Abstract: The present invention discloses a system and method for non-intrusive monitoring and prediction of cardiac function of a user. The system (100) comprises a sensor device (102), a data capturing device (104), a data receiver module (106), an acoustic engine (108) and user devices (110), which communicate by using communication network (112). The sensor device (102) comprises a sensor array to capture micro-vibrations of physiological parameters of a user through a surface/mattress under which the sensor device (102) is positioned. The acoustic engine (108) converts the digital time-based vibration signals into frequency-based acoustic outputs such as physiological condition acoustic signals. Further, the acoustic engine (108) is configured to determine the user's current and future health issues based on the physiological condition acoustic signals. does not require trained medical practitioners to analyze the vibration signal of the user to determine the physiological conditions of the user.

Abstract: System and Method for Efficiently Identifying a Subject A system and a method for efficiently identifying a subject is provided. The invention provides for segmenting micro-voltage digital signals into intervals of a pre-defined time period. Further, the invention provides for transforming the segmented micro-voltage digital signals into a frequency domain for computing on a Mel's scale. The Mel's scale provides a unique signature of the subject in the form of a Melspectrogram image. Lastly, the invention provides for passing the Melspectrogram image through a trained deep learning model. The features associated with the Melspectrogram image are extracted into a feature map for obtaining predicted labels associated with the subject based on labels used during training of the deep learning model for identifying the subject.