, and the step of adjusting the first set of treatment parameters to a second set of treatment parameters comprises the sub-step of receiving the second set of treatment parameters from the library.

[0112] The step of adjusting the first set of treatment parameters may include adjusting the first set of treatment parameters by a practitioner, an experienced user, or a subject.

[0113] The step of adjusting the first set of treatment parameters may include adjusting the first set of treatment parameters in an automatic manner.

[0114] Optionally, a calculated field distribution of the sound field in the body part using a digital 3D model of the body part and a set of adjusted treatment parameters may be calculated.

[0115] The difference between the calculated field distribution and the target field distribution for a set of adjusted treatment parameters can be determined.

[0116] The difference between the calculated field distribution and the target field distribution for a set of adjusted treatment parameters can be used for further adjustment steps.

[0117] The steps of calculating the calculated field distribution for a set of adjusted treatment parameters, determining the difference between the calculated field distribution and the target field distribution, and adjusting the set of treatment parameters may be repeated several times.

[0118] In embodiments including the steps of determining a first set of treatment parameters and adjusting the first set of treatment parameters to a second set of treatment parameters, the second set of treatment parameters is typically selected in the step of selecting a set of treatment parameters. However, in these embodiments, the step of selecting a set of treatment parameters is a step of selecting a set of treatment parameters from the first set of treatment parameters and the second set of treatment parameters.

[0119] In the step of determining a first set of treatment parameters, the first set of treatment parameters may be received from a library.

[0120] Alternatively, the first set of treatment parameters may be a set of preset treatment parameters, which may depend on at least one of the body part and the position of at least one transducer for stimulating the body part.In this embodiment, at least no library is required to participate in the step of determining the first set of treatment parameters.

[0121] In embodiments where the target field distribution is determined by using a library, the first set of treatment parameters may be related to the target field distribution and thus to subject specific data applied and optionally transmitted to the library.

[0122] In one embodiment, the method may comprise the steps of providing a wearable device comprising at least one transducer and arranging the wearable device at a body part.

[0123] In such an embodiment, the step of determining a first set of treatment parameters may include the sub-step of reading a position of at least one transducer relative to the body part.

[0124] For example, at least one transducer is equipped to generate sound waves for stimulation and a first set of treatment parameters is determined after a step of placing the wearable device at the body part and after a sub-step of reading (which means determining) the position of the at least one transducer on the body part.

[0125] In an embodiment comprising the step of arranging the wearable device at the body part and the sub-step of reading the position of at least one transducer equipped for stimulation, the method may comprise the further step of determining a deformation of a geometric property of the body part caused by the wearable device and / or the at least one transducer.

[0126] A comparison between the data representing the 3D geometrical property generated in the step of measuring the geometrical property and the position of the at least one transducer may be used to determine the deformation.

[0127] Alternatively, a comparison may be made between the digital 3D model and the positions of the transducers.

[0128] Optionally, the method may comprise a routine of adapting the digital 3D model if deformation of the geometrical properties of the body part is observed.The adaptation may be to at least one of: the geometrical properties given in the digital 3D model and the tissue features used in the 3D model.

[0129] In embodiments where tissue features are not added to the measured geometric properties, the data representing the geometric properties may be adapted if deformations of the geometric properties of the body part are observed.

[0130] The position of the at least one transducer may be transmitted to the library. The selection criteria may identify operating parameters of the at least one transducer that are expected to generate a field distribution that is closest to the target field distribution. In particular, the operating parameters are closest to the target field distribution relative to other operating parameters for the same or similar position of the at least one transducer stored in the library.

[0131] In one embodiment, the first set of treatment parameters received from the library includes operating parameters of at least one transducer and a target location.

[0132] In this embodiment, the wearable device may be equipped to position at least one transducer at a target location.

[0133] Independent of the embodiment, the wearable device may also include at least one of a positioning point and / or line arrangement, a transducer for generating and measuring sound waves in the step of measuring geometric properties, a transducer for generating and measuring sound waves in the step of measuring tissue characteristics, and a device for determining object-specific data.

[0134] In the step of calculating the calculated field distribution of the sound field in the body part using the digital 3D model of the body part and the first set of treatment parameters, the first set of treatment parameters may be used to determine an excitation of the body part represented by the digital 3D model.

[0135] The step of calculating the calculated field distribution, such as the numerical simulation included therein, may be repeated for different sets of treatment parameters. Thus, a plurality of calculated field distributions may be generated, each field distribution being associated with a particular set of treatment parameters. The step of selecting a set of treatment parameters from at least two different sets of treatment parameters may then include selecting one of these multiple sets of particular treatment parameters.

[0136] For example, a specific set of treatment parameters is selected that has a calculated field distribution that differs from the target field distribution by less than a preset value. The preset value can be a set of preset values. For example, the set of preset values ​​can be a preset distribution of maximum difference.

[0137] The preset value (a set of preset values) may be set in relation to the difference (a set of values) described above in relation to the step of determining the difference between the calculated field distribution and the target field distribution.

[0138] A preset value (a set of preset values) may define local or global stopping conditions for repeated calculations for different sets of treatment parameters.

[0139] The calculation may be iterative, wherein the repeated calculation is stopped as soon as the global and local changes of the calculated field distribution of two subsequent iteration steps are smaller than preset global and / or local values.

[0140] In one embodiment, the steps of calculating the calculated field distribution, determining the difference between the calculated field distribution and the target field distribution, and adjusting are repeated until the difference between the calculated field distribution and the target field distribution is less than a preset value.

[0141] In other words, the preset value defines a stop condition for repeating the steps.

[0142] Preset values ​​defining the stop conditions may be received from a library.

