System and method for stroke identification and treatment

Abstract

The invention relates to a monitoring and treatment system for stroke detection and treatment, comprising at least one sensor, at least one stimulator and circuitry configured to receive and analyze data received from the at least one sensor and further configured for activating / deactivating the at least one stimulator in view of the analyzed data; where the circuitry is configured to assess at least one of stiffness of an artery; and where the at least one stimulator is configured to provide one or more of Vagus -Nerve- Stimulation (VNS) and Baroreceptor stimulation.

Description

[0001] SYSTEM AND METHOD FOR STROKE IDENTIFICATION AND TREATMENT

[0002] RELATED APPLICATION / S

[0003] This application claims the benefit of priority of U.S. Provisional Patent Application No. 63 / 555,597 filed on 20 February 2024 and from U.S. Provisional Patent Application No. 63 / 559, 290 filed on 29 February 2024, the contents of which are incorporated herein by reference in their entirety.

[0004] FIELD AND BACKGROUND OF THE INVENTION

[0005] The present invention, in some embodiments thereof, relates to systems and methods for stroke identification and treatment and, more particularly, but not exclusively, to automated systems and methods for stroke identification and treatment.

[0006] Additional background art includes U.S. Patent application No. US20200253491A1 disclosing an apparatus that includes a mobile, neck wearable combinatorial ultrasound / near infrared sensors system configured for detection of embolic events in carotid arteries.

[0007] European patent application No. EP3677175A1 disclosing an apparatus and method comprising: obtaining first measurement data relating to blood flow in a left vertebral artery of a subject from a first sensor of an apparatus applied to a neck of the subject; obtaining second measurement data relating to blood flow in a left carotid artery of the subject from a second sensor of the apparatus applied to the neck of the subject; obtaining third measurement data relating to blood flow in a right carotid artery of the subject from a third sensor applied to the neck of the subject; and obtaining fourth measurement data relating to blood flow in a right vertebral artery of the subject from a fourth sensor applied to the neck of the patient, wherein: the first to fourth measurement data are obtained in synchronism with each other; and each of the first to fourth measurement data includes one or more of pulse amplitude, blood flow velocity or blood flow quantity for the respective artery.

[0008] U.S. Patent application No. US20170281023A1 disclosing a system for determining blood flow to and from the brain of a patient includes a plurality of magnetic elements configured to be positioned adjacent to the neck of the patient and apply at least one magnetic field to the neck of the patient. The system includes a plurality of electrodes configured to be in electrical contact with the neck of the patient, the electrodes configured to detect a voltage induced across the neck of the patient responsive to the applied magnetic field and blood flow through the neck of the patient. The system includes a support component for holding the plurality of magnetic elements and the plurality of electrodes at the neck of the patient. U.S. Patent No. US 11375911B2 disclosing a carotid physiological parameter monitoring system, comprising: an electrocardiographic (ECG) monitoring device, a carotid pulse wave detector, and at least one controller. The ECG monitoring device is disposed on a user's left and right wrists or on the user's chest to obtain ECG waveforms. The carotid pulse wave detector is disposed on the user's neck at a position corresponding to the user's carotid arteries for obtaining carotid pulse waveforms. The controller is provided in at least one of the ECG monitoring device, the carotid pulse wave detector, and a mobile device, wherein the controller is configured to obtain the user's carotid physiological parameter(s) (which may include carotid pulse wave velocity or carotid blood pressure) by calculating with the ECG waveforms and / or the carotid pulse waveforms.

[0009] U.S. Patent No. US 11412944B2 disclosing a method for measuring sound from vortices in the carotid artery comprising: first and second quality control provisions, wherein the quality control compares detected sounds to pre-determined sounds, and upon confirmation of the quality control procedures, detecting sounds generated by the heart and sounds from vortices in the carotid artery for at least 30 seconds.

[0010] U.S. Patent application No. US20110196245A1 disclosing a method of finding an indication of a degree of cerebro-vascular bilateral asymmetry in a subject, comprising: a) measuring a first impedance waveform and a second impedance waveform of the subject's head as functions of time, in each case by finding a potential difference between two voltage electrodes associated with passing a given injected current through the head between at least two current electrodes, wherein in each case the voltage electrodes are located asymmetrically on the head, or the current is injected asymmetrically into the head, or both, and wherein the locations of the voltage electrodes and the distribution of current injection in measuring the second impedance waveform are minor images of what they are in measuring the first impedance waveform; and b) finding the indication of the degree of bilateral asymmetry from a difference between characteristics of the first and second impedance waveforms.

[0011] SUMMARY OF THE INVENTION

[0012] Following is a non-exclusive list including some examples of embodiments of the invention. The invention also includes embodiments which include fewer than all the features in an example and embodiments using features from multiple examples, also if not expressly listed below.

[0013] Example 1. A monitoring and treatment system for stroke detection and treatment, comprising: a. at least one sensor; b. at least one stimulator; c. circuitry configured to receive and analyze data received from said at least one sensor and further configured for activating said at least one stimulator in view of said analyzed data; wherein said circuitry is configured to assess at least one of stiffness of an artery; and wherein said at least one stimulator is configured to provide one or more of Vagus-Nerve-

[0014] Stimulation (VNS) and Baroreceptor stimulation.

[0015] Example 2. The system according to example 1, wherein said at least one sensor and said at least one stimulator are positioned externally to said patient and attached to a location on the skin of said patient.

[0016] Example 3. The system according to example 1 or example 2, wherein said at least one sensor is positioned externally to said patient and attached to a location on the skin of said patient and said at least one stimulator is implanted in said patient.

[0017] Example 4. The system according to any one of examples 1-3, wherein said at least one stimulator is positioned externally to said patient and is attached to a location on the skin of said patient and said at least one sensor is implanted in said patient.

[0018] Example 5. The system according to any one of examples 1-4, wherein said at least one sensor and said at least one stimulator are implanted in said patient.

[0019] Example 6. The system according to any one of examples 1-5, further comprising at least one additional external device configured to communicate with said at least one sensor and / or said at least one stimulator.

[0020] Example 7. The system according to any one of examples 1-6, wherein said circuitry is positioned in said at least one additional external device.

[0021] Example 8. The system according to any one of examples 1-7, wherein said at least one additional external device is one or more of: a cellphone, a tablet, a computer or any other dedicated electronic device.

[0022] Example 9. The system according to any one of examples 1-8, wherein said at least one sensor includes one or more micro-electromechanical systems (MEMS)-based altimeter sensors.

[0023] Example 10. The system according to any one of examples 1-9, wherein said at least one sensor includes one or more integrated digital pressure sensors.

[0024] Example 11. The system according to any one of examples 1-10, wherein said one or more integrated digital pressure sensors are configured to detect pressures of 5 to 1000 mbar.

