Abstract: A mechanism for identifying orthosomnia, being the preoccupation with sensor-derived sleep measures or automated sleep analysis processes, within an individual. Interactions between the individual and a software application performing a sleep analysis process are monitored and used to generate a predictive indicator that indicates a likelihood that the individual has orthosomnia. This predictive indicator may be used to control the software application, and in particular, to control the display of information provided by the software application.

Abstract: An apparatus and method involve not just comparing a patient's recovery but improving predications by grouping the patient into a phenotype to trend the patient's rate of progress compared to existing phenotype clusters to predict, based on a comparison of rate of progress of decline, and assess in order to benefit in the improvement of allocation and timing of future resource needs, including the economic impact.