Automation in experiments carried out on animals is getting more and more important in research. Computers take over laborious and time-consuming activities like recording and analysing images of the experiment scene. The first step in an image analysis is finding and distinguishing between the observed animals and then tracking all objects during the experiment. In this paper four tracking methods are presented. Quantitative and qualitative figures of merit are applied to confront those methods. The comparison takes into consideration the level of correct object recognition during different disturbances, the speed of computation, requirements as to the frame rate and image illumination, quality of recovering from occluded situations and others.

Disorders of the heart and blood vessels are the leading cause of health problems and death. Early detection of them is extremely valuable as it can prevent serious incidents (e.g. heart attack, stroke) and associated complications. This requires extending the typical mobile monitoring methods (e.g. Holter ECG, tele-ECG) by introduction of integrated, multiparametric solutions for continuous monitoring of the cardiovascular system.

In this paper we propose the wearable system that integrates measurements of cardiac data with actual estimation of the cardiovascular risk level. It consists of two wirelessly connected devices, one designed in the form of a necklace, the another one in the form of a bracelet (wrist watch). These devices enable continuous measurement of electrocardiographic, plethysmographic (impedance-based and optical-based) and accelerometric signals. Collected signals and calculated parameters indicate the electrical and mechanical state of the heart and are processed to estimate a risk level. Depending on the risk level an appropriate alert is triggered and transmitted to predefined users (e.g. emergency departments, the family doctor, etc.).