DETECTING, QUANTIFYING, AND/OR CLASSIFYING SEIZURES USING MULTIMODAL DATA

• US 20130096441A1
• Filed: 12/03/2012
• Published: 04/18/2013
• Est. Priority Date: 10/01/2010
• Status: Active Grant

• Current Assignee: Flint Hills Scientific, LLC
• Original Assignee: Flint Hills Scientific, LLC
• Inventors: OSORIO, Ivan
• Granted Patent: US 8,888,702 B2
• Time in Patent Office: Days
• US Class Current: 600/484
• CPC Class Codes: A61B 3/113 for determining or recording eye movement
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A61B 5/0531 Measuring skin impedance
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/1117 Fall detection
• CPC Class Codes: A61B 5/14539 for measuring pH
• CPC Class Codes: A61B 5/14542 for measuring blood gases A61B5/14551 takes precedence
• CPC Class Codes: A61B 5/165 Evaluating the state of mind, e.g. depression, anxiety
• CPC Class Codes: A61B 5/364 Detecting abnormal ECG interval, e.g. extrasystoles, ectopic heartbeats
• CPC Class Codes: A61B 5/366 Detecting abnormal QRS complex, e.g. widening
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/4094 Diagnosing or monitoring seizure diseases, e.g. epilepsy
• CPC Class Codes: A61B 5/686 Permanently implanted devices, e.g. pacemakers, other stimulators, biochips A61B5/6861 takes precedence
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 7/003 : Detecting lung or respiration noise
• CPC Class Codes: A61N 1/36064 : Epilepsy
• CPC Class Codes: A61N 1/36135 : using physiological parameters
• CPC Class Codes: A61N 1/36585 : controlled by two or more physical parameters
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Methods, systems, and apparatus for detecting an epileptic event, for example, a seizure in a patient using a medical device. The determination is performed by providing an autonomic signal indicative of the patient'"'"'s autonomic activity; providing a neurologic signal indicative of the patient'"'"'s neurological activity; and detecting an epileptic event based upon the autonomic signal and the neurologic signal.

Claims

1-31. -31. (canceled)

32. A method for detecting an epileptic event based upon a patient'"'"'s cardiac signal and kinetic activity, comprising:

providing a cardiac signal indicative of the patient'"'"'s heart activity;

determining at least one cardiac index from the cardiac signal, wherein said at least one cardiac index is selected from a heart rate and at least one EKG morphology feature;

providing a kinetic signal indicative of body movement of the patient;

detecting an epileptic event based on a change in the at least one cardiac index selected from;

an increase in the patient'"'"'s heart rate;

a decrease in the patient'"'"'s heart rate;

or

a change in said at least one EKG morphology feature; and

performing a further action based on said kinetic signal, wherein said further action is selected from

confirming the detecting of the epileptic event;

or

not confirming the detecting of the epileptic event.

33. The method of claim 32 further comprising:

determining at least one kinetic index selected from a body posture,

a body position,

a fall,

a parameter derived from an accelerometer signal selected from a movement, a frequency per unit time, a time interval between movements, a movement direction in at least one plane, an acceleration, a velocity, a force, or

a change in one or more of the foregoing, and wherein performing said further action is based on the at least one kinetic index.

34. The method of claim 32 further comprising determining a kinetic index selected from a cessation of movement or an increase in the patient'"'"'s heart rate.

35. The method of claim 33 wherein performing said further action based on said kinetic signal is based upon the temporal relationship between the change in the at least one cardiac index and the kinetic signal.

36. The method of claim 32 further comprising classifying said epileptic event based upon at least one cardiac index and at least one kinetic index.

37. The method of claim 32, further comprising classifying said epileptic event based upon at least one of the patient'"'"'s heart rate, heart rhythm, EKG morphology, EKG wave intervals, an accelerometer signal, an inclinometer signal, a respiratory signal, a skin signal, a blood gases signal, a blood pH, an force, vocal sounds, an EMG signal, an oculogram signal, an EEG signal, an ECoG signal, a responsiveness of the patient, an awareness of the patient, or a stress marker.

38. The method of claim 37 wherein classifying said event comprises classifying the event as one or more of:

an unconfirmed seizure;

a confirmed seizure;

a non-epileptic seizure;

a primarily generalized tonic-clonic seizure,

a secondarily generalized tonic-clonic seizure;

an absence seizure;

a tonic seizure;

an atonic seizure

a partial seizure;

a simple partial seizure;

a complex partial seizure;

a simple partial seizure with secondary generalization;

or

a complex partial seizure with secondary generalization.

39. The method of claim 32, further comprising providing, following said confirming the detecting of the epileptic event, at least one of a responsiveness signal indicative of the patient'"'"'s responsiveness and an awareness signal indicative of the patient'"'"'s awareness, and classifying the epileptic event based upon the at least one of the responsiveness signal and the awareness signal.

