System and method for hemodynamic anomaly detection for diagnosis and treatment

Abstract

The invention relates to a monitoring and treatment system for stroke detection and treatment, comprising at least one sensor; circuitry configured to receive and analyze data received from the at least one sensor; where the circuitry is configured to assess one or more of stiffness, pressure, displacement of a soft tissue over an artery.

Description

[0001] SYSTEM AND METHOD FOR HEMODYNAMIC ANOMALY DETECTION FOR DIAGNOSIS AND TREATMENT

[0002] RELATED APPLICATION / S

[0003] This application claims the benefit of priority of U. S. Provisional Patent Application Nos. 63 / 761,233 filed on February 21, 2025, and 63 / 915,906 filed on November 12, 2025, the contents of both 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 hemodynamic anomaly detection for diagnosis and treatment and, more particularly, but not exclusively, to automated systems and methods for hemodynamic anomaly detection, stroke probability, optionally stroke identification, for diagnosis 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:

[0014] a. at least one sensor;

[0015] b. circuitry configured to receive and analyze data received from said at least one sensor;wherein said circuitry is configured to assess one or more of stiffness, pressure, displacement of a soft tissue over an artery.

[0016] Example 2. The system according to example 1, further comprising at least one stimulator. Example 3. The system according to example 1 or example 2, wherein said circuitry is further configured for activating said at least one stimulator in view of said analyzed data.

[0017] Example 4. Th system according to any one of examples 1-3, wherein said at least one stimulator is configured to provide one or more of Vagus-Nerve-Stimulation (VNS) and Baroreceptor stimulation.

[0018] Example 5. The system according to any one of examples 1-4, wherein said at least one sensor is positioned externally to said patient and attached to a location on the skin of said patient.

[0019] Example 6. The system according to any one of examples 1-5, wherein said at least one stimulator are positioned externally to said patient and attached to a location on the skin of said patient.

[0020] Example 7. The system according to any one of examples 1-6, 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.

[0021] Example 8. The system according to any one of examples 1-7, 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.

[0022] Example 9. The system according to any one of examples 1-8, wherein said at least one sensor and said at least one stimulator are implanted in said patient.

[0023] Example 10. The system according to any one of examples 1-9, further comprising at least one additional external device configured to communicate with said at least one sensor and / or at least one stimulator.

[0024] Example 11. The system according to any one of examples 1-10, wherein said circuitry is positioned in said at least one additional external device.

[0025] Example 12. The system according to any one of examples 1-11, 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.

[0026] Example 13. The system according to any one of examples 1-12, wherein said at least one sensor includes one or more micro-electromechanical systems (MEMS)-based pressure sensors.

[0027] Example 14. The system according to any one of examples 1-13, wherein said at least one sensor includes one or more integrated digital pressure sensors.

[0028] Example 15. The system according to any one of examples 1-14, wherein said one or more integrated digital pressure sensors are configured to detect pressures of 5 to 1000 mbar.Example 16. The system according to any one of examples 1-15, wherein said circuitry comprises a controller and / or a processor comprising dedicated neural network-powered algorithms configured for detecting abnormalities in various measurements of hemodynamic parameters made by said at least one sensor.

[0029] Example 17. The system according to any one of examples 1-16, wherein said system is configured to send an alert when a result of said assessment is above or below a predetermined value.

[0030] Example 18. The system according to any one of examples 1-17, wherein said system is configured to transmit the measured data to a gateway and / or to the cloud.

[0031] Example 19. The system according to any one of examples 1-18, wherein said at least one sensor comprises a chargeable battery.

[0032] Example 20. The system according to any one of examples 1-19, wherein said at least one stimulator comprises a chargeable battery.

[0033] Example 21. The system according to any one of examples 1-20, wherein said circuitry comprises a chargeable battery.

[0034] Example 22. The system according to any one of examples 1-21, wherein the system comprises one or more batteries that are wirelessly rechargeable.

[0035] Example 23. The system according to any one of examples 1-22, wherein said at least one sensor is configured to collect data in one or more measurement modalities.

[0036] Example 24. The system according to any one of examples 1-23, 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.

[0037] Example 25. The system according to any one of examples 1-24, wherein said at least one sensor is a sensor array.

[0038] Example 26. The system according to any one of examples 1-25, wherein said system comprises two sensors.

[0039] Example 27. The system according to any one of examples 1-26, wherein said at least one sensor is configured to measure soft tissue changes that may reflect one or more of said pressure, said stiffness, said displacement and reactivity of an artery.

[0040] Example 28. The system according to any one of examples 1-27, wherein said system is configured to communicate with other systems used by said patient.

[0041] Example 29. The system according to any one of examples 1-28, wherein said other systems are one or more of cardiac rhythm systems, neurotological systems and drug delivery systems.Example 30. The system according to any one of examples 1-29, wherein said circuitry comprises instructions to analyze said data by performing a Dicrotic Notch Timing and / or Area Under Curve (AUC) Analysis.

[0042] Example 31. The system according to any one of examples 1-30, wherein said Dicrotic Notch Timing and / or AUC Analysis comprises one or more of:

[0043] a. calculating a temporal duration from an onset of an arterial pulse to an occurrence of a dicrotic notch; and

[0044] b. computing a ratio of the area under the curve (AUC) from said dicrotic notch forward to a total pulse waveform area.

[0045] Example 32. A method for stroke detection and treatment, comprising:

[0046] a. positioning at least one sensor at a certain distance of an artery;

[0047] b. monitoring for a change in one or more of stiffness, pressure, displacement of a soft tissue over said artery;

[0048] c. detecting said change;

[0049] d. automatically determining stroke evolution.

[0050] Example 33. The method according to example 32, further comprising providing one or more of Vagus-Nerve-Stimulation (VNS) and Baroreceptor stimulation based on a result of said determining.

[0051] Example 34. The method according to example 32 or example 33, further comprising reassessing said one or more of stiffness, pressure, displacement of a soft tissue over said artery.

[0052] Example 35. The method according to any one of examples 32-34, further comprising repeating said providing one or more of Vagus -Nerve- Stimulation (VNS) and Baroreceptor stimulation if necessary.

[0053] Example 36. The method according to any one of examples 32-35, wherein said determining stroke evolution comprises analyzing data by performing a Dicrotic Notch Timing and / or Area Under Curve (AUC) Analysis.

[0054] Example 37. The method according to any one of examples 32-36, wherein said Dicrotic Notch Timing and / or AUC Analysis comprises one or more of:

[0055] a. calculating a temporal duration from an onset of an arterial pulse to an occurrence of a dicrotic notch; and

[0056] b. computing a ratio of the area under the curve (AUC) from said dicrotic notch forward to a total pulse waveform area.

[0057] Example 38. A method of assessing a stroke, comprising:

[0058] a. detecting parameters from soft tissue over carotid arteries on both sides of a neck;

[0059] b. performing a comparative analysis on said detected parameters;c. assessing whether there are differences between said sides;

[0060] d. providing an alert based on a result of said assessing.

[0061] Example 39. A method of guiding a user to position sensors, comprising:

[0062] a. detecting, for each sensor, a physiological signal;

[0063] b. performing an automatic quality assessment of said detected physiological signal; and c. if necessary, providing instructions to said user to where to move each sensor in order to improve said detected physiological signal.

[0064] Example 40. A method for comparing signals detected at two different points and measuring their decay rate while removing noise, comprising:

[0065] a. acquiring a signal over a soft tissue;

[0066] b. cleaning said acquired signal;

[0067] c. performing a systematic change adjustment;

[0068] d. performing a comparison and decay analysis.

[0069] Example 41. A method for non-invasive detection and characterization of vascular changes within or leading to the brain, comprising analyzing the decay of the pulse wave between two closely positioned pressure sensors over a soft tissue over a carotid artery.

[0070] Example 42. The method according to example 41, further comprising one or more of: a. performing a setup;

[0071] b. performing waveform isolation and analysis; and

[0072] c. using the decay factor to perform physiological interpretations.

[0073] Example 43. A holder for a monitoring and treatment system comprising two units, the holder comprising a plurality of configurable elements configured to allow positioning of said units on a desired location on a patient at a desired level of pressure.

[0074] Example 44. The holder according to example 43, further comprising one or more of the following components:

[0075] a. a neck holder;

[0076] b. an arms holder connected to said neck holder;

[0077] c. two arms, each attached to a side of said arms holder;

[0078] d. a housing positioned at a distal end of each said two arms; said housing configured to reversibly hold a unit from said two units.

[0079] Example 45. The holder according to example 43 or example 44, wherein said plurality of configurable elements are positioned in at least one component from said one or more components.

[0080] Example 46. The holder according to any one of examples 43-45, wherein said plurality of configurable elements are characterized by a mechanism selected from the group consisting of:a. a translational adjustment mechanism;

[0081] b. a rotational adjustment mechanism;

[0082] c. a multi-axis rotational mechanism;

[0083] d. a combined translation + rotation mechanism;

[0084] e. a flexible and / or compliant adjustment mechanism;

[0085] f. a detachable and / or reconfigurable positioning mechanism;

[0086] g. a constraint and locking mechanism;

[0087] h. an actively controlled adjustment mechanism.

[0088] Example 47. A sensor assembly, comprising:

[0089] a. a sensor housing comprising one or more compliant domes;

[0090] b. one or more printed circuit boards (PCB) comprising one or more micro-electromechanical systems (MEMS)-based pressure sensors;

[0091] c. a housing lid, configured to hermetically enclose the PCB with the one or more sensors within the housing;

[0092] wherein said sensor assembly is configured to utilize a barometric transduction principle designed to capture minute physiological fluctuations by means of said one or more sensors being hermetically enclosed in said one or more domes.

[0093] Example 48. The sensor assembly according to example 47, wherein said assembly comprises a hermetically sealed sensing chamber, generated by the compliant dome and the housing lid.

[0094] Example 49. The sensor assembly according to example 47 or example 48, wherein said chamber contains a predetermined volume of a compressible medium.

[0095] Example 50. The sensor assembly according to any one of examples 47-49, wherein said compressible medium is one or more of air, a compressible gas and a specific compressible liquid / oil.

[0096] Example 51. The sensor assembly according to any one of examples 47-50, wherein said one or more compliant domes are configured to contact a skin surface of a patient overlying a carotid artery.

[0097] Example 52. The sensor assembly according to any one of examples 47-51, wherein said assembly is configured to sense as a pulse wave propagates through an artery, by sensing a resulting lateral displacement of an arterial wall and overlying tissue which causes a transient reduction in the volume of the chamber.

