Abstract: An apparatus configured to generate an output quality error estimate using a machine-learning error estimation model to compare an output meeting a predetermined quality threshold with an output image reconstructed from a plurality of images, and provide the output quality error estimate for use in estimating if a second subsequent image is required, in addition to a first subsequent image to obtain a cumulative output having an output quality error meeting a predetermined error threshold. Also an apparatus configured, using a received output quality error estimate generated using a machine-learning error estimation model as above, to estimate if a second subsequent image is required, in addition to a first subsequent image, to obtain a cumulative output having an output quality error meeting a predetermined error threshold.

Abstract: The application relates to apparatus, methods and computer programs for determining pulse wave velocity, The apparatus includes circuitry configured for: receiving a first ballistocardiograph signal indicative of a pulse wave travelling in a first direction at a first time, the pulse wave having a pulse velocity and receiving a second ballistocardiograph signal indicative of the pulse wave travelling in a second direction at a second time, wherein the second direction is, at least partially, perpendicular to the first direction. The circuitry is also configured for determining the pulse wave velocity based one the first ballistocardiograph signal and the second ballistocardiograph signal.

Abstract: An apparatus configured to generate an output quality error estimate using a machine-learning error estimation model to in compare an output meeting a predetermined quality threshold with an output image reconstructed from a plurality of images, and provide the output quality error estimate for use in estimating if a second subsequent image is required, in addition to a first subsequent image to obtain a cumulative output having an output quality error meeting a predetermined error threshold. Also an apparatus configured, using a received output quality error estimate generated using a machine-learning error estimation model as above, to estimate if a second subsequent image is required, in addition to a first subsequent image, to obtain a cumulative output having an output quality error meeting a predetermined error threshold.