[0143] For example, to repeat the calculation in an iterative manner.

[0144] The calculations may include or consist of numerical simulations.

[0145] In embodiments where the target field distribution is received from a library, the preset values ​​may be related to the target field distribution and thus to the application, and if transmitted to the library, to the object specific data.

[0146] The preset values ​​may be a set of values ​​adapted to define a set of values ​​for a difference between a calculated field distribution and a target field distribution.

[0147] The preset value can represent a global stop condition and / or a local stop condition. The latter can be defined by a set of values.

[0148] In one embodiment, at least one of the measured geometrical properties and the subject specific information is taken into account in the step of selecting a set of treatment parameters.

[0149] In one embodiment, the step of selecting a set of treatment parameters comprises comparing a first expected field distribution associated with a first set of treatment parameters to the target field distribution, and comparing a second expected field distribution associated with a second set of treatment parameters to the target field distribution.

[0150] In one embodiment, the step of generating object specific data comprises the following sub-steps:

[0151] adding tissue characteristics of the body part to the measured geometrical properties;

[0152] - Generating a digital 3D model of the body part based on the measured geometrical properties and the added tissue features.

[0153] In one embodiment, the following steps are also included:

[0154] Determine the first set of treatment parameters;

[0155] Calculating a calculated field distribution of the acoustic field in the body part using the digital 3D model of the body part and the first set of treatment parameters;

[0156] · determining the difference between the calculated field distribution and the target field distribution;

[0157] Adjusting the first set of treatment parameters to a second set of treatment parameters;

[0158] The step of selecting a set of treatment parameters comprises selecting from the first set of treatment parameters and the second set of treatment parameters.

[0159] In one embodiment, the steps of calculating the calculated field distribution, determining the difference between the calculated field distribution and the target field distribution, and adjusting the first set of treatment parameters are repeated until the difference between the calculated field distribution and the target field distribution is less than a preset value.

[0160] In one embodiment, the step of transmitting said subject specific data to an electronic library is included, wherein said electronic library is configured to perform the steps of determining a target field distribution and selecting a set of treatment parameters.

[0161] In one embodiment the further step of measuring neuronal activity of said body part and / or measuring electrical activity of said body part is included.

[0162] In one embodiment, the method further includes: providing a wearable device including at least one transducer, placing the wearable device at the body part, and reading the position of the at least one transducer relative to the body part.

[0163] According to a second aspect of the invention, a method for verifying a set of treatment parameters for acoustic stimulation is provided, as described below. This method can be implemented in combination with the method according to the first aspect. However, as pointed out in detail below, the method according to the second aspect of the invention can be used to verify treatment parameters that are not generated by the method according to the first aspect.

[0164] The method according to the second aspect may be extended by an adjustment step. In this case, the second aspect relates to a method for verifying and adjusting a set of treatment parameters for acoustic wave stimulation.

[0165] The method according to the second aspect is capable of verifying and optionally adjusting a set of subject-specific treatment parameters for acoustic wave stimulation. The method comprises the following steps:

[0166] • Determine the target field distribution of the sound field in the body part to be stimulated.

[0167] The step of determining a target field distribution may be performed in any embodiment of the corresponding step of the first aspect.

[0168] • Receiving a set of treatment parameters for at least one transducer, wherein the set of treatment parameters is designed relative to a target field distribution.

[0169] In particular, the set of treatment parameters is designed to maximally approximate the target field distribution using the information at hand and the procedure selected for designing the set of treatment parameters.

[0170] For example, a set of treatment parameters is selected from among various possible sets of parameters to maximally approximate the target field distribution.

[0171] For example, a set of treatment parameters that is expected to be closest to the target field distribution is selected. The selection may depend on experience. For example, the experience may be stored and / or provided to the practitioner or patient.

[0172] Generate a subject-specific 3D model of the body part to be stimulated.

[0173] Determine the difference between the target field distribution and the field distribution determined in the object-specific 3D model.

[0174] The field distribution determined in the object-specific 3D model may be, for example, a calculated (eg simulated) field distribution in the object-specific digital 3D model or a measured field distribution in the object-specific physical 3D model.

[0175] In an embodiment comprising the step of receiving a set of therapy parameters for at least one transducer, the set of therapy parameters is received from an electronic library (hereinafter "library"), in particular from a library as described in relation to the first aspect.

[0176] In such an embodiment, the received set of treatment parameters may be a set of treatment parameters stored in a library associated with a field distribution that best fits the target field distribution.

[0177] In an embodiment, the set of treatment parameters is calculated, for example, by using numerical simulation.

[0178] In particular, the set of treatment parameters may be determined by using numerical simulations.

[0179] For some applications, a so-called inverse problem can be solved. This means that for some applications a set of treatment parameters can be calculated from the target field distribution, for example by numerical simulation.

[0180] For applications where the inverse problem cannot be solved, the calculations (or numerical simulations as the case may be) may be based on a subject-specific or non-subject-specific digital model of the body part. The first set of treatment parameters may be received from a library, may be determined by a practitioner, or may be determined by a patent. The first set of treatment parameters may be used to determine a first excitation of the model of the body part. In such an embodiment, the calculations (or numerical simulations as the case may be) give a first calculated field distribution in the subject-specific or non-subject-specific digital model of the body part.

[0181] The second set of treatment parameters may be determined based on the first calculated field distribution, in particular based on a comparison between the first calculated field distribution and a target field distribution.

[0182] The second set of treatment parameters may be generated by adjustments to the first set of treatment parameters, wherein the adjustments reduce the difference between the field distribution (in the body part) associated with the second set of treatment parameters and the target field distribution.

