Claims:We claim:
1. A method for monitoring behaviour of a patient in real-time, the method comprising:
receiving, by a patient monitoring device , data related to the patient from one or more sources;
classifying, by the patient monitoring device, the received data into one or more categories based on one or more rules;
correlating, by the patient monitoring device, the categorized data to identify one or more activity patterns corresponding to the patient, wherein each of the one or more activity patterns are associated with an activity performed by the patient at predefined time intervals; and
detecting, by the patient monitoring device, abnormal behaviour of the patient if the one or more identified activity patterns are different from one or more predefined activity patterns corresponding to the patient.
2. The method as claimed in claim 1 further comprises providing, by the patient monitoring device, a notification related to the abnormal behaviour of the patient to one or more receiving entities.

3. The method as claimed in claim 1 further comprises:
comparing, by the patient monitoring device, the abnormal behaviour of the patient with a symptom learning table, to identify one or more symptoms corresponding to the abnormal behaviour of the patient, wherein each of the one or more symptoms is associated with a precaution measure; and

indicating, by the patient monitoring device, the precaution measure corresponding to the identified symptom to the one or more receiving entities.

4. The method as claimed in claim 3, wherein the symptom learning table is extracted from one or more medical repositories associated with the patient monitoring system.

5. The method as claimed in claim 1 further comprises:
identifying, by the patient monitoring device, one or more remedies for the detected abnormal behaviour of the patient; and
indicating, by the patient monitoring device, the identified one or more remedies to at least one of the patient and the one or more receiving entities.

6. The method as claimed in claim 1, wherein the received data is at least one of audio data, video data, image data, medical data and patient data.

7. The method as claimed in claim 1, wherein the one or more sources are at least one of audio recording device, video capturing device, image capturing device and one or more medical devices.

8. The method as claimed in claim 1, wherein the categorized data is converted into text format based on predefined configuration information and stored in the memory.

9. The method as claimed in claim 1, wherein the received data is filtered to retain the data required for monitoring the behaviour of the patient in real-time.

10. The method as claimed in claim 1, wherein the one or more rules are at least one of predefined and dynamically updated

11. A patient monitoring device for monitoring behaviour of a patient in real-time, the patient monitoring device comprising:
a processor; and
a memory communicatively coupled to the processor , wherein the memory stores the processor-executable instructions, which, on execution, causes the processor to:
receive data related to the patient from one or more sources;
classify the received data into one or more categories based on one or more rules;
correlate the categorized data to identify one or more activity patterns corresponding to the patient, wherein each of the one or more activity patterns are associated with an activity performed by the patient at predefined time intervals; and
detect abnormal behaviour of the patient if the one or more identified activity patterns are different from one or more predefined activity patterns corresponding to the patient.
12. The patient monitoring device as claimed in claim 11, wherein the processor is further configured to provide a notification related to the abnormal behaviour of the patient to one or more receiving entities.

13. The patient monitoring device as claimed in claim 11, wherein the processor is further configured to:
compare the abnormal behaviour of the patient with a symptom learning table, to identify one or more symptoms corresponding to the abnormal behaviour of the patient, wherein each of the one or more symptoms is associated with a precaution measure; and

indicating the precaution measure corresponding to the identified symptom to the one or more receiving entities.

14. The patient monitoring device as claimed in claim 13, wherein the processor is configured to extract symptom learning table from one or more medical repositories associated with the patient monitoring system.

15. The patient monitoring device as claimed in claim 11, wherein the processor is further configured to:

identify one or more remedies for the detected abnormal behaviour of the patient; and

indicate the identified one or more remedies to at least one of the patient and the one or more receiving entities.

16. The patient monitoring device as claimed in claim 11, wherein the received data is at least one of audio data, video data, image data, medical data and patient data.

17. The patient monitoring device as claimed in claim 11, wherein the one or more sources are at least one of audio recording device, video capturing device, image capturing device and one or more medical devices.

18. The patient monitoring device as claimed in claim 11, wherein the processor is configured to convert the categorized data into text format based on predefined configuration information and stored in the memory.

19. The patient monitoring device as claimed in claim 11, wherein the processor is configured to filter the received data to retain the data required for monitoring the behaviour of the patient in real-time.

20. The patient monitoring device as claimed in claim 11, wherein the one or more rules are at least one of predefined and dynamically updated.

21. A non-transitory computer readable medium including instructions stored thereon that when processed by at least one processor causes a patient monitoring device to perform operations comprising:
receiving data related to the patient from one or more sources;

classifying the received data into one or more categories based on one or more rules stored in a memory associated to the patient monitoring system;

correlating the categorized data to identify one or more activity patterns corresponding to the patient, wherein each of the one or more activity patterns are associated with an activity performed by the patient at predefined time intervals; and

detecting abnormal behaviour of the patient if the one or more identified activity patterns are different from one or more predefined activity patterns corresponding to the patient.

Dated this 13th day of November 2015

SWETHA S.N
OF K & S PARTNERS
AGENT FOR THE APPLICANT
, Description:TECHNICAL FIELD
The present subject matter is related, in general to monitoring system, and more particularly, but not exclusively to a method and a system, for monitoring behaviour of a patient in real-time.