An existing C++ library for efficient segmentation of ultrasound recordings by means of Kalman filtering, the real-time contour tracking library (RCTL), is used as a building block to implement and assess the performance of different Kalman smoothing techniques: fixed-point, fixed-lag, and fixed-interval smoothing. An experimental smoothing technique based on fusion of tracking results and learned mean state estimates at different positions in the heart-cycle is proposed. A set of $29$ recordings with ground-truth left ventricle segmentations provided by a trained medical doctor is used for the performance evaluation.The clinical motivation is to improve the accuracy of automatic left-ventricle tracking, which can be applied to improve the automatic measurement of clinically important parameters such as the ejection fraction. The evaluation shows that none of the smoothing techniques offer significant improvements over regular Kalman filtering. For the Kalman smoothing algorithms, it is argued to be a consequence of the way edge-detection measurements are performed internally in the library. The statistical smoother's lack of improvement is explained by too large interpersonal variations; the mean left-ventricular deformation pattern does not generalize well to individual cases.

This thesis is an attempt to explore certain aspects of the subject called non-contact, ambient-light photoplethysmography, where we hope to reveal benecialproperties the technique may have. We have a clear focus on technical possibilitybut the medical relevance of it is also discussed and conrmed.Conclusions from previous work are exemplied { the ability we have with thismethod to compute an exact heart rate estimate, from the skin surface both onour face and in the palm of our hand, with and without the subject moving duringrecording; the presence of signal uctuations akin to those of breathing. Moreover,that the pulsations are strong enough to enable subdivision into smaller segmentsand a mapping of how the pulse amplitude is distributed among them.Other information is obtained: the phase information contained in the signalis robust enough that not only the average heart rate over some time but also itsshort time variability can be seen with more than a minimum of detail resolution.From a recording where both face and hand is in view, we further substantiate theclaim of phase robustness by estimating the phase delay, i.e. the dierence in bloodpressure wave travel time between forehead and palm.The concept of Independent Component Analysis has been suggested as a way ofimproving the output of the method|a procedure we investigate and nd limitedsupport for. Other, more simplistic signal processing approaches are found to havepositive traits in achieving overall signal clarity.