[0183] A second calculation, and optionally a second numerical simulation, may be performed to confirm that the second set of treatment parameters results in a second calculated field distribution that is closer to the target field distribution than the first calculated field distribution.

[0184] A third set of treatment parameters may be determined from the second calculated field distribution to reduce a difference between a field distribution (in the body part) associated with the third set of treatment parameters and a target field distribution.

[0185] At least one further calculation (or numerical simulation as appropriate) may be performed to confirm that the third set (or another set as appropriate) of treatment parameters causes the third (another) calculated field distribution to be closer to the target field distribution than the second (previous) calculated field distribution.

[0186] In other words, the steps of adjusting a set of treatment parameters and determining a calculated field distribution associated with the adjusted set of treatment parameters may be performed in a repetitive (eg, iterative) manner.

[0187] Supplemental materials providing information relevant to the application of multiple sets of treatment parameters and target field distributions may be provided to support practitioners and / or subjects (e.g., patients) in determining a target field distribution and / or a set of treatment parameters.

[0188] The set of treatment parameters determined in this manner may be the set of treatment parameters received in the step of receiving a set of treatment parameters.

[0189] At least one transducer is equipped to generate sound waves suitable for stimulating the body part to be stimulated.

[0190] At least one transducer can be arranged or can be arranged in a wearable device.

[0191] In embodiments comprising the step of generating a subject specific 3D model of the body part to be stimulated, the subject specific 3D model may be a subject specific physical 3D model.

[0192] The object specific 3D model may be an object specific physical 3D model independent of the embodiment of the step of receiving a set of treatment parameters. In particular, the object specific 3D model may be an object specific physical 3D model independent of the way in which the set of treatment parameters is determined.

[0193] The physical 3D model is a real (which means not virtual) model of the body part to be stimulated.

[0194] The object-specific physical 3D model has geometrical properties corresponding to those measured on the body part of the object to be stimulated. Ideally, it consists of materials that simulate the physical and especially acoustic properties of the object's tissue.

[0195] One or more geometrical properties and tissue characteristics may be measured in any manner as described in relation to the first aspect.

[0196] The method may comprise the step of measuring a geometrical property of the body part, such as in any of the embodiments described in relation to the first aspect.

[0197] The method may comprise the step of measuring a tissue characteristic of the body part, such as in any of the embodiments described in relation to the first aspect.

[0198] In embodiments comprising the step of generating a subject specific 3D model of the body part to be stimulated, the subject specific 3D model may be a subject specific digital 3D model, in particular a digital 3D model as described with respect to the first aspect.

[0199] In one embodiment, the object specific 3D model is an object specific physical 3D model, and the method comprises the further steps of:

[0200] • Providing a wearable device comprising at least one transducer.

[0201] Wearable devices may be equipped to stimulate body parts.

[0202] In any of the embodiments described with respect to the first aspect, the wearable device may be a wearable device equipped (used) to generate sound waves for stimulation.

[0203] Place wearable devices on the physical 3D model.

[0204] The wearable device may include a securing device.

[0205] The wearable device may include means for arranging it in a reproducible manner on the physical 3D model and / or on the body part to be stimulated.

[0206] Applying a set of treatment parameters to the wearable device.

[0207] The set of treatment parameters comprises operating parameters of the at least one transducer and information on the placement of the at least one transducer to the body part (to the physical 3D model, as the case may be).

[0208] The wearable device and the at least one transducer may be equipped with the at least one transducer for positioning relative to the body part (relative to the physical 3D model) according to a set of treatment parameters.

[0209] Alternatively, at least one transducer may be arranged in a fixed manner on the wearable device and the relative position relative to the body part (physical 3D model) may be a fixed parameter, which has also been considered as a fixed parameter in the previous steps.

[0210] However, the fixed parameters may depend on the application, the body part and the subject specific data (including one or more measured geometrical properties of the body part).

[0211] • Determining a field distribution generated by the arranged wearable device and a set of parameters applied to the arranged wearable device by measuring.

[0212] For example, measurements may include reading a grid of sensors integrated in the physical 3D model or moving sensors to different locations in the physical 3D model.

[0213] In an embodiment, the received set of therapy parameters is a set of therapy parameters determined according to any embodiment of the method for determining a set of subject specific therapy parameters for acoustic wave stimulation (ie the method according to the first aspect).

[0214] The method for verifying a set of treatment parameters for acoustic wave stimulation may include any steps associated with the method according to the first aspect. In particular, the method for verifying a set of treatment parameters for acoustic wave stimulation may include any combination of steps associated with the embodiments of the method according to the first aspect.

[0215] As mentioned above, the method according to the second aspect may be extended by an adjustment step. This means that, in one embodiment, the method may comprise the step of adjusting the received set of treatment parameters.

[0216] The adjusting step may comprise the sub-step of determining a difference between the target field distribution and the field distribution determined in the object specific 3D model.

[0217] If the difference is smaller than a preset value, the adjusting step may be omitted.

[0218] The adjusting step may be repeated, for example in an iterative manner, wherein a set of treatment parameters adjusted in a previous repetition (iteration) may be applied in a repetition (iteration) subsequent to the previous repetition (iteration).

[0219] The repetition (iteration) may be stopped if the difference between the target field distribution and the field distribution determined in the subject-specific 3D model for a set of treatment parameters is less than a preset value.

[0220] In one embodiment, the set of treatment parameters is received from or calculated in an electronic library.

[0221] In one embodiment, the object specific 3D model is an object specific physical 3D model.

[0222] In one embodiment, the following steps are also included:

[0223] · Providing a wearable device comprising at least one transducer;

[0224] · Arranging the wearable device on the physical 3D model;

[0225] Applying the set of treatment parameters to the wearable device;

[0226] Therein, the field distribution in the object-specific physical 3D model is determined by measurement.

