Systems and methods for detecting strokes
A system for detecting strokes includes a sensor device configured to obtain physiological data from a patient, for example brain activity data. The sensor device can include electrodes configured to be disposed at the back of the patient's neck or base of the skull. The electrodes can detect electrical signals corresponding to brain activity in the P3, Pz, and/or P4 brain regions or other brain regions. A computing device communicatively coupled to the sensor device is configured to receive the physiological data and analyze it to indicate whether the patient has suffered a stroke.
1. A stroke detection system comprising:
a sensor device configured to obtain physiological data from a patient, wherein the sensor device comprises a housing and a plurality of electrodes disposed on the housing and the housing is configured to be disposed at a portion of a neck or a head of the patient, and the physiological data comprises electrical brain activity data and electrical heart activity data of the patient sensed via the plurality of electrodes; and
processing circuitry configured to:
determine that instructions were output to the patient that instruct the patient to perform one or more actions;
receive, from the sensor device, at least a portion of the physiological data during an attempt by the patient to perform the one or more actions;
analyze at least the portion of the physiological data during the attempt by the patient to perform the one or more actions to generate a patient stroke indicator; and
based on the analysis, generate the patient stroke indicator,
wherein the patient stroke indicator includes at least one of:
determining whether a patient has suffered a stroke,
determining a risk that a patient will suffer a stroke,
determining a location of a stroke,
providing a confidence score associated with a determination of patient stroke, or
classifying an identified stroke as ischemic or hemorrhagic.
2. The system of claim 1 , wherein the sensor device is configured to detect brain activity data corresponding to activity in at least one of the P3, Pz, and P4 brain regions via the plurality of electrodes.
3. The system of claim 1 , wherein the sensor device is configured to be disposed at or adjacent a rear portion of a neck or skull base of the patient.
4. The system of claim 1 , wherein the housing is configured to be implanted within the patient.
5. The system of claim 4 , wherein the housing is configured to be implanted subcutaneously.
6. The system of claim 1 , wherein the housing is configured to be disposed over skin of the patient.
7. The system of claim 1 , wherein the processing circuity comprises processing circuitry of the sensor device.
8. The system of claim 1 , further comprising a computing device configured to be communicatively coupled to the sensor device and receive the physiological data from the sensor device, wherein the processing circuitry comprises processing circuitry of the computing device.
9. The system of claim 1 , wherein the processing circuitry is configured to analyze the physiological data by at least filtering the physiological data to separate the electrical brain activity data from the electrical heart activity data.
10. The system of claim 9 , wherein the processing circuitry is configured to analyze both the electrical brain activity data and the electrical heart activity data and generate the patient stroke indicator based on the analysis of both the electrical brain activity data and the electrical heart activity data.
11. The system of claim 10 , wherein the processing circuitry is configured to apply a respective classification algorithm to each of the electrical brain activity data and the electrical heart activity data, and generate the patient stroke indicator based on classifications by the algorithms.
12. The system of claim 1 , wherein the physiological data comprises motion data, and wherein the processing circuitry is further configured to analyze the motion data and generate the patient stroke indicator based on the analysis of the motion data.
13. The system of claim 12 , wherein the processing circuitry is configured to apply a respective classification algorithm to each of the electrical brain activity data, the electrical heart activity data, and the motion data, and generate the patient stroke indicator based on classifications by the algorithms.
14. The system of claim 12 , wherein the processing circuity is configured to make a fall determination based on the analysis of the motion data.
15. The system of claim 1 , further comprising further comprising a computing device configured to:
communicate with the sensor device; and
instruct the patient to perform the one or more actions.
16. The system of claim 15 , wherein the physiological data comprises first physiological data, and the computing device comprises one or more sensors configured to obtain second physiological data during the attempt to perform the one or more actions by the patient.
17. The system of claim 16 , wherein the one or more sensors of the computing device comprise one or more of a camera or a microphone.
18. The system of claim 1 , wherein the patient stroke indicator is probabilistic.
19. The system of claim 18 , wherein the processing circuitry is further configured to generate a probabilistic etiology classification of a stroke.
