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

• US 20130225992A1
• Filed: 02/25/2013
• Published: 08/29/2013
• 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 8,852,100 B2
• Time in Patent Office: Days
• US Class Current: 600/437
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• 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 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• 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 5/026 Measuring blood flow A61B3/1233, A61B3/1241 take precedence
• CPC Class Codes: A61B 5/0531 Measuring skin impedance
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/1117 Fall detection
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• 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 5/4266 sweat secretion
• 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 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: A61B 7/04 Electric stethoscopes microphones, acoustic transducers therefor H04R
• CPC Class Codes: A61B 8/0883 for diagnosis of the heart
• CPC Class Codes: A61N 1/36064 : Epilepsy
• CPC Class Codes: A61N 1/36135 : using physiological parameters
• CPC Class Codes: A61N 1/36139 : with automatic adjustment
• 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

A method, comprising receiving at least one of a signal relating to a first cardiac activity and a signal relating to a first body movement from a patient; triggering at least one of a test of the patient'"'"'s responsiveness, awareness, a second cardiac activity, a second body movement, a spectral analysis test of the second cardiac activity, and a spectral analysis test of the second body movement, based on at least one of the signal relating to the first cardiac activity and the signal relating to the first body movement; determining an occurrence of an epileptic event based at least in part on said one or more triggered tests; and performing a further action in response to said determination of said occurrence of said epileptic event. Further methods allow classification of epileptic events. Apparatus and systems capable of implementing the method.

Claims

1-23. -23. (canceled)

24. A method, comprising:

receiving a signal relating to a cardiac activity from a patient;

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

receiving a signal relating to a body movement from the patient;

deriving at least one body movement index from the body movement signal, wherein said at least one body movement index is selected from a body posture, a body position, a fall, and a body movement derived from an accelerometer;

detecting a possible epileptic seizure based on at least one of the at least one cardiac index and the at last one body movement index;

triggering a test of the patient'"'"'s responsiveness based on said detecting;

performing one of

(a) confirming the detecting of the possible epileptic seizure;

or

(b) overruling the detecting of the possible epileptic seizure,

wherein said confirming or overruling is based upon the result of the responsiveness test; and

performing a further action in response to said confirming the detecting of the possible epileptic seizure.

31. A method, comprising:

receiving a signal relating to a body movement from the patient;

determining from said body movement signal that the patient is in a first, non-recumbent position;

detecting an epileptic seizure by determining from said body movement signal that the patient has had a fall from said first, non-recumbent position to a second position;

triggering a test of the patient'"'"'s responsiveness based at least on part said determining that the patient has had a fall;

performing one of

(a) confirming the detecting of the epileptic seizure;

or

(b) overruling the detecting of the epileptic seizure,

wherein said confirming or overruling is based upon the result of the responsiveness test.

34. A method of detecting an epileptic seizure, comprising:

receiving at least two body signals selected from a body movement signal, a cardiac activity signal, and a responsiveness signal;

determining at least one feature from each of said at least two body signals, wherein

(a) the feature determined from the cardiac signal is an increase in the patient'"'"'s heart rate above an interictal reference value;

(b) the feature determined from the first body movement signal is selected from

(i) an increase in axial or limb muscle tone substantially above an interictal or exercise value for the patient;

(ii) a decrease in axial muscle tone when the patient is in a non-recumbent position;

(iii) a fall followed by an increase in body muscle tone;

or

(iv) a fall followed by generalized epileptic body movements; and

(c) the feature determined from the responsiveness signal is

(i) a decrease in the patient'"'"'s responsiveness below an interictal reference value;

(ii) a decrease in the patient'"'"'s awareness below an interictal reference value; and

performing a further action in response to said confirming the detecting of the possible epileptic seizure.

37. A system for detecting an epileptic seizure, comprising:

an autonomic signal module for receiving a cardiac signal and determining at least one cardiac feature selected from an increase in the patient'"'"'s heart rate above an interictal value and a heart beat morphology feature;

a neurological signal module for receiving at least one of a kinetic signal and a cognitive signal and determining at least one of a kinetic feature from the kinetic signal and a cognitive feature from the cognitive signal, wherein

said kinetic feature is selected from (a) an increase in axial or limb muscle tone substantially above an interictal or exercise value for the patient, (b) a decrease in axial muscle tone when the patient is in a non-recumbent position, (c) a fall followed by an increase in body muscle tone, or (d) a fall followed by generalized epileptic body movements; and

said cognitive feature is selected from (a) a decrease in the patient'"'"'s responsiveness below an interictal reference value, (b) a decrease in the patient'"'"'s awareness below an interictal reference value, (c) a memory feature, (d) an attention feature, and (e) a language feature; and

a detection module for (a) detecting an epileptic seizure based on at least two of a cardiac feature, a kinetic feature, an awareness feature, and a responsiveness feature, and (b) performing a further action in response to said detecting.