[0025] Example 12. The system according to any one of examples 1-11, wherein said circuitry comprises a controller and / or a processor comprising dedicated Al-powered algorithms configured for detecting abnormalities in various measurements of hemodynamic parameters made by said at least one sensor.

[0026] Example 13. The system according to any one of examples 1-12, wherein said system is configured to send an alert when a measurement of said stiffness of an artery is above or below a predetermined value.

[0027] Example 14. The system according to any one of examples 1-13, wherein said system is configured to transmit the measured data to a gateway and / or to the cloud.

[0028] Example 15. The system according to any one of examples 1-14, wherein one or more of said at least one sensor, said at least one stimulator and said circuitry comprise a chargeable battery.

[0029] Example 16. The system according to any one of examples 1-15, wherein one or more of said at least one sensor, said at least one stimulator and said circuitry comprise a battery that are wirelessly rechargeable.

[0030] Example 17. The system according to any one of examples 1-16, wherein said at least one sensor is configured to collect data in one or more measurement modalities,

[0031] Example 18. The system according to any one of examples 1-17, wherein said at least one sensor comprise one or more of: a piezoelectric sensor, a magnetic sensor, an accelerometer, a fiberoptic, a pressure sensor, a temperature, a PPG sensor and a resistive / optical strain gauge sensor.

[0032] Example 19. The system according to any one of examples 1-18, wherein said at least one sensor is a sensor array.

[0033] Example 20. The system according to any one of examples 1-19, wherein said system comprises two sensors.

[0034] Example 21. The system according to any one of examples 1-20, wherein said at least one sensor is configured to measure one or more of pressure, stiffness, displacement and reactivity of an artery. Example 22. The system according to any one of examples 1-21, wherein said system is configured to communicate with other systems used by said patient.

[0035] Example 23. The system according to any one of examples 1-22, wherein said other systems are one or more of cardiac rhythm systems, neurotological systems and drug delivery systems.

[0036] Example 24. The system according to any one of examples 1-23, wherein said circuitry comprises instructions to analyze said data by performing a Dicrotic Notch Timing and Area Under Curve (AUC) Analysis.

[0037] Example 25. The system according to any one of examples 1-24, wherein said Dicrotic Notch Timing and AUC Analysis comprises one or more of: a. calculating a temporal duration from an onset of an arterial pulse to an occurrence of a dicrotic notch; and b. computing a ratio of the area under the curve (AUC) from said dicrotic notch forward to a total pulse waveform area.

[0038] Example 26. A method for stroke detection and treatment, comprising: a. positioning at least one sensor at a certain distance of an artery; b. monitoring for a change in stiffness in said artery; c. detecting a stiffness change; d. automatically determining stroke evolution; e. providing one or more of Vagus-Nerve-Stimulation (VNS) and Baroreceptor stimulation based on a result of said determining.

[0039] Example 27. The method according to example 26, further comprising reassessing stiffness state and, if necessary, repeating said providing one or more of Vagus-Nerve-Stimulation (VNS) and Baroreceptor stimulation.

[0040] Example 28. The method according to example 26 or example 27, wherein said determining stroke evolution comprises analyzing data by performing a Dicrotic Notch Timing and Area Under Curve (AUC) Analysis.

[0041] Example 29. The method according to any one of examples 26-28, wherein said Dicrotic Notch Timing and AUC Analysis comprises one or more of: a. calculating a temporal duration from an onset of an arterial pulse to an occurrence of a dicrotic notch; and b. computing a ratio of the area under the curve (AUC) from said dicrotic notch forward to a total pulse waveform area.

[0042] Unless otherwise defined, all technical and / or scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention pertains. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of embodiments of the invention, exemplary methods and / or materials are described below. In case of conflict, the patent specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and are not intended to be necessarily limiting.

[0043] As will be appreciated by one skilled in the art, some embodiments of the present invention may be embodied as a system, method or computer program product. Accordingly, some embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, some embodiments of the present invention may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied thereon. Implementation of the method and / or system of some embodiments of the invention can involve performing and / or completing selected tasks manually, automatically, or a combination thereof. Moreover, according to actual instrumentation and equipment of some embodiments of the method and / or system of the invention, several selected tasks could be implemented by hardware, by software or by firmware and / or by a combination thereof, e.g., using an operating system.

[0044] For example, hardware for performing selected tasks according to some embodiments of the invention could be implemented as a chip or a circuit. As software, selected tasks according to some embodiments of the invention could be implemented as a plurality of software instructions being executed by a computer using any suitable operating system. In an exemplary embodiment of the invention, one or more tasks according to some exemplary embodiments of method and / or system as described herein are performed by a data processor, such as a computing platform for executing a plurality of instructions. Optionally, the data processor includes a volatile memory for storing instructions and / or data and / or a non-volatile storage, for example, a magnetic hard-disk and / or removable media, for storing instructions and / or data. Optionally, a network connection is provided as well. A display and / or a user input device such as a keyboard or mouse are optionally provided as well.

[0045] Any combination of one or more computer readable medium(s) may be utilized for some embodiments of the invention. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

[0046] A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electromagnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0047] Program code embodied on a computer readable medium and / or data used thereby may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0048] Computer program code for carrying out operations for some embodiments of the present invention may be written in any combination of one or more programming languages, including an object-oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0049] Some embodiments of the present invention may be described below with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general-purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0050] These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function / act specified in the flowchart and / or block diagram block or blocks. The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0051] Some of the methods described herein are generally designed only for use by a computer, and may not be feasible or practical for performing purely manually, by a human expert. A human expert who wanted to manually perform similar tasks might be expected to use completely different methods, e.g., making use of expert knowledge and / or the pattern recognition capabilities of the human brain, which would be vastly more efficient than manually going through the steps of the methods described herein.

[0052] BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

[0053] Some embodiments of the invention are herein described, by way of example only, with reference to the accompanying drawings. With specific reference now to the drawings in detail, it is stressed that the particulars shown are by way of example and for purposes of illustrative discussion of embodiments of the invention. In this regard, the description taken with the drawings makes apparent to those skilled in the art how embodiments of the invention may be practiced.