[0098] Example 53. The sensor assembly according to any one of examples 47-52, wherein said assembly is manufactured under contact atmospheric conditions to ensure that the chamber comprises the required compressible medium.Example 54. The sensor assembly according to any one of examples 47-53, wherein said assembly comprises one or more channels / microchannels configured to allow filling the chamber with the compressible medium after the assembly of the sensor assembly.

[0099] 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.

[0100] 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.

[0101] 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.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 readonly 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.

[0102] 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, electro-magnetic, 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.

[0103] 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.

[0104] 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).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.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF DRAWINGS

[0109] 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.In the drawings:

[0110] Figure la is a schematic representation of an exemplary monitoring and treatment system comprising a device for stroke detection and Vagus-Nerve-Stimulation (VNS) / Barorecep tor-stimulation treatment, according to some embodiments of the invention;

[0111] Figures Ib-c are schematic representations of exemplary sensor assemblies, according to some embodiments of the invention;

[0112] Figure 2 is an image of an external configuration, according to some embodiments of the invention;

[0113] Figure 3 is a schematic representation of an external configuration, according to some embodiments of the invention;

[0114] Figures 4a-4c are schematic representations of exemplary implantable configurations of the device, according to some embodiments of the invention;

[0115] Figure 5 is a schematic representation of an implantable configuration, according to some embodiments of the invention;

[0116] Figures 6a-6c are schematic representations of different external configurations, according to some embodiments of the invention;

[0117] Figure 7 is an exemplary implantable stimulator, according to some embodiments of the invention;

[0118] Figure 8 is a schematic representation of an exemplary magnetic rechargeable sensor, according to some embodiments of the invention;

[0119] Figure 9 is a schematic representation of exemplary membrane sensors, according to some embodiments of the invention;

[0120] Figure 10 is a flowchart of an exemplary principle of action of the system, according to some embodiments of the invention;

[0121] Figure 11 is a graph presenting the results of recordings of 27 patients. High-quality bilateral pulse waveforms were recorded in 27 patients;

[0122] Figure 12 shows a typical example of a pulse wave;

[0123] Figure 13 shows an exemplary comparison between a template and a pulse wave;

[0124] Figure 14 shows exemplary templates;

[0125] Figure 15 shows a flowchart of an exemplary method of assessing a stroke, according to some embodiments of the invention;

[0126] Figure 16 shows a flowchart of an exemplary method of guiding a user to position sensors, according to some embodiments of the invention;Figure 17 shows a flowchart of an exemplary method of monitoring a patient using AUC values, according to some embodiments of the invention;

[0127] Figures 18a-b show exemplary visualizations of alerts generated by the system, according to some embodiments of the invention;

[0128] Figure 19 shows a schematic representation of an exemplary neck-pillow comprising the system, according to some embodiments of the invention;

[0129] Figure 20 showing a schematic representation of an exemplary use of Hall sensors detecting changed parallel and perpendicular to the artery, according to some embodiments of the invention;

[0130] Figures 21a-f showing schematic representations of exemplary holders, according to some embodiments of the invention;

[0131] Figure 22 is a graph of LVO probability indicator across participants;

[0132] Figure 23 is a graph showing the results of a rat study;

[0133] Figure 24 is a graph showing the results of an astronaut study;

[0134] Figure 25 is a graph showing the results of a stroke patient that underwent thrombectomy; Figure 26 is a schematic representation of a device and the data visualized during monitoring; Figures 27a-c are results of monitoring of two distinct patients and the relevant control; and Figure 28 is a graph summarizing the results of the monitoring.

[0135] DESCRIPTION OF SPECIFIC EMBODIMENTS OF THE INVENTION

[0136] The present invention, in some embodiments thereof, relates to systems and methods for hemodynamic anomaly detection for diagnosis and treatment and, more particularly, but not exclusively, to automated systems and methods for hemodynamic anomaly detection, stroke probability, optionally stroke identification, for diagnosis and treatment.

[0137] Overview

[0138] A broad aspect of some embodiments of the invention relates to preventing strokes by providing a treatment before the extensive damage 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 alerting, optionally treating, and possibly preventing, the impending stroke. In some embodiments, the system comprises one or more sensors positioned in the vicinity of the carotid arteries. In some embodiments, the sensors are configured to monitor changes in the carotid pulse waves and / or in the stiffness / pressure / displacement of the soft tissue over the arteries. In some embodiments, once the sensors detect certain predetermined parameters and / or the sensed parameters pass a certain threshold, the system notifies a physician and / or other dedicatedpersonnel. In some embodiments, once the sensors detect certain predetermined parameters and / or the sensed parameters pass a certain threshold, the system activates a treatment, with or without immediate supervision of physician and / or other dedicated personnel. In some embodiments, the treatment is one or both of Vagus Nerve Stimulation (VNS) and Baroreceptor-stimulation.

[0139] In some embodiments, the system comprises dedicated neural network (referred also just as “Al”) based algorithms configured for the personalized monitoring and optional treatment of the specific patient. 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 / pressure / displacement of the soft tissue over the arteries. In some embodiments, the device comprises a high sensitivity pressure sensor (MEMS-based) with an integrated digital pressure sensor (5 to 1000 mbar) (also referred herein to an “altimeter sensor”). 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, optionally, the device comprises one or more stimulator, either external or implanted, configured to provide one or both of Vagus Nerve Stimulation (VNS) and Baroreceptor- stimulation. 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 one or more of stiffness, pressure and displacement of the soft tissue over 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 an electronic device and / or user interface device (for example a tablet or cellphone) through a secured application. In some embodiments, the device is a wireless rechargeable device.

[0140] 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.

[0141] In some embodiments, the one or more sensors and one or more optional stimulators are encapsuled in small units (also called “devices” or “sensing assemblies” or “sensing unit(s)”). In some embodiments, the units are attached to the neck of the patient, for example using removable patches. In some embodiments, the units are attached and / or mounted into a neck arc (also referred to as “holder”), which holds the unit in the correct position on the neck of the patient and at the correct pressure.An aspect of some embodiments of the invention relates to dedicated holder for monitoring and treatment units configured to hold units at correct positions on the neck of the patient and at the correct level of pressure to ensure correct measurements and treatment.

[0142] 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.

[0143] Referring now to Figure la, showing a schematic representation of an exemplary monitoring and optionally treatment system comprising a device 100 (referred hereinafter just as: device 100) for hemodynamic anomaly detection and optionally Vagus-Nerve-Stimulation (VNS) and / or Baroreceptor- stimulation treatment, according to some embodiments of the invention.

[0144] In some embodiments, the system comprises a device 100 which comprises one or more of: at least one sensor 102, at least oneExemplary controller 104, and optionally at least one stimulator 106. In some embodiments, the device 100 is in communication with an external additional device 108 comprising a user interface, for example one or more of a cellphone, a tablet, a computer or any other dedicated electronic device.

[0145] 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 one or more of the stiffness, the pressure and the displacement of the soft tissue over 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 pressure 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 / neural network algorithms aimed at detecting abnormalities in the various measurements of hemodynamic parameters, and generating timely alerts to the user, a physician and / or other dedicated personnel, and optionally, providing treatments.

[0146] 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 an electronic device, for example a cellphone or tablet device, through a secured application.

[0147] In some embodiments, the device 100 is a wirelessly chargeable device.Exemplary sensor 102

[0148] 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 to send the measured data to theExemplary controller 104. In some embodiments, the measured data is one or more of: stiffness, pressure, displacement of the soft tissue over the arteries, blood pressure measurements, patient’s pulse, ECG, temperature and movement.

[0149] 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, high sensitivity pressure sensor (MEMS -based) with an integrated digital pressure sensor and a resistive / optical strain gauge sensor. In some embodiments, a system comprises two devices 100. In some embodiments, the two devices 100 are positioned one on each side of the neck, either adhered to the skin of the patient with adhesive patches or implanted (see below -Exemplary configurations) or held by a dedicated holder (see below). In some embodiments, there is only one device 100, and the device 100 comprises detached units (not shown) comprising sensors and / or optional stimulators, the detached units being configured to receive / transmit data from / to the device 100.

[0150] In some embodiments, the at least one sensor is a sensing unit which 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 soft tissue over 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.

[0151] 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.

[0152] In some embodiments, the at least one sensor 102 assesses the outer contour of an artery in the soft tissue. In some embodiments, the parameters monitored for the arterial contour assessment are at least one of the following: pressure, stiffness, displacement, reactivity. In some embodiments,optionally, pressure is measured within the artery. In some embodiments, stiffness / pressure / displacement is measured by assessing the rigidity of the arterial walls through the soft tissue. In some embodiments, displacement is measured by assessing any movement or changes in position of the artery as reflected by the changes and / or displacements in the soft tissue in the area of the arteries. In some embodiments, reactivity is measured by evaluating how the artery responds to various stimuli or conditions such as CO2 accumulation.

[0153] In some embodiments, the at least one sensor 102 is configured to perform fall and / or movement detection.

[0154] In some embodiments, the at least one sensor 102 is configured to perform aneurysm / bleeding detection by sensing a drop in unilateral pressure. In some embodiments, the aneurysm is at least one of: cerebral aneurysm, aortic aneurysm. In some embodiments, a risk of aneurysm is indicated by detecting a unilateral pressure drop and / or increased variability in measured pressure.

[0155] Referring now to Figures Ib-c, showing schematic representations of exemplary sensor assemblies, according to some embodiments of the invention. In some embodiments, the at least one sensor 102 is a sensing assembly comprising one or more of the following parts:

[0156] 1. a sensor housing 112 comprising one or more compliant domes 114 (3 are shown).

[0157] 2. one or more printed circuit boards (PCB) 116 comprising one or more micro-electromechanical systems (MEMS)-based pressure sensors 118 (schematically shown in Figure 1c); for example, in some embodiments there is one PCB comprising a plurality of sensors, while in other embodiments, there are a plurality of PCBs each comprising a single sensor. In some embodiments, the sensor comprises am internal structure 126 or seal that secures the sensor in place, maintaining the integrity of the internal pressurized environment.

[0158] 3. a housing lid 120, configured to hermetically enclose the PCB 116 with the sensors 118 within the housing 112.

[0159] In some embodiments, the sensing assembly that utilizes a barometric transduction principle designed to capture minute physiological fluctuations, as schematically shown in Figure 1c. In some embodiments, the sensing assembly comprises a hermetically sealed sensing chamber 124, generated by the compliant dome 114 and the housing lid 120, containing a predetermined volume of a compressible medium, such as air, a compressible gas, or a specific compressible liquid / oil. In some embodiments, the chamber 124 is bounded by a high-precision barometric sensor 118 at its base and the compliant dome 114 is a flexible, opaque membrane at its contact interface.

