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 comprising:
a housing configured to be subcutaneously implanted at a portion of a neck or a head of a patient;
a plurality of electrodes on the housing; and
circuitry within the housing configured to obtain physiological data of the patient, wherein 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:
analyze the physiological data; and
based on the analysis, provide a patient stroke indicator.
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 processing circuitry comprises processing circuitry of the sensor device.
5. 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.
6. 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.
7. The system of claim 6 , wherein the processing circuitry is configured to analyze both the electrical brain activity data and the electrical heart activity data and provide the patient stroke indicator based on the analysis of both the electrical brain activity data and the electrical heart activity data.
8. The system of claim 7 , 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 provide the patient stroke indictor based on classifications by the algorithms.
9. 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 provide the patient stroke indicator based on the analysis of the motion data.
10. The system of claim 9 , 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 provide the patient stroke indictor based on classifications by the algorithms.
11. The system of claim 9 , wherein the processing circuitry is configured to make a fall determination based on the analysis of the motion data.
12. 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 one or more actions,
wherein the sensor device is configured to obtain at least a portion of the physiological data during an attempt to perform the one or more actions by the patient.
13. The system of claim 12 , 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.
14. The system of claim 13 , wherein the one or more sensors of the computing device comprise one or more of a camera or a microphone.
15. The system of claim 1 , wherein the patient stroke indicator is probabilistic.
16. The system of claim 15 , wherein the processing circuitry is further configured to provide a probabilistic etiology classification of a stroke.
17. A device comprising:
at least one housing configured to be subcutaneously disposed at a rear portion of a neck or skull of a patient;
a plurality of electrodes 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.
18. The device of claim 17 , wherein the device further comprises processing circuitry configured to:
analyze the detected electrical signals; and
provide a patient stroke indicator based on the analysis.
19. The device of claim 17 , wherein the device is configured to be implanted within the patient.
20. The device of claim 17 , wherein the at least one housing has a volume of less than about 1.2 cc.
21. A method for detecting strokes, the method comprising:
detecting physiological data from a patient via a sensor device subcutaneously disposed at a rear portion of a neck or skull of the patient, wherein the physiological data comprises electrical brain activity data and electrical heart activity data of the patient sensed via a plurality of electrodes disposed on a housing of the sensor device;
analyzing the physiological data; and
based on the analysis, providing a patient stroke indicator.
22. The method of claim 21 , wherein the electrical brain activity corresponds to activity in at least one of the P3, Pz, and P4 brain regions of the patient.
23. The method of claim 21 , wherein analyzing the physiological data comprises filtering the physiological data to separate the electrical brain activity data from the electrical heart activity data.
24. The method of claim 21 , wherein analyzing the physiological data comprises:
analyzing both the electrical brain activity data and the electrical heart activity data; and
providing the patient stroke indicator based on the analysis of both the electrical brain activity data and the electrical heart activity data.
25. The method of claim 24 , 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 providing the patient stroke indicator comprises providing the patient stroke indictor based on classifications by the algorithms.
26. The method of claim 21 , wherein the physiological data comprises motion data.
27. The method of claim 26 , 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 providing the patient stroke indicator comprises providing the patient stroke indictor based on classifications by the algorithms.
28. The method of claim 26 , wherein analyzing the physiological data comprises making a fall determination based on the motion data.
29. The method of claim 21 , wherein obtaining physiological data from the patient comprises:
providing a prompt for the patient to perform one or more actions; and
obtaining at least some of patient physiological data while the patient attempts to perform the one or more actions.
30. The method of claim 21 , wherein the patient stroke indicator is probabilistic.
31. The method of claim 30 , further comprising providing a probabilistic etiology classification of a stroke.