20. A device comprising:
at least one housing configured to be disposed at a rear portion of a neck or skull base of a patient; and
a plurality of electrodes disposed on the housing, the electrodes configured to detect electrical signals corresponding to brain activity in at least the P3, Pz, and P4 brain regions of the patient;
processing circuitry configured to:
determine that instructions were output to the patient that instruct the patient to perform one or more actions;
receive at least a portion of the detected electrical signals during an attempt by the patient to perform the one or more actions;
analyze at least the portion of the electrical signals during the attempt by the patient to perform the one or more actions to generate a patient stroke indicator; and
generate the patient stroke indicator based on the analysis,
wherein the patient stroke indicator includes at least one of:
determining whether a patient has suffered a stroke,
determining a risk that a patient will suffer a stroke,
determining a location of a stroke,
providing a confidence score associated with a determination of patient stroke, or
classifying an identified stroke as ischemic or hemorrhagic.
21. The device of claim 20 , wherein the device is configured to be implanted within the patient.
22. The device of claim 20 , wherein the device is configured to be disposed over skin of the patient.
23. The device of claim 20 , wherein the at least one housing has a volume of less than about 1.2 cc.
24. A method for detecting strokes, the method comprising:
obtaining physiological data from a patient via a plurality of electrodes disposed on a housing of a sensor device disposed at a rear portion of a neck or base of a skull of the patient;
determining that instructions were output to the patient that instruct the patient to perform one or more actions;
receiving, from the sensor device, at least a portion of the physiological data during an attempt by the patient to perform the one or more actions;
analyzing at least the portion of the physiological data obtained during the attempt by the patient to perform the one or more actions to generate a patient stroke indicator; and
based on the analysis, generating the patient stroke indicator,
wherein the patient stroke indicator includes at least one of:
determining whether a patient has suffered a stroke,
determining a risk that a patient will suffer a stroke,
determining a location of a stroke,
providing a confidence score associated with a determination of patient stroke, or
classifying an identified stroke as ischemic or hemorrhagic.
25. The method of claim 24 , wherein obtaining physiological data comprises detecting electrical brain activity via the plurality of electrodes of the sensor device, the electrical brain activity corresponding to activity in at least one of the P3, Pz, and P4 brain regions of the patient.
26. The method of claim 24 , wherein the physiological data comprises electrical brain activity data and electrical heart activity data, and wherein analyzing the physiological data comprises filtering the physiological data to separate the electrical brain activity data from the electrical heart activity data.
27. The method of claim 24 , wherein the physiological data comprises electrical brain activity data and electrical heart activity data, and
wherein analyzing the physiological data comprises:
analyzing both the electrical brain activity data and the electrical heart activity data; and
generating the patient stroke indicator based on the analysis of both the electrical brain activity data and the electrical heart activity data.
28. The method of claim 27 , wherein analyzing the physiological data comprises applying a respective classification algorithm to each of the electrical brain activity data and the electrical heart activity data, and wherein generating the patient stroke indicator comprises generating the patient stroke indicator based on classifications by the algorithms.
29. The method of claim 24 , wherein the physiological data comprises motion data.
30. The method of claim 29 , wherein the physiological data further comprises electrical brain activity data and electrical heart activity data, and
wherein analyzing the physiological data comprises applying a respective classification algorithm to each of the electrical brain activity data, the electrical heart activity data, and the motion data, and wherein generating the patient stroke indicator comprises generating the patient stroke indicator based on classifications by the algorithms.
31. The method of claim 29 , wherein analyzing the physiological data comprises making a fall determination based on the motion data.
32. The method of claim 24 , wherein the sensor device is implanted subcutaneously within the patient.
33. The method of claim 24 , wherein the sensor device is disposed over skin of the patient.
34. The method of claim 24 , wherein the patient stroke indicator is probabilistic.
35. The method of claim 34 , further comprising generating a probabilistic etiology classification of a stroke.