Systems and methods for vagus nerve monitoring and stimulation
The present disclosure generally relates to devices, systems, and methods for detecting, monitoring, predicting, and/or treating medical conditions (e.g., epileptic seizures) using one or more sensors configured to collect biomarker data from a human subject (e.g., vagal tone and/or physiological or other biomarkers).
1 . A monitoring system, comprising:
one or more sensors, comprising an electroencephalogram (“EEG”) sensor; a heart rate sensor; and/or an electromyography (“EMG”) sensor, wherein the one or more sensors is configured to detect, measure, and/or monitor one or more biomarkers of the human subject;
a housing, configured to be worn on a head of the human subject;
a light sensor, integrated into the housing and configured to detect a signal indicative of an ambient light level;
at least one pupillometer, integrated into the housing and configured to detect a signal indicative of a pupil size of the human subject; and
a controller, comprising a processor and memory, communicatively linked to the one or more sensors, the light sensor, and the at least one pupillometer, wherein the controller is configured to
(a) determine an ambient light level based on the signal detected by the light sensor;
(b) determine a pupil size of the human subject, based on the signal detected by the pupillometer;
(c) determine a normalized pupil size measurement for the human subject, based on the ambient light level and the pupil size of the human subject; and
(d) predict a likelihood of the human subject experiencing a seizure within a predetermined time period, and a classification of the seizure, using one or more pre-trained classifiers, based on (i) the one or more biomarkers detected, measured, and/or monitored by the one or more sensors, and (ii) the normalized pupil size measurement.
2 . The system of claim 1 , further comprising:
a second one or more sensors, comprising a photoplethysmogram (“PPG”) sensor, a blood pressure sensor, a respiration sensor, and/or an inertial motion sensor, wherein the second one or more sensors is configured to detect, measure, and/or monitor one or more biomarkers of the human subject;
wherein the controller is communicatively linked to the second one or more sensors and further configured to
predict a likelihood of the human subject experiencing a seizure within a predetermined time period, and a classification of the seizure, using one or more pre-trained classifiers, based on (i) the one or more biomarkers detected, measured, and/or monitored by the one or more sensors, and (ii) the normalized pupil size measurement; and (iii) the one or more biomarkers detected, measured, and/or monitored by the second one or more sensors.
3 . The system of claim 2 , wherein the one or more sensors and/or the second one or more sensors comprises one or more sensors communicatively linked to the controller by a wireless connection.
4 . The system of claim 2 , wherein the biomarkers detected, measured, and/or monitored by the second one or more sensors comprises:
a) a heart rate of the human subject;
b) a blood pressure of the human subject;
c) a respiration rate or respiration cycle of the human subject; and/or
d) a position, orientation and/or motion of the human subject.
5 . The system of claim 1 , wherein the controller is further configured to predict a likelihood of the human subject experiencing a seizure within a predetermined period of time comprising
a) the next 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59 or 60 seconds;
b) the next 1, 2, 3, 4, or 5 minutes; and/or
c) a time range bounded by any pair of time points listed in a) or b).
6 . The system of claim 5 , wherein the controller is configured to transmit a text, audio, and/or visual alert to a local, mobile, or remote electronic device, computer, or server, owned or operated by a hospital or medical professional, when the controller predicts a likelihood of the human subject experiencing a seizure within the predetermined period of time.
7 . The system of claim 1 , wherein the housing is configured to rest on a bridge of a nose of the human subject and comprises two temple members configured to secure the housing on the head of the human subject.
8 . The system of claim 1 , wherein
the EEG sensor comprises one or more electrodes connected to at least one of the two temple members;
the heart rate sensor comprises a microphone, an inertial measurement unit (“IMU”), and/or an ECG sensor comprising one or more electrodes connected to at least one of the two temple members;
the EMG sensor comprises one or more electrodes connected to the housing by a lead, or is positioned within a second housing and communicatively linked to the controller by a wireless connection; and/or
the second one or more sensors comprises one or more implantable or external sensors.
9 . The system of claim 1 , wherein the EEG sensor, the heart rate sensor, and/or the EMG sensor comprises one or more electrodes connected to the housing by one or more leads.
10 . The system of claim 1 , wherein the controller is at least partially integrated into the housing.
11 . The system of claim 1 , wherein the biomarkers detected, measured, and/or monitored by the one or more sensors comprise:
a) an electrical signal indicative of brain activity of the human subject;
b) an electrical signal indicative of heart activity of the human subject; and/or
c) an electrical signal indicative of skeletal muscle activity of the human subject.
12 . The system of claim 1 , wherein the controller is further configured to classify seizures experienced by the human subject based on type or severity level.
13 . The system of claim 1 , wherein the controller is further configured to store seizure history data in the memory, wherein the seizure history data is based on a time of occurrence, a type, and/or a severity level, of detected seizures.
14 . The system of claim 1 , wherein the controller is further configured to alert the human subject using a textual, audio and/or visual indicator when the controller predicts that a seizure is imminent, or likely to occur within a period of time.
15 . The system of claim 1 , wherein the controller is further configured to transmit seizure history data to a local, mobile, or remote electronic device, computer, or server, wherein the seizure history data is based on a time of occurrence, a type, and/or a severity level, of detected seizures.