[0160] In some embodiments, while in operation, the sensing assembly is positioned such that the compliant dome 114 (the membrane) is in biased contact with the skin surface overlying the carotid artery 122. In some embodiments, a calibrated initial compressive force (pre-load) is applied to thechamber 124, establishing a baseline internal pressure and ensuring optimal coupling. In some embodiments, as a pulse wave propagates through the artery 122, the resulting lateral displacement of the arterial wall and overlying tissue causes a transient reduction in the volume of the chamber 124, as schematically shown in Figure 1c. In some embodiments, according to the physical relationship where pressure is inversely proportional to volume ($P \propto 1 / V$). this volumetric contraction induces a measurable increase in internal pressure in the chamber 124. In some embodiments, the integrated barometric sensor 118 — whether digital or analog — captures these high-frequency pressure variations with high fidelity, allowing for the precise reconstruction of the arterial pulse wave morphology.

[0161] In some embodiments, to enhance the sensitivity of the transduction mechanism, the flexible membrane of the dome 114 is optionally engineered with a specialized geometric profile, for example characterized by a dome-shaped architecture incorporating discrete stress-relief features or flex points (e.g., nipple-like protrusions). In some embodiments, this geometry is designed to maximize the mechanical compliance of the interface, significantly reducing the force required to induce a volumetric change. In some embodiments, by strategically placing these flex points along the surface of the dome 114, the membrane can undergo greater deformation in response to subtle arterial movements compared to a standard flat or uniform elastic surface. In some embodiments, this optional structural optimization serves to minimize mechanical impedance and ensures that the kinetic energy of the pulse wave is efficiently transferred into the compressible medium rather than being dissipated by the stiffness of the material itself. In some embodiments, the increased flexibility facilitates a superior signal-to-noise ratio (SNR) and enables the barometric sensor 118 to detect even low-amplitude physiological signals, ensuring consistent performance across varying anatomical profiles and attachment conditions.

[0162] In some embodiments, as will be further explained below, the sensor is also subjected to an external pressure 128 (see Figure 1c), which maintains the sensor at the correct position and at the correct required contact to allow for a correct monitoring.

[0163] In some embodiments, during the manufacturing of the sensor assemblies, a constant atmospheric pressure is maintained so as to ensure that the chamber comprises the required compressible medium. In some embodiments, additionally or alternatively, the housing comprises dedicated channels / microchannels (not shown) which allow filling the chamber with the compressible medium after the assembly of the sensor assembly.

[0164] In some embodiments, one of the compliant domes 114 is flattened (not shown) and a temperature sensor is used in that flattened dome, while the other domes 114 are kept as disclosed herein.Exemplary controller 104

[0165] In some embodiments, the device 100 comprises at least one controller 104 configured for receiving data from the at least one sensor 102, for example via cables or wirelessly. In some embodiments, theExemplary controller 104 is configured to control the actions performed by the device 100 and compile the measured data. In some embodiments, theExemplary 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.

[0166] Exemplary stimulator 106

[0167] In some embodiments, optionally, 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).

[0168] 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.

[0169] In some embodiments, the stimulator 106 is configured to provide either of the abovementioned treatments.

[0170] Exemplary external additional device 108

[0171] 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.

[0172] 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, theexemplary 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 / pressure / displacement of the soft tissue over 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.

[0173]

[0174] 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).

[0175]

[0176] of the device 100

[0177] In some embodiments, the device 100, whether an external device or an implantable device, comprises one or more of the following components:

[0178] - 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 theExemplary controller 104 and / or processor. Optionally, the A / D converter should be of at least 8 bits to meet the specific application requirements.

[0179] - Bluetooth / Wi-Fi / RF / other transmitters for transmitting the signals to theExemplary 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.

[0180] - 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.

[0181] - A receiver (that may form part of theExemplary controller 104 and / or processor), designed to collect signals from the at least one sensor 102, allowing for possible synchronous operation when a pluralityof 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.

[0182]

[0183] external

[0184] 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 / pressure / displacement of the soft tissue over 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).

[0185] In some embodiments, in the external configuration, all the components of the device (the sensor 102, theExemplary controller 104 and the optional stimulator 106) are housed in a single housing unit, located on the skin (by means for example of a patch or a holder), in the location of the target blood vessel to be monitored. In some embodiments, only the at least one sensor 102 and the optional stimulator 106 are housed in a single housing, while theExemplary controller 104 is positioned in an external device in communication (either wired or wirelessly) with the at least one sensor 102 and the optional stimulator 106.

[0186] In some embodiments, the housing unit is attached to the skin, for example by means of patches. In some embodiments, the housing units are held by a dedicated holder (see below), configured to hold each housing unit at the right location on the neck and at the correct pressure to ensure correct monitoring and / or treatment.

[0187] 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.

[0188] In some embodiments, each housing unit 302 comprises at least one sensor 102, an optional 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 / RF / WIFI module 310, a memory storage unit 312, a capacitor 314 and a battery 316. In some embodiments, theBluetooth / RF / WIFI module wirelessly connects the device to a processor in an additional external device 108, having data analysis software.

[0189]

[0190] Referring now to Figures 4a-4c, showing exemplary implantable configurations of the device 100, according to some embodiments of the invention.

[0191] 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.

[0192] In some embodiments, in the implantable configuration, the implanted device 100 comprises the at least one sensor 102 and at least oneExemplary controller 104 (not shown), whereas the optional stimulator 406 is placed externally, as shown for example in Figured 4b and 4c. In this case, the optional 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.

[0193] Referring now to Figure 5, showing a schematic representation of an implantable configuration 500, according to some embodiments of the invention.

[0194] 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 optional stimulator 406. In some embodiments, the external optional stimulator 406 can optionally be connected to an additional external device 108 such as an electronic device comprising a user interface (for example a cellphone or a tablet). In some embodiments, the implantable device 100 comprises one or more of: a Bluetooth / RF / WIFI 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.

[0195] In some embodiments, the external optional stimulator 406 comprises one or more of: a Bluetooth / RF / WIFI module 514 and a capacitor 516. In some embodiments, additional external device 108 comprises a GUI, an application for operating specialized analysis software, and agateway. In some embodiments, the specialized analysis software comprises algorithms provided by the present invention, detailed below.

[0196]

[0197] different i

[0198] In some embodiments, in the implantable configuration, the components of the system can be divided (positioned) between the implantable device 100, the external optional stimulator 406 and the additional external device 108.

[0199] Referring now to Figures 6a-6c showing schematic representations of different external configurations, according to some embodiments of the invention.

[0200] 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 optional stimulator 504 (not shown). In some embodiments, the implantable device 100 comprises a Bluetooth / RF / WIFI 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 / RF / WIFI 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.

[0201] 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.

[0202] 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 a wearable external charging device 606.

[0203]

[0204] stimulator

[0205] Referring now to Figure 7, showing an exemplary implantable optional stimulator, according to some embodiments of the invention. In some embodiments, the optional stimulator 106 isimplanted 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).

[0206] In some embodiments, the implantable optional stimulator is used with an implanted device 100 or with an external device 100.

[0207] Exemplary integration with other systems

[0208] 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); and / or general cardiac procedures, for example, working alongside protection device like Sentinel™, offering additional protection for patients at high risk of stroke. 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.

[0209]

[0210] sensors

[0211] 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.

[0212]

[0213] membrane i sensors

[0214] Referring now to Figure 9, showing a schematic representation of exemplary membrane sensors, according to some embodiments of the invention.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

[0215] pres sure- 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.

[0216] 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 / high-sensitive pressure) 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 a high- sensitivity pressure sensor that uses high resolution pressure and / or temperature output to allow the implementation of a pressure / thermometer function without any additional sensing. In some embodiments, the software application (firmware) uses the pressure / temperature read out to calibrate and compensate the pressure sensor accordingly and the presented pressure already reflects that compensation.

[0217]

[0218] thermal

[0219] In some embodiments, the system employs temperature analysis to extract thermal insights from arterial signals captured by thermal sensors placed on the carotid arteries (optionally left and right). In some embodiments, using for example temperature, analysis techniques the system evaluates the temperature of signals from both sides. In some embodiments, comparative analysis between the right and left arterial temperature highlights asymmetries, leveraging the hypothesis that large vessel occlusions (LVOs) on one side of the neck create distinct spectral discrepancies due to localized vascular disruptions.

[0220]

[0221] of action of the system

[0222] Referring now to Figure 10, showing a flowchart of an exemplary principle of action of the system, according to some embodiments of the invention.

[0223] In some embodiments, the exemplary principle of action comprises the following actions:1. Detecting a change in one or more of stiffness, pressure, displacement of the soft tissue over the artery 1002.

[0224] 2. Automatically determining stroke evolution 1004.

[0225] 3. Providing treatment (VNS and / or baroreceptor stimulation) 1006.

[0226] 4. Reassessing a state in one or more of stiffness, pressure, displacement of the soft tissue over the artery 1010.

[0227] 5. If necessary - repeating provision of optional treatment 1012.

[0228] Exemplary waveform type specifications

[0229] In some embodiments, the algorithm, optionally using AI / neural networks, 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.

[0230] 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.

[0231] Additional results can be found in the examples below.

[0232] Exemplary combination of parameters in the assessment of stiffness

[0233] In some embodiments, a combination of parameters is used in the assessment of one or more of stiffness, pressure, displacement of the soft tissue over the artery. For example:

[0234] 1. Number: as stiffness, pressure, displacement of the soft tissue over the artery increases - the number of peaks decreases.

[0235] 2. Sharpness: as stiffness, pressure, displacement of the soft tissue over the artery increases - the sharpness of the peaks decreases.

[0236] 3. Prominence: as stiffness increases, pressure, displacement of the soft tissue over the artery - the prominence of peaks decreases.

[0237] 4. Dicrotic Notch Timing and Area Under Curve (AUC) Analysis.

[0238]

[0239] In some embodiments, the algorithm can be divided into two classes: quality assessment and hemodynamic anomaly detection.Dicrotic Notch Timing and Area Under Curve

[0240] 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.

[0241] Welch's t-Test for Statistical Comparison of Arterial Features

[0242] 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.

[0243]

[0244] assessment:

[0245] In order to ensure that the system perform properly, the hemodynamic anomaly 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.