[0054] In the drawings:

[0055] Figure 1 is a schematic representation of an exemplary monitoring and treatment system comprising a device for stroke detection and Vagus -Nerve- Stimulation (VNS) / Baroreceptor- stimulation treatment, according to some embodiments of the invention;

[0056] Figure 2 is an image of an external configuration, according to some embodiments of the invention;

[0057] Figure 3 is a schematic representation of an external configuration 300, according to some embodiments of the invention;

[0058] Figures 4A-4C are schematic representations of exemplary implantable configurations of the device, according to some embodiments of the invention;

[0059] Figure 5 is a schematic representation of an implantable configuration 500, according to some embodiments of the invention;

[0060] Figures 6A-6C are schematic representations of different external configurations, according to some embodiments of the invention; Figure 7 is an exemplary implantable stimulator, according to some embodiments of the invention;

[0061] Figure 8 is a schematic representation of an exemplary magnetic rechargeable sensor, according to some embodiments of the invention;

[0062] Figure 9 is a schematic representation of exemplary membrane sensors, according to some embodiments of the invention;

[0063] Figure 10 is a flowchart of an exemplary principle of action of the system, according to some embodiments of the invention;

[0064] Figure 11 is a graph presenting the results of recordings of 27 patients. High-quality bilateral pulse waveforms were recorded in 27 patients;

[0065] Figure 12 shows a typical example of a pulse wave;

[0066] Figure 13 shows an exemplary comparison between a template and a pulse wave;

[0067] Figure 14 show exemplary templates;

[0068] Figure 15 is a graph of LVO probability indicator across participants;

[0069] Figure 16 is a graph showing the results of a rat study;

[0070] Figure 17 is a graph showing the results of an astronaut study; and

[0071] Figure 18 is a graph showing the results of a stroke patient that underwent thrombectomy.

[0072] DESCRIPTION OF SPECIFIC EMBODIMENTS OF THE INVENTION

[0073] The present invention, in some embodiments thereof, relates to systems and methods for stroke identification and treatment and, more particularly, but not exclusively, to automated systems and methods for stroke identification and treatment.

[0074] Overview

[0075] A broad aspect of some embodiments of the invention relates to preventing strokes by providing a treatment before the stroke occurs. An aspect of some embodiments of the invention relates to automated systems and methods for monitoring an impending stroke and automated systems and methods for treating, and possibly preventing, the impending stroke. In some embodiments, the system comprises a sensor positioned in the vicinity of the carotid arteries. In some embodiments, the sensors ae configure to monitor changes in the carotid pulse waves and / or in the stiffness of the arteries. In some embodiments, once the sensors detect certain predetermined parameters and / or the sensed parameters pass a certain threshold, the system activates the treatment. In some embodiments, the treatment is Vagus Nerve Stimulation (VNS). In some embodiments, the treatment is Baroreceptor-stimulation. In some embodiments, the treatment is a combination of the aforementioned treatments.

[0076] In some embodiments, the system comprises dedicated Al based algorithms configured for the personalized monitoring and treatment of the specific patient.

[0077] In some embodiments, the device is a small form factor device, either external or implantable for monitoring changes in the carotid pulse waves and / or in the stiffness of the arteries. In some embodiments, the device comprises an altimeter sensor (MEMS-based) with an integrated digital pressure sensor (5 to 1000 mbar). In some embodiments, the device comprises a high resolution, low power ASIC. In some embodiments, the device comprises a capacitor and / or a battery. In some embodiments, the device comprises a stimulator, either external or implanted, configured to provide Vagus Nerve Stimulation (VNS). In some embodiments, the device comprises a stimulator, either external or implanted, configured to provide Baroreceptorstimulation. In some embodiments, the device comprises one or more stimulators, either eternal or internal, and configured to provide more than one type of treatment. In some embodiments, the device is configured for measuring continuous monitoring of blood velocity to the brain. In some embodiments, the device is configured for measuring stiffness of the arteries. In some embodiments, the system comprises algorithms with Al for abnormality detection and alert. In some embodiments, optionally, the system is configured for data transmission to gateway and cloud. In some embodiments, the system comprises a cloud-based application and data access. In some embodiments, the access is from a tablet or cellphone through a secured application. In some embodiments, the device is a wireless rechargeable device.

[0078] In some embodiments, a potential advantage of providing VNS and / or Baroreceptorstimulation is that it potentially reduces infarct volumes, potentially improves neurological deficits, potentially reduces reperfusion injury, potentially promotes neuroprotection and potentially stimulates neuroplasticity.

[0079] Before explaining at least one embodiment of the invention in detail, it is to be understood that the invention is not necessarily limited in its application to the details of construction and the arrangement of the components and / or methods set forth in the following description and / or illustrated in the drawings and / or the Examples. The invention is capable of other embodiments or of being practiced or carried out in various ways.

[0080] Referring now to Figure 1, showing a schematic representation of an exemplary monitoring and treatment system comprising a device 100 (referred hereinafter just as: device 100) for stroke detection and Vagus-Nerve-Stimulation (VNS) and / or Baroreceptor-stimulation treatment, according to some embodiments of the invention. In some embodiments, the system comprises a device 100 which comprises one or more of: at least one sensor 102, at least one controller 104, and at least one stimulator 106. In some embodiments, the device 100 is in communication with an external additional device 108, for example one or more of a cellphone, a tablet, a computer or any other dedicated electronic device.

[0081] In some embodiments, the device 100 is designed to be a small form factor device for continuous Pulse Wave Velocity (PWV) monitoring and / or for monitoring the stiffness level of the arteries, configured to continuously monitor blood flow to the brain. In some embodiments, the device 100 comprises one or more micro-electromechanical systems (MEMS)-based altimeter sensor, having an integrated digital pressure sensor (see below). In some embodiments, integrated digital pressure sensor can detect pressures of 5 to 1000 mbar. In some embodiments, the circuitry of the device 100 comprises a high resolution, low-power application- specific integrated circuit (ASIC. In some embodiments, the system comprises a controller and / or processor, equipped with specialized Al-powered algorithms aimed at detecting abnormalities in the various measurements of hemodynamic parameters, and generating timely alerts to the user.

[0082] In some embodiments, the device 100 is configured to transmit the measured data to a gateway and / or to the cloud, providing the possibility of implementation of cloud-based application and data access. In some embodiments, data access is available through a cellphone or tablet device, through a secured application.

[0083] In some embodiments, the device 100 is a wirelessly chargeable device.

[0084] Exemplary sensor 102

[0085] In some embodiments, the at least one sensor 102 is configured to measure data indicative of one or more hemodynamic parameters of the monitored individual and send the measured data to the controller 104. In some embodiments, the measured data is one or more of: blood pressure measurements, patient’s pulse, ECG, temperature and movement.

