DETECTING, ASSESSING AND MANAGING EPILEPSY USING A MULTI-VARIATE, METRIC-BASED CLASSIFICATION ANALYSIS

• US 20180116580A1
• Filed: 12/29/2017
• Published: 05/03/2018
• 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 10,349,882 B2
• Time in Patent Office: Days
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 2560/0475 Special features of memory means, e.g. removable memory cards
• 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 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/026 Measuring blood flow A61B3/1233, A61B3/1241 take precedence
• 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 5/1118 Determining activity level
• CPC Class Codes: A61B 5/14503 invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors A61B5/1459, A61B5/1464, A61B5/1473, A61B5/1482, A61B5/14865 take precedence
• 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 5/283 Invasive
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• 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 5/4836 : Diagnosis combined with treatment in closed-loop systems or methods A61B5/0036 takes precedence
• CPC Class Codes: A61B 5/4848 : Monitoring or testing the effects of treatment, e.g. of medication
• CPC Class Codes: A61B 5/486 : Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/686 : Permanently implanted devices, e.g. pacemakers, other stimulators, biochips A61B5/6861 takes precedence
• CPC Class Codes: A61B 5/7246 : using correlation, e.g. template matching or determination of similarity
• 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 5/7267 : involving training the classification device
• CPC Class Codes: A61B 5/7275 : Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• 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 5/742 : using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/743 : Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• 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: A61M 16/1005 : with O2 features or with parameter measurement
• CPC Class Codes: A61M 2202/0208 : Oxygen
• CPC Class Codes: A61M 2205/3303 : Using a biosensor
• CPC Class Codes: A61N 1/36064 : Epilepsy
• CPC Class Codes: A61N 1/36135 : using physiological parameters
• CPC Class Codes: G16H 20/10 : relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 20/40 : relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 : for calculating health indices; for individual health risk assessment

Abstract

A method for identifying changes in an epilepsy patient'"'"'s disease state, comprising: receiving at least one body data stream; determining at least one body index from the at least one body data stream; detecting a plurality of seizure events from the at least one body index; determining at least one seizure metric value for each seizure event; performing a first classification analysis of the plurality of seizure events from the at least one seizure metric value; detecting at least one additional seizure event from the at least one determined index; determining at least one seizure metric value for each additional seizure event, performing a second classification analysis of the plurality of seizure events and the at least one additional seizure event based upon the at least one seizure metric value; comparing the results of the first classification analysis and the second classification analysis; and performing a further action.

Claims

1. A medical device system, comprising:

a seizure determination unit configured to detect a first seizure event and a second seizure event based upon body data of a patient;

a classification analysis unit configured to classify the first seizure event and the second seizure event;

a classification analysis comparator unit configured to identify a change between a first seizure event classification and a second seizure event classification; and

an event unit configured to log the change between the first seizure event classification and the second seizure event classification.

2. The medical device system of claim 1, further comprising a warning unit configured to generate a first warning based on a first level of change between the first seizure event classification and the second seizure event classification.

3. The medical device system of claim 2, wherein the warning unit is configured to generate a second warning based on a second level of change between the first seizure event classification and the second seizure event classification.

4. The medical device system of claim 1, wherein the classification unit is further configured to determine a first characteristic difference between the first seizure event classification and the second seizure event classification.

5. The medical device system of claim 1, wherein the classification unit is further configured to determine trend data between the first seizure event classification and the second seizure event classification.

6. The medical device system of claim 1, wherein the seizure determination unit configured to detect a third seizure event based upon body data of the patient and the classification analysis unit is further configured to classify a third seizure event.

7. The medical device system of claim 6, wherein the warning unit is further configured to generate a third warning based on a first level of change between at least one of:

the first seizure event classification and the second seizure event classification;

the first seizure event classification and a third seizure event classification; and

the second seizure event classification and the third seizure event classification.

8. The medical device system of claim 7, wherein the warning unit is configured to generate a fourth warning based on a second level of change between at least one of:

the first seizure event classification and the second seizure event classification;

the first seizure event classification and the third seizure event classification; and

the second seizure event classification and the third seizure event classification.

9. The medical device system of claim 6, wherein the classification unit is further configured to determine a first characteristic difference between at least one of:

the first seizure event classification and the second seizure event classification;

the first seizure event classification and a third seizure event classification; and

the second seizure event classification and the third seizure event classification.

10. The medical device system of claim 6, wherein the classification unit is further configured to determine trend data between at least one of:

the first seizure event classification and the second seizure event classification;

the first seizure event classification and a third seizure event classification; and

the second seizure event classification and the third seizure event classification.

11. The medical device system of claim 1, wherein the classification unit is further configured to identify a new seizure class.

12. The medical device system of claim 11, wherein the event unit is further configured to log the new seizure class.

13. The medical device system of claim 12, wherein the event unit is further configured to transmit to an external device data relating to the new seizure class.

14. The medical device system of claim 13, wherein the warning unit is further configured to issue a new seizure class warning.

15. The medical device system of claim 1, wherein the classification analysis unit is further configured to identify an extreme seizure event.

16. The medical device system of claim 15, wherein the event unit is further configured to log data relating to the extreme seizure event.

17. The medical device system of claim 16, wherein the event unit is further configured to transmit to an external device data relating to the extreme seizure event.

18. The medical device system of claim 17, wherein the warning unit is further configured to issue an extreme seizure event warning.

19. The medical device system of claim 1, further comprising one or more processors configured to determine a patient'"'"'s condition change.

20. The medical device system of claim 19, wherein the event unit is configured to log data relating to the patient'"'"'s condition change.