[0227] In an embodiment, the object specific 3D model is a digital 3D model and wherein the field distribution in the object specific digital model is determined by numerical simulation.

[0228] In one embodiment, the received set of treatment parameters is a set of treatment parameters determined according to the above method.

[0229] In one embodiment, the step of adjusting a received set of treatment parameters is included if a difference between said target field distribution and a field distribution determined in said subject specific 3D model is greater than a preset value.

[0230] A set of treatment parameters determined or validated by the described methods may be used by a treatment device (eg, a wearable device).

[0231] The therapeutic device may be configured to perform the method described in any of the embodiments.

[0232] The treatment device comprises a carrier element to which at least one transducer is mounted or to which at least one transducer is mountable, for example by means of the carrier element comprising at least one fixing element.

[0233] The carrier element may be configured to be fastened to a body part to be stimulated.

[0234] The treatment device and the carrier element are described in detail in an application entitled "Treatment devices for acoustic wave stimulation" filed on the same date as the present application by the same applicant. The disclosure of said application is incorporated herein by reference.

[0235] However, if the digital 3D model comprises a model of the surface of the body part or a part thereof to be stimulated, the generated digital 3D model can be used to produce the object specific carrier element.

[0236] The carrier element generated by using the digital 3D model comprises a rigid part having a surface forming the negative side of the surface of the body part to be stimulated. In other words, the rigid part comprises a surface formed according to the surface of the body part or a part of the surface of the body part. This means that the surface of the carrier element is adapted to the surface of the body part.

[0237] The carrier element may be manufactured by a rapid manufacturing process, for example milling, turning, casting or an additive manufacturing process (such as printing, for example 3D printing).

[0238] Typically, the carrier element and the therapeutic device are not only wearable, but also portable by the subject.

[0239] In particular, the carrier element (therapeutic device) is portable due to its size and weight.

[0240] The carrier element, in particular the rigid part, can be made of a lightweight material. BRIEF DESCRIPTION OF THE DRAWINGS

[0241] The subject matter of the invention will be explained in more detail below with reference to exemplary embodiments shown in the drawings, which schematically show:

[0242] Figure 1 is a flow chart of steps common to various embodiments of the method for determining a set of subject-specific treatment parameters for acoustic wave stimulation according to the first aspect of the present invention;

[0243] Figure 2 is a flow chart of one embodiment of a method for determining a set of subject-specific treatment parameters for acoustic wave stimulation;

[0244] Figure 3is a flow chart of another embodiment of a method for determining a set of subject-specific treatment parameters for acoustic wave stimulation;

[0245] Figure 4 is a flow chart of yet another embodiment of a method for determining a set of subject-specific treatment parameters for acoustic wave stimulation;

[0246] Figure 5 is a flow chart of steps common to multiple embodiments of the method for validating a set of treatment parameters for acoustic wave stimulation according to the second aspect of the present invention;

[0247] Figure 6 is a flow chart of one embodiment of a method for validating a set of treatment parameters for acoustic wave stimulation;

[0248] Figure 7 is a flow chart of another embodiment of a method for validating a set of treatment parameters for acoustic wave stimulation;

[0249] Figure 8 is a flow chart of a manufacturing process of a subject specific carrier element; and

[0250] Figure 9-10 are two exemplary embodiments of object-specific carrier elements. DETAILED DESCRIPTION

[0251] Figure 1 A flow chart showing the steps of a method for determining a set of subject-specific treatment parameters for acoustic wave stimulation. This means that Figure 1 The basic steps of the method according to the first aspect of the invention are shown. The steps shown are common to a number of embodiments of the method for determining specific treatment parameters for a group of subjects.

[0252] In a first step S10, subject specific data are generated. This step S10 of generating subject specific data comprises measuring at least one geometrical property of a body part of the subject, said body part being the body part to be stimulated.

[0253] The geometrical properties include at least the shape of the body part. The shape can be measured, for example, by a method as described above (in particular one of the methods comprising the following steps: "taking two pictures"; "providing a wearable device", which is equipped accordingly; using a medical imaging method such as MRI, CT or a body scanner) or by a combination of these methods.

[0254] The geometrical properties may include further information about the internal structure of the body part. For example, the information about the internal structure may be generated by the methods described above (particularly one of the methods including "applying sound waves" and using a medical imaging method such as MRI or CT) or by a combination of these methods.

[0255] The subject specific data may include further information such as gender, age, weight, height, BMI, body fat content, fat percentage, muscle percentage, etc.

[0256] In step S20, after the step of generating object specific data, a target field distribution of the sound field in the body part is determined. In other words, a distribution of the sound field in the body part is determined, wherein the distribution is able to stimulate the body part in a way that produces a desired effect. Therefore, the step S20 of determining the target field distribution generally includes a sub-step of selecting an application.

[0257] For example, depending on the application and body part, the target field distribution may include a focal point at the measured or expected location of a neuron or at the measured or expected location of a portion of a body part (e.g., a muscle or tendon).

[0258] The target field distribution may be determined based on at least one of: measurements of geometrical properties of the body part, in particular when including information about the internal structure of the body part (including information about the nervous system); experience of a practicing physician; applying supplementary material related to the target field distribution; and consulting a library, wherein the library may be automated in the sense that it determines the target field distribution based on input given by a user. The library may be an electronic library as described above and below.

[0259] In step S30 following the step of determining the target field distribution, a set of treatment parameters is selected from at least two sets of treatment parameters.

[0260] Typically, a set of treatment parameters includes (i) operating parameters for at least one transducer configured to generate an acoustic field for stimulation, and (i) a position of the at least one transducer relative to a body part.

