Abstract: Disclosed herein are systems and methods for contactless sleep monitoring. The contactless sleep monitoring system collects patient data from a plurality of sensors, including thermal, radar, and audio sensors. The data is then processed using various signal processing techniques. Machine learning algorithms then convert the thermal data, audio data, and radar data into latent representations, preserving the features of each type of data but enabling them to be combined together for analysis. Finally, the system fuses the representations and then predicts sleep states by performing machine learning analysis on the fused data. Sleep states include sleep stages and sleep conditions.

Abstract: A computer-implemented method for determining a heart rate and respiratory rate from a radio frequency signal comprises inputting a radio frequency signal obtained from a test subject into a neural network. The method further comprises training the neural network using the radio frequency signal and extracting a heart rate and a respiratory rate from the radio frequency signal using the neural network. Further, the method comprises comparing the heart rate and the respiratory rate extracted from the radio frequency signal to a verifiable heart rate and verifiable respiratory rate for the test subject to compute an error measure. Finally, the method comprises using the error measure to apply back propagation to adjust front end parameters for one or more layers of the neural networks to improve a prediction accuracy of the neural network.

Abstract: Embodiments of remote health monitoring systems and methods are disclosed. In one embodiment, a plurality of sensors is configured for contact-free monitoring of at least one bodily function. A signal processing module communicatively coupled with the plurality of sensors is configured to receive data from the plurality of sensors. A first sensor is configured to generate a first set of data associated with a first bodily function. A second sensor is configured to generate a second set of data associated with a second bodily function. A third sensor is configured to generate a third set of data associated with a third bodily function. The signal processing module is configured to receive and process the first set of data, the second set of data, and the third set of data. The signal processing module is configured to generate at least one diagnosis of a health condition responsive to the processing.