Claims:1. Method of detecting arrhythmia using photoplethysmogram (PPG) signal, said method comprising:

a. extracting photoplethysmogram (PPG) signals from a patient using an image capturing device (202) coupled with a mobile communication device (204);
b. extracting cardiac parameter from the extracted photoplethysmogram (PPG) signals using a feature extraction module (206);
c. identifying presence of cardiac abnormalities as reinforcement filtering of detecting premature ventricular contraction and ventricular flutter from the extracted cardiac parameters using an abnormality detection module (208);
d. analysing the extracted cardiac parameters to investigate statistical trend and to perform statistical closeness approximation of the extracted photoplethysmogram (PPG) signals using a closeness criteria evaluation module (210); and
e. predicting and subsequently classifying type of arrhythmia using a decision module (212).

2. The method as claimed in claim 1, wherein the photoplethysmogram (PPG) signals are extracted from a user’s peripheral body parts.

3. The method as claimed in claim 2, wherein the user’s peripheral body parts are selected from a group comprising of fingertip, ear, toe; and forehead.

4. The method as claimed in claim 1, wherein the photoplethysmogram (PPG) signals are extracted from a user using a light emitting source attached to the image capturing device (202) coupled with the mobile communication device (204).

5. The method as claimed in claim 1, wherein the image capturing device (202) coupled with the mobile communication device (204) extracts photoplethysmogram signals (PPG) as a video stream.

6. The method as claimed in claim 1, wherein the extraction of cardiac parameter is performed using signal processing technique.

7. The method as claimed in claim 1, wherein the extracted cardiac parameter is heart rate.

8. The method as claimed in claim 1, wherein the identification of presence of abnormalities in the extracted photoplethysmogram (PPG) signals is performed by calculating Hurst exponent of the stream of heart rates derived from the extracted PPG signal as reinforcement filtering of detecting premature ventricular contraction and ventricular flutter.

9. The method as claimed in claim 1, wherein the analysis of the cardiac parameters to investigate statistical trend and to perform statistical closeness approximation from the extracted photoplethysmogram (PPG) signals is performed to evaluate morphological trend.

10. The method as claimed in claim 1, wherein the classification of type of arrhythmia is based on the statistical trend investigation and the performed statistical closeness approximation.

11. The method as claimed in claim 1, wherein the classification of type of arrhythmia comprises of classifying into critical and non-critical.

12. The method as claimed in claim 11, wherein the critical type of arrhythmia is selected from a group comprising of premature ventricular contraction, ventricular flutter and asystole.

13. The method as claimed in claim 11, wherein the non-critical type of arrhythmia is selected from a group comprising of bradycardia and extreme ventricular tachycardia.

14. A system of detecting arrhythmia using photoplethysmogram (PPG) signals; said system comprising:
a. an image capturing device (202) coupled with a mobile communication device (204), adapted for extracting photoplethysmogram signals from a patient;
b. a feature extraction module (206) adapted for extracting cardiac parameter from the extracted photoplethysmogram (PPG) signals;
c. an abnormality detection module (208) adapted for identifying presence of cardiac abnormalities as reinforcement filtering of detecting premature ventricular contraction and ventricular flutter from the extracted cardiac parameters;
d. a closeness criteria evaluation module (210) adapted for analysing the extracted cardiac parameters to investigate statistical trend and to perform statistical closeness approximation of the extracted photoplethysmogram (PPG) signals;
e. a decision module (212) adapted for predicting and subsequently classifying type of arrhythmia.
, Description:As Attached