[0246] Figure 12 shows a typical example of a pulse wave.

[0247] The quality assessment algorithm can be broken into 3 steps:

[0248] 1. Peak Detection

[0249] 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.

[0250] 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 frequencyof 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.

[0251] 2. Detect pulse wave onset and termination

[0252] 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.

[0253] Exemplary Additional Approaches: Calculating per pulse wave the termination point.

[0254] 3. Exemplary Quality Assessment

[0255] 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.

[0256] 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.

[0257] 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 hemodynamic anomaly detection.

[0258] 4. Subsets of pulse wave

[0259] 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.5. Fiduciary Points

[0260] 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.

[0261] 6. Type Matching

[0262] 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.

[0263] Hemodynamic Anomaly Detection (Avert):

[0264] 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.

[0265] 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.

[0266] 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.

[0267] Exemplary predictive analytics and AI-Driven insights

[0268] In some embodiments, the system is configured to leverage AI and machine learning to analyze collected data, providing predictive insights into future health risks, for example:

[0269] Risk Stratification: In some embodiments, the system is configured to generate personalized health risk profiles based on trends in arterial and systemic parameters (received in real-time and / or from general historical measurements). For example, in a non-limiting way, the AI / neural network is provided with one or more of the following parameters and their relevant values in healthy and sick patients: age, sex, blood pressure, glucose levels, kidney function, familial history, previous historyof stroke, amount of daily activity and others. In some embodiments, based on the generated risk profiles, the system is configured to dynamically adjust monitoring sensitivity based on individual patient history and current conditions.

[0270] Stroke Prediction: In some embodiments, the system is provided with advanced algorithms for early prediction of stroke based on subtle changes in monitored parameters, for example changes in variability and / or short intermittent elevation of pressure, optionally days before it happens. In some embodiments, real-time information is in addition compared with predetermined data to allow for early prediction of stroke.

[0271] In some embodiments, as mentioned elsewhere herein, the system is configured to work in integration with wearables and health ecosystems. For example, synchronize data with consumergrade wearables to create a holistic health monitoring ecosystem; and integrating the system with telehealth platforms for continuous care.

[0272]

[0273] Analysis

[0274] In some embodiments, the system employs frequency domain analysis to extract harmonic insights from arterial signals captured by sensors placed on the carotid arteries (optionally left and right). In some embodiments, using for example Fast Fourier Transform (FFT) and / or other spectral analysis techniques, such as spectral peak identification, band power calculations, and phase coherence analysis, the system evaluates the frequency spectra of signals from both sides. In some embodiments, comparative analysis between the right and left arterial spectra highlights asymmetries, leveraging the hypothesis that large vessel occlusions (LVOs) on one side of the neck create distinct spectral discrepancies due to localized vascular disruptions. This differential analysis enhances the system's diagnostic capability for detecting LVOs.

[0275] Referring now to Figure 15, showing a flowchart of an exemplary method of assessing a stroke, according to some embodiments of the invention. In some embodiments, the method comprises one or more of the following actions:

[0276] 1. Detecting parameters from carotid arteries from both sides (1502);

[0277] 2. Performing comparative analysis on the detected parameters (1504);

[0278] 3. Assessing whether there are differences between the sides (1506);

[0279] 4. If relevant (there is a significant difference between the sides), providing an alert based on a result of said assessment (1508).Transient Phase Variability Monitoring

[0280] In some embodiments, similar to what was disclosed above for “Harmonic Insights through Spectral Analysis”, the system monitors the transient variability of arterial signals, between two distinct side-arteries, to detect the instability associated with large vessel occlusions (LVOs). During an LVO event, the affected side exhibits significantly greater signal variability compared to the contralateral side. This phenomenon is quantified using metrics such as the standard deviation of signal amplitude, phase shift irregularities in frequency domain analysis, and temporal fluctuations in waveform features like pulse timing and shape. By analyzing these variability metrics, the system identifies abnormal signal dynamics indicative of vascular instability, enhancing its ability to detect and localize LVOs accurately.

[0281] Inter-Channel Variance Reduction for Si

[0282]

[0283] In some embodiments, the system employs inter-channel variance reduction techniques to enhance the accuracy and reliability of signal analysis. Multiple channels (typically 2 or 3) are utilized on each side of the neck to capture arterial signals. For feature calculation, the outputs from all channels on a given side are aggregated using statistical methods such as averaging, weighted integration, or consensus algorithms. This approach mitigates channel- specific noise and artifacts, producing a unified and robust representation of arterial activity for each side. By reducing interchannel variability, the system ensures high-quality data for detecting asymmetries indicative of large vessel occlusions (LVOs).

[0284]

[0285] for Si Assessment: The system utilizes deep learning models, such as Convolutional Neural Networks (CNNs), to assess the quality of physiological signals captured by the sensors. A trained classifier analyzes time-series data to determine the likelihood that a given signal contains detectable arterial pulses. For example, the CNN is trained on samples each comprising of 3 seconds long sequence of pressure samples taken from a pressure sensor. Each sampled is labeled either one (1) - if the sensors is placed firmly on the Carotid Artery, or zero (0) if it is not placed on the Carotid artery. Rather than providing a binary output, the classifier generates a continuous probability score between 0 and 1, derived from the activation of the final layer of the neural network (softmax / probability layer). This probability score is used, using two thresholds, to classify each channel into one of three quality levels:

[0286] • Green: Signal quality is sufficient for accurate analysis (above the upper threshold).

[0287] • Yellow: Signal quality is marginal and may require adjustment (between the thresholds). • Black / Red: Signal quality is inadequate for analysis (below the lower threshold).By providing real-time feedback, the system guides users in optimizing sensor placement to ensure reliable data acquisition. This approach enhances the overall robustness of arterial monitoring.

[0288] Referring now to Figure 16, showing a flowchart of an exemplary method of guiding a user to position sensors, according to some embodiments of the invention. In some embodiments, the method comprises one or more of:

[0289] 1. Detecting for each sensor a physiological signal (1602);

[0290] 2. Performing automatic quality assessment of the physiological signal (1604);

[0291] 3. Providing instructions to user to where to move each sensor to improve the physiological signal (1606) - if necessary.

[0292]

[0293] for Pulse Feature Detection In some embodiments, the system is configured to employ advanced deep learning architectures to accurately identify key features of arterial pulse waveforms: the onset, the dicrotic notch, and the end of the pulse. In some embodiments, for this task, a sequence-to-sequence neural network model is utilized, with architectures such as a Convolutional Neural Network (CNN) for feature extraction combined with a Recurrent Neural Network (RNN) or a Transformer for temporal pattern recognition. These architectures are well- suited for analyzing timeseries data due to their ability to capture both local features and long-range dependencies.

[0294] In some embodiments, the model processes input time-series data and outputs precise locations of the pulse onset, dicrotic notch, and end, represented as sample indices. In some embodiments, training is conducted using supervised learning with labeled datasets, leveraging loss functions such as Mean Squared Error (MSE) for regression tasks to minimize errors in predicted sample positions. For example, the model is trained on samples each comprises of for example 10 seconds long sequence of pressure samples taken from a pressure sensor is placed on the Carotid Artery. Together with a triple labeling accompanying each sample and comprised of (stat sample, dicrotic notch sample, end sample).

[0295] A potential advantage of doing this is that by automating this aspect of pulse waveform analysis, the system achieves high accuracy and consistency in detecting these features, which are essential for further analysis and monitoring of arterial health.

[0296]

[0297] Neutralization for Enhanced Pulse Analysis In physiological monitoring, the heart rate (HR) and respiratory rate (RR) often exhibit a harmonic relationship, with HR typically being an integer multiple of RR — commonly around a 4:1 ratio. This harmonic coupling can introduce respiratory artifacts into the pulse signal, complicating accurate analysis.

[0298] To address this, the system implements a frequency-domain filtering approach:1. Frequency Identification: Fast Fourier Transform (FFT) is applied to the acquired signal to identify the fundamental frequencies of both respiration and pulse, as well as their respective harmonics.

[0299] 2. Selective Filtering: y filters are applied to attenuate the respiratory fundamental frequency and its harmonics, ensuring that only those components not overlapping with the pulse harmonics are targeted.

[0300] 3. Signal Reconstruction: an inverse FFT is performed to reconstruct the time-domain signal, now with minimized respiratory interference, facilitating more accurate pulse waveform analysis.

[0301] In some embodiments, a potential advantage of this method is that it effectively isolates the pulse signal from respiratory artifacts, enhancing the precision of subsequent analyses in both time and frequency domains.

[0302] Wave Decay Measurement Between Two Points (with an Exemplary Cerebrovascular Use)

[0303] In some embodiments, as part of signal processing, wave propagation analysis, and health monitoring, the system is configured to evaluate the decay (attenuation) of a propagating physiological wave between at least two defined measurement points. In some embodiments, the propagating wave comprises an arterial pulse wave, and the system analyzes how one or more waveform characteristics change over a known distance within the body. In some embodiments, the decay measurement supports diagnostics, monitoring, and predictive analytics, including early identification of anomalies or disruptions in the system through which the wave propagates.

[0304] In some embodiments, the method includes placing at least two sensors at two defined points and acquiring time-based waveform data from each point. In some embodiments, the sensors comprise pressure sensors or other sensors capable of measuring arterial waveforms. In some embodiments, the two points are selected to be close to each other (e.g., along a single vascular segment) or farther apart (e.g., different body locations), and in some embodiments more than two points are used. In some embodiments, the system is configured to compute a decay factor (or attenuation rate) between points based on differences in one or more waveform characteristics, including one or more of: amplitude, energy, morphology, timing, slopes, inflection points, secondary features, and / or other derived wavepropagation features.

[0305] In some embodiments, the system is configured to improve reliability of the decay measurement by reducing artifacts and accounting for systematic influences. In some embodiments, the method includes cleaning the acquired signals to remove noise, motion-related distortions, and outliers, and performing adjustments to compensate for baseline drift, offsets, sensor placementvariability, calibration effects, and / or environmental influences. In some embodiments, after cleaning and adjustment, the processed signals are compared between the measurement points and the decay factor is estimated using one or more computational models.

[0306] In some embodiments, the decay factor is used to detect and characterize abnormalities affecting wave propagation. In some embodiments, different abnormalities produce different decay patterns and / or waveform changes, and the system is configured to infer one or more of: presence of an abnormality, an abnormality category, severity level, and / or a location category based on the measured decay and related waveform features. In some embodiments, measurements from multiple subjects and / or repeated sessions are used to populate a database for statistical or machine-learning methods that support automated monitoring, trend analysis, and alert generation.