[0086] In some embodiments, the at least one sensor 102 is positioned in the vicinity of at least one blood vessel carrying blood to / from the brain, as will be further explained below. In some embodiments, the at least one sensor 102 is configured to collect data in one or more measurement modalities (e.g., optical, ultrasound, capacitive). In some embodiments, the at least one sensor 102 is one or more of: a piezoelectric sensor, a magnetic sensor, an accelerometer, a fiberoptic, a pressure sensor, a PPG sensor and a resistive / optical strain gauge sensor. In some embodiments, the device 100 is comprised of two sensors 102. In some embodiments, the two sensors 102 are positioned one on each side of the neck, either adhered to the skin of the patient with adhesive pads or implanted (see below - Exemplary configuration). In some embodiments, the at least one sensor is a sensing unit comprises an array of sensors configured to collect the measured data from the carotid artery. In some embodiments, the sensing unit comprises a two-dimensional array of sensors configured to be placed in a vicinity of an area of the individual's neck covering the carotid artery; the control and processing unit is configured to activate one or more sensors of the two-dimensional array of sensors to collect the measured data.

[0087] As mentioned above, in some embodiments, the device 100 comprises at least one sensor 102, configured to collect data in one or more measurement modalities (e.g., optical, ultrasound, capacitive). In some embodiments, the at least one sensor 102 is one or more of the following: a temperature sensor, a piezoelectric sensor, a pressure sensor. In some embodiments, the at least one sensor 102 comprises at least one of an electrocardiogram (ECG) detector, a pulse wave detector and / or an acoustic signals detector.

[0088] Exemplary controller 104

[0089] In some embodiments, the device 100 comprises at least one controller 106 configured for receiving data from the at least one sensor 102, for example via cables or wirelessly. In some embodiments, the controller 104 is configured to control the actions performed by the device 100 and compile the measured data. In some embodiments, the controller 104 is configured to generate a command receivable as an alert by at least one additional component of the system (see below exemplary device components). In some embodiments, the alert is sent to the patient and / or to the additional external device 108. In some embodiments, the alert is configured to trigger the VNS treatment by the stimulator 106.

[0090] Exemplary stimulator 106

[0091] In some embodiments, treatment is provided by the stimulator 106 in the form of Vagal Nerve Stimulation (VNS). In some embodiments, the stimulator 106 is either positioned externally, meaning attached to the skin of the patient, or is implanted within the patient (see - Exemplary configurations).

[0092] In some embodiments, treatment provided by the stimulator 106 is in the form of Baroreceptor-stimulation. In some embodiments, the stimulator 106 is configured to provide an electrical stimulation to the Baroreceptors, which in turn cause the relaxation of the arteries.

[0093] In some embodiments, the stimulator 106 is configured to provide either of the abovementioned treatments. Exemplary external additional device 108

[0094] In some embodiments, the external additional device 108 comprises a processor 110 configured to receive measured data from the device 100 and analyze the received data. In some embodiments, the device 100 and the external additional device 108 communicate between each other, either wirelessly or via cables, to allow proper operation of the system. In some embodiments, the external additional device 108 comprises a graphic user interface (GUI) and software programmed to run specialized analysis algorithms, which are further explained below.

[0095] In some embodiments, the processor 110 processes / analyzes the measured data received from the at least one sensor 102 to determine a hemodynamic parameter such as blood velocity, blood flow, blood volume, heart rate variability, vessel volume, blood characteristics such as oxygen or other constituents. Optionally, the processor 110 then analyzes the hemodynamic parameter(s). In some embodiments, an exemplary sampling rate is from about 500Hz to about IKHz, optionally from about 300Hz to about 1.5KHz, optionally from about 200Hz to about 3KHz. In some embodiments, the exemplary sampling rate is divided between channels, for example, in a sampling rate of IKHz, there will be used a sampling rate of 250Hz per channel in the case of 4 channels. In some embodiments, upon detecting a predetermined change over time in the hemodynamic parameter(s), individually or among different parameters - like stiffness of the arteries, the processor generates output data indicative of the blood supply to the brain. In some embodiments, the output data is used to generate an alert to the user, notifying of a change in the blood supply to the brain, according to pre-determined base levels, for example, predetermined base levels that are / were present in the relevant specific patient. In some embodiments, the processor generates the output data once there is a difference above a predetermined base level between the measured data or the processed hemodynamic data and baseline data.

[0096] Exemplary configurations

[0097] In some embodiments, the device 100 is configured to be positioned externally, for example, on the surface of the skin of a patient (referred hereinafter to as an “external device” and comprises an “external configuration” (see below). In some embodiments, optionally, one or more parts of the device 100 are placed within the tissue of the patient - in these cases, such device is referred hereinafter to “implanted / implantable device” and comprises an “implantable configuration” (see below). Exemplary components of the device 100

[0098] In some embodiments, the device 100, whether an external device or an implantable device, comprises one or more of the following components:

[0099] - A / D converter (may be integral with at least one sensor 102), depending on the transmission protocol for transmitting the signals detected by the sensor 102 and transmitted to the controller 104 and / or processor. Optionally, the A / D converter should be of at least 8 bits to meet the specific application requirements.

[0100] - Bluetooth / Wi-Fi / other transmitters for transmitting the signals to the controller 104 and / or processor or a wired network. In some embodiments, the method of transmitting the data, whether wired or wireless, depends on safety, environmental and ergonomic considerations.

[0101] - A power supply, for example a battery included for powering any and / or all of the parts / components of the device 100. In some embodiments, the battery is small, lightweight, and flat, designed to allow for continuous operation.

[0102] - A receiver (that may form part of the controller 104 and / or processor), designed to collect signals from the at least one sensor 102, allowing for possible synchronous operation when a plurality of sensors is present. In some embodiments, where the monitored hemodynamic parameter is the pulse wave of the blood, the receiver is adapted to a sampling rate of more than 10Hz.

[0103] Exemplary external configuration

[0104] Referring now to Figure 2, showing an image of an external configuration, according to some embodiments of the invention. In some embodiments, for example, parts of the device 100 (for example the at least one sensor 102) are attached to the neck of the patient to monitor hemodynamic parameter(s) from the carotid artery(ies) and / or stiffness of the arteries. Ascending carotid arteries carrying blood to the brain are located on the right and left sides of the neck. In some embodiments, the at least one sensor 102 is attached to the neck of the patient in the vicinity of one or more of the following: the common carotid artery, the internal carotid artery (stemming from the common carotid artery and supplying blood to the brain arteries), and / or the external carotid artery (stemming from the common carotid artery and supplying blood to the facial area).

[0105] In some embodiments, in the external configuration, all the components of the device (the sensor 102, the controller 104 and the stimulator 106) are housed in a single housing unit, located on the skin, in the location of the target blood vessel to be monitored. In some embodiments, only the at least one sensor 102 and the stimulator 106 are housed in a single housing, while the controller 104 is positioned in an external device in communication (either wired or wirelessly) with the at least one sensor 102 and the stimulator 106.