[0261] There are sets of treatment parameters that are able to generate a field distribution in the body part that approximates the target field distribution in a good way.

[0262] Various selection criteria may be considered in step S30 of selecting a set of treatment parameters from at least two sets of treatment parameters. For example, at least one of the following criteria may be considered:

[0263] Possibility to arrange at least one transducer on a body part;

[0264] Knowledge of the success scenarios for multiple sets of parameters that may be suitable for the chosen application;

[0265] Knowledge of the side effects of multiple sets of parameters that may be appropriate for the chosen application;

[0266] • The difference between the body part to be stimulated and the body part on which the target field distribution is determined.

[0267] For example, the difference may lie in one or more geometrical properties of the body part, its tissue characteristics and / or other subject-specific data (e.g. gender, age, weight, height, BMI, body fat content, fat percentage, muscle percentage).

[0268] Figure 2 A flow chart of an exemplary embodiment of a method for determining a set of subject-specific treatment parameters for acoustic wave stimulation is shown.

[0269] In this embodiment, an electronic library (hereinafter referred to as "library") is used in the step S20 of determining the target field distribution and in the step S30 of selecting a set of treatment parameters. Thus, the method shown comprises a step 40 of transferring subject specific data to the library.

[0270] In particular, the object-specific data generated in the step S10 of generating object-specific data and comprising information on geometrical properties of the body part are transmitted.

[0271] The application selected in step S20 of determining the target field distribution may also be transferred to the library. Alternatively, the electronic library may be combined with a user interface as described above. The user interface may be configured to help the user select the desired application.

[0272] In the illustrated embodiment, the library is in communication with the computer.

[0273] The computer may be configured to select a target field distribution among a plurality of target field distributions stored in the library that is expected to provide the best results for the selected application.

[0274] The computer may be configured to apply a selection criterion, on which the step S30 of selecting a set of treatment parameters is based. In particular, the computer may be configured to select a set of treatment parameters from a plurality of sets of treatment parameters stored in a library, the set of treatment parameters being expected to generate a field distribution that better approximates the target field distribution than the expected field distributions generated by the other sets of treatment parameters.

[0275] Figure 3 A flow chart illustrating another exemplary embodiment of a method for determining a set of subject-specific treatment parameters for acoustic wave stimulation is shown.

[0276] Computation, and in particular numerical simulation, is used in the exemplary embodiment shown to determine a set of subject-specific treatment parameters that generate a field distribution that is expected to approximate the target field distribution in a manner sufficient for the selected application.

[0277] Hence, the method shown comprises a step S11 of adding tissue features of the body part to the measured geometrical properties of the body part.

[0278] The tissue characteristics may be measured by the methods described above, in particular one of the methods including "applying acoustic waves" and "applying optical tomography", or by a combination of these methods. Alternatively or additionally, for example, approximate tissue characteristics generated by a function describing a specific material or a stored characteristic representing the tissue may be used.

[0279] The illustrated method comprises the further step S12 of generating a digital (ie virtual) 3D model of the body part.

[0280] In the embodiment shown, the digital 3D model is a model with the measured geometric properties of the tissue features added, wherein the model is represented in a manner that can be used for numerical simulation. For example, it can be represented by a commercial numerical simulation program, such as Comsol's Comsol Multiphysics or CADFEM's Ansys, as needed.

[0281] Alternatively, the digital 3D model or information related thereto may be used to determine the target field distribution.The target field distribution may be determined by using a library.

[0282] In this case, a computer in communication with the library may be configured to determine a target field distribution in the digital 3D model, for example by adapting a field distribution stored for a similar digital 3D model. This may result in a high quality target field distribution for the application and body part.

[0283] Figure 3 The method shown comprises a further step S50 of determining a first set of treatment parameters. For example, the first set of treatment parameters may be derived from a target field distribution by a practitioner or subject, optionally supported by supplementary material including information relating the field distribution to the set of parameters, or in an automatic manner, such as by a computer configured to determine a set of treatment parameters from a plurality of sets of stored treatment parameters. The computer may be a computer in communication with a library, and the set of treatment parameters may be stored in the library.

[0284] Based on the number of stored treatment parameters and target field distributions, it is also envisaged that the computer is configured to calculate a first set of treatment parameters.

[0285] In the embodiment shown, the digital 3D model and the first set of treatment parameters are used as input to step S51 of calculating the calculated field distribution.

[0286] In the illustrated embodiment, calculating includes performing numerical simulations.

[0287] The method shown comprises a further step S52 of determining a difference between the target field distribution and the calculated field distribution and a further step S53 of adjusting the first set of treatment parameters to a second set of treatment parameters.

[0288] The steps S51 of calculating the calculated field distribution, S52 of determining the difference and S53 of adjusting may be repeated to determine sets of treatment parameters that generate a field distribution that approximates the target field distribution. Figure 3 Indicated by dashed arrows.

[0289] Ideally, the repetitions are iterations that continually improve the approximation of the target field distribution.

[0290] The step S53 of adjusting may store the determined difference to determine whether the adjustment results in an improvement. The stored difference may be further used in the step S30 of selecting a set of treatment parameters.

[0291] at last, Figure 3 The method shown comprises a step S30 of selecting a set of treatment parameters, which in the embodiment shown selects a set of treatment parameters that results in a calculated field distribution having a minimum difference from a target field distribution. In the simple case of only one repetition, this means selecting a set of treatment parameters from the first and second sets of treatment parameters.