[0307] Exemplary use (cerebrovascular assessment):

[0308] In some embodiments, the system is configured for non-invasive detection and characterization of vascular changes within or leading to the brain by analyzing pulse-wave decay between two closely positioned sensors placed along the carotid artery. In some embodiments, subtle changes in waveform characteristics measured over a short known distance provide information indicative of intracranial abnormalities such as aneurysms or partial blockages, supporting early detection and characterization and, in some embodiments, serving as an adjunct to other clinical assessments.

[0309] Exemplary method of monitoring a patient and performing severity assessment using AUC values and / or dicrotic notch timing (DN)

[0310] Figure 17 shows a flowchart of an exemplary method of monitoring a patient using AUC / DN values, according to some embodiments of the invention. In some embodiments, as mentioned above, patients are monitored 1720 and, according to the data collected by the sensors, a first AUC / DN parameter is calculated 1722.

[0311] For the sake of the explanations below, only AUC will be used as an example. It should be noted that the monitoring comprises monitoring AUC values and / or dicrotic notch timing (DN), and dedicated thresholds are set to either or a combination of both. In some embodiments, the following calculations are performed using the AUC values, the dicrotic notch timing (DN), or using derivates or calculations derived from either or a combination of both.

[0312] In the following explanations, arbitrary values will be used. These are provided to allow a person having skills in the art to understand the invention. These values can change, or other values can be used, and the presented values are not meant to limit the invention in any way.In some embodiments, for example, patients presenting a low AUC ( for example below 30) means that a stroke or LVO risk are minimal. In some embodiments, for example, patients presenting an intermediate AUC (for example from about 30 to about 79) without clinical symptoms means, that there is no stroke or LVO risk but optionally require follow up and clinical context. In some embodiments, for example, patients presenting a high AUC (in relation to a predetermined threshold) (for example an AUC above 79) means high risk of stroke or LVO.

[0313] In some embodiments, the system is configured to have a threshold. For example, for the sake of the explanations, the system is configured with a threshold of 79. In some embodiments, if a patient presents an AUC of 79 or above (meaning an AUC above the threshold) 1724, the system activates an active surveillance monitoring method 1726.

[0314] In some embodiments, the difference between regularly monitoring and the active surveillance monitoring method, is that the active surveillance monitoring method is activated only when the AUC present above the preset threshold and there is high risk to the patient. In some embodiments, when the active surveillance monitoring method is activated, a physician or a dedicated personnel is notified.

[0315] For the sake of the following explanations, and without limiting the invention in any way, the threshold was set at the arbitrary number 79; when the measured AUC is above 79 (the threshold) for the first time, this activates the active surveillance monitoring method, and the value at that moment will be referred to as AUCto - where TO is the time when the AUC was measured and was found above the threshold for the first time.

[0316] In some embodiments, from the moment the active surveillance monitoring method is activated, the system is configured to perform measurements at set intervals 1728, for example every 5 minutes, or every 10 minutes, or every 15 minutes, or for example at any interval between 5 and 20 minutes, and calculate a new AUC at that time point 1730. For example, for the sake of the explanations, the system is configured to measure and calculate new AUCs every 5 minutes. This means that the system will generate after 30 minutes, the following AUCs: AUCt5, AUCt10, AUCt15, AUCt20, AUCt25, AUCt30. Each AUC representing the calculated AUC at that time point after the AUCto.

[0317] In some embodiments, the system is configured to calculate the difference between the different AUCs to assess the present state of the patient 1732.

[0318] In some embodiments, the system is configured to calculate the difference between the different AUCs to assess the outcome of the patient 1732.

[0319] Exemplary patterns (not an exhaustive list) can be as following:

[0320] T5-T10 — transient elevations of AUC above 79 the threshold for less than 10 minutes may not be clinically significant and could represent noise or minor transient ischemic changes.T15 and beyond — sustained high AUC values >80 for more than 15 minutes have a higher risk for developing neurological disability.

[0321] Beyond 30 minutes — suggest a correlation with clinical correlation with stroke-like injury. When AUC returns to baseline (below 79) within 10-15 minutes, it can be interpreted this as a transient event.

[0322] The longer and higher the AUC elevation, the more the risk for a severe clinical event. Recurrent moderate elevations (multiple “mini-beeps”) may cumulatively impact cognitive function and could signal increased long-term stroke risk.

[0323]

[0324] and Visualization In some embodiments, the processed data is displayed in a user-friendly format, highlighting key parameters such as decay rate, noise level, and signal integrity. In some embodiments, alerts are generated for anomalies or deviations from expected values, for example as shown in Figures 18a-b.

[0325] Exemplary automated timed alert for acute treatment after alert

[0326] In some embodiments, the system is optionally configured to provide stimulation by means of electrical pulses and configured to alert a physician and / or other dedicated personnel that a treatment should or is advisable to be provided.

[0327] In some embodiments, treatments are configured to release nitric oxide (NO), for example after tele-medicine intervention.

[0328] In some embodiments, the system is configured to work jointly with a pharmacological release system according to the specific regulations and indications for use of the released medication. In some embodiments, once the system detects an occurrence, the pharmacological release system is activated, together or separately from the stimulator.

[0329] In some embodiments, the system is in communication with tele-medicine services. In some embodiments, once the system detects an occurrence, the system contacts a dedicated tele-medicine service updating them on the situation.

[0330] In some embodiments, the system is configured to enable treatment as a method that is preapproved and not automated, enabling telemedicine facilitated treatment according to medical management protocols.

[0331] Exemplary additional uses of the system (not cardiovascular)

[0332] In some embodiments, the system can be configured to check fluctuations and deterioration of cognitive function due to vascular dementia, for example, by the positive sensing of the presence of repetitive strokes in the patient.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.

[0333] In some embodiments, the system is configured to alert in cases of an aneurysm, for example, by sensing a drop in the values of the monitored parameters.

[0334] In some embodiments, the system is configured to monitor the progression of cerebrovascular diabetes complications, for example, by monitoring the stiffness / pressure / displacement of the soft tissue over the arteries that increases in diabetes cases.

[0335]

[0336] additional

[0337] Referring now to Figure 19, showing a schematic representation of an exemplary neck-pillow comprising the system, according to some embodiments of the invention. In some embodiments, the system is configured to be compatible and / or incorporated with objects and / or accessories, having a different, well-defined purpose. For example, of those objects is a neck pillow 2000, designed to be used in flights and / or space missions. In some embodiments, the system is mounted and / or is part of a “smart” neck pillow, having the carotid blood flow monitoring system described herein. In some embodiments, the neck pillow is configured with the at least one sensor, configured to provide continuous, non-invasive health monitoring during flights and space missions and / or with the stimulator to provide proper therapeutic treatments when needed. In some embodiments, the smart neck pillow is configured to collect data pertaining to at least one of: transient cognitive impairment, vascular changes, and stress.

[0338] In some embodiments, the smart neck pillow is used in prolonged or high-risk scenarios. In some embodiments, the smart neck pillow is used in healthcare settings for bedridden patients or during extended transport in ambulances and emergency evacuations.

[0339] In some embodiments, system is configured monitor hemodynamic changes and arterial health using ear-based sensors integrated into a hearing aid device. In some embodiments, the hearing aid is configured to track at least one of pulse, photoplethysmography (PPG), or sound waves related to blood flow dynamics. In some embodiments, the hearing aid is geared to collect data specifically from the external carotid artery.

[0340] In some embodiments, the system is incorporated into a headband. In some embodiments, the headband comprises at least one sensor configured to measure at least one of: blood flow velocity, arterial stiffness / pressure / displacement of the soft tissue over the arteries and pulse waveforms. In some embodiments, the headband is geared to collect data specifically from the temporal artery.

[0341] In some embodiments, the system is configured for monitoring changes in the temperature, for example, just in one side of the neck (this is because it is expected to sense an increase in thetemperature in the occluded side). In some embodiments, the temperature sensors are positioned in any of the devices / systems disclosed herein.

[0342] Exemplary detection of early signs of cognitive dysfunction

[0343] In some embodiments, the system is configured to detect and address early signs of cognitive dysfunction associated with carotid stiffness, arterial atherosclerosis, or carotid stenosis. In some embodiments, the system is configured to offer therapeutic interventions (e.g., VNS, baroreceptor stimulation) to stabilize cognitive function. In some embodiments, early signs of cognitive dysfunction are detected by sensing one or more of the following:

[0344] Carotid Stiffness and Cognitive Decline: Increased carotid stiffness links to reduced brain volumes and diminished cognitive performance (e.g., memory, attention)

[0345] • Carotid Intima-Media Thickening (CIMT): Higher CIMT is associated with poor cognitive function due to vascular risks and subclinical atherosclerosis

[0346] • Transient Hypoperfusion Episodes: A root cause of transient cognitive dysfunction, potentially reversible with real-time intervention (e.g., VNS or baroreceptor stimulation).

[0347] use of hall sensors and metallic elements

[0348]

[0349] and flow via

[0350]

[0351] and doppler effect

[0352] Referring now to Figure 20, showing a schematic representation of an exemplary use of Hall sensors detecting changed parallel and perpendicular to the artery, as described herein, according to some embodiments of the invention.

[0353] In some embodiments, the system comprises one or more hall sensors. In some embodiments, more specifically, the system is configured to perform a non-invasive and minimally invasive monitoring systems for measuring physiological parameters, specifically pressure and flow dynamics, using Hall sensors and metallic elements.

[0354] Pressure Measurement: A metallic piece reacts to pressure changes by displacing in response to force variations. A Hall sensor detects the displacement and converts it into a measurable signal correlated with pressure changes. The metallic piece can be placed either externally on the skin or minimally invasively beneath the skin for long-term monitoring.

[0355] Flow Measurement: at a 90-degree angle, the system measures flow-induced displacement from the iron component of the red blood cell flow and leverages the Doppler effect for analyzing flow dynamics.

[0356] Variations in the magnetic field caused by flow are processed to determine velocity and direction as well as turbulence.Exemplary holder (arc neck device)

[0357] Referring now to Figures 21a-b, showing schematic representations of exemplary holders, according to some embodiments of the invention.

[0358] Referring now to Figure 21a, showing a general view of an exemplary holder 2200, according to some embodiments of the invention. In some embodiments, an exemplary holder 2200 comprises the following parts: a neck holder 2202; an arms holder 2204; two arms 2206a-b; each arm comprising: an elongated body 2208 and a device holder 2210, which are configured to allow for the reversible attachment of monitoring / treatment devices 2212.