[0106] Referring now to Figure 3, showing a schematic representation of an external configuration 300, according to some embodiments of the invention. In some embodiments, an exemplary layout of an external configuration 300 comprises two housing units 302, each adhered to one side of the subject’s neck (the neck not shown), proximal to the target blood vessel 304 to be monitored.

[0107] In some embodiments, each housing unit 302 comprises at least one sensor 102, a stimulator 106, (for example a VNS generator and / or Baroreceptor stimulation generator) and an analog to digital converter 306. In some embodiments, the two housing units 302 are connected, for example, via cables, to an external unit 308 comprising, for example, a Bluetooth module 310, a memory storage unit 312, a capacitor 314 and a battery 316. In some embodiments, the Bluetooth module wirelessly connects the device to a processor in an additional external device 108, having data analysis software.

[0108] Exemplary implantable configuration

[0109] Referring now to Figures 4A-4C, showing exemplary implantable configurations of the device 100, according to some embodiments of the invention.

[0110] In some embodiments, one or more parts of the device 100 are configured to be placed within the tissue of the patient, in an implantable configuration, as schematically seen for example in Figure 4A. In some embodiments, in the implantable configuration the device 100 is positioned in the vicinity of the target blood vessel to be monitored, for example, within from about 3cm to about 5cm, optionally from about 2cm to about 7cm, optionally from about 1cm to about 9cm of the target blood vessel to be monitored 304.

[0111] In some embodiments, in the implantable configuration, the implanted device 100 comprises the at least one sensor 102 and at least one controller 104 (not shown), whereas the stimulator 406 is placed externally, as shown for example in Figured 4B and 4C. In this case, the stimulator 406 is, for example, a clip-on device localized in the patient’s ear 408, as seen in Figure 4B or a handheld device 406, configured to be placed on the patient’s neck 410, as seen in Figure 4C, in a location proximal to the carotid sheath, within which runs the Vagus nerve.

[0112] Referring now to Figure 5, showing a schematic representation of an implantable configuration 500, according to some embodiments of the invention.

[0113] In some embodiments, the anatomical location of the implanted device is in the vicinity of the target blood vessel to be monitored, for example within from about 5mm to about 10mm, optionally from about 4mm to about 50mm, optionally from about 1mm to about 5cm of the target blood vessel 304 to monitored. In some embodiments, the implantable configuration comprises an implantable device 100 and an external stimulator 406. In some embodiments, the external stimulator 406 can optionally be connected to an additional external device 108 such as a cellphone or tablet. In some embodiments, the implantable device 100 comprises one or more of: a Bluetooth module 502, a memory storage unit 504, a chargeable battery 506, a sensor module array 508, an analog to digital converter 510, and microcontroller 512.

[0114] In some embodiments, the external stimulator 406 comprises one or more of: a Bluetooth module 514 and a capacitor 516. In some embodiments, additional external device 108 comprises a GUI, an application for operating specialized analysis software, and a gateway. In some embodiments, the specialized analysis software comprises algorithms provided by the present invention, detailed below.

[0115] Exemplary different implantable configurations

[0116] In some embodiments, in the implantable configuration, the components of the system can be divided (positioned) between the implantable device 100, the external stimulator 406 and the additional external device 108.

[0117] Referring now to Figures 6A-6C showing schematic representations of different external configurations, according to some embodiments of the invention.

[0118] Referring now to Figure 6A showing a first exemplary implantable configuration, according to some embodiments of the invention. In some embodiments, this interface comprises the implantable device 100, schematically shown implanted in each side of the neck, and an external stimulator 504 (not shown). In some embodiments, the implantable device 100 comprises a Bluetooth module 502, a memory storage unit 504, and a power source 506. In some embodiments, the power source is for example a chargeable battery. In some embodiments, the implantable device 100 comprises the sensor array 508, the A2D 510 and a controller 512. In some embodiments, the external unit 108 comprises a Bluetooth module 514, the required software, and a battery (optionally rechargeable) and / or a charging module for the implantable device 100. In some embodiments, an external storage 602 is provided, for example connected via cloud, onto which and from which data is transmitted into and from the system.

[0119] Referring now to Figure 6B showing a second exemplary implantable configuration, according to some embodiments of the invention. The configuration shown in Figure 6B is similar to that shown in Figure 6A with the difference that the implantable device 100 does not comprise the controller 512, which allows the implantable device 100 to be smaller. In this case, the implantable device 100 is controlled by the external unit 108. Referring now to Figure 6C, showing a third exemplary implantable configuration, according to some embodiments of the invention. The configuration shown in Figure 6C is similar to that shown in Figure 6B with the difference that the implantable device 100 does not comprise a rechargeable battery 506. Instead, the implantable device 100 comprises a capacitor 604 which charged by an wearable external charging device 606.

[0120] Exemplary implantable stimulator

[0121] Referring now to Figure 7, showing an exemplary implantable stimulator, according to some embodiments of the invention. In some embodiments, the stimulator 106 is implanted in the patient. Similar to a pacemaker, electrodes 702 are implanted in the relevant area. In this case, on the Vagus Nerve 704 and / or in the vicinity of baroreceptors in the arteries. The electrodes then, are extended using a lead 706 towards a pulse generator 708, which receives the commands from the device 100 (not shown).

[0122] In some embodiments, the implantable stimulator is used with an implanted device 100 or with an external device 100.

[0123] Exemplary integration with other systems

[0124] In some embodiments, the system is configured to communicate with other systems. For example, with cardiac rhythm products (for example Insertable Cardiac Monitors (ICM); Transvenous implantable cardioverter defibrillators (ICDs); and / or Pacing Systems); and or with neurotological products (for example: deep brain stimulation (DBS) systems’ and / or drug delivery systems). In some embodiments, a potential advantage of integrating the device with other systems is that it potentially allows to share battery and enable multiple functions within a single implanted device, which allows to optimize power usage and functionality within a unified system.

[0125] Exemplary magnetic rechargeable sensors

[0126] Referring now to Figure 8, showing a schematic representation of an exemplary magnetic rechargeable sensor 800, according to some embodiments of the invention. In some embodiments, the body temperature is used for energy harvesting. In some embodiments, the system is configured for detecting magnetic field changes induced by blood flow using for example a hall sensor 804. In some embodiments, the system is configured to allow the pulse displacement to charge a capacitor and / or a battery 802 using a thermal charger 806. In some embodiments, the system is configured to perform data acquisition: for example, the amount of magnetic energy generated is proportional to the red blood cells (RBC) speed (flow) in an artery 304, and can be acquired for waveform data 808 of the capacitor charging reflecting pressure changes (schematically shown in Figure 8), and displacement reflects the pressure change at 90 degrees.

[0127] Exemplary membrane implantable sensors

[0128] Referring now to Figure 9, showing a schematic representation of exemplary membrane sensors, according to some embodiments of the invention.

