Abstract: A method for tracking and assessing a wound includes identifying a wound from an image output by a camera, identifying a set of wound features based on the image, detecting a temperature of the wound from at least one heat sensor, triggering at least one response if the wound temperature is outside of a therapeutic temperature zone, processing the set of wound features and wound temperature using machine learning, determining an optimal wound healing trajectory based on the set of wound features and the wound temperature using machine learning, predicting at least one future wound condition based on the optimal wound healing trajectory using machine learning, and displaying the optimal wound healing trajectory and the at least one future wound condition on a display.

Abstract: A method includes receiving subject training data comprising a plurality of images of subjects in a plurality of positions on a person support apparatus, labeling the plurality of images based on the positions of the subjects to generate labeled subject training data, generating synthetic training data comprising computer generated images of artificial subjects in a plurality of positions on an artificial person support apparatus, labeling the synthetic training data based on the positions of the artificial subjects to generate labeled synthetic training data, and training a machine learning model based on the labeled subject training data and the labeled synthetic training data, using supervised learning techniques, to generate a trained model to predict a subject position based on an image of the subject.

Abstract: A patient monitoring system includes a computing device that having a processor and a memory, the memory comprising instructions that, when executed, cause the system to receive, from a thermographic camera, at least one image corresponding to a temperature of a region of interest and a surrounding area that surrounds the region of interest; use an artificial intelligence model to analyze the at least one image; detect a difference in temperature of the region of interest relative to the surrounding area; and issue an alert related to an incontinence event when the difference in temperature exceeds a threshold value.

Abstract: A system is disclosed for generating synthetic patient data. The system includes one or more patient data monitoring devices, and a computing device that receives patient data from the one or more patient data monitoring devices. The system receives patient data from the one or more patient data monitoring devices. The system analyzes the patient data in real-time to learn one or more characteristics. The system generates synthetic patient data based on the one or more characteristics. The synthetic patient data including data representative of the patient data that is different from the patient data. The system stores the synthetic patient data in a database.