[0359] In some embodiments, the neck holder 2202 is configured to be positioned around the neck of the patient. In some embodiments, the neck holder is flexible enough to allow the positioning of the neck holder 2202 on the neck without causing pain to the patient, while being stiff enough to avoid an unwanted removal of the neck holder 2202 from the neck.

[0360] In some embodiments, the arms holder 2204 is connected to the neck holder 2204. In some embodiments, the arms holder 2204 is stiff and is configured to keep a desired positioning of the arms 2206a-b, once set by a user.

[0361] In some embodiments, at each end of the arms holder 2204 there is an arm 2206a-b. In some embodiments, the exemplary holder 2200 comprises a plurality of configurable elements that allow to change and / or personalize the position of the monitoring / treatment devices 2212 according to the anatomy of the patient.

[0362] Referring now to Figure 21b showing exemplary configurable elements that allow to change and / or personalize the position of the monitoring / treatment devices 2212, according to some embodiments of the invention.

[0363] In some embodiments, the arms 2206a-b are held by an arm housing 2214. In some embodiments, the arm 2206a-b is inserted within the arm housing 2214, and is allow to move up and down (see arrow 2216) and be held in place by an engaging mechanism (not shown) within the housing, the engages the indentations 2218 in the arms 2206a-b.

[0364] In some embodiments, the arm housing 2214 is attached to the arms holder 2204 using a pivot 2220 that allows the movement of the arm housing 2214 as shown by arrow 2222.

[0365] In some embodiments, the device holder 2210 is held by the arm 2206a-b using, for example, a ball-and-socket joint 2224 (see detail in Figure 21b) also known as spherical joint, which allows many degrees of freedom, which are useful to allow correct positioning of the monitoring / treatment devices 2212 on the neck.

[0366] In some embodiments, the device holder 2210 is sized and shaped to hold the monitoring / treatment devices 2212.In some embodiments, the exemplary holder 2200 is configured to allow a user to position the monitoring / treatment devices 2212 on the neck in a manner that ensures the correct positioning and / or with the correct pressure on the neck to allow for correct monitoring and / or treatment.

[0367] In some embodiments, the exemplary holder 2200 is made of kind of suitable material, or combination thereof, for example metals, plastics, rubber, etc.

[0368] In some embodiments, the exemplary holder 2200 is configured to be worn either on the back of the neck or on the front of the neck, according to the needs and / or the preference of the user.

[0369] In some embodiments, the holder utilizes a floating suspension architecture configured to mechanically decouple the sensor housing from the external frame. This mechanism maintains a Constant Normal Force (CNF) against the arterial site, ensuring continuous sensor-to-tissue coupling and effectively rejecting motion artifacts caused by swallowing or neck rotation, independent of the frame's position.

[0370] In some embodiments, the configurable elements are characterized by one or more of the following mechanisms:

[0371] 1. Translational (Linear) Adjustment Mechanisms: (Change position without changing orientation) 1.1 Sliding mechanisms: Linear rail and carriage; Slot-and-pin arrangement; Dovetail slide; T-slot guide; Channel-guided slider; Configurable via: friction, clamp, set screw, detent.

[0372] 1.2 Telescoping mechanisms: Nested tubular segments; Rectangular telescoping beams; Multi-stage telescoping arms; Configurable via: spring pin, twist- lock, collet, friction sleeve.

[0373] 1.3 Lead-screw / threaded translation: Lead screw and nut; Thumb screw with captive nut; Micrometer screw; Advantages: high precision, self-locking.

[0374] 1.4 Rack-and-pinion: Linear rack with rotating pinion; Gear-driven translation.

[0375] 1.5 Elastic linear compliance: Spring-loaded plungers; Elastomeric pads; Flexible beams; Useful for: micro-adjustment and skin contact force control.

[0376] 2. Rotational Adjustment Mechanisms (Single-Axis)

[0377] 2.1 Hinge joints: Simple pin hinge; Living hinge; Barrel hinge.

[0378] 2.2 Pivot joints: Friction pivot; Detented pivot; Lockable pivot; Common in: arm-to-frame connections.

[0379] 2.3 Ratcheting joints: Toothed wheel and pawl; Incremental angular indexing.

[0380] 2.4 Torsion-biased joints: Spring-loaded pivots; Self-returning hinges.3. Multi- Axis Rotational Mechanisms

[0381] 3.1 Ball-and-socket (spherical) joints: Free-rotating ball joint; Friction-retained ball joint: Elastically compliant socket; Limited-range ball joint.

[0382] 3.2 Universal joints (Cardan joints): Two orthogonal pivot axes; Limited angular freedom compared to ball joints.

[0383] 3.3 Gimbal mechanisms: Nested orthogonal frames; Typically 2-3 rotational DoF.

[0384] 4. Combined Translation + Rotation Mechanisms

[0385] 4.1 Slotted rotational joints: Pivot combined with arcuate slot; Allows angular + radial adjustment.

[0386] 4.2 Helical (screw-cam) mechanisms: Rotation produces translation; Common in precision positioning.

[0387] 4.3 Eccentric cam mechanisms: Off-center rotation shifts position; Fine lateral adjustment.

[0388] 4.4 Floating mounts: Limited translation in multiple directions; Often spring-biased.

[0389] 5. Flexible / Compliant Adjustment Mechanisms: (No discrete joints)

[0390] 5.1 Flexure hinges: Monolithic elastic hinges; Zero backlash.

[0391] 5.2 Bendable arms: Gooseneck structures; Memory-metal or spring-steel cores.

[0392] 5.3 Elastomeric couplings: Rubber bushings; Silicone mounts.

[0393] 6. Detachable / Reconfigurable Positioning Mechanisms

[0394] 6.1 Quick-release couplings: Snap-fit connectors; Bayonet mounts.

[0395] 6.2 Modular attachment interfaces: Rail-mounted modules; Magnetic mounts; Docking interfaces.

[0396] 6.3 Indexed repositioning systems: Hole-and-pin arrays; Pegboards; Position indexing plates.

[0397] 7. Constraint and Locking Mechanisms (Not DoF, but critical to configurability)

[0398] 7.1 Friction locking: Compression collars; O-ring friction; Elastomer-assisted friction.

[0399] 7.2 Positive locking: Set screws; Cam locks; Over-center clamps.

[0400] 7.3 Selective release: Push-button locks; Lever-actuated releases.

[0401] 8. Actively Controlled Adjustment (Optional)

[0402] 8.1 Motorized mechanisms: Micro-motors; Servo-driven joints.

[0403] 8.2 Shape-changing elements: Shape-memory alloys; Electroactive polymers.

[0404] 8.3 Pneumatic / hydraulic micro-actuators.

[0405] It should be understood that the elements disclosed herein are just examples provided to allow a person having skills in the art to understand the principles of the invention. Other elements and / or mechanisms can be used.In some embodiments, when a user positions the sensors, either with the devices or the patches, the system is configured to provide feedback on the positioning of the sensors and the relative pressure of the sensors on the neck. In some embodiments, the feedback is a visual feedback provided on the electronic device. In some embodiments, while the user is positioning the sensors, the system is configured to assess the correct position by activating the sensors and assess, for example in relation to predetermined values, if the sensors are positioned at the correct location and with the correct pressure.

[0406] Referring also to Figures 21c-f, showing additional schematic representations of the exemplary holders, according to some embodiments of the invention.

[0407] In some embodiments, an exemplary holder 2230, as shown for example in Figures 21c-d, comprises a neck band 2232, ergonomically configured to be comfortable for wearing on the neck of the patient, optionally comprising a soft adaptor for the neck 2234. In some embodiments, similarly to what was disclosed above, the exemplary holder 2230 comprises one or more reconfigurable elements 2236 / 2238 configured to allow personalization of the positioning of the monitoring / treatment devices 2212 on the neck in a manner that ensures the correct positioning and / or with the correct pressure on the neck to allow for correct monitoring and / or treatment.

[0408] In some embodiments, as mentioned above, an exemplary holder 2230 comprises one or more of the following components / elements: A neck band 2232 around the back of the neck on which two sensor assemblies 2212 are mounted. In some embodiments, the sensor assembly 2212 includes, for example, a flexible card with a number of sensors and a sponge, housed in a flexible casing (not shown). In some embodiments, a 7-wire cable extends from the card (not shown). In some embodiments, the cable is routed in an internal channel along the neck band (not shown). In some embodiments, the sensor assembly 2212 is supported by a stage 2240 that rotates within a range of + / -30 degrees. In some embodiments, the stage provides a rigid back for the sensor assembly 2212. In some embodiments, the position of the sensor assembly 2212 can be adjusted in two dimensions - 1) radially towards the neck, 2) circumferentially along the neck band 2232. In some embodiments, optionally, a driver card is located along the neck band 2232, to which the cables from both sensor assemblies 2212 reach, and from which a USB cable optionally exits towards an external electronic device. In some embodiments, the whole system is wireless, and does not comprise wires running within the neck band 2232.

[0409]

[0410] In some embodiments, the user is provided with one or more of the following instructions when provided with the exemplary holder, as shown in any of the Figures 21a-21f:1. Threading the neck band 2232 behind (or in front) the patient’s neck;

[0411] 2. In case the system is wired: Connecting the USB to the electronic device and activating the system. In case the system is wireless: wirelessly connecting the sensors to the electronic device and activating the system;

[0412] 3. Initial positioning of the sensors in the arterial area;

[0413] 4. Initial attachment of each of the sensors to the skin in the desired area with minimal force by turning the adjustment screw or any other configurable element found in the holder;

[0414] 5. Correcting the position as needed by using the degrees of freedom of the sensors in any of the positions where the configurable elements are located, either along the along the circumference of the neck band or on the components holding the sensors;

[0415] 6. Tightening the sensors to the skin in the final position;

[0416] 7. Testing performance against the system;

[0417] 8. Receiving confirmation and starting monitoring.

[0418] Figures 21e-f show schematic representations of an exemplary holder 2230 being worn by a user.

[0419] Exemplary confirmation of correct location and pressure

[0420] In some embodiments, as mentioned above, before beginning the monitoring, the user positions the sensors on the neck and the system comprises a feature that confirms whether the user positioned correctly the sensors. In some embodiments, the confirmation is a visual confirmation, for example, on the screen of the electronic device, indicating the user the state of the positioning. For example, the system can use colors, like RED, YELLOW and GREEN to indicate wrong positioning, almost correct positioning and correct positioning. In some embodiments, other ways to indicate the user can be used, for example sounds or vibrations.