40. A method for detecting an epileptic event based upon a patient'"'"'s cardiac signal and kinetic activity, comprising:

providing a kinetic signal indicative of body movement of the patient;

determining at least one kinetic index from said kinetic signal, wherein said at least one kinetic index is selected from a body posture, a body position, a fall, a parameter derived from an accelerometer signal selected from a movement, a frequency per unit time, a time interval between movements, a movement direction in at least one plane, an acceleration, a velocity, a force, or a change in one or more of the foregoing;

providing a cardiac signal indicative of the patient'"'"'s heart activity;

detecting an epileptic event based on said at least one kinetic index; and

performing a further action based on said cardiac signal, wherein said further action is selected from

confirming the detecting of the epileptic event;

or

not confirming the detecting of the epileptic event.

41. The method of claim 40 further comprising:

determining at least one cardiac index selected from a heart rate, an EKG morphology feature, an EKG rhythm feature, or an EKG wave interval feature,

and wherein performing said further action is based on the at least one cardiac index.

42. The method of claim 41, further comprising classifying said epileptic event based upon at least one of a cardiac index, a kinetic index, a respiratory index, a skin index, a blood gases signal, a blood pH, a force index, vocal sounds, ocular activity, an EEG signal, an ECoG signal, an EMG signal, a responsiveness of the patient, an awareness of the patient, or a stress marker.

43. The method of claim 42 wherein classifying said event comprises classifying the event as one or more of:

an unconfirmed seizure;

a confirmed seizure;

a non-epileptic seizure;

a primarily generalized tonic-clonic seizure,

a secondarily generalized tonic-clonic seizure;

an absence seizure;

a tonic seizure;

an atonic seizure

a partial seizure;

a simple partial seizure;

a complex partial seizure;

a simple partial seizure with secondary generalization;

or

a complex partial seizure with secondary generalization.

44. The method of claim 40, further comprising providing, following said confirming the detecting of the epileptic event, at least one of a responsiveness signal indicative of the patient'"'"'s responsiveness or an awareness signal indicative of the patient'"'"'s awareness, and classifying the epileptic event based upon the at least one of the responsiveness signal or the awareness signal.

45. A method for detecting an epileptic event based upon a patient'"'"'s cardiac signal and kinetic activity, comprising:

providing a cardiac signal indicative of the patient'"'"'s heart activity;

determining at least one cardiac index from the cardiac signal, wherein said at least one cardiac index is selected from a heart rate, an EKG morphology feature, an EKG rhythm feature, or an EKG wave interval feature;

characterizing the at least one cardiac index as either indicative of an epileptic event or not indicative of an epileptic event;

providing a kinetic signal indicative of body movement and type of body movement of the patient;

characterizing the kinetic signal as either indicative of an epileptic event or not indicative of an epileptic event; and

detecting an epileptic event only if both of the heart rate and the kinetic signal are indicative of an epileptic event.

46. The method of claim 45 further comprising performing a further action in response to detecting an epileptic event, wherein said further action is selected from providing a therapy to the patient, providing a warning to one of a patient or a caregiver, or logging data relating to the epileptic event.

47. The method of claim 45 further comprising classifying said epileptic event based upon at least one cardiac index and at least one kinetic index.

48. The method of claim 47 wherein classifying said event comprises classifying the event as one or more of:

an unconfirmed seizure;

a confirmed seizure;

a non-epileptic seizure;

a primarily generalized tonic-clonic seizure,

a secondarily generalized tonic-clonic seizure;

an absence seizure;

a tonic seizure;

an atonic seizure

a partial seizure;

a simple partial seizure;

a complex partial seizure;

a simple partial seizure with secondary generalization;

a complex partial seizure with secondary generalization.

49. The method of claim 45, wherein the cardiac signal is provided by an electrocardiogram (EKG), and the kinetic signal is provided by an accelerometer, an inclinometer, an actigraph, an EMG, a mechanogram or two or more thereof.

50. The method of claim 45, further comprising providing an awareness signal indicative of the patient'"'"'s awareness following said detecting, and characterizing the epileptic event based upon the awareness signal.

51. A medical device system for detecting an epileptic event based upon multimodal signals, comprising:

a first sensor for detecting a first modal data and a second sensor for detecting a second modal data relating to a patient'"'"'s body, the first modal data comprising a kinetic signal and the second modal data comprising a cardiac signal of the patient'"'"'s body; and

a medical device (MD) coupled to the patient'"'"'s body and operatively coupled to the first sensor and the second sensor;

the MD comprising;

a kinetic signal module for receiving the kinetic signal;

a cardiac signal module for receiving the cardiac signal;

a detection module for determining whether an epileptic event has occurred based on;

1) detecting an epileptic event using one of said kinetic signal module and said cardiac signal module, and

2) confirming or not confirming said epileptic event using the other of said kinetic signal module and said cardiac signal module,

52. The medical device system of claim 51 further comprising an output module for providing a signal indicating at least one of no seizure detection, a possible seizure detection, or a confirmed seizure detection.