Abstract: A system determines onset of a prediabetic state and associated risk of type 2 diabetes without evidential symptoms. In an implementation, a computer implemented method for monitoring an onset and progress of prediabetes in an individual includes periodically capturing an insulin level of an individual and a blood glucose level of the individual over a predetermined time interval for a predefined period, deriving an insulin production trend or a relative insulin resistivity trend over the predefined period, wherein the relative insulin resistivity is a ratio of an insulin level and a blood glucose level, wherein the trends are indicative of trend categories comprising an increasing trend, a steady trend and a decreasing trend, and determining a status of prediabetes in the individual based on at least one of the insulin production trend, relative insulin resistivity trend, and personal data of the individual.

Abstract: Disclosed is a method and system for recommending a set of insulin dosages for a patient. The method estimates a blood glucose level of the patient using a physiological glucose-insulin module based on a set of patient-related information. Thereafter, an insulin dosage calculator calculates the set of insulin dosages based on an output of the physiological glucose-insulin module and contextual information associated with the patient. Finally, the set of insulin dosages are presented to the patient.

Abstract: The invention provides a method and system of separating and locating a plurality of acoustic sources in a human body. The system includes a plurality of sensors, a processing unit and an output device. The method includes recording a plurality of signals by utilizing the plurality of sensors, wherein the plurality of sensors are arranged about one or more portions of the human body. A signal processing technique is applied for separating a plurality of sets of statistically independent sounds from the plurality of signals. Thereafter, a correlation technique is applied on the plurality of sets of statistically independent sounds to obtain a plurality of sets of reference signal dependent sounds. Finally, an advance acoustic location technique is applied on each of the plurality of sets of reference signal dependent sounds to locate the plurality of acoustic signal sources.