[0421] The below is an exemplary method of assessing the correct positioning of the sensors. It should be understood that the below is just one way to perform the assessment, which is provided to allow a person having skills in the art to understand the invention, and is not intended to be limiting in any way.

[0422] Exemplary method of assessment

[0423] In some embodiments, a first set of checkups are performed which determine if measurements from the hardware are valid. In some embodiments, this involves one or more of: 1. estimating the sampling rate; 2. checking if a physical signal is read; 3. checking histogram spread of data buffer;and 4. checking the dynamic range of measurements. In some embodiments, the algorithm runs serially over each channel of sensor data.

[0424] 1. Estimate sampling rate fs and test if sampling rate is within an allowable region:

[0425] 70Hz ≤ fs≤ 700Hz

[0426] 2. Convert time samples to:

[0427]

[0428] 3. Load config parameters

[0429] 4. Check physical signal - calculate mean of data buffer (per channel) and check if it within a set threshold:

[0430] ^

[0431]

[0432] avgthresh−min≤ avg ≤ avgthresh−max

[0433] 5. Check histogram spread of data buffer values and test if the number of nonzero bins is above a set threshold - to ensure that correct pressure measurements are made:

[0434]

[0435] nbins_thresh≤ nbins

[0436] 6. Check dynamic range of measurements per channel and test if the number is above a minimum threshold:

[0437]

[0438] dynrange_thresh≤ dynrange

[0439] In some embodiments, the next set of checkups performs filtering and normalization of data to standardize the detection across all channels and patients.

[0440] 1. Bandpass filtering to remove low frequency components and noisy components in high frequency range: 0.5 - 10 Hz

[0441] 2. Normalization:

[0442] = ŝ(t),

[0443]

[0444] (It should be noted that the mean / JSequals zero because of the use of the bandpass filter)

[0445] In some embodiments, then, features are extracted to test if the pulse exists or not.

[0446] Feature 1: Check standard deviation and determine if strong signal or not

[0447] f 0, CT < CT / ™

[0448] I 2, CTfi6W< CT < CTf1Kid

[0449] =| i 1, CT“id< — CT < ^ riffh

[0450]

[0451] V 0, at< ct

[0452] Where:2 = strong signal detected, indicated in code by 2 flags set to 1, sig_flag and strong_sig_flag 1 = signal detected, only sig_flag set to 1

[0453] 0 = no signal detected

[0454] Feature 2 Calculate number of zero crossings and check if above a threshold:

[0455] nzcthresh-low

[0456] nzcflag= 1, nzcthresh-low≤

[0457]

[0458] nzcthresh-high≤ nzc

[0459] If number of zero crossings is below the low threshold, then an output of 2 means that the signal indicates having a high SNR. This is indicted in code by setting 2 variable flags to 1, flag and strong_sig_flag.

[0460] If number of zero crossings is between a low and high threshold then output, meaning that signal indicates having a mid SNR. This is indicated in code by setting the variable, flag, to 1

[0461] If number of zero crossings is above a high threshold, then signal has too low of an SNR and cannot identify a pulse.

[0462] Feature 3 Evaluate pulse features estimate the pulse period and width for up-half pulse. Once these estimations are obtained, then test if they are within a threshold band.

[0463] Final output prediction:

[0464] Conditions to output yellow (pred = 1) or green (pred = 2)

[0465] 1. If the signal:

[0466] a. Is physical, i.e.

[0467] avgthresh-min≤ avg ≤ avgthresh-max

[0468] b. Has histogram spread which goes above minimum threshold, i.e.

[0469] nbins_thresh≤ nbins

[0470]

[0471] T.

[0472] —f ii'nns

[0473] c. Has dynamic range which goes above a minimum threshold, i.e.

[0474] dynrange_thresh≤ dynrange

[0475] d. Has standard deviation which is either equal to 1 or 2, i.e.

[0476] tow<, high

[0477] O; O j

[0478] 2. If algorithm detected a pulse (detect_pulse_bool = 1).

[0479] If these conditions are met, then the following is checked:

[0480] 1. If σflag=2 and nzcflag=2, then set pred=2

[0481] 2. If σflag=1 or nzcflag=1, then set pred=1

[0482] 3. Otherwise, set pred=0As used herein with reference to quantity or value, the term “about” means “within ± 10 % of’.

[0483] The terms “comprises”, “comprising”, “includes”, “including”, “has”, “having” and their conjugates mean “including but not limited to”.

[0484] The term “consisting of’ means “including and limited to”.

[0485] 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.

[0486] 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.

[0487] 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.

[0488] 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.

[0489] 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 artAs 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.

[0490] 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.

[0491] 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.

[0492] 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.

[0493] EXAMPLES

[0494] 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.

[0495] Example 1

[0496] 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.

[0497] 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. Toassess the sensitivity and specificity of LVO detection using the recorded signal. 3. To investigate the accuracy variation based on individual parameters.

[0498] Referring now to Figure 22, showing a graph of LVO probability indicator across participants. The model learned personalized baseline hemodynamic activity overtime, similar to wellness applications.

[0499] Continuously outputs an LVO probability; Triggers an alarm above a threshold.

[0500] Using a threshold of 50% probability, LVOs are detected at 83% accuracy (median of 100%).

[0501] 27 participants; 5 false positives 8 false negatives.

[0502] The threshold did not vary according to gender, age, and BMI.

[0503] Referring now to Figure 23, 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).

[0504] Referring now to Figure 24, 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.

[0505] Referring now to Figure 25, 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.

[0506] Example 2

[0507] Early large vessel occlusions (LVO) Detection by Carotid Monitoring

[0508] Perioperative strokes frequently go unrecognized in sedated or critically ill patients. A continuous, operator-independent neuromonitoring was performed in patients as explained below. Methods

[0509] A blinded observational study of 17 Intensive Care Unit (ICU) inpatients (age 68+11; 4 women, 13 men) was conducted: post- coronary-artery -bypass-grafting (CABG) or transcatheter-aortic-valve-implantation (TAVI) or neuro-ICU with >4 / 11 prespecified stroke-risk factors; most non-enrollments did not meet this threshold.

[0510] Bilateral adhesive barosensors continuously recorded carotid pulse waveforms for 23.8+9.1 hours (Figure 26). The carotid monitor connects to bilateral sensor arrays. Raw carotid waveformsare displayed during recording and processed in real-time into area-under-the-curve (AUC) plots -both schematically shown.

[0511] Alerts were triggered when side-to-side differences in area-under-the-curve (AUC) and / or dicrotic notch timing exceeded uniform thresholds. Clinicians were blinded to outputs, and results did not influence care. Neurologists, adjudicated outcomes with imaging confirmation when available; events lacking imaging were considered indeterminate and counted as false-positives. Results

[0512] All three confirmed large vessel occlusions (LVOs) were detected (sensitivity 100% [95% Confidence Interval (CI) 29.2-100]; specificity 85.7% [95% CI 57-98], rising to 100% when indeterminate events were excluded).

[0513] Two additional indeterminate cases lacked imaging confirmation — one post-CABG with neurological decline and one subarachnoid hemorrhage with vasospasm.

[0514] Alerts occurred within therapeutic windows — when expedited imaging and, if indicated, thrombectomy would have been feasible — in two cases: (Figure 27a) a sedated post-CABG patient in the first postoperative hour; confirmatory imaging was obtained 5-days later; and (Figure 27b) an alert consistent with reperfusion ~10-hours before clinical confirmation. Control shown in Figure 27c.

[0515] Figure 27a shows data related to Patient #1: A sustained left-dominant elevation (red) was detected within 1-hour of ICU admission post-CABG, triggering an algorithmic alert (red*; p=6.7×10−9) that occurred early within the yellow-marked therapeutic window. Clinical recognition of MCA occlusion followed 5-days later (red brain-icon). The patient required prolonged ICU care (bed), 5-months of rehabilitation, never regained independence (wheelchair), and died 11 -months later.

[0516] Figure 27b shows data related to Patient #2: A right-dominant elevation (dark-blue) appeared within 30 min post-CABG, also triggering an early algorithmic alert (red*; p=5.4×10−10) within the therapeutic window, coinciding with confusion (red-?-icon) but without confirmatory imaging (classified as false positive). At 2-months, the patient had persistent decline and required assisted living (walker).

[0517] Figure 27c shows data related to Control: Symmetric bilateral AUC traces without alerts demonstrate a true negative.

[0518] Alerts associated with neurological deterioration showed markedly low mean- AUC (<0.07; p<l 0 ), unlike silent events (~0.26-0.36; p=0.37). An intermediate AUC (0.14) occurred in one subarachnoid hemorrhage case with systemic complications (Figure 28).It can be seen in Figure 28, Mean AUC correlation: (1 and 2) = alerts with confirmed deterioration (Patients#l-2). (3) = vasospasm without LVO (Patient#3, false positive). (4 and 5) = LVO events (Patients#4-5, true positives). White = true negatives. Patients#l-2 showed markedly low mean AUC values (0.061 and 0.068; p<0.000001), suggesting sustained hemodynamic impairment. In contrast, Patients#4-5, both true positives without subsequent deterioration, had AUC values similar to controls (0.360 and 0.262 vs. control mean 0.260+0.087; p=0.37). Patient#3 (vasospasm) showed an intermediate value (0.141), though interpretation was confounded by sepsis, DIC, and resuscitation.

[0519] Illustrative cases highlight clinical and economic impact. One patient experienced a severe Middle Cerebral Artery (MCA) stroke requiring prolonged ICU care, rehabilitation, and assisted living, culminating in death 11 -months later. Illustrative projections based on national average suggest direct and rehabilitation costs reached -$300,000 in Israel and -$675,000 in the United States.

[0520] All 17 completed monitoring without device-related complications. Signal quality was high (88% analyzable) across routine care; one motion-artifact alert occurred during transfer.

[0521] Discussion

[0522] Continuous bilateral carotid pressure monitoring detected neurologic ally significant events during hospitalization. In two cases, alerts occurred within an actionable window when expedited imaging and thrombectomy might have been feasible, unlike conventional surveillance. Imaging delays rendered onset indeterminate but consistent with early MCA occlusion. Unlike continuous-Electroencephalography (EEG) (seizure-focused, not validated for LVO detection), Trans-Cranial-Doppler (TCD)(operator-dependent, intermittent), or Near-InfraRed-Spectroscopy (NIRS) (oxygenation surrogate), carotid monitoring provides continuous hemodynamic asymmetry surveillance; to date, no modality has shown reliable automated alert for inpatient stroke detection and / or hemodynamic anomaly detection.

