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EP-4247246-B1 - SYSTEMS FOR DETERMINATION OF TREATMENT THERAPEUTIC WINDOW, DETECTION, PREDICTION, AND CLASSIFICATION OF NEUROELECTRICAL, CARDIAC AND/OR PULMONARY EVENTS, AND OPTIMIZATION OF TREATMENT ACCORDING TO THE SAME

EP4247246B1EP 4247246 B1EP4247246 B1EP 4247246B1EP-4247246-B1

Inventors

  • HEASMAN, JOHN MICHAEL
  • COOK, Mark James
  • KLUPACS, Robert John
  • HOARE, ROHAN

Dates

Publication Date
20260513
Application Date
20211116

Claims (11)

  1. A system (100, 300) for analyzing a physiological condition associated with an epilepsy patient, the system comprising: - a processor device (104) comprising a microprocessor (258), a memory (260), and communication circuitry (256); - an array (102) of electroencephalogram (EEG) electrodes (110) configured to be disposed on the patient, the array (102) (i) communicatively coupled to the processor device (104) via the communication circuitry (256), (ii) generating electroencephalogram (EEG) data (262) from signals detected by the array (102) while the array (102) is disposed on the patient, and (iii) providing the EEG data (262) to the processor device (104); - a photoplethysmography sensor (108) configured to be disposed on the patient, the sensor (108) (i) communicatively coupled to the processor device (104) via the communication circuitry (256), (ii) generating photoplethysmogram (PPG) data (267) from signals detected by the sensor (108) while the sensor (108) is disposed on the patient, and (iii) providing the PPG data (267) to the processor device (104); - a user-interface, stored in the memory (260) and configured to be executed by the microprocessor (258) to cause a display of the processor device (104) to display a user interface (106) configured to receive side-effect data (268) indicating side effects perceived by the patient; - an analysis routine (270, 302), stored in the memory (260) and configured to be executed by the microprocessor (258), the analysis routine (270, 302) operable to (1) receive the EEG data (262) and the PPG data (267); (2) receive the side effect data (268); (3) determine a plurality of feature values (272), the plurality of feature values (272) including each of: (i) one or more feature values of the EEG data (262), (ii) one or more feature values of the PPG data (267), (iii) one or more features of the side effect data (268); and (4) based on the plurality of feature values (272), detect and classify events associated with the physiological condition, the classified events (274) including side-effect events, - a routine (273, 500) configured to monitor the classified events (274, 274') and to determine, from the monitored classified events (274, 274'), an efficacy of an administered therapeutic treatment, wherein the efficacy is classified as (i) sub-therapeutic or (ii) therapeutic and wherein the efficacy is classified as (i) side-effect free or (ii) causing one or more side-effects, and wherein the routine (273, 500) is configured to determine a therapeutic dose that is in a side-effect free therapeutic window.
  2. A system according to claim 1, wherein the analysis routine comprises a static model.
  3. A system according to claim 1, wherein the analysis routine comprises a trained artificial intelligence (AI) model.
  4. A system according to claim 3, wherein the trained Al model is configured according to an Al algorithm based on a previous plurality of feature values.
  5. A system according to claim 1, wherein the efficacy is determined according to a number of occurrences of clinical events of the monitored event data.
  6. A system according to any one of claims 1 to 5, wherein the events associated with the physiological condition are classified by the analysis routine as epileptic events or non-epileptic events.
  7. A system according to any one of claims 1 to 6, the system further comprising a treatment strategy routine, stored in the memory (260) and configured to be executed by the microprocessor (258), the treatment strategy routine operable to (i) recommend a pharmacological agent to treat the physiological condition according to the detected and classified events; and/or (ii) administer, via a treatment device coupled to the microprocessor (258), a pharmacological agent to treat the physiological condition according to the detected and classified events.
  8. A system according to any one of claims 1 to 7, the system further comprising a treatment strategy routine, stored in the memory (260) and configured to be executed by the microprocessor (258), the treatment strategy routine operable to (i) recommend a change in a dose, concentration, timing, or frequency of a pharmacological agent to treat the physiological condition according to the detected and classified events; and/or (ii) administer, via a treatment device coupled to the microprocessor, a change in a dose, concentration, timing, or frequency of a pharmacological agent to treat the physiological condition according to the detected and classified events (274, 274').
  9. A system according to any one of claims 1 to 8, the system further comprising a treatment strategy routine, stored in the memory (260) and configured to be executed by the microprocessor (258), the treatment strategy routine operable to (i) recommend a vagal nerve stimulation protocol to treat the physiological condition according to the detected and classified events; and/or (ii) administer, via a treatment device coupled to the microprocessor, a vagal nerve stimulation protocol to treat the physiological condition according to the detected and classified events (274, 274').
  10. A system according to any one of claims 1 to 9, the system further comprising a treatment strategy routine, stored in the memory (260) and configured to be executed by the microprocessor (258), the treatment strategy routine operable to (i) recommend an epicranial, transcranial, or intracranial stimulation protocol to treat the physiological condition according to the detected and classified events; and/or (ii) administer, via a treatment device coupled to the microprocessor, an epicranial, transcranial, or intracranial stimulation protocol to treat the physiological condition according to the detected and classified events (274, 274').
  11. A system according to any one of claims 1 to 10, wherein the analysis routine (270, 302) is further operable to predict, based on the plurality of feature values one or more future events associated with the physiological condition.