[0129] In some embodiments, using the whole microchip surface or membrane attachment, based on passive sensors such as piezoelectric-based (optionally requiring anchoring of the sensor to limit rotation), the surface of the microchip will contain a pressure-sensitive membrane and electrical resistors. In some embodiments, changes in pressure causes the membrane to change shape. In some embodiments, an electrical current is proportional to the distortion created in the resisters.

[0130] In some embodiments, the inner component of the controller of the device is a membrane 902 that senses displacement and converts it into voltage. In some embodiments, this mechanism is similar to piezoelectric sensors, which are attached to a stiff membrane to detect displacement. In some embodiments, the membrane 902 is sensitive to displacement and vibrates accordingly. In some embodiments, these vibrations of the membrane 902 are detected as pressure changes in the pressure (altimeter) sensor 904. In some embodiments, the sensor 904 then translates these pressure changes to electrical signals. In some embodiments, these signals are then processed (digitized) and used for detecting changes. In some embodiments, as mentioned herein elsewhere, the device comprises an altimeter sensor that uses high resolution temperature output to allow the implementation of an altimeter / thermometer function without any additional sensing. In some embodiments, the software application (firmware) uses the temperature read out to calibrate and compensate the altimeter accordingly and the presented pressure already reflects that compensation.

[0131] Exemplary principle of action of the system

[0132] Referring now to Figure 10, showing a flowchart of an exemplary principle of action of the system, according to some embodiments of the invention.

[0133] In some embodiments, the exemplary principle of action comprises the following actions:

[0134] 1. Detecting a stiffness change 1002.

[0135] 2. Automatically determining stroke evolution 1004.

[0136] 3. Providing treatment (VNS and / or baroreceptor stimulation) 1006.

[0137] 4. Reassessing stiffness state 1010. 5. If necessary - repeating provision of treatment 1012.

[0138] Exemplary waveform type specifications

[0139] In some embodiments, the algorithm, optionally using Al, is configured for detecting hemodynamic fluctuations in the neck's Carotid arteries (flow to the brain) by tracking waveform variations, which reflect changes in the brain's arteries.

[0140] Referring now to Figure 11, showing a graph presenting the results of recordings of 27 patients. High-quality bilateral pulse waveforms were recorded in 27 patients. The model achieved 83% accuracy in detecting LVOs, which proved that the system successfully detects carotid pulse wave changes during acute LVO.

[0141] Additional results can be found in the examples below.

[0142] Exemplary combination of parameters in the assessment of stiffness

[0143] In some embodiments, a combination of parameters is used in the assessment of stiffness. For example:

[0144] 1. Number: as stiffness increases - the number of peaks decreases.

[0145] 2. Sharpness: as stiffness increases - the sharpness of the peaks decreases.

[0146] 3. Prominence: as stiffness increases - the prominence of peaks decreases.

[0147] 4. Dicrotic Notch Timing and Area Under Curve (AUC) Analysis.

[0148] Exemplary algorithms / methods

[0149] In some embodiments, the algorithm can be divided into two classes: quality assessment and stroke detection.

[0150] Dicrotic Notch Timing and Area Under Curve (AUC) Analysis

[0151] In some embodiments, the system leverages advanced waveform analytics to monitor arterial activity in the neck for the detection of large vessel occlusions (LVOs). Specifically, the algorithm calculates the temporal duration from the onset of the arterial pulse to the occurrence of the dicrotic notch, a critical point in the waveform indicative of vascular function. Additionally, it computes the ratio of the area under the curve (AUC) from the dicrotic notch forward to the total pulse waveform area. These features are tracked continuously over time to provide dynamic insights into vascular behavior and potential pathological changes. Welch's t-Test for Statistical Comparison of Arterial Features

[0152] In some embodiments, to evaluate the significance of mean differences between arterial features — such as the Area Under the Curve (AUC) — from the right and left sides, the system employs Welch's t-test. This statistical test is specifically designed to handle comparisons between two populations with potentially unequal variances and sample sizes, which is particularly relevant in the context of physiological signal analysis. By applying Welch's t-test, the system quantifies the degree of asymmetry between the right and left arterial signals, providing a robust measure of statistical significance. This approach is ideally suited for detecting differences that may indicate the presence of a large vessel occlusion (LVO), where such asymmetries are expected to arise due to localized vascular impairments.

[0153] Exemplary quality assessment:

[0154] In order to ensure that the system perform properly, the stroke detection algorithm is trained on and evaluates only the high quality and informative segment of the data. The algorithms begin with an assumption that the only informative part of the signal is the pulse wave following each pulse of the heart.

[0155] Figure 12 shows a typical example of a pulse wave.

[0156] The quality assessment algorithm can be broken into 3 steps:

[0157] 1. Peak Detection

[0158] Exemplary Approach: One channel is chosen to be used to detect pulse waves based on identifying the peaks. The channel is chosen at random to start and then according to the which channel has the highest quality signal based on the recent history of the quality assessment outputs.

[0159] Additional Exemplary Approaches: Adding conditions for evaluating suggested peaks such as weighing the suggestions by the resulting frequency of the peaks. It is expected for the frequency of peaks to be within the range of normal heart rates (60-100 bpm). Choosing peaks with good agreement between channels. This has a tradeoff of better accuracy at the expense of time and computational power.

[0160] 2. Detect pulse wave onset and termination

[0161] Exemplary Approach: The onset (as shown for example in Figure 12 by dot 1202) is calculated independently for each channel. A Method adapted from Martinez et al. 2022. In short, candidates for the upstroke of the pulse wave are determined by finding the peaks of the first derivative of the signal (as shown for example in Figure 12 by dot 1204). The candidates are then weighted according to their height in the normalized first derivative signal. For each candidate, the preceding trough in the original signal is found. A second weight is calculated by comparing the signal to a reference template (dual double frequency) using DTW and then taking the DTW computed distance of each point in the signal to the onset foot of the template. The onset of the pulse wave is the trough in the signal with the highest composite weight of first derivative height and distance from the reference foot. Termination of pulses is set as 400ms following the onset.

[0162] Exemplary Additional Approaches: Calculating per pulse wave the termination point.

[0163] 3. Exemplary Quality Assessment

[0164] Exemplary Approach: Quality assessment is done by template matching pulse waves to a reference template (dual double frequency template) using DTW (as shown for example in Figure 13). Lower values indicate a better match.

[0165] DTW TEMPLATE MATCHING: The pulse wave is matched to the reference template. The distance between points along the pulse wave are mapped to points along the reference and the distance between those points are calculated. DTW score is the average distance over all points.

