Claims:1. A system for monitoring and treating diabetes, the system comprising:

a continuous glucose monitoring (CGM) device, the CGM device configured to monitor a glucose concentration in a patient for a predefined time period and generate a data corresponding to the glucose concentration in the patient;
a user interface for providing a set of parameters;
a processor in communication with the CGM device, wherein the processor comprising,
a glucose insulin glucagon soft sensor module receiving the data from the CGM device as an input and processing the data using a mathematical model to provide a processed data as an output,
a soft sensor calibration module receiving the processed data from the glucose insulin glucagon soft sensor module and the set of parameters from the user interface as input, the soft sensor calibration module configured to estimate a plurality of patient specific parameters based on the input received from the user interface and the glucose- insulin-glucagon soft sensor module,
a control module to estimate an optimum amount of inulin and glucagon need to be delivered to maintain the glucose concentration within a predefined normal limits, and
an advisory module for providing a plurality of advisory instructions to improve the health of the patient; and
a glucagon-insulin delivery pump in communication with the control module, the glucagon-insulin delivery pump configured to deliver the optimum amount of insulin and glucagon to the patient estimated by the control module.

2. The system of claim 1, wherein the soft sensor calibration module further receives input from the CGM device, the CGM device measures the glucose concentration in the patient’s blood, wherein the soft sensor calibration module compares the glucose concentration with the predefined normal limits to re-estimate the plurality of patient specific parameters if the glucose concentration is outside the predefined normal limits.

3. The system of claim 1 further includes a database for storing the plurality of patient specific parameters over a period of time.

4. The system of claim 1, wherein the soft sensor calibration module estimates the plurality of patient specific parameters using a predefined mathematical model.

5. The system of claim 1, wherein the set of parameters correspond to meal intake by the patient.

6. The system of claim 1, wherein the set of parameters include a plurality of physical activities performed by the patient, the plurality of physical activities includes at least one of a running, walking, swimming, training or a similar activity.

7. The system of claim 1, wherein the set of parameters includes other medications consumed by the patient.

8. The system of claim 1 further includes an output display device to provide a set of instructions to the patient.

9. The system of claim 1, wherein the soft sensor calibration module is controlled by the user interface.

10. The system of claim 1, wherein the control module further configured to vary the flow rate of insulin and glucagon delivered out of the glucagon-insulin delivery pump based on the computations done using an optimal control algorithm.

11. The system of claim 1, wherein the data produced by the glucose-insulin-glucagon soft sensor module includes measure of at least one of a postprandial glucose, glucose utilization, endogenous glucose production, renal excretion, subcutaneous insulin kinetics, or insulin secretion.

12. The system of claim 1, wherein the advisory module is one of a knowledge based or a rule base advisory module.

13. The system of claim 1, wherein the diabetes is diabetes Type 1 or diabetes Type 2.

14. A method for monitoring and treating diabetes, the method comprising:

monitoring a glucose concentration in a patient’s body using a continuous glucose monitoring (CGM) device for a predefined time period, wherein the CGM device generating a data corresponding to the glucose concentration in the patient’s body;
providing a set of parameters using a user interface;
providing the data and the set of parameters as an input to a glucose-insulin-glucagon soft sensor module, wherein the glucose-insulin-glucagon soft sensor module processes the data using a mathematical model and provides a processed data as an output;
estimating a plurality of patient specific parameters based on the input received from the user interface and the glucose-insulin-glucagon soft sensor module using a soft sensor calibration module;
estimating an optimum amount of insulin and glucagon, using a control module, which need to be delivered to maintain the glucose concentration within a predefined normal limits;
delivering an optimum amount of insulin and glucagon by the glucagon-insulin delivery pump based on the input received from the control module;
measuring a blood glucose concentration using the CGM device, wherein the CGM device is in communication with the control module; and
re-estimating the plurality of patient specific parameters to control the glucagon-insulin delivery pump, if the blood glucose concentration is not within a predefined normal limits.

15. The method of claim 14 further includes the step of providing an advisory instructions to improve the health of the patient.

16. The method of claim 14, wherein the soft sensor calibration module estimating the plurality of patient specific parameters using a predefined mathematical model.

17. The method of claim 14, wherein the soft sensor calibration module using at least one of a non-linear least squares method, Levenberg-Marquardt algorithm, gradient based method or collocation method to estimate the plurality of patient specific parameters through nonlinear optimization.
, Description:As Attached