Description

TECHNICAL FIELD The present disclosure relates to systems and methods for monitoring various types of physiological activity in a subject. In particular, the disclosure relates to systems and methods for monitoring neurological activity in a subject and, more particularly, to detecting and classifying events occurring in the subject that are, or appear similar to, epileptic events. The disclosure also relates particularly to methods and systems for monitoring electroencephalographical and photoplethysmographical activity in a subject and, more particularly, to determining a therapeutic window of a treatment, and detecting, predicting, classifying neuroelectrical, vestibular, cochlear, cardiac, and pulmonary events and conditions occurring in the subject, and using the detection, prediction, and classification, combined with the determined therapeutic window to optimize treatment. BACKGROUND OF THE DISCLOSURE Epilepsy is considered the world's most common serious brain disorder, with an estimated 50 million sufferers worldwide and 2.4 million new cases occurring each year. Epilepsy is a condition of the brain characterized by epileptic seizures that vary from brief and barely detectable seizures to more conspicuous seizures in which a sufferer vigorously shakes. Epileptic seizures are unprovoked, recurrent, and due to unexplained causes. Additionally, epilepsy is but one of a variety of physiopathologies that have neurological components. Among these, epilepsy, inner ear disorders, and certain sleep disorders affect tens of millions of patients and account for a variety of symptoms with effects ranging from mild discomfort to death. Vestibular disorders, sometimes caused by problems with signaling between the inner ear's vestibular system and the brain, and other times caused by damage or other issues with the physical structures in the inner ear, can cause dizziness, blurred vision, disorientation, falls, nausea, and other symptoms that can range from uncomfortable to debilitating. Cochlear disorders are commonly associated with changes in the ability to hear, including hearing loss and tinnitus, and may be temporary, long-lasting, or permanent. Sleep apnea, meanwhile, is a sleep disorder in which breathing may stop while a person is sleeping. Sleep apnea may be obstructive in nature (e.g., the physiology of the throat may block the airway), or may be neurological (central sleep apnea) in nature. The effects of sleep apnea may be relatively minor (e.g., snoring, trouble sleeping, etc.) and lead to poor sleep quality, irritability, headaches, trouble focusing, and the like, or can be more severe including causing neurological damage or even cardiac arrest and death. Diagnosing these disorders can be challenging, especially where, as with epilepsy or sleep apnea, diagnosis typically requires detailed study of both clinical observations and electrical and/or other signals in the patient's brain and/or body. Diagnosing epilepsy typically requires detailed study of both clinical observations and electrical and/or other signals in the patient's brain and/or body. Particularly with respect to studying electrical activity in the patient's brain (e.g., using electroencephalography to produce an electroencephalogram (EEG)), such study usually requires the patient to be monitored for some period of time. The monitoring of electrical activity in the brain requires the patient to have a number of electrodes placed on the scalp, each of which electrodes is typically connected to a data acquisition unit that samples the signals continuously (e.g., at a high rate) to record the signals for later analysis. Medical personnel monitor the patient to watch for outward signs of epileptic or other events, and review the recorded electrical activity signals to determine whether an event occurred, whether the event was epileptic in nature and, in some cases, the type of epilepsy and/or region(s) of the brain associated with the event. Because the electrodes are wired to the data acquisition unit, and because medical personnel must monitor the patient for outward clinical signs of epileptic or other events, the patient is typically confined to a small area (e.g., a hospital or clinical monitoring room) during the period of monitoring, which can last anywhere from several hours to several days. Moreover, where the number of electrodes placed on or under the patient's scalp is significant, the size of the corresponding wire bundle coupling the sensors to the data acquisition unit may be significant, which may generally require the patient to remain generally inactive during the period of monitoring, and may prevent the patient from undertaking normal activities that may be related to the onset of symptoms. While ambulatory encephalograms (aEEGs) allow for longer-term monitoring of a patient outside of a clinical setting, aEEGs are typically less reliable than EEGs taken in the clinical setting, because clinical staff do not constantly