[0523] Hemodynamic detection was based on bilateral pressure-change metrics using AUC analysis. Similar hemodynamic metrics, such as stroke volume flow, are leveraged by Al-driven cardiac monitoring platforms. Markedly low mean-AUC values (<0.07) were consistently associated with acute neurologic deterioration, reflecting sustained unilateral compromise. This builds on principles of bilateral symmetry in the Circle of Willis, disrupted in LVOs where persistent asymmetry reflects perfusion mismatch. While carotid pressure monitoring has been proposed previously, this provides preliminary clinical evidence of real-time, non-invasive utility. Based on observed event rates, estimated numbers-needed-to-treat to prevent one clinically significant disabling stroke is approximately 8-9 very high-risk patients. Small cohort (n=17; 3 LVOs) with wide ConfidenceIntervals (Cis), incomplete imaging (n=2) and restricted enrollment (post-cardiac, neuro-ICU), limiting generalizability to other inpatient populations.

[0524] Conclusion: Real-time carotid monitoring improves perioperative stroke surveillance.

[0525] Example 3

[0526] Early Detection of Large Vessel Occlusions with Carotid Pressure Monitoring - Cohort Study Background:

[0527] Perioperative and neuro-ICU strokes are often missed until after the therapeutic window. The non-invasive, bilateral carotid monitoring system was evaluated for real-time detection of large- vessel occlusion (LVO) in high-risk in-patients in a cohort observational study.

[0528] Methods:

[0529] Seventeen adults (mean age 68+11 years) in cardiothoracic and neuro-critical units were monitored for 11.9 + 14.5 h with adhesive barosensor arrays. Every five minutes, the algorithm compared right-sided and left-sided pulse-pressure waveforms; alerts were issued when AUC and dicrotic-notch asymmetries satisfied predefined Welch-test thresholds (p<2 / IO8and p<0.005, respectively). Alert logs were reviewed against adjudicated clinical diagnoses.

[0530] Results:

[0531] All three clinically confirmed LVOs were detected (sensitivity 100%; 95% CI 29.2-100). With two false positives and twelve true negatives, specificity was 85.7%, positive predictive value 60%, negative predictive value 100%, and overall accuracy 88.2%. Alerts in two critical cases occurred within the therapeutic window — immediately post-CABG under sedation and two to five days before overt decline — while a third LVO was recognized only after monitoring had stopped 24 h post-TAVI. Mean AUC <0.07 characterized events with neurological deterioration, whereas clinically silent alerts showed control-range AUCs (~0.26-0.36). Signal quality was high (88% analyzable), and no devicerelated adverse events were observed.

[0532] Conclusions:

[0533] Carotid monitoring enabled continuous, operator independent detection of unilateral hemodynamic compromise hours to days before clinical recognition, without reacting to non-neurological events. These findings support its validation as a real time “stroke vital sign” for high risk perioperative and ICU patients, with potential for integration into routine surveillance."Example 4

[0534] Exemplary instructions for use (IFU)

[0535] 1. DEVICE DESCRIPTION

[0536] The device is a non-invasive monitoring system that measures pressure variations in the carotid artery region using high-resolution barometric sensors.

[0537] System Components:

[0538] A. Head Unit: A single-use arch (holder) with flexible positioning arms and silicone housing containing a plurality of barometric pressure sensors (for example, three on each side of the neck). B. Interface box: A reusable electronics module that connects the Head Unit to the Display Unit via, for example, USB.

[0539] C. Display unit: A medical-grade tablet or cellphone or any other electronic device running the dedicated application / software, which displays real-time carotid waveform data.

[0540] 2. INTENDED USE / INDICATIONS FOR USE

[0541] In some embodiments, the system is intended for continuous, semi-continuous, real-time monitoring of carotid blood flow waveforms in adult patients. It provides bilateral waveform data, which can be used for one or more of: for informational purposes only; for diagnosis; for treatment; and for clinical decision-making.

[0542] In some embodiments, the device is intended for use in one or more of the following settings: hospital settings and home setting, optionally under the supervision of qualified healthcare professionals, and for monitoring durations of up to 14 days or more as necessary.

[0543] 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.

[0544] 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. circuitry configured to receive and analyze data received from said at least one sensor; wherein said circuitry is configured to assess one or more of stiffness, pressure, displacement of a soft tissue over an artery.

2. The system according to claim 1, further comprising at least one stimulator.

3. The system according to claim 2, wherein said circuitry is further configured for activating said at least one stimulator in view of said analyzed data.

4. Th system according to claim 2, wherein said at least one stimulator is configured to provide one or more of Vagus -Nerve- Stimulation (VNS) and Baroreceptor stimulation.

5. 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.

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

7. The system according to claim 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.

8. The system according to claim 2, 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.

9. The system according to claim 2, wherein said at least one sensor and said at least one stimulator are implanted in said patient.

10. 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 at least one stimulator.

11. The system according to claim 10, wherein said circuitry is positioned in said at least one additional external device.

12. 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.

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

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

15. The system according to claim 14, wherein said one or more integrated digital pressure sensors are configured to detect pressures of 5 to 1000 mbar.

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

17. The system according to claim 1, wherein said system is configured to send an alert when a result of said assessment is above or below a predetermined value.

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

19. The system according to claim 1, wherein said at least one sensor comprises a chargeable battery.

20. The system according to claim 2, wherein said at least one stimulator comprises a chargeable battery.

21. The system according to claim 1, wherein said circuitry comprises a chargeable battery.

22. The system according to claim 1, wherein the system comprises one or more batteries that are wirelessly rechargeable.

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

24. 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.

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

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

27. The system according to claim 1, wherein said at least one sensor is configured to measure soft tissue changes that may reflect one or more of said pressure, said stiffness, said displacement and reactivity of an artery.

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

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

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

31. The system according to claim 24, wherein said Dicrotic Notch Timing and / or 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; andb. computing a ratio of the area under the curve (AUC) from said dicrotic notch forward to a total pulse waveform area.

32. 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 one or more of stiffness, pressure, displacement of a soft tissue over said artery;c. detecting said change;d. automatically determining stroke evolution.

33. The method according to claim 32, further comprising providing one or more of Vagus-Nerve-Stimulation (VNS) and Baroreceptor stimulation based on a result of said determining.

34. The method according to claim 32, further comprising reassessing said one or more of stiffness, pressure, displacement of a soft tissue over said artery.

35. The method according to claim 34, further comprising repeating said providing one or more of Vagus-Nerve-Stimulation (VNS) and Baroreceptor stimulation if necessary.

36. The method according to claim 32, wherein said determining stroke evolution comprises analyzing data by performing a Dicrotic Notch Timing and / or Area Under Curve (AUC) Analysis.

37. The method according to claim 36, wherein said Dicrotic Notch Timing and / or 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; andb. computing a ratio of the area under the curve (AUC) from said dicrotic notch forward to a total pulse waveform area.

38. A method of assessing a stroke, comprising:a. detecting parameters from soft tissue over carotid arteries on both sides of a neck;b. performing a comparative analysis on said detected parameters;c. assessing whether there are differences between said sides;d. providing an alert based on a result of said assessing.

39. A method of guiding a user to position sensors, comprising:a. detecting, for each sensor, a physiological signal;b. performing an automatic quality assessment of said detected physiological signal; and c. if necessary, providing instructions to said user to where to move each sensor in order to improve said detected physiological signal.

40. A method for comparing signals detected at two different points and measuring their decay rate while removing noise, comprising:a. acquiring a signal over a soft tissue;b. cleaning said acquired signal;c. performing a systematic change adjustment;d. performing a comparison and decay analysis.

41. A method for non-invasive detection and characterization of vascular changes within or leading to the brain, comprising analyzing the decay of the pulse wave between two closely positioned pressure sensors over a soft tissue over a carotid artery.

42. The method according to claim 41, further comprising one or more of:a. performing a setup;b. performing waveform isolation and analysis; andc. using the decay factor to perform physiological interpretations.

43. A holder for a monitoring and treatment system comprising two units, the holder comprising a plurality of configurable elements configured to allow positioning of said units on a desired location on a patient at a desired level of pressure.

44. The holder according to claim 43, further comprising one or more of the following components:a. a neck holder;b. an arms holder connected to said neck holder;c. two arms, each attached to a side of said arms holder;d. a housing positioned at a distal end of each said two arms; said housing configured to reversibly hold a unit from said two units.

45. The holder according to claim 44, wherein said plurality of configurable elements are positioned in at least one component from said one or more components.

46. The holder according to claim 43, wherein said plurality of configurable elements are characterized by a mechanism selected from the group consisting of:a. a translational adjustment mechanism;b. a rotational adjustment mechanism;c. a multi-axis rotational mechanism;d. a combined translation + rotation mechanism;e. a flexible and / or compliant adjustment mechanism;f. a detachable and / or reconfigurable positioning mechanism;g. a constraint and locking mechanism;h. an actively controlled adjustment mechanism.

47. A sensor assembly, comprising:a. a sensor housing comprising one or more compliant domes;b. one or more printed circuit boards (PCB) comprising one or more micro-electromechanical systems (MEMS)-based pressure sensors;c. a housing lid, configured to hermetically enclose the PCB with the one or more sensors within the housing;wherein said sensor assembly is configured to utilize a barometric transduction principle designed to capture minute physiological fluctuations by means of said one or more sensors being hermetically enclosed in said one or more domes.

48. The sensor assembly according to claim 47, wherein said assembly comprises a hermetically sealed sensing chamber, generated by the compliant dome and the housing lid.

49. The sensor assembly according to claim 47, wherein said chamber contains a predetermined volume of a compressible medium.

50. The sensor assembly according to claim 49, wherein said compressible medium is one or more of air, a compressible gas and a specific compressible liquid / oil.

51. The sensor assembly according to claim 47, wherein said one or more compliant domes are configured to contact a skin surface of a patient overlying a carotid artery.

52. The sensor assembly according to claim 47, wherein said assembly is configured to sense as a pulse wave propagates through an artery, by sensing a resulting lateral displacement of an arterial wall and overlying tissue which causes a transient reduction in the volume of the chamber.

53. The sensor assembly according to claim 47, wherein said assembly is manufactured under contact atmospheric conditions to ensure that the chamber comprises the required compressible medium.

54. The sensor assembly according to claim 47, wherein said assembly comprises one or more channels / microchannels configured to allow filling the chamber with the compressible medium after the assembly of the sensor assembly.

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