16 . The system of claim 1 , wherein the local or remote electronic, device, computer, or server is owned or operated by a hospital or a medical professional.
17 . The system of claim 1 , wherein the system further comprises
an external or implantable stimulator comprising at least one electrode capable of delivering electrical stimulation to the vagus nerve;
wherein the controller is communicatively linked to the stimulator and further configured to activate, modulate, and/or terminate stimulation after detecting that the human subject is experiencing a seizure or based on the likelihood of the human subject experiencing a seizure.
18 . A method of monitoring seizures experienced by a human subject, comprising:
obtaining a first set of biomarkers for the human subject using one or more sensors, comprising an electroencephalogram (“EEG”) sensor, a heart rate sensor; and/or an electromyography (“EMG”) sensor, wherein the one or more sensors is configured to detect, measure, and/or monitor one or more biomarkers of the human subject; and
detecting a signal indicative of an ambient light level, from a light sensor integrated into a housing worn on the head of the humans subject;
detecting a signal indicative of a pupil size of the human subject, using at least one pupillometer integrated into the housing worn on the head of the humans subject;
determining an ambient light level based on the signal detected by the light sensor, and a pupil size of the human subject, based on the signal detected by the pupillometer;
determining a normalized pupil size measurement for the human subject, based on the ambient light level and the pupil size of the human subject; and
predicting a likelihood of the human subject experiencing a seizure within a predetermined time period, and a classification of the seizure, using one or more pre-trained classifiers, based on (i) the one or more biomarkers detected, measured, and/or monitored by the one or more sensors, and (ii) the normalized pupil size measurement.
19 . The method of claim 18 , further comprising:
obtaining a second set of biomarkers for the human subject using a second one or more sensors, comprising a photoplethysmogram (“PPG”) sensor, a blood pressure sensor, a respiration sensor, and/or an inertial motion sensor, wherein the second one or more sensors is configured to detect, measure, and/or monitor one or more biomarkers of the human subject; and
wherein the controller is further configured to predict the likelihood of the human subject experiencing a seizure within a predetermined time period, and a classification of the seizure, using one or more pre-trained classifiers, based on (i) the one or more biomarkers detected, measured, and/or monitored by the one or more sensors, and (ii) the normalized pupil size measurement, and (iii) the one or more biomarkers detected, measured, and/or monitored by the second one or more sensors.
20 . The method of claim 19 , wherein
the EEG sensor comprises one or more electrodes connected to at least one of the two temple members;
the heart rate sensor comprises a microphone, an IMU, or an ECG sensor comprising one or more electrodes connected to at least one of the two temple members;
the EMG sensor comprises one or more electrodes connected to the housing by a lead, or is positioned within a second housing and communicatively linked to the controller by a wireless connection; and/or
the second one or more sensors comprises one or more implantable or external sensors.
21 . The method of claim 20 , wherein the EEG sensor, the ECG sensor, and/or the EMG sensor comprises one or more electrodes connected to the housing by one or more leads.
22 . The method of claim 19 , wherein the housing is configured to rest on a bridge of a nose of the human subject and comprises two temple members configured to secure the housing on the head of the human subject.
23 . The method of claim 19 , wherein the controller is at least partially integrated into the housing.
24 . The method of claim 19 , wherein the one or more sensors and/or the second one or more sensors comprises one or more sensors communicatively linked to the controller by a wireless connection.
25 . The method of claim 19 , wherein the biomarkers detected, measured, and/or monitored by the second one or more sensors comprises:
a) a heart rate of the human subject;
b) a blood pressure of the human subject;
c) a respiration rate or respiration cycle of the human subject; and/or
d) a position, orientation and/or motion of the human subject.
26 . The method of claim 19 , wherein the controller is further configured to store seizure history data in the memory, wherein the seizure history data is based on a time of occurrence, a type, and/or a severity level, of detected seizures.
27 . The method of claim 19 , wherein the controller is further configured to alert the human subject using a text, audio, and/or visual indicator when the controller predicts that a seizure is imminent, or likely to occur within the predetermined period of time.
28 . The method of claim 19 , wherein the controller is further configured to alert the human subject using a text, audio, and/or visual indicator when the controller predicts that a seizure is likely to occur within the next 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, or 60 seconds.
29 . The method of claim 19 , wherein the method further comprises
stimulating a vagus nerve of the human subject using an external or implantable stimulator comprising at least one electrode capable of delivering electrical stimulation to the vagus nerve;
wherein the controller is communicatively linked to the stimulator and further configured to activate, modulate, and/or terminate stimulation (a) after detecting that the human subject is experiencing a seizure or (b) based on predicting the likelihood of the human subject experiencing a seizure.
30 . The method of claim 18 , wherein the biomarkers detected, measured, and/or monitored by the one or more sensors comprises:
a) an electrical signal indicative of brain activity of the human subject;
b) an electrical signal indicative of heart activity of the human subject; and/or
c) an electrical signal indicative of skeletal muscle activity of the human subject.
31 . The method of claim 18 , wherein the controller is further configured to predict a likelihood of the human subject experiencing a seizure within a predetermined time period comprising:
a) the next 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59 or 60 seconds;
b) the next 1, 2, 3, 4, or 5 minutes; and/or
c) a time range bounded by any pair of time points listed in a) or b).