Detecting, assessing and managing epilepsy using a multi-variate, metric-based classification analysis
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.
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 is configured to detect a third seizure event based upon body data of the patient and the classification analysis unit is further configured to classify the 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.