[0166] Exemplary Additional Approaches: The fixed reference may be changed for an adaptive reference learned from the real time data. DTW can be used in feature engineering to extract relevant information regarding the signal that can be used in the machine learning models for stroke detection.

[0167] 4. Subsets of pulse wave

[0168] The pulse wave is the summation of a forward and backward wave and different time windows within the pulse are dominated differently by each sub-wave. Using the DTW score from different time windows may be a relevant feature in the model.

[0169] 5. Fiduciary Points

[0170] Since DTW maps points on the pulse wave to points along the reference, DTW can be used to define fiduciary points such as the peak and the dicrotic notch by identifying the point whose mapping to the relevant point on the reference is of the shortest distance.

[0171] 6. Type Matching

[0172] Different shapes of the pulse wave are associated with different levels of arterial stiffness and can be correlated with age. Stiffness is highly likely to change with the formation of an LVO. Determining which shape has the closest DTW match with the pulse wave could be used as a feature providing domain relevant information about the pulse wave. Currently four templates are used (Types A, B, C, and D, see Figure 14). However more precision could be achieved by modeling the forward and reverse waves and creating additional types at a finer resolution by modulating the timing of each wave.

[0173] Stroke Detection (Avert):

[0174] Deep Learning Autoencoder model inputs time series and learns its own normal baseline activity and represents activity in a bottleneck layer. The time series is reconstructed from the bottleneck layer and compared to the original signal.

[0175] Error signal: Occlusion labels are compared with model error from reconstructing time series. It is assumed that the error should increase during occlusion because this is a deviation from normal activity. An error threshold is set to mark as occlusion.

[0176] Clustering of pulse wave variants: The bottleneck layer can be thought of a dimension reduction of the signal. A k-means algorithm is applied to this reduced representation of the pulse waves to cluster the pulse waves into clusters. The hypothesis is that there might be clusters or distribution of clusters that are associated with the presence of an LVO.

[0177] Exemplary additional uses of the system (not cardiovascular)

[0178] In some embodiments, the system can be configured to check fluctuations and deterioration of cognitive function, for example, by the positive sensing of the presence of repetitive strokes in the patient.

[0179] In some embodiments, the system comprises an integrated GPS for the monitoring of the location of the patient, for example, for patients suffering of dementia.

[0180] In some embodiments, the system is configured to alert in cases of an aneurysm, for example, by sensing a drop in stiffness.

[0181] In some embodiments, the system is configured to monitor the progression of diabetes, for example, by monitoring the stiffness of the arteries that increases in diabetes cases.

[0182] In some embodiments, the system is configured to monitor orthostatic hypertension.

[0183] As used herein with reference to quantity or value, the term “about” means “within ± 10 % of’.

[0184] The terms “comprises”, “comprising”, “includes”, “including”, “has”, “having” and their conjugates mean “including but not limited to”.

[0185] The term “consisting of’ means “including and limited to”.

[0186] The term “consisting essentially of’ means that the composition, method or structure may include additional ingredients, steps and / or parts, but only if the additional ingredients, steps and / or parts do not materially alter the basic and novel characteristics of the claimed composition, method or structure.

[0187] As used herein, the singular forms “a”, “an” and “the” include plural references unless the context clearly dictates otherwise. For example, the term “a compound” or “at least one compound” may include a plurality of compounds, including mixtures thereof.

[0188] Throughout this application, embodiments of this invention may be presented with reference to a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the invention. Accordingly, the description of a range should be considered to have specifically disclosed all the possible subranges as well as individual numerical values within that range. For example, description of a range such as “from 1 to 6” should be considered to have specifically disclosed subranges such as “from 1 to 3”, “from 1 to 4”, “from 1 to 5”, “from 2 to 4”, “from 2 to 6”, “from 3 to 6”, etc.; as well as individual numbers within that range, for example, 1, 2, 3, 4, 5, and 6. This applies regardless of the breadth of the range.

[0189] Whenever a numerical range is indicated herein (for example “10-15”, “10 to 15”, or any pair of numbers linked by these another such range indication), it is meant to include any number (fractional or integral) within the indicated range limits, including the range limits, unless the context clearly dictates otherwise. The phrases “range / ranging / ranges between” a first indicate number and a second indicate number and “range / ranging / ranges from” a first indicate number “to”, “up to”, “until” or “through” (or another such range-indicating term) a second indicate number are used herein interchangeably and are meant to include the first and second indicated numbers and all the fractional and integral numbers therebetween.

[0190] Unless otherwise indicated, numbers used herein and any number ranges based thereon are approximations within the accuracy of reasonable measurement and rounding errors as understood by persons skilled in the art

[0191] As used herein the term “method” refers to manners, means, techniques and procedures for accomplishing a given task including, but not limited to, those manners, means, techniques and procedures either known to, or readily developed from known manners, means, techniques and procedures by practitioners of the chemical, pharmacological, biological, biochemical and medical arts.

[0192] As used herein, the term “treating” includes abrogating, substantially inhibiting, slowing or reversing the progression of a condition, substantially ameliorating clinical or aesthetical symptoms of a condition or substantially preventing the appearance of clinical or aesthetical symptoms of a condition. It is appreciated that certain features of the invention, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the invention, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable subcombination or as suitable in any other described embodiment of the invention. Certain features described in the context of various embodiments are not to be considered essential features of those embodiments, unless the embodiment is inoperative without those elements.

[0193] Various embodiments and aspects of the present invention as delineated hereinabove and as claimed in the claims section below find experimental support in the following examples.

[0194] EXAMPLES

[0195] Reference is now made to the following examples, which together with the above descriptions illustrate some embodiments of the invention in a non-limiting fashion.

[0196] A study was performed to Assess Hemodynamic Changes for Detection of Large Vessel Occlusions (LVO) in High-Risk Hospitalized Patients. The study was a blinded randomized, controlled study to assess stroke detection and alert device, where the study group provides a Stroke-Alert and the control group was a recording only.

[0197] The study objectives where to: 1. Determine the percentage of LVOs detected using Stroke Alert (Study group) versus standard clinical methods (Control group), including: a. timing of treatment within the therapeutic window, significantly earlier than standard clinical methods; b. patient outcomes: Comparison of patient outcomes, including changes in NIHSS scores and hospitalization duration, between the Study group and the control group; and c. user feedback: Evaluation of clinical team feedback regarding the usability and integration of the device in the clinical workflow. 2. To assess the sensitivity and specificity of LVO detection using the recorded signal. 3. To investigate the accuracy variation based on individual parameters.

[0198] Referring now to Figure 15, showing a graph of LVO probability indicator across participants.

[0199] The model learned personalized baseline hemodynamic activity.

[0200] Continuously outputs an LVO probability; Triggers an alarm above a threshold.