[0292] Figure 3 The embodiment of can also be considered as an exemplary embodiment of a method for validating a set of treatment parameters for acoustic wave stimulation (second aspect). This is because it includes a step S12 of generating a 3D model (i.e. a digital 3D model) of the body part to be stimulated, which can be subject-specific, and a step S52 of determining the difference between the target field distribution and the field distribution determined (i.e. simulated) in the 3D model (digital 3D model) which can be subject-specific, wherein the steps allow checking the consistency between the field distribution expected to be generated by a set of treatment parameters and the target field distribution.

[0293] Figure 4 A flow chart of yet another exemplary embodiment of a method for determining a set of subject-specific treatment parameters for acoustic wave stimulation is shown.

[0294] In this embodiment, the step S30 of selection is not necessarily the final step of the method. However, the method may optionally comprise a further step S31 of selection which may be the final step of the method.

[0295] The method shown includes an optional final step S31 of selection and the preceding step of providing multiple selectable sets of treatment parameters, particularly when a set of treatment parameters selected in the first selection step S30 is expected to produce a set of treatment parameters that causes a field distribution that only approximates the target field distribution in an insufficient manner.

[0296] For example, this might be the case if at least one of the following applies:

[0297] o The subject specific data transmitted to the library is insufficient to determine a target field distribution and / or a set of treatment parameters that is sufficiently specific to the subject.

[0298] o The stored set of parameters and / or field distributions only approximates the object specific application in a coarse manner.

[0299] ○ The method used to determine the target field distribution is not sophisticated enough.

[0300] More specifically, Figure 4 The method shown in comprises a step S10 of generating subject specific data (including measuring at least one geometrical property of the body part to be stimulated), a step S40 of transferring the subject specific data to a library, a step S20 of determining a target field distribution and a step S30 of selecting a set of treatment parameters.

[0301] These steps are described in Figure 1-3 The method may be performed in any of the embodiments described wherein the set of treatment parameters is selected from a plurality of sets of treatment parameters stored in a library.

[0302] The method shown comprises a step S11 of adding tissue features of the body part to the measured geometrical properties of the body part and a step S12 of generating a digital 3D model of the body part. These steps may be based on the Figure 3 Any of the embodiments described may be implemented.

[0303] In the illustrated embodiment, the added step S11 and the step S12 of generating a digital 3D model are not used for determining a target field distribution or for selecting the set of treatment parameters from a plurality of sets of treatment parameters.

[0304] Instead, the added step S11 and the step S12 of generating the digital 3D model are used to determine whether the selected set of treatment parameters is adapted to the subject specific situation in a sufficient manner. This is done in the method shown, which comprises a step S51 of calculating the calculated field distribution with the selected set of treatment parameters and the subject specific digital 3D model of the body part, and comprises a step S52 of determining the difference between the target field distribution and the calculated field distribution.

[0305] Optionally, the target field distribution may be adapted to observed differences between geometrical properties and / or tissue characteristics of the body part to be stimulated and geometrical properties and / or tissue characteristics on which the determined target field distribution is based (not shown).

[0306] If the method comprises the optional step of adapting the target field distribution, the step S52 of determining the difference may determine the difference between the adjusted target field distribution and the calculated field distribution.

[0307] If the difference determined in the step S52 of determining the difference is greater than a preset value, the method includes a step S53 of adjusting a set of treatment parameters into a set of adjusted treatment parameters, which is independent of the specific implementation of the step S52 of determining the difference.

[0308] The step S51 of calculating, the step S52 of determining the difference and the step S53 of adjusting can be performed in relation to Figure 3 The method may be performed in any of the embodiments described, wherein the step S53 of adjusting may include a sub-step of storing the differences and / or a sub-step of transmitting the determined differences to a repository.

[0309] The step S51 of calculating, the step S52 of determining the difference and the step S53 of adjusting can be as described in relation to Figure 3 The repetition of each set of treatment parameters that results in a field distribution that approximates the target field distribution is repeated as described. Figure 3 Indicated by dashed arrows.

[0310] If the method shown includes a step S53 of adjusting a set of treatment parameters into a set of adjusted treatment parameters, the method may include a further step S31 of selecting a set of treatment parameters, wherein the set of treatment parameters is selected from the set of adjusted treatment parameters and a set of treatment parameters selected from a plurality of sets of treatment parameters stored in a library.

[0311] Figure 4 The embodiment of can also be considered as an exemplary embodiment of a method for validating a set of treatment parameters for acoustic wave stimulation (second aspect). This is because it includes a step S12 of generating a 3D model (i.e. a digital 3D model) of the body part to be stimulated, which can be subject-specific, and a step S52 of determining the difference between the target field distribution and the field distribution determined (i.e. simulated) in the 3D model (digital 3D model) which can be subject-specific, wherein the steps allow checking the consistency between the field distribution expected to be generated by a set of treatment parameters and the target field distribution.

[0312] Figure 5 A flow chart showing the steps of a method for validating a set of treatment parameters for acoustic wave stimulation. This means that Figure 5 The steps of a method according to the second aspect of the invention are shown. The steps shown are common to a number of embodiments of the method for validating a set of treatment parameters.

[0313] The method comprises a step S20 of determining the target field distribution. This step may be performed in relation to Figure 1-4 Any of the embodiments described may be performed.

[0314] The method further comprises a step S100 of receiving a set of treatment parameters. The received set of treatment parameters is verified by the method. This also means that the received set of treatment parameters is designed for a target field distribution. In other words, the received set of treatment parameters is designed to generate a field distribution that approximates the target field distribution. The degree of approximation depends on various aspects, such as the difference in geometrical properties and / or tissue characteristics between the body part on which the target field distribution is determined and the body part to be stimulated, the procedure selected to determine or design a set of treatment parameters, etc.

[0315] The received set of treatment parameters may be, for example, Figure 1-4 A set of treatment parameters determined in any of the embodiments described.

[0316] The method further comprises a step S110 of generating an object-specific 3D model of the body part to be stimulated. Figure 1-4 The invention is described and implemented in any embodiment that is object-specific, which means that it comprises at least one information of the object related to the overall characteristics of the object-specific 3D model. In particular, the at least one relevant information is a geometrical property, which means at least the shape of the body part. The object-specific 3D model may include tissue characteristics of the body part to be stimulated.

[0317] The method used for validation is based on determining the difference between the target field distribution and the field distribution determined in a subject-specific 3D model of the body part to be stimulated.

[0318] The 3D model can be a physical ("real") 3D model, such as in Figure 6 In the case of an embodiment of the invention, or a digital ("virtual") 3D model, such as in Figure 7 The situation in the embodiment of .

[0319] The method comprises a step S150 for determining a difference between a target field distribution and a field distribution determined in a subject-specific 3D model of the body part to be stimulated.

[0320] The determined difference may be used to decide whether a received set of treatment parameters results in a field distribution in the body part that fits the target field distribution in a manner sufficient for application to the body part and the selected application.

[0321] Figure 6 A flow chart of an exemplary embodiment of a method for validating a set of treatment parameters for acoustic wave stimulation is shown. In the illustrated embodiment, an object-specific physical 3D model of the body part to be stimulated and a field distribution measured in the object-specific physical 3D model, the measured field distribution being generated by the received set of treatment parameters, are used in the method for validation.

[0322] The method shown comprises a step S111 of generating an object-specific physical 3D model of the body part to be simulated. In other words, it is a step of generating Figure 5 The object-specific physical 3D model of the object-specific 3D model of the method shown is generated in step S110 .

[0323] Figure 6 The method further comprises a step S160 of providing a wearable device that is equipped to stimulate a body part and thus is equipped to stimulate an object specific physical 3D model of the body part.

[0324] In particular, the wearable device comprises at least one transducer equipped for generating sound waves in a body part. This means that the wearable device comprises at least one transducer equipped for generating a sound field distribution in a body part.

[0325] In step S161 of arranging the wearable device on the object-specific physical 3D model, the wearable device is worn on the object-specific physical 3D model.

[0326] The wearable device is arranged on the object-specific physical 3D model in a manner that at least one transducer is arranged relative to the object-specific physical 3D model according to a received set of treatment parameters. Alternatively, at least one transducer can be rearranged on the wearable device in a manner that after rearranging the at least one transducer, the at least one transducer is arranged relative to the object-specific physical 3D model according to the received set of treatment parameters.

[0327] Said relative arrangement of at least one transducer may be considered as a first sub-step of step S170 of applying the received set of therapy parameters to at least one transducer equipped to generate a sound field in the body part.

[0328] The step S170 of applying a set of treatment parameters comprises a second sub-step of applying operating parameters to at least one transducer according to the received set of treatment parameters. This sub-step is performed after the first sub-step of arranging at least one transducer relative to the body part.

[0329] Furthermore, the method shown comprises a step S180 of measuring the field distribution generated in the object-specific physical 3D model. This can be done, for example, by reading a sensor grid integrated in the physical 3D model or by moving the sensor to different positions in the physical 3D model and reading the field characteristics (e.g. its intensity) at each position.

[0330] In a step S150 of determining a difference between a target field distribution and a field distribution determined in an object specific 3D model (in the embodiment shown an object specific physical 3D model), a difference between the measured field distribution and the target field distribution is determined.

[0331] Figure 7 A flow chart of another exemplary embodiment of a method for validating a set of treatment parameters for acoustic stimulation is shown. In the illustrated embodiment, an object-specific digital 3D model of a body part to be stimulated and a field distribution calculated in the object-specific digital 3D model are used in the method for validation, wherein the field distribution generated in the object-specific digital 3D model by the received set of treatment parameters is calculated.

[0332] The method shown comprises a step S112 of generating an object-specific digital 3D model of the body part to be simulated. In other words, it is a step of generating a digital 3D model of the body part to be simulated. Figure 5 The object-specific digital 3D model is generated in step S110 of the object-specific 3D model of the method shown.

[0333] The step S112 of generating an object-specific digital 3D model can be based on Figure 1-4 Any disclosed embodiment may be implemented.

[0334] Figure 7 The method also includes a step S181 of calculating a field distribution generated in digital 3D by a received set of treatment parameters.

[0335] The step S181 of calculating the field distribution comprises performing a numerical simulation.A numerical simulation may be set up and run in any of the above-described embodiments relating to a numerical simulation for calculating a field distribution in a body part.

[0336] In a step S150 of determining a difference between a target field distribution and a field distribution determined in an object specific 3D model (in the embodiment shown an object specific digital 3D model), a difference between the calculated field distribution and the target field distribution is determined.

[0337] Figure 7 A step S190 of adjusting the received set of treatment parameters is shown as an optional feature. In case the validation of the received set of treatment parameters is negative, which means that the received set of treatment parameters is deemed insufficient for application to the body part, such an adjustment step may be any embodiment of the validation method, in particular Figure 5-7 A portion of the embodiment shown in FIG.

[0338] Step S190 of adjusting the received set of treatment parameters or an adjusted set of treatment parameters, step S181 of calculating the field distribution in the digital 3D model, and step S150 of determining the difference between the target field distribution and the calculated field distribution are repeated to determine a verified set of treatment parameters.

[0339] Figure 8A flow chart of an exemplary manufacturing process of a subject-specific carrier element 1 is shown, which means that the carrier element 1 comprises a rigid part comprising a surface 17 forming a negative side of the surface of the body part to be stimulated.