[0201] Using a threshold of 50% probability, LVOs are detected at 83% accuracy (median of 100%).

[0202] 27 participants; 5 false positives 8 false negatives.

[0203] The threshold did not vary according to gender, age, and BMI. Referring now to Figure 16, showing the results of a rat study. Large vessels in the brain were occluded to assess whether the system successfully detects the changes during stroke evolution and reperfusion. The combination of pulse waveform types, identified by the Al, changes following the onset of stroke. This provides a unique fingerprint that differentiates between the stroke side (right) and the non- stroke side (left).

[0204] Referring now to Figure 17, showing the results of an astronaut study. Microgravity in space causes an observed increase in blood flow to the brain, which is reflected on both sides. Astronaut data: The pulse waves identified by the Al, change from baseline after two weeks of microgravity in the international space station.

[0205] Referring now to Figure 18, showing the results of a stroke patient that underwent thrombectomy (opening of the occluded artery); change in flow is observed on the stroke side. Thrombectomy: The combination of pulse wave types, identified by the Al, changes following freeing of the occlusion by thrombectomy. This provides a unique fingerprint for stroke.

[0206] Although the invention has been described in conjunction with specific embodiments thereof, it is evident that many alternatives, modifications and variations will be apparent to those skilled in the art. Accordingly, it is intended to embrace all such alternatives, modifications and variations that fall within the spirit and broad scope of the appended claims.

[0207] It is the intent of the applicant(s) that all publications, patents and patent applications referred to in this specification are to be incorporated in their entirety by reference into the specification, as if each individual publication, patent or patent application was specifically and individually noted when referenced that it is to be incorporated herein by reference. In addition, citation or identification of any reference in this application shall not be construed as an admission that such reference is available as prior art to the present invention. To the extent that section headings are used, they should not be construed as necessarily limiting. In addition, any priority document(s) of this application is / are hereby incorporated herein by reference in its / their entirety.

Claims

WHAT IS CLAIMED IS:

1. A monitoring and treatment system for stroke detection and treatment, comprising: a. at least one sensor; b. at least one stimulator; c. circuitry configured to receive and analyze data received from said at least one sensor and further configured for activating said at least one stimulator in view of said analyzed data; wherein said circuitry is configured to assess at least one of stiffness of an artery; and wherein said at least one stimulator is configured to provide one or more of Vagus-Nerve-Stimulation (VNS) and Baroreceptor stimulation.

2. The system according to claim 1, wherein said at least one sensor and said at least one stimulator are positioned externally to said patient and attached to a location on the skin of said patient.

3. The system according to claim 1, wherein said at least one sensor is positioned externally to said patient and attached to a location on the skin of said patient and said at least one stimulator is implanted in said patient.

4. The system according to claim 1, wherein said at least one stimulator is positioned externally to said patient and is attached to a location on the skin of said patient and said at least one sensor is implanted in said patient.

5. The system according to claim 1, wherein said at least one sensor and said at least one stimulator are implanted in said patient.

6. The system according to claim 1, further comprising at least one additional external device configured to communicate with said at least one sensor and / or said at least one stimulator.

7. The system according to claim 6, wherein said circuitry is positioned in said at least one additional external device.

8. The system according to claim 6, wherein said at least one additional external device is one or more of: a cellphone, a tablet, a computer or any other dedicated electronic device.

9. The system according to claim 1, wherein said at least one sensor includes one or more micro-electromechanical systems (MEMS)-based altimeter sensors.

10. The system according to claim 1, wherein said at least one sensor includes one or more integrated digital pressure sensors.

11. The system according to claim 1, wherein said one or more integrated digital pressure sensors are configured to detect pressures of 5 to 1000 mbar.

12. The system according to claim 1, wherein said circuitry comprises a controller and / or a processor comprising dedicated Al-powered algorithms configured for detecting abnormalities in various measurements of hemodynamic parameters made by said at least one sensor.

13. The system according to claim 1, wherein said system is configured to send an alert when a measurement of said stiffness of an artery is above or below a predetermined value.

14. The system according to claim 1, wherein said system is configured to transmit the measured data to a gateway and / or to the cloud.

15. The system according to claim 1, wherein one or more of said at least one sensor, said at least one stimulator and said circuitry comprise a chargeable battery.

16. The system according to claim 1, wherein one or more of said at least one sensor, said at least one stimulator and said circuitry comprise a battery that are wirelessly rechargeable.

17. The system according to claim 1, wherein said at least one sensor is configured to collect data in one or more measurement modalities.

18. The system according to claim 1, wherein said at least one sensor comprise one or more of: a piezoelectric sensor, a magnetic sensor, an accelerometer, a fiberoptic, a pressure sensor, a temperature, a PPG sensor and a resistive / optical strain gauge sensor.

19. The system according to claim 1, wherein said at least one sensor is a sensor array.

20. The system according to claim 1, wherein said system comprises two sensors.

21. The system according to claim 1, wherein said at least one sensor is configured to measure one or more of pressure, stiffness, displacement and reactivity of an artery.

22. The system according to claim 1, wherein said system is configured to communicate with other systems used by said patient.

23. The system according to claim 1, wherein said other systems are one or more of cardiac rhythm systems, neurotological systems and drug delivery systems.

24. The system according to claim 1, wherein said circuitry comprises instructions to analyze said data by performing a Dicrotic Notch Timing and Area Under Curve (AUC) Analysis.

25. The system according to claim 24, wherein said Dicrotic Notch Timing and AUC Analysis comprises one or more of: a. calculating a temporal duration from an onset of an arterial pulse to an occurrence of a dicrotic notch; and b. computing a ratio of the area under the curve (AUC) from said dicrotic notch forward to a total pulse waveform area.

26. A method for stroke detection and treatment, comprising: a. positioning at least one sensor at a certain distance of an artery; b. monitoring for a change in stiffness in said artery; c. detecting a stiffness change; d. automatically determining stroke evolution; e. providing one or more of Vagus -Nerve- Stimulation (VNS) and Baroreceptor stimulation based on a result of said determining.

27. The method according to claim 26, further comprising reassessing stiffness state and, if necessary, repeating said providing one or more of Vagus -Nerve- Stimulation (VNS) and Baroreceptor stimulation.

28. The method according to claim 26, wherein said determining stroke evolution comprises analyzing data by performing a Dicrotic Notch Timing and Area Under Curve (AUC) Analysis.

29. The method according to claim 28, wherein said Dicrotic Notch Timing and AUC Analysis comprises one or more of: a. calculating a temporal duration from an onset of an arterial pulse to an occurrence of a dicrotic notch; and b. computing a ratio of the area under the curve (AUC) from said dicrotic notch forward to a total pulse waveform area.

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