[0340] Figure 8 An essential step of the manufacturing process shown is step S112 of generating an object specific digital 3D model of the body part to be stimulated, wherein said step S112 generates a model of the surface of the body part to be stimulated or a part of the surface of the body part to be stimulated when used in the manufacturing process.

[0341] The actual production step S200 of the carrier element may comprise a rapid manufacturing process, for example milling, turning, casting or a rapid additive manufacturing process (such as printing, for example 3D printing).

[0342] In principle, Figure 8 The other steps shown are optional. However, if the manufactured carrier element 1 comprises a limited number of locations where at least one transducer can be mounted, or if the manufactured carrier element 1 comprises fixing elements 10 at the target location of each transducer required in a specific application, then it is necessary Figure 8 Additional steps as shown.

[0343] The target position of the transducer is the position of the transducer relative to the body part that is needed to generate a target field distribution in the body part when a set of treatment parameters is applied. In many embodiments, the target position is part of the set of treatment parameters.

[0344] Fig. 9 For example, it is shown that Figure 8 Two different views of an exemplary embodiment of an object-specific carrier element 1 produced by the process are shown.

[0345] The carrier element 1 comprises a portion 16 of rigid material forming the negative side of the body part to be stimulated, which means that it comprises a surface 17 forming the negative side of the surface of the body part to be stimulated.

[0346] The carrier element 1 is shown in a simplified manner adapted to the forearm of a specific user.

[0347] Fig. 9 The carrier element 1 is not only subject-specific, meaning that it not only comprises a surface 17 that forms a nearly perfect negative side of the forearm of the subject (but not another subject in general), but it is also treatment-specific. This means that the fixation element 10 and the transducer (when mounted to the carrier element 1) have positions that correspond to the target positions of a specific treatment after mounting the carrier element 1 on the body part.

[0348] It goes without saying that it can be imagined that Fig. 9The carrier element 1 shown, however, comprises a plurality of fixation elements, each of which is located at a position corresponding to a target position for a specific treatment after mounting the carrier element 1 on a body part.

[0349] Fig.10 For example, it is shown that Figure 8 A further exemplary embodiment of an object-specific carrier element 1 produced by the process is shown.

[0350] The carrier element 1 shown is Fig. 9 The carrier element 1 shown in FIG. 1 differs in that it comprises a plurality of fixing elements 10 . This means that Fig.10 The carrier element 1 is user-specific and not treatment-specific. Instead, the transducers can be mounted in a position and number corresponding to a set of treatment parameters for one of various possible treatments.

[0351] For example, the mounting of the transducer can be supported by markings arranged on the carrier element.

[0352] Alternatively, the transducer may be fixedly mounted to the fixation element 10, and the controller of the treatment device may be configured to activate the transducer as dictated by the set of treatment parameters.

Claims

1. An apparatus for determining a set of subject-specific treatment parameters for acoustic wave stimulation, configured to perform the following steps: generating subject specific data, wherein the step of generating subject specific data comprises measuring geometrical properties of the body part; determining a target field distribution in the body part, wherein the step of determining the target field distribution comprises selecting an application; Features comprising the step of selecting a set of treatment parameters from at least two different sets of treatment parameters, wherein the step of selecting a set of treatment parameters is performed before the step of applying any set of treatment parameters to the body part; The step of selecting a set of treatment parameters includes comparing a first expected field distribution associated with the first set of treatment parameters with the target field distribution, and comparing a second expected field distribution associated with the second set of treatment parameters with the target field distribution.

2. The device for determining a set of subject-specific treatment parameters for acoustic wave stimulation according to claim 1, wherein at least one of the measured geometrical properties and the subject-specific information is taken into account in the step of selecting a set of treatment parameters.

3. The apparatus for determining a set of subject-specific treatment parameters for acoustic wave stimulation according to claim 1, wherein the step of generating subject-specific data comprises the following sub-steps: adding tissue characteristics of the body part to the measured geometrical properties; - Generating a digital 3D model of the body part based on the measured geometrical properties and the added tissue features.

4. The apparatus for determining a set of subject-specific treatment parameters for acoustic wave stimulation according to claim 3, comprising the steps of: Determine the first set of treatment parameters; Calculating a calculated field distribution of the acoustic field in the body part using the digital 3D model of the body part and the first set of treatment parameters; · determining the difference between the calculated field distribution and the target field distribution; · adjusting the first set of treatment parameters to a second set of treatment parameters; The step of selecting a set of treatment parameters comprises selecting from the first set of treatment parameters and the second set of treatment parameters.

5. An apparatus for determining a set of object-specific treatment parameters for acoustic wave stimulation according to claim 4, wherein the steps of calculating the calculated field distribution, determining the difference between the calculated field distribution and the target field distribution, and adjusting the first set of treatment parameters are repeated until the difference between the calculated field distribution and the target field distribution is less than a preset value.

6. The apparatus for determining a set of subject-specific treatment parameters for acoustic stimulation according to claim 1, comprising the step of transmitting the subject-specific data to an electronic library, wherein the electronic library is configured to perform the steps of determining a target field distribution and selecting a set of treatment parameters.

7. The apparatus for determining a set of subject-specific treatment parameters for acoustic wave stimulation according to claim 1, comprising the further step of measuring neuronal activity of the body part and / or measuring electrical activity of the body part.

8. The apparatus for determining a set of subject-specific treatment parameters for acoustic wave stimulation according to claim 1, further comprising: The steps of providing a wearable device comprising at least one transducer, arranging the wearable device at the body part, and reading a position of the at least one